Poverty Reduction: Policies and Global Integration

i

ISBN: 978-969-8858-03-2

POVERTY REDUCTION:Policies and Global Integration

Munir AhmadSuleman Aziz Lodhi

An ISOSS Publication

ii

© 2008 by Islamic Countries Society of Statistical Sciences,Lahore, (Pakistan)

ISBN ISBN: 978-969-8858-03-2

Edition 1st , 2009

Printed in Pakistan

Printer: Izharsons Printers,9-Rattigan Road, Lahore (Pakistan).

Publisher: Islamic Countries Society of Statistical Sciences, Lahore (Pakistan).

iii

Table of Contents

PrefaceContributors

Chapter-1 A Framework for Developing National Poverty Eradication Policy in the New Economy

Suleman Aziz Lodhi and Munir Ahmad 1-16

Chapter-2: Critical Resources for Poor Families: A critique of the United Nations Millennium Development Goals

Sally Bould 17-36

Chapter-3: Poverty and Inequality Mapping in Developing CountriesFrancesca Ballini, Gianni Betti and Laura Neri 37-64

Chapter-4: Tackling the Relationship between Prisoner Re-entry and Poverty

Monica L.P. Robbers 65-86

Chapter-5: Immigrant Women and the Labor MarketSandy D. Alvarez 87-97

Chapter-6: Measurement of Poverty in Pakistan: A New Method 99-106Munir Ahmad

Chapter-7: Poverty: A New Target for Technology –An Analysis on Poverty reduction with the help of Technology

Khalil Ahmed 107-117

iv

Contributors

Ahmad, Munir (Pakistan)National College of Business Administration and Economics, Lahore, PakistanEmail: [email protected]

Ahmed, Khalil (Pakistan)National College of Business Administration & Economics, Lahore, PakistanEmail: [email protected]

Alvarez, Sandy D. (USA)Dept of Sociology and Anthropology, Shippensburg University, 429 Grove Hall, 1871 OLD Main, Shippensburg, PA 17257Email: [email protected]

Ballini, Francesca (Italy) C.R.I.DI.RE. – University of Siena, Piazza S. Francesco, 8, 53100 Siena – ItalyEmail: [email protected]

Betti, Gianni (Italy)C.R.I.DI.RE. – University of Siena, Piazza S. Francesco, 8, 53100 Siena – ItalyEmail: [email protected]

Bould, Sally (USA)Senior Research Fellow, Centre for Population, Poverty and Socio-economic Policy Studies, Differdange, Luxembourgand Professor Emerita University of Delaware, Newark, Delaware 19716 USAEmail: [email protected]

Lodhi, Suleman Aziz (Pakistan)National College of Business Administration and Economics, Lahore, PakistanEmail: [email protected]

Neri, Laura (Italy)C.R.I.DI.RE. – University of Siena, Piazza S. Francesco, 8, 53100 Siena – ItalyEmail: [email protected]

Robbers, Monica L.P. (USA)Marymount University, 2807 North Glebe Road, Arlington VA 22207, USAEmail: [email protected]

v

PREFACE

The world is undergoing globalization; an all-embracing cultural and technological revolution. This revolution has created many opportunities for us, but at the same time has threatened the world with serious challenges from energy crises, global warming, environmental degradation to political turbulence, extremism and terrorism. Regional poverty somehow appears to correlate with violence and extremism, giving a perception that poverty is the root cause of these problems, and if financial income of a region is increased, the region will breakout of the poverty cycle. The book argues that increasing financial inflow alone will not be a sufficient remedy as poverty is not a cause rather an indicator that the socio-political system in the region is not functioning properly.

The governments have been measuring poverty too narrowly focusing on financial dimension only, whereas poverty is much more than that. Poverty studies need to be approached in a more comprehensive way, adding new dimensions to bring out the true picture of the society. If money was the solution of poverty, it’s likely that poverty would have been eradicated long ago. The national leaders in developing countries continue to ignore the interdependence of social issues with poverty in the region. The policies are developed to address the symptoms, while the root causes are ignored. This problem solving approach may be able to give temporary relief, but as the cause of the problem exists in the system, same problems emerge again, in similar or a more developed form. Skewed distribution of wealth in a region; not only imposes serious vulnerability in developing effectiveness of the region, but it also has negative impact on global stability.

What does the book intends to achieveA lot has been written on poverty and strategies to eradicate poverty, but these strategies have not been very successful on the ground for many countries. Donors and aid agencies have worked on the issue for some time. Governments have formulated national policies, however, the status quo continues. A plausible reason is that the policy makers do not view poverty in its full dimensions, its interconnectivity with social, technical and justice systems.

This book firstly intends to highlight the interconnectivity of poverty in a region with its social setup. Illustrating that poverty eradication steps must be planned in broader aspect, ensuring that the region is able to maintain a sustainable system for continuing its socio-economic activities. Otherwise, the system would return to its previous state.Secondly the book emphasises on significance of not considering financial indicators as the sole measurement tools of poverty. The purpose is to present the leaders and policy makers with the multifaceted concept of poverty, in its social context.

Developing a poverty eradication policy requires a rethinking of social policy. The need is to change the culture of poverty in the region and give basic rights to all individuals in a society, raising awareness in masses; facilitating health care services and education. These basic rights form the structure of social systems and once they are established, the system will itself gain strength and become economically stable.

Rich countries have created a culture of better democratic rights and civil liberties, which is conducive to economic activities. They have established respect for the rule of law and security of property rights; increased investment in human capital; but the poor

vi

countries have a high level of government deformations. The national leaders in these countries should adopt a holistic approach for developing poverty measurement and poverty eradication policies.

The book will be useful for researchers, social entrepreneurs and policymakers in understanding poverty and developing successful policies for its reduction. A summary of the chapters in the book is as under:-

Chapter-1: A Framework for Developing National Poverty Eradication Policy in the New EconomyPolicies for eradicating poverty in the developing countries have consistently failed or did not make much progress in most of the countries. A plausible reason for this failure is that these policies were not developed, keeping in mind the multiple dimensions of poverty. The policy makers rather perceived a narrow view of poverty, confining it to financial dimension only without realizing that low financial income is an indicator of poverty and not the poverty itself.

The chapter primarily, focuses on bringing out the multiple dimensions of poverty measurement in the present times. The purpose is to provide policy makers an insight on poverty measurement issues and suggest a framework for analysis and development of national poverty eradication policy.

Chapter-2: Critical Resources for Poor Families: A critique of the United NationsMillennium Development GoalsThis paper proposes an anti-poverty approach of enabling poor families to be more productive and poor children to attain education. Opportunities provided by globalization are problematic because they are in the formal labor force where combining child care with productive activity is no longer possible. The Millennium Development Goals of reducing extreme poverty and hunger, and promoting education and health require a focus on families but the MDGs are limited to enabling individuals. The idea that enabling individuals can accomplish these goals leaves out families where children need care.

A gender equity approach has focused efforts on empowering adult women rather than on women in poor families. But for poor mothers income plus child care (including pre-school education) is the only way these mothers can empower themselves and their children and hope for a future without poverty.

The history of a child care organization, Care, Health and Education for Children in Poverty (CHECP), located in South Asia illustrates the problems faced by NGO’s. The conclusion proposes a structure of sustainable child care programs and the critical role of funding by international donor agencies.

vii

Chapter-3: Poverty and Inequality Mapping in Developing CountriesPoverty and inequality maps - spatial descriptions of the distribution of poverty and inequality - are most useful to policy-makers and researchers when they are finely disaggregated, that is when they represent small geographic units, such as cities, municipalities, districts or other administrative partitions of a country. In order to produce poverty and inequality maps, living standard surveys covering income and consumption are econometrically combined with data from censuses or other sample surveys large enough to allow disaggregation of the poverty and inequality estimates.

Chapter-4: Tackling the Relationship between Prisoner Re-entry and PovertyEach year some 650,000 people are released from various correctional facilities in the United States Problems that inmates encounter upon their release are plentiful and complicated. More than half of those released are repeat offenders, one quarter has substance abuse problems, 12 percent are homeless, and 14 percent are mentally ill. All of these variables are well established in research as contributing to poverty. When an offender reenters society with few legitimate options and few social supports, the cycle of poverty and crime begins again.

This chapter examines the relationship between prisoner reentry and poverty. The reentry process is described along with assessment of reentry programs from various jurisdictions that demonstrate potential for reducing poverty. This includes programs established to serve special populations. Critical success factors from programs are identified and the chapter concludes with recommendations for practitioners, policy-makers and researchers.

Chapter-5: Immigrant Women and the Labor MarketThe importance of the immigrant women’s role in the American labor market is worth noting due to both the magnitude of their participation and the effect it has on immigrant and host community alike. Their experiences and acceptance of cultural beliefs of the host community have affected their participation in the labor market. Whereas Cuban women participated in the labor market as a means of helping their family to regain some of their prior socioeconomic status they experienced in Cuba. Their participation in the labor was expected to end when their husbands were able to succeed in their own ventures.

This study examines the role of immigrant women in the labor market and the challenges they face as they try to assist their families in attaining success in their host community.

Chapter-6: Measurement of Poverty in Pakistan: A New MethodIt is generally considered that population and poverty go hand in hand. In this paper, we show that population is not an important poverty parameter. We measure the poverty on the basis of eight factors of population and housing data (1998) and show that illiteracy is the most important poverty parameter.

viii

Chapter-7: Poverty: A New Target for TechnologyTechnology is a rapidly evolving assistant to human in scientific and social sectors. Though this innovative assistance is available to human since centuries, yet 21st century is prominent due to the swift expansion and advancement in technology borders. Either it’s the field of medical science or engineering; exploration of new space frontiers or insights of computation, technology is providing research, development and deployment resources. In an extreme contrast, poverty exists with same characteristics of growth and effectiveness on human lives, although poverty is a many centuries old entity in human culture, but 21st century is prominent in timeline due to the engraving effects of poverty on human lives. This paper analyses some of the technologies effective to eradicate or reduce poverty.

In the end, we hope that the book will bring to light, the image that poverty is not a regional problem, which can be tackled by any country alone, rather a critical global issue concerning the survival of mankind.

Religious intolerance, regional hatred, terrorism are some of the major issues hindering global peace, and poverty does have a catalyst role in exaggerating these problems and resultantly destabilizing the systems. Poverty eradication certainly does not mean giving handouts, but it does require a combine effort at global level in developing consensus on viewing poverty comprehensively.

It would not be an exaggeration to say that poverty is associated with de-gradation of social systems, like law and order, democracy, human rights, freedom of expression, theright to know and the most importantly, the human equality. We believe that no poverty eradication effort can be successful if we by-pass these issues.

Munir Ahmadand

Suleman Aziz LodhiAugust 25, 2008

1

CHAPTER 1

A FRAMEWORK FOR DEVELOPING NATIONAL POVERTY ERADICATION POLICY IN THE NEW ECONOMY

Suleman Aziz Lodhi1 and Munir Ahmad2

National College of Business Administration and EconomicsLahore, Pakistan

Email: [email protected] [email protected]

ABSTRACT

Policies for eradicating poverty in the developing countries have consistently failed or did not make much progress in most of the countries. A plausible reason for this failure is that these policies were not developed, keeping in mind the multiple dimensions of poverty. The policy makers rather perceived a narrow view of poverty, confining it to financial dimension only not realizing that low financial income is an indicator of poverty and not the poverty itself.

The chapter primarily, focuses on bringing out the multiple dimensions of poverty measurement in the present times. The purpose is to provide policy makers an insight on poverty measurement issues and suggest a framework for analysis and development of national poverty eradication policy.

Keywords: Poverty, Policy development, Knowledge economy, New economy

POVERTY REDUCTION: Policies and Global Integration2

INTRODUCTION

A historical phrase, which made headlines across the world on 21st July, 1969, “A small step for a man, but a giant leap for the mankind”, turned out to be a leap for mankind in the technological domain only. As human race made advances in the field of technology, the gap between the “have” and ‘have-nots” kept increasing at a high rate. This gap between the rich and poor countries has reached extreme level, with the poor being denied the right to even basic necessities of life. More than 1 billion people are denied the right to clean water and 2.6 billion people lack access to adequate sanitation. At the start of the 21st century unclean water is the world’s second biggest killer of children as every year around 1.8 million children die as a result of diarrhea and other diseases caused by unclean water or poor sanitation (UNDP 2006). But on the other hand, most of the developing world governments feel satisfied in reporting an increase in per capita GDP as exclusive indicator of poverty reduction.

It is argued that this number alone provides insufficient information for assessing poverty in a region. It is important to remember that “per capita GDP” is an average, and therefore, it carries all errors found in considering average to be a true representative of a certain data set or population. These figures include highly rich families and miserably poor families, more over, the lower bound on an income that a person can have is zero, but there is no upper limit for the income. As a result GDP gives a biased picture of average income in a country.

International bodies are now projecting a broader concept of poverty, arguing that poverty eradication needs to be approached with a more comprehensive view. UNDP (2003) advocates for right based view of poverty. Similarly the World Bank (WDR 1990) views poverty not only as deprivation of material resources but also low achievement in education, health, vulnerability, exposure to risk, voicelessness and powerlessness. A broader approach of deprivation like the above gives a deeper understanding of poverty and its causes. It helps the policy makers to realize that different aspects of poverty interact and reinforce one another in many ways. The same philosophy can be used to fight poverty, as good outcome of health policy would not only improve wellbeing, but also increase income-earning potentials of a region. Similarly increasing education in a region not only improves health outcomes, it also increases earning capacity of the region.

The chapter discusses the multiple dimensions of poverty in a society and argues on adopting a broader view for measuring poverty in a region. The purpose is to provide policy makers an insight on poverty issues. The last section of the chapter gives suggestions for developing a National Poverty Eradication Policy (NPEP) to face the challenges of the emerging New Economy.

Link to Sustainable DevelopmentA typical definition of sustainable development given by economists is that each generation is at least as well off as the previous generation. There is no arguing that economic growth can help in alleviating poverty, but how the benefits of the growth are distributed among the population is critical for a region. Economists now advocate that the larger the gaps between rich and poor, the little the growth potential in a country or

Ahmad, M. and Lodhi, S.A. 3

region. These gaps not only restrict the development opportunities for the poor, but also bound the growth potential of the countries economic progress (SPRC 2004)

One of the reasons for slow growth in developing countries is their low productivity, which again can be improved by training and education. Education support programs like adult education, subsidy for school supplies play an important role in reducing the economic gap. Similarly providing improved health services for the population results in higher productivity for the region.

The efficient use of a country’s natural resources is important for its sustainable development. Solow (1999) explains that a country takes the income from the use of its natural resources and it should re-invest it in its people. This investment could be in the form of education programs, health care or infrastructure like electricity, water, sewage, and thus the opportunities can be preserved for the future generations. Poor rural families lack access to basic facilities, making it difficult for them to improve their future, leaving them little choice but to move to cities to find opportunities. This shift in population again adds strain on the infrastructure of the cities. Therefore, reducing the gap between the rich and poor is in the interest of a region as a whole, it increases the countries growth potentials and at the same time it will put the country on a path of improving living standards for all.

Poverty Measurement a ReviewPoverty measurement has always been a cause of public concern; the issue has gained significant importance in the era of globalization. There is a large difference in view on what poverty means and even greater differences on how to measure it. Similarly there are a number of technical issues in statistical measurement of poverty. Poverty assessment reports are usually criticized by stakeholders; due to these conceptual and methodological variations. The stakeholders are doubtful regarding the reliability of the results. What poverty measures should be used in aggregating data? Does the choice matter? These are some of the questions that policy makers should consider seriously before setting down to develop a strategy. Presenting a comprehensive guide on concepts and statistical methods for poverty measurement is beyond the scope of this chapter. The purpose of presenting a review of poverty measurement approaches is to explore conceptual views on the issue and help policy makers in deciding appropriate approach for their programs. Table (1) summarizes a few popularly used approaches for evaluating poverty in a region.


Table 1:Approaches for Measuring Poverty

Measuring Poverty Per Capita GDP Poverty Line and Unsatisfied Basic Needs Development Indices

1- Human Development Index2- Human Poverty Index

Defining Inequality The Gini Coefficient Shares of Income Inequality in Practice

Perhaps the most frequently used measure for evaluating poverty by governments is Per Capita GDP. It measures the average income per person in a country. This measure gives some information on income, but this includes extremely rich families as well as exceedingly poor families. As said earlier, the lower limit on the income is bounded by zero; however there is no upper limit on income. This gives an inflated picture of the average standard of living. GDP represents an average income for every man, woman and child in a country, but every man, woman and child is not generating this income. Further we cannot say that average income per person reflects well-being of a household. Lastly the buying power of the income may be even more or less than that indicated by the GDP, as it depends on the exchange rate used in calculating it.

Many (Saunders 2002) have argued that measuring poverty in financial terms is viewing it too narrowly. Poverty means much more than just lack of financial earning. This view promotes that poverty must be viewed in a holistic manner. The population in a region is not just poor; it is correlated with low education, health care facilities, corruption and general unrest. It is argued that simply providing the poor with additional income would not solve anything. The socio-economic system in a society must be developed to improve the performance of a community and make it sustainable in the region. Peter (SPRC 2004) has collected some alternative definitions of poverty as given in Table 2. These definitions of poverty bring out its social aspects and provide the researchers a new prospect to use social indicators for measuring poverty.

Another popular way to evaluate poverty is to use poverty line, it tries to establish a minimum level of income or consumption expenditure that a household must have so that the household is able to meet basic needs in a community. According to this method if the household income is found short of this amount, it may be considered to be impoverished.


Table 2:Alternative Definitions of Poverty

Adam Smith (1776)*‘The necessaries include not only the commodities which are indispensably necessary for the support of life but whatever the custom renders it indecent for creditable people, even of the lowest order, to be without.

Seebohm Rowntree (1899)*‘[A family is counted as poor if their] … total earnings are insufficient to obtain the minimum necessities of merely physical efficiency’

William Beveridge (1942)* ‘In considering the minimum income needed by persons of working age for subsistence during interruption of earnings, it is sufficient to take into account food, clothing, fuel, light and household sundries, and rent, though some margin must be allowed for inefficiency in spending’

Ronald Henderson (1975)*‘Insofar as poverty is defined by reference to a minimum acceptable standard of living, it is a relative concept. [It requires] a value judgment [that] must reflect the productivity of the economy and community attitudes. The task of determining a minimum standard of living is difficult given the variety of lifestyles and values in a society and the range of matters, such as food, shelter, clothing, health and education, that must be considered’

Peter Townsend (1979)*‘Individuals’ families and groups in the population can be said to be in poverty when they lack the resources to obtain the types of diet, participate in the activities and have the living conditions and amenities which are customary, or at least widely encouraged or approved, in the societies to which they belong’

Joanna Mack and Stewart Lansley (1985)*‘Poverty is an enforced lack of socially perceived necessities’

Amartya Sen (1992)*‘Poverty [is] the failure of basic capabilities to reach certain minimally acceptable levels. The functioning relevant to this … can vary from such elementary physical ones as being well-nourished, being adequately clothed and sheltered, avoiding preventable morbidity, etc., to more complex social achievements such as taking part in the life of the community, being able to appear in public without shame, and so on’*Source: SPRC 2004

Poverty lines are drawn at the national level based on expenditures, but still some argue that the picture presented is not complete (Ahmad, 2003). It is possible for some to live in poverty and enjoyed good health and enjoy a long life, but on the other hand, a person may be educated with a university degree and enjoy a good health, but may face a pre-mature death, due to illness or an accident. The Unsatisfied Basic Needs methodology advocates that living in poverty not only means the lack of material resources, but it also includes the lack of opportunity to live a normal life. This includes into poverty a life that ends prematurely, or is difficult to live, painful or risky, or even if it lacks knowledge and connections with others. This in fact, brings into discussion the


qualitative aspects of poverty. Developing qualitative indicators for poverty brings into sight the multidimensional aspects of poverty. Some basic needs indicators that can be used by countries evaluating regional poverty are given in Table 3.

Table 3:Indicators for Evaluating Regional Poverty

1. Households in homes with inadequate physical characteristics2. Overcrowded homes3. Homes without toilets4. Households with children not in school5. Households with high economic dependence6. Survival capacity

United Nations Development Programme uses a number of development indices for measuring poverty; however two of these indices are of interest here, they are: The Human Development Index (HDI) and the Human Poverty index (HPI). These methods focus on human aspect of poverty and development. Indices are a useful way to combine data type gathered from different resources into a single unit. These indices of countries can be compared to evaluate the level of poverty in different countries (See UNDP, 2006 and Ahmad et al., 2003).

The UN method uses three parameters for calculating Human Development Index. These are (1) A long and healthy life; which is measured by using life expectancy at birth (2) Knowledge; it is measured by the adult literacy rate and the gross enrollment ratio and (3) Decent living standard; indirectly evaluated by GDP per capita. United Nations also calculates two versions of Human Poverty Index, HPI-1 and HPI-2. The first index HPI-1 is used for measuring poverty in countries that are considered as developing countries and HPI-2 is used for selected countries forming Organization of Economic and Development (OEDC) countries. The HP-1 uses the same parameters as the HDI. However the statistics used to measure each parameter is different; this is because HDI-1 is designed to measure the lack of performance of the same parameters. It is calculated by measuring (1) Long and healthy life, measured by probability at birth of not surviving to age forty. (2) Knowledge that is indicated by adult illiteracy rate and (3) Decent living standard indicated by percentage of population without access to an improved water source and the percentage of children who are underweight for their age.

Data from Human Development Report 2006 (UNDP 2006) gives pretty true picture on the human side of poverty measurement and when these figures are complemented with GDP per capita figures for the same country; an interesting insight is gained. Table 4 gives the HDI and GDP per capita for selected countries for the year 2004. The graph for the same data is shown in figure 1.


Figure 1:Human Development Indices Selected Countries for the year 2004

Source: UNDP Human Development Report 2006

The data shows that the Czech Republic has HDI index of 0.885 with GDP per capita US$ 19,408, where as United Arab Emirates which has a much higher GDP per capita of US$ 24,056 stands lower on HDI index at 0.839. In other words people living in Czech Republic despite earning lower income than those living in United Arab Emirates are living a better quality of life. The quality of life in Bahrain is the same as in Chile. Both countries having HDI of 0.859, but the GDP of Bahrain is double than Chile. Similarly the quality of life in Pakistan with GDP per capita of US$ 2,225 is the same as of those living in Bhutan with considerable lower GDP per capita of US$ 1,969.

Table 4: Human Development Index and GDP Per Capita

Selected Country Data for the Year 2004

Country HDIGDP Per Capita

(PPP US$)Czech Republic 0.885 19,408United Arab Emirates 0.839 24,056Chile 0.859 10,874Bahrain 0.859 20,758Pakistan 0.539 2,225Bhutan 0.538 1,969Angola 0.439 2,180Tanzania 0.430 674

Source: UNDP Human Development Report 2006

Angola and Tanzania have Human Development Index scores of 0.439 and 0.430 respectively, but their GDP per capita have significant difference. This shows that HDI


presents the social aspect of poverty in a much better form than that can be assessed by viewing GDP figures. The GDP figures therefore should not be viewed or reported in isolation.

The size of the middle class plays an important role in economic development of a country. Measuring inequality is also used by researchers to evaluate poverty in the society. The difference between those with the highest income and those with the lowest has significance effect on economic development. The Gini Coefficient is calculated to measure how unequal the income distribution in a country is. It is developed from first drawing Lorenz curve, showing the total national income held by each percentage of the population. If a country has perfectly equal income distribution, the Lorenz curve drawn would be a straight line with a 45- degree angle. It is expected in this case that the poorest 10% of population would have 10% of the income, the poorest 20% would have 20% of the income and so on. It is understood that no country can have perfectly equal income distribution. It is always that the poorest 10% have less than the 10% of income and the richest have more income than their percentage predicted by Lorenz curve. Therefore a typical Lorenz curve for a country will bend below the 45-degree line. The Gini coefficient is calculated by computing area between the Lorenz curve and the 45-degree line and then dividing it by the area between 45-degree line and the horizontal line. Gini value close to zero indicates a relatively equal distribution of income, while Gini value close to one equal indicates highly unequal income distribution in a society.

Relative share of the income of the rich and the poor members of a society can also be an indicator of inequality. The poorest population in a society is unable to earn income according to its share. This means that the poor will remain poor in that society. And at the same time, the system is providing rich, better opportunities for earning higher income.

Inequalities are not limited to income inequalities only. Gini coefficient and income-share inequality numbers provide a fair picture of ground realities, but still there is more to poverty than these numbers can give. The quality of basic services like health, education and rule of law provided to the majority population gives a picture ofinequalities in practice. The poor members of society may have a greater need for health services as they are at a higher risk of getting sick due to lack of clean drinking water and sanitation conditions. Similarly poor population may have higher mortality rate due to lack of medical care and low nutrition, but in practice they may not be getting their due share of these services from the governments. Education can play an important role in alleviating poverty in a region, as level of education in a society is increased it becomes more productive. It also plays a role of catalyst in improving effectiveness of health awareness programmes. The condition of Law and Order System of a society and its practice plays a vital role in development of a society. If a law in practice treats poor and rich differently, the society can not develop.

The New Wealth of Nations It has been more than two hundred years, when Adam Smith (1976 referred to by UNDP, 2003) acknowledged the potential role of manufacturing in economics of a society. The world has now entered an era, in which the wealth of nations is dependent on its ability to create, transform and capitalize knowledge. The era of Knowledge-based industries have


arrived. The science and technology sectors are expanding faster than most of the other Industries. This rapidly increasing demand for knowledge-based products and services is changing the structure of global economy, and transforming the economic infrastructures of many countries. There is general consensus that in the new economic paradigm

1) The wealth of a nation is not limited to its natural resources any longer. Traditional national assets like oil, minerals, agricultural and manufactured products are now complemented with a new nontraditional category of resources in the form of intangible asset.

2) Knowledge is a primary competitive factor in economy today.3) The accumulation, transformation, and value creation from knowledge require

active and voluntary participation of intellectuals. Therefore, countries should adopt strategies to maximize an environment of collaboration.

Employee know-how, innovative capabilities, skills are the brainpower of an organization, playing a predominant role in productive power of the corporation. The human resources account for an increasing proportion of the capital generation in industries (Sveiby 1997). Empirical studies suggest that major percent of the value created by a firm comes, not from management of traditional physical assets, but rather from the management of its intangible assets (Prusak 2001, Sveiby 2002).

Sveiby (2007) has compiled thirty four methods for measuring intangibles assets, he extends the classification method originally suggested by Luthy (1998) and Williams (2000) and categorizes them into four classifications. (1)Direct Intellectual Capital methods (DIC); this estimates the $-value of intangible assets by identifying its various components. (2)Market Capitalization Methods (MCM) calculates the difference between a company's market capitalization and its stockholders' equity as the value of its intellectual capital or intangible assets.(3) Return on Assets methods (ROA); it is average pre-tax earnings of a company for a period of time, divided by the average tangible assets of the company and lastly, (4) Scorecard Methods (SC) in this various components of intangible assets or intellectual capital are identified and measured by developing indicators and indices. A report is generated and reported in scorecards or as graphs. Measurement methods offer different advantages. The ROA and MCM methods are useful for analyzing merger & acquisition situations and can also be used for stock market valuations. The SC methods create a comprehensive picture of an organisation’s health than financial figures alone. Selected methods for measuring intangible assets are compiled in Table (4). It gives some of the recognized methods for evaluating intangible assets. There is a great variety in the approaches, as each method has its own strength and focus for evaluating intangible assets.

Malhotra (2003) has discussed methods for measuring intangible assets of nations extensively, he has modified Balance Scorecard (Kaplan and Norton 1992) to suggest a framework for measuring and managing knowledge assets of a nation. Skandia Navigator is also used by some researchers (Edvinsson and Malone 1997) for measuring and developing national policy initiatives. Bontis (2001, 2004) has also discussed methods for measuring intangible assets. The authors of the chapter however, prefer to adopt Intangible Assets Monitor (Sveiby 1997) for measuring the wealth of nations.


After a careful review of methods for measuring intangible assets, the authors here suggest to extend the model of Intangible Asset Monitor (Sveiby 1997) and use it for assessing the wealth of nations. Figure 2 gives a suggested framework for measuring national wealth of nations in the new economy. The authors suggest that total wealth of a country may be viewed as sum of its tangible and intangible assets.

The tangible assets of a nation would include traditional resources of nations like forests, mineral resources, oil, factories, infrastructure, agricultural and material products. Assets that are tangible are recorded under this category. But the wealth of a nation is not limited to tangible assets only; there are assets besides these tangibles assets in a nation. These assets are classed as Intangible assets. The Intangible assets are further classed into three categories; which are (1) External Structure (2) Internal Structure and (3) Competence.

Table 4:Selected Methods for Measuring Intangible Assets

Approx. year Label Major Proponent

2004 National Intellectual Capital Index Bontis (2004)2002 IC Rating™ Edvinsson (2002)2002 Value Chain Scoreboard™ Lev B. (2002)2000 The Value Explorer™ Andriessen & Tiessen (2000)2000 Intellectual Asset Valuation Sullivan (2000)2000 Total Value Creation, TVC™ Anderson & McLean (2000)1999 Knowledge Capital Earnings Lev (1999)1997 Market-to-Book Value Stewart (1997), Luthy (1998)

1997Value Added Intellectual Coefficient (VAIC™)

Pulic (1997)

1997 IC-Index™Roos, Roos, Dragonetti and Edvinsson (1997)

1996 Technology Broker Brooking (1996)1996 Citation- Weighted Patents Bontis (1996)1995 Holistic Accounts Rambøll Group1994 Skandia Navigator™ Edvinsson and Malone (1997)1994 Intangible Asset Monitor Sveiby (1997)1992 Balanced Score Card Kaplan and Norton (1992)1990 HR statement Ahonen (1998)

1988Human Resource Costing & Accounting (HRCA)

Johansson (1996)

1950’s Tobin’s q Tobin J. Source: Adopted from Sveiby 2007

The External Structure includes a nation’s external relations, its trade agreements like FTAs, RTAs, defense pacts, participation in international bodies, the image of a country in international community etc. The value of these assets would show in the form of influence the country is able to exercise internationally and solve its issues in global


aspects. The Internal Structure of a country, that adds to a national wealth include all that may promote collaboration, knowledge sharing and innovation in a country. Therefore the internal structure of a country would include functioning of justice system, democracy, education system, health system, right to information and freedom to form associations, basic human rights etc.

Figure 2: A Framework for Measuring Wealth of Nations

The third category of Intangible assets is “Competence”, at national level this asset category would include literacy level in a country, the quality of research activity taking place in the country, working of professional associations. The list in the above three Intangible asset categories is not limited and can be expanded.

Developing Poverty Eradication Policy in Knowledge EconomyDevelopment economists, policy makers and social scientists are well aware of interdependent nature of national policies. Initiatives taken to improve literacy under education policy are beneficial not only for health related initiatives, but they also strengthen economic activities in a region. Similarly, foreign policy of a country cannot work in isolation; it will have corresponding effect on the country’s trade policy.

The authors therefore suggest, developing a policy matrix instead of a single policy for initiating poverty reduction actions. The policy makers may evaluate the assets of a nation using the framework and then, develop policies to build-up the tangible as well as intangible assets of a nation. Once a nation starts to progress by building its intangible assets, the human development index (HDI) of the country would also start to improve, meaning that quality of life in the region would recover. It would also have a positive outcome on business opportunities in the region.

The authors have extended IAM (Intangible Asset Monitor) by Sveiby (1997) and used it for monitoring national assets. (Figure 3)

National Wealth

Tangible Assets Intangible Assets

1- External Structure2- Internal Structure3- Competence


Figure 3: A Policy Matrix for Enhancing National Assets

TangibleAssets

Intangible Assets

ExternalStructure

InternalStructure

Competence

Str

ateg

ic I

mp

erat

ives

and

Pol

icy

Pri

orit

y GrowVolume

Innovate/Renew

UtilizeEfficiently

MinimizeRisk

Developing a poverty reduction policy based on the policy matrix (figure 3) is beyond the scope of this chapter. Therefore the authors have limited themselves to developing a framework only and not gone ahead with developing indicators. In practice the policy makers would first have to develop indicators for assessing the status of each category of intangible asset of a country and then in the light of these indicators, the policy makers may propose initiatives for building the assets. The policy developed should include efforts to renew, improve utilization and minimize risk of loosing these national assets.

CONCLUSION

Poverty is a multifaceted socio-economic phenomenon which cannot be measured in financial terms alone. It is more closely related with quality of life of the people living in a region than simply the earning capacity of the population. Low income in a region is the result of low performance of its social systems; not the poverty itself. In other words, low income is the effect of poverty and not a cause itself.

Therefore, policies target at increasing the financial earning alone would never be successful in raising a region out of poverty. Policies should be designed to improve the social system as a whole. This is not something that can be attained in a short time or with a little effort. A continuous focus and growth in the right direction is needed for development of a sustainable socio-economic system.

REFERENCES

Ahmad, Munir; Ahmad, Akhlaq and Afzal, Shahzad (2003). Population and Environment. Book on “Population of Pakistan – An Analysis of 1998 Population and Housing Census” (Editors: A.R. Kemal, Mohammad Irfan and Naushin Mahmood), Pakistan Institute of Development Economics and UNFPA, Islamabad, Pakistan. 383-409

Bontis, Nick (2001). Assessing knowledge assets: A review of the models used to measure intellectual capital, International Journal of Management Reviews, Vol. 3: 1, 41-60.


Bontis, Nick (2004). National Intellectual Capital Index: A United Nations initiative for the Arab region, Journal of Intellectual Capital, Vol. 5:1, 13-39.

Edvinsson, Leif and Malone, Michael (1997). Intellectual Capital - Realizing your company's true value by finding its hidden brainpower, Harper Collins New York.

Kaplan, Robert and Norton, David (1992). The balanced scorecard - measures that drive performance, Harvard Business Review, 70, 1, 71-9.

Luthy, David (1998). Intellectual capital and its measurement. Available Online: http://www3.bus.osaka-cu.ac.jp/apira98/archives/htmls/25.htm

Malhotra, Yogesh (2003). Measuring National Knowledge Assets: Conceptual Framework and Analytical Review, United Nations Department of Economic and Social Affairs, Ad Hoc Expert Group Meeting on Knowledge Systems for Development. New York, 4-5 September 2003.

Prusak, Laurence (2001). Where did knowledge management come from? IBM Systems Journal, Vol. 40, No 4. 1002-1007.

Saunders, Peter (2002). The Ends and Means of Welfare. Coping with Economic and Social Change in Australia, Cambridge University Press, Melbourne.

Solow, Robert (1999). Notes on Social Capital and Economic Performance, Journal of Economic Literature, Vol. XL (March 2002), 139-154.

SPRC (2004). Social Policy Research Towards a Credible Poverty Framework: From Income Poverty to Deprivation. 1-18.

Sveiby, Karl and Roland, Simons (2002).Collaborative climate and effectiveness of knowledge work - an empirical study. Journal of Knowledge Management, Vol. 6: 5, 420-433.

Sveiby, Karl (1997). The New Organizational Wealth: Managing and Measuring Knowledge Based Assets. San Francisco: Berrett-Koehler.

Sveiby, Karl (2007). Methods for Measuring Intangible Assets: [available on line: site visited 12/15/07] http://www.sveiby.com/Portals/0/articles/IntangibleMethods.htm

UNDP (1990). Human Development Report, Concept and Measurement of Human Development. 9-16.

UNDP (2003). Poverty Reduction and Human Rights. A Practice Note, 2-14.

UNDP (2006). United Nations Development Programme, Human Development Report 2006, 1-24.

Williams, Mitchell (2000). Is intellectual capital performance and disclosure practices related? Journal of Intellectual Capital, Vol. 2 No.3, 192-203.

World Bank (1990). World Development Report. World Bank. Washington D.C. USA.

World Bank (2007). World Development Report. World Bank. Washington D.C. USA.


About the Authors

Suleman Aziz Lodhi, joined the Public Health Engineering Department (Pakistan) in 1995 as Assistant Director MIS and worked on community development projects. It was during this time that he developed a keen interest in community development and sustainability issues. He later joined secretariat of a premier trade association and headed its Economic Research Cell. Presently, he is working with academia after completion his Ph.D. in Knowledge Management. His present research interests include knowledge economy, community development and social network analysis.

Munir Ahmad, born in Sialkot, studied in Murray College, Sialkot, Institute of Statistics, University of the Punjab, Lahore, and taught at University of the Punjab, Karachi University, Karachi and Michigan Tech. University, Houston, Michigan, USA. He did his post graduate degree at Aberdeen University, Aberdeen, UK and Ph.D. from Iowa State University, USA. He is the author of more than 150 research papers published in national and international journals. He is currently working as Rector. National College of Business Administration and Economics and Professor of Statistics in the School of Business Administration and Economics. His area of research is statistics, population, data neural network, and various management sciences.

15

CHAPTER 2

CRITICAL RESOURCES FOR POOR FAMILIES: A critique of the United Nations Millennium Development Goals

Sally Bould, Ph.D.Senior Research Fellow, Centre for Population,

Poverty and Socio-Economic Policy Studies, Differdange, Luxembourg and Professor Emerita, University of Delaware, Newark, Delaware 19716 USA

Email: [email protected]

ABSTRACT

This paper proposes an anti-poverty approach of enabling poor families to be more productive and enabling poor children to attain education. Opportunities provided by globalization are problematic because they are in the formal labor force where combining child care with productive activity is no longer possible. The Millennium Development Goals of reducing extreme poverty and hunger, and promoting education and health require a focus on families but the MDG goals are limited to enabling individuals. The idea that enabling individuals can accomplish these goals leaves out families where children need care.

A gender equity approach has focused efforts on empowering adult women rather than on women in poor families. But for poor mothers income plus child care (including pre-school education) is the only way these mothers can empower themselves and their children and hope for a future without poverty.

The history of a child care organization Care, Health and Education for Children in Poverty (CHECP), located in South Asia illustrates the problems faced by NGO’s in providing child care. The conclusion proposes a structure of sustainable child care programs and the critical role of funding by international donor agencies.

Keywords: Millennium Development Goals, child care, gender equality, poor families, child health, education, sustainability.


INTRODUCTION

The dominant anti-poverty model in the United Nations is reflected in the Millennium Development Goals (MDG) and the position of Jeffrey D. Sachs, Director of the UN Millennium Project. This paper questions first, the anti poverty efforts of the MDG and, second, the “simply add money” formula of Sachs (2005a). The first, because the MDG does not deal with issues faced by poor families and the second because there is no evidence that simply adding money solves these problems, at least not without careful program planning (Easterly, 2006). What is required, rather, is a careful examination of the situation of poor families and their needs and an understanding of how to set up programs that are sustainable in the difficult political and financial environments of poor communities. This proposal is informed by research at a child care center, Care Health and Education for Poor Children (CHECP) in a South Asian country, (Cf. Bould, 2006a). This paper will address why child care programs may be one of the most effective ways of meeting the Millennium Development Goals of a) eradicating extreme poverty and hunger; b) achieving universal primary education and c) reducing child mortality.

Eradicating extreme poverty and hunger MDG 1Globalization can provide opportunities for more productive activities, especially for poor women. These opportunities, however, are problematic because they are in the formal labor force where combining child care with productive activity is no longer possible. All able-bodied adult men and women in poor families need to be productive to achieve a better standard of living. Able-bodied grandmothers are more productive working than in providing child care. Productivity of women can be enhanced by taking some of the domestic caregiving tasks for young children out of the family.

The economic activity of women in the developing world has changed dramatically in the past 50 years as women have entered the paid work force. Working as a traditional unpaid family worker or an own account worker allowed the woman to combine traditional economic activity with child care. Work settings and working conditions were set by tradition in such a way that women made their economic contribution to the family at the same time and place as they took care of children. With the development of the market economy, the growth in landlessness and now globalization, this traditional approach to child care is no longer viable for economically active women. The alternative, which is the expectation of the economists, is that there will be a grandmother or other adult woman family member available for child care. (1) Although this is often the case for better off families, it is either not available or an inappropriate solution for poor families. First, these families still face high death rates as well as high rates of disability. Grandmothers, if they are still alive, are not likely to be fully able to care for the young children. And if the grandmothers are able, they are likely to be working as well. In poor families all able bodied adult members need to work. Providing child care can effectively increase the productivity of women in poor families and thereby decrease hunger and poverty.

Universal primary education MDG 2Child care decreases the need for economic activity by children. Providing child care is especially critical for the education of girls, as it is typical that when poor families need child care, the girls are kept home from school to perform this task. This relationship can


be seen with the reaction to the financial collapse in Argentina. The government, in order to meet the requirements of the international organizations, specifically the International Monetary Fund (IMF), cut back spending on social services and cut back on child care programs. The effect was a drop in school enrollment for girls from poor families (UN, 2000, p. 4). There is similar evidence from other countries concerning how girls from poor families are kept at home to help with child care (Cf. UNICEF, 2006 p. 41). Achieving the goal of universal primary education involves providing access to education for poor children, and especially poor girls; the case of India is an example where efforts at universal enrollment rates have failed precisely because of the failure to sustain enrollments of poor children. Poor girls 6-14 years old in India in the early 90s had an enrollment rate of only 37.5%; poor boys did better at nearly 50%. During the 90s the overall dropout rate declined only marginally and girls still had higher dropout rates (Pal and Ghosh, 2007, p.340). Studies in Ghana and Cote d’ Ivoire (Cf. Hyde, 1993 p. 112) and India and Bangladesh (Cf. Kahn, 1993, p.228) show that social class is the most important factor in predicting girls education. What is limiting the participation of poor children, especially girls, in the education system? For India, Pal and Ghosh (2007, p. 340) argue that it is a lack of supplies, teachers and buildings, but with the exception of toilets (Kahn, 1993, p. 231), these factors are not likely to be decisive for girls from poor families attending primary school. (2) Much more critical for these families is likely to be the need for girls to perform child care (Cf. Tara, 1985). The government of Morocco supports pre-school education for ages 4-5 because it “is a means of generalizing education,” [and]…It frees elder brothers/sisters from taking care of younger siblings and engenders continuing longer at school and increases the probability of girls being schooled and having access to waged jobs.” (Kingdom of Morocco, 2006).

There is another factor which limits the school attendance of poor children. Poor children are likely to have the most difficult time making the transition to primary school. This is especially true for poor minority families (Kahn, 1993, p. 226). The case of CHECP illustrates this problem as the families are not only poor, but also of the Delit caste. These poor children are now accepted in the government school system but due to their caste status they are not welcome at school, especially by their fellow students. Their parents can help them neither with their school work nor with the school bureaucracy. Here CHECP (3)has played a critical role in preschool education, after school programs and helping parents communicate effectively with school officials. Preschool education means that the poor child enters primary school with a background and an experience of attending preschool which makes the transition to primary school easier. Furthermore, the pattern of school attendance is begun at ages 3-5, when it can reduce the mother’s burden. Then, when the child is old enough to help the mother, the pattern of school attendance is already well established and less likely to be broken. In terms of sustaining primary school enrollments, after school programs can provide critical help with homework that poor parents are not able to provide. CHECP provides this help with homework as well as intervening with the school bureaucracy on behalf of the student.

The United Nations (UNICEF, 2005a) fails to understand these problems of enrollment for poor children as seen in the assumption that past progress in the Islamic world can be projected in to future success. In the case of Egypt, high levels of success from 1980 to 2001 are reflected in the rapid increase in girls’ enrollment. Now the


enrollment rate of girls in primary school is 90% (UNICEF, 2005a, p. 15). But enrolling the final 10% of girls will be much more difficult due to the fact that these are the poorest families who are most likely to need the labor of the girls. In addition these poor families are least able to help their children in the transition to school. Poor children and especially poor minority children face difficulties in the transition to school and school attendance even in the United States. In the United States, however, the Head Start program during the preschool years has enabled many poor minority children to achieve in school (Cf. Vinovskis, 2005).

What is needed is a broader perspective in understanding the issues of poor families with respect to school enrollment and sustained school attendance. Simple solutions, such as making the school more attractive, or even paying the family to send the children have not been very effective. Preschool establishes a pattern of attendance during the early years when it helps the poor family. It also prepares the child for school, a task that can be problematic for poor illiterate parents. Understanding school enrollment and school attendance requires an analysis of families in countries which have provided the opportunities for schooling, but have not understood the disappointing results.

Reducing child mortality- MDG 4The goal of child health for poor families can best be met at day care and preschool centers. The challenge of child health is often one of health service delivery for poor families. If delivery requires that the poor mother add this task to her domestic burden, then she may be overwhelmed and/or have to lose productivity. If health care is delivered by a home visit from nurse, then the delivery of primary health care becomes too expensive. A key obstacle to lowering child mortality is the fact that poor mothers access health services only when the disease reaches emergency levels and the child is already at risk of death. Child care allows the staff to be in constant contact with the children and their mothers and they can identify problems, e.g. diarrhea or respiratory distress syndrome before they become life threatening. They can also provide the mothers with the necessary health education for prevention. CHECP began as an effort to reduce child mortality; it has been very successful in achieving that goal through health education and service delivery. When the program first started in the mid 1970s children at CHECP were suffering from severe malnutrition and worm infestations. First, CHECP established feeding programs and then set up a day care center in 1977 with special attention to nutrition and provided treatment for worms. Children are now much better nourished and the problem of worms is under control. Day care and preschool can provide access to health care and health education for poor families not by adding to the mother’s burden but by subtracting from it.

There is also another reason that day care can contribute to the health and safety of the children of poor women. These women typically work in “wage employment in informal jobs (that is without secure contracts, worker benefits or legal protection)” (UNRISD, 2005, p. 76). The mother has to go to work even if she cannot find adequate child care, even if she has to leave her young children alone, even if the child is sick; if she does not go to work she is likely to lose her job and therefore be unable to feed her family. Young children are exposed to accidents, accidents which could have been prevented with adequate child care.


As the discussion above illustrates, child care and preschool programs are essential in achieving the Millennium Development Goals (MDG), of eradicating extreme poverty and hunger (Goal 1); achieving universal primary education (Goal 2); and reducing child mortality (Goal 4). These three goals require a focus on poor families but the MDG goals are conceptualized as “enabling individuals” not as enabling families. The focus on children’s primary education is important, but it does not take into account the family situations which may limit the child’s educational opportunities as well as the child’s access to health care. An emphasis on child health care which requires additional demands on the time of poor mothers is likely to reduce their productivity and the family’s access to income and food. The United Nations Millennium Project has engaged 250 experts in 10 thematic task forces but has failed to attend to this simple fact that poor individuals and children live in families (Bould, 2006b).

Gender Equity Goal 3The difficulties in achieving goals 1, 2 and 4 must also be understood in the context of discussions of Goal 3: Promote Gender Equality and Empower women. In the UN material there is an overwhelming focus on Goal 3 but this goal has been defined without serious consideration of women’s family roles. Women are analyzed as individuals, not as mothers. This obscuring of family responsibilities has a most critical negative effect on poor women. The Gender and Development (GAD) perspective envisions “Mainstreaming a gender perspective [is] the process of assessing the implications for men and women of any planned action, including legislations, policies and programmes.” (United Nations, 1999, p. ix). Gender Equality is defined by the United Nation MDG in terms of three domains (1) “capacities… fundamental to individual well being..” such as education; (2) “access to resources and opportunities…”, such as employment and (3) “security” from violence and conflict (UN Millennium Project, 2005, pp. 31-32). The indicators of this gender equity are enrollment ratios, literacy ratios and women’s share of wage employment (4) as well as women’s share of seats in parliament. These measures have been judged to be remarkably narrow (Saith, 2006, p. 6). Women’s family roles enter into the discussion only in their role as victims of family violence.

The UN Millennium Project, Task Force on Gender Equality prepared by a group of 27 leading experts discusses child care on only one page out of 257 pages of the report (2005: 97). In the section on “making it happen” there is no discussion of child care. Instead the report recommends studying women’s poverty, doing a gender analysis, and developing a gender-aware public spending documentation as well as a public sector management strategy. Jeffery Sachs lauds the report and its recommendations (2005b, p. iv). Meanwhile it is clear that poor women need child care and poor children need preschool education. Ignoring these immediate needs, while studying and planning, leaves these women and their children at risk. Another discussion of Goal 3 by Kabeer (2003) makes no mention of child care even though it discusses poverty eradication. Similarly a UN report on the situation in Latin America by Daeren (2001, p. 15ff.) focuses on better access for women to the labor market and the need for “Greater compatibility between paid work and family responsibilities” but without any references to the child care needed by poor and working class women. In the UN publication, Gender Equality (UNRISD, 2005 p. 52-54) the section on “Trends in gender differences


in access to opportunities and resources” there is no mention of child care. (See also Kasente et al, 2002).

Ironically, it is primarily in reference to developed countries that the United Nations publications discuss child care. . The 2006 UNICEF publication on the State of the World’s Children discusses “A childcare crisis in the formal sector” (pp. 41-42), but almost all of the references are to research in developed countries. A discussion of “family friendly workplaces” is restricted to industrialized countries only (p. 43). In reviewing the experience of four countries with work and family issues, the Division for Social Policy and Development of the United Nations (2000) discusses child care at length only in the Netherlands, a developed country where poverty has been virtually eradicated by United Nations standards. In the section on “Women, work and social policy” in Gender Equality (UNRISD, 2005, pp65-140) there is no discussion of child care with the exception of the OECD countries where there are vague references to “institutions ” and to nannies (pp. 69-71). Otherwise this section discusses only the rapid increase in women’s work force participation without any reference to what happens to their children (Bould, 2006a).

The gender equality approach of Goal 3 has obscured the needs of poor women by focusing efforts on “empowering adult women”. This “new” analysis at the UN downplays the dimension of economic resources by focusing on women’s need for power and status. In the UN publication, Understanding Poverty from a Gender Perspective,from the Women and Development Unit, one group cautions against a focus on material deprivation measures of poverty because:

….policy makers risked ending up with poverty reductions strategies which were designed to impact on the situation of women, but neglected to alter gender conditions. This would lead the State to prioritize the satisfaction of women’s practical and immediate needs, while ignoring their strategic interests and thus reinforcing the cultural patterns and objective conditions that perpetuated gender inequality. (United Nations, 2004, p.57)

This new approach emphasizes dignity, self-respect and self-esteem which are all important dimensions in the lives of all women and men. But for poor women these aspects are not within reach if they cannot feed their families. A poor woman gains respect and self-esteem by contributing to the economic well-being of her children and other family members (Ahmed and Bould 2004). This new criticism of the money measure of poverty does not take into consideration that self-esteem is a dependent variable, not an independent variable (Cf. Weber 1963; Endeley 2001).

A recent criticism in a UN document of the “feminization of poverty” is that “it prioritizes income over other forms of deprivation” (Chant 2003, p. 28). She continues her argument in that:

… the preoccupation of women and income in the feminization of poverty thesis is dangerous for two main reasons: one, because, analytically, it occludes the social dimensions of gender and of poverty and two, because in policy terms, it translates into single-issue, single group interventions which have little power to destabilize deeply-embedded structures of gender inequality in the home, the labour market, and other institutions” (Chant, 2003, p. 30 )


Although it is true that the feminization of poverty leaves out men there are serious problems with Chant’s argument. The first problem is that all persons, men and women and their children, who live on less than $2 a day must prioritize income and the second is that what feminizes poverty is women’s child care burden (Starells, Bould and Nicholas 1994). Poverty reduction programs need to focus on immediate needs of poor families, and this means the material needs of poor women and children.

Most serious, however is the reason, seemingly dominant in the UN “gender equality approach,” which is an emphasis on the need to “destabilize deeply embedded structures of gender inequality in the home, the labor market and other institutions.” Unfortunately child care programs are often viewed by strict gender equality advocates as only reinforcing women’s gender roles in the care of children. The UN Committee on the Elimination of Discrimination against Women (CEDAW), responding to the Government of Bulgaria’s report, declared that the UN Committee “considered that the persistence of the emphasis on women’s role as mothers, together with the extensive protection provided to women as mothers, tended to perpetuate sex role stereotypes…” (As cited in European and North American WomenAction, Bulgaria Report. 2000, FN 2 p. 6). In their evaluation of a Mexican anti Poverty program Progresa/Oportunidades the gender experts criticize the program for not involving fathers in taking children to school and to local health clinics (UNRISD, 2005, p.138). But involving fathers still is an illusive goal in developed countries. It would be better to simply focus on the additional burden these programs put on poor mothers, and to examine how the mothers’ burdens could be reduced in the short term by child care and preschool centers.

Examining countries that have implemented the goal of “destabilizing deeply embedded structures of gender inequality” (Chant, 2003) show that it is a very problematic goal. But in countries like Sweden, where there is no child poverty by UN standards, the goal of changing gender structures is appropriate, even if difficult (Cf. Horelli and Vespa, 1994). To ask that poor developing countries confront this as a priority goal is to ask the poor to wait for the destabilization of gender inequality before asking for the material basis of their survival. Providing child care for poor mothers would not change the mothers’ responsibilities for child care; it would only help poor mothers with their burden of child care and enable them to be more productive. The goal of gender equality in the provision child care is an appropriate goal for a country like Sweden, with universal access to excellent child care and preschool and no serious child poverty; it seems hardly appropriate now for developing countries.

While the UN documentation claims that there is a “double dividend of genderequality, “ (UNICEF, 2006) the way gender equality is being defined in Goal 3, puts in conflict with Goal 1: The elimination of extreme poverty and hunger. Pro gender budgeting is not the same as pro poor budgeting (United Nations, 2005). Furthermore, pro gender budgeting and gender equality in the labor force are factors which can increase overall inequality in a society because marriages tend to be homogamous with respect to economic status; women with good jobs will marry men with good jobs, and women with low wage jobs will marry men with low wage jobs (Bould, 1984). And increasing inequality can lead to increasing poverty unless special efforts are made to protect the poor in the context of growing inequality and rising rates of inflation. The


poor could be protected by programs of pre-school and child care but such programs are generally not a factor in pro poor budgeting nor in pro gender budgeting.

Why is child care not in the forefront of the UN agenda?The above review of the discussion of Goal 3, Gender Equality, indicates that the only serious discussion of child care by UN staff occurs in Western Europe. Ironically, this is the region of the world with the lowest levels of poverty. There appears to be a relationship between low levels of poverty and a high attention given to child care. Child care is on the agenda in Western Europe because women who work on policy issues do not have a large labor pool of poor women available to provide in-home care. Child care issues, however, are less likely to be high on the agenda of women who work on policy issues in developing countries because they do have access to in-home child care provided by poor women. In addition, middle class women in developing countries have often had access to grandmothers, and other female family members for child care as these families can afford to have non-economically active members. Only now, with the opportunities in developing countries for other forms of work for poor women and life long professional work for middle class women, is child care becoming a problem for middle class families. At a conference in India, the professional women who were grandmothers were worried about the care of their grandchildren but not ready to quit their jobs to provide care.(5) The worst case scenario for this new labor shortage for domestic workers occurs in India with the use of children from poor families as domestic helpers (Gentleman, 2007, p.8). These child laborers are the new supply of domestic in-home help and this domestic help is classified as one of the worst forms of child labor. It puts children of the poor in potentially abusive conditions and without access to schooling.

In the town of “Sangupur” where the research on CHECP took place, the availability of poor women for in-home child care has been sharply reduced by the opportunities now available for factory work. In response, a private day care center was established where infants and preschool children are provided with excellent care. The young mothers work in middle class jobs nearby and pay for the full cost of care. But in the private day care marketplace, there is no way that poor mothers can afford the full cost of care. Now there are opportunities for middle class women and poor women to work together to provide this essential service, a service which enables poor women to be come more productive and for their children to have a better life; it also eases the concerns of middle class mothers and grandmothers about the care of the family’s young children.

Making it happen: problematic approaches Jeffery Sachs (2005a) proposes that the solution to poverty primarily requires more money. It is true that money will be needed to provide these essential services for poor families. But critics have pointed out that a lot of money has already been spent and the results have been disappointing (Easterly, 2006). It part, programs have been based on misguided assumptions but also there is the question of who benefited from these programs. Evidence suggests that little of this money trickles down to the poor, and much of it is siphoned off in corruption. One response to this issue has been a recent emphasis on privatization (Phillips, 2003). But privatization is usually not an effective way of


reaching poor families. In terms of day care and preschool programs, privatization only works for middle class families, as poor families can not afford to pay for care.

Sustainability is another popular approach of funding organizations. They want their programs to be “sustainable” after their initial funding. “No funding organization wants to adopt a program” (Kiritz and Mundell, 1988). This model works well where the program can generate its own income such as in micro credit programs. It is also assumed to work well for short training programs. These “sustainable” programs leave the funding agency free of any long term commitments and able to move on to the next fashionable idea. But it is precisely a long term commitment which is needed by day care and preschool programs if they are to be effective.

In the case of CHECP there was long term commitment and funding from 1977 through 1993. The record of accomplishment during this period was impressive with respect to reducing hunger and child mortality, increasing child health and nutrition, and getting these poor minority children prepared for, enrolled in and attending school. The program also enabled poor families to take adequate care of their children which resulted in closing down the orphanage. CHECP was registered as a Non Governmental Organization (NGO) with full legal status and in 1994 it took over the management responsibility as well as funding responsibility. This move was celebrated as one of ending the paternalistic relationship with the funding agency. (6) The funding agency continued to support the program for several more years until a problem with the management of the finances occurred.

Local control sounds positive in theory, but in practice it leaves the organization vulnerable to local politics, corruption and graft. This issue is not just a problem in developing countries, but for poverty programs in the United States as well. In the case of CHECP, some years after local control was established the funding agency noted that there were irregularities in the organizations finances. Around this time a fire destroyed all the financial records and the funding agency cut all ties with the organization. In addition, the ownership of the assets of the organization is now questioned. What had been a clear ownership became murky, restricting the organizations ability to take out a loan. (7) The model of autonomous local control is too vulnerable to local politics and local power grabs for it to be sustainable. The role of overseeing the finances of an organization needs to be shared with the international funding agency that must step in and help at critical junctures rather than simple wash its hands of the problem. Ongoing monitoring and support is required to sustain these programs, not only in assuring adequate funding, but also in order to prevent or at least reduce graft and corruption. Funds must be monitored with checks and balances to prevent disabling levels of graft. Furthermore, if corruption does occur, then the funding agency needs to step in and help deal with the issue, rather that just letting go and giving up. In the case of CHECP local control has put the poor children at risk; it may have to close its doors and leave the children outside (Bould, 2006a).

Making it happen: The role of the stateNational polices which provide funding for child care and preschool are widely available in Western Europe. The role of the national government in subsidizing child care is also evidenced in Latin America, notably Chile, Argentina and Mexico( 8). Unfortunately,


these are the areas of spending that the International Monetary Fund (IMF) targets for reduction in a fiscal crisis. One way this spending cut is accomplished is by limiting the hours of care available. While this approach may still provide preschool a few hours a day, it is severely limited in the goal of enabling the mothers to be more productive since the hours of child care available do not match existing jobs in the formal labor market.

In Mexico, the program Progresa/Oportunidades provided child centered programs which did not increase the productivity of the mothers. In this case the mothers were “paid” to be sure the children attended school and got health care. But this only added to the mother’s burden without increasing her productivity. It also excluded families, probably the most needy, who could not manage to get their children to school and to health clinics. (UNRISD, 2005, p. 139). Preschool programs could prepare children and their mothers for future school attendance, provide health care, and enable the mothers to become more productive.

For poorer developing countries, however, national governments must focus their budgets on basic health and education. The responsibility of moving ahead with child care and preschool programs should be the focus of international donor agencies and organizations. As long as the United Nations policies overlook families and bifurcates their programs into gender equity on the one hand, and children on the other, the problems that face poor families will be overlooked.

Making it Happen: Partnerships with funding organizations The United Nations needs to reset the agenda to address the needs of poor families with young children. In doing so, it needs to be linked closely with funding organizations which can both initiate and sustain programs of child care for poor families. International funding organizations need to rethink their current approach to funding programs targeted either at children or at women. And the emphasis on competition and funding only the “best” program will not work in terms of the needs of all children and their mothers. This approach emphasizes a one shot infusion of money for a “best” program which fits the current fashion, such as women’s empowerment or children in war zones. After that infusion, the funding agency can go onto other more “innovative” approaches. Child care and pre-school do not fit this funding model first, because they are not sustainable and require on-going support. Second their staff are not trained in grantsmanship but in service delivery. An effective child care and preschool program requires permanency and sustained action to ensure that the children are not left at the door when the current funding runs out.

Why look for more “innovation” when child care programs work? The funding model needs to be one of a partnership. The partnership model can move away from the old paternalistic model, but retain the funding agencies responsibility for ongoing support. This model has been used for the Education for all Fast-Track Initiative which partners developing countries with donors (UNICEF 2005, p 14). What is needed is a joint responsibility of the funding agency and the local child care center in order to deal most effectively with the critical problem of funds being siphoned off for other purposes especially the enrichment of local individuals who are in positions of control. Overall the problem of security of the funds and the assets of the child care organization is central to any program development. In some settings the financial dependence issue can be


addressed by setting up the child care organization so it can generate some of its own funding. This means that the funding organization would need to provide capital and technical assistance for successful fundraising.

CONCLUSION

The millennium development goals, including the means proposed to attain them have been seriously questioned (Easterly, 2006; Saith, 2006). Much effort and money has been expended in addressing questions of measurement and estimates of cost. For example Saith (2006, p. 1173ff ) cites Gown et al. estimates of “ $7-$13 per capita” for 10 years to promote gender equality and empower women. Gown proposes this in order to achieve a “transformation of social norms and patriarchal structures” (cited in Saith. 2006, p.1174). Money, however, can not buy empowerment, but it can buy child care and preschool. These programs can enable women, especially poor women, to increase their productivity. And contributing significantly to the family income can increase the say that poor women have in family decisions (Ahmed and Bould, 2005). Saith (2006) asks what would it cost to get the parents to agree to send the girl child to school? And the answer is the cost of child care and preschool programs would reduce the incentive of poor families to keep their girls home from school to provide child care. These programs can reduce poverty in the near future by enhancing the income earning potential of poor mothers. Child care and preschool can also be viewed as a long term poverty reduction programs in enabling the education of poor children as well as assuring a healthy start in life for all children. But in order to be effective for poor families, child care and preschool must be subsidized. In Western Europe it is subsidized by the state, but in poor developing countries it needs to be subsidized by international donor agencies. This would require a new set of international priorities and the development of partnerships so that long term funding would be available.

ACKNOWLEDGEMENTS

The fieldwork discussed here was supported by the Center for International Studies at the University of Delaware, Newark DE, USA

REFERENCES

Ahmed, S.S. and Bould, S. (2004). One able daughter is worth 10 illiterate sons. Journal of Marriage and Family, 66, 1332-1341.

Bergmann, B.R. (1996). Saving Our Children From Poverty: What the United States Can Learn from France. New York: Russell Sage Foundation.

Bould, S. (1984). Development and the Family: Third World Women and Inequality, International Journal of Sociology and Social Policy (December) 38-51.

Bould, S. (2006a). The Need for International Family Policy: Mothers as Carers and as Workers. 75-98 in L. Haas and S. K. Wisendale (eds.) Families and Social Policy: National and International Perspectives.

Bould, S. (2006b). Where Are the Family Experts at the United Nations? National Council on Family Relations, Report, Vol. 51 (1) March Family Focus.


Chant, S. (2003). New Contributions to the Analysis of Poverty: Methodological and: Conceptual Challenges to Understanding Poverty from a Gender Perspective. Santiago, Chile: United Nations.

Daeren, L. (2001). The Gender Perspective in Economic and Labour Policies. Santiago, Chile: United Nations.

Easterly, W. (2006). The White Man’s Burden. The Penguin Group: USA.

Endeley, J.B. (2001). Conceptualizing women’s empowerment in societies in Cameroon: How does money fit in? In C. Sweetman (Ed.) Gender, Development, and Money(34-41). Oxford, England: Oxfam.

European and North American WomenAction (2000). Bulgaria Report, Women’s Alliance for Development. www.enawa.org (website as of 12 January, 2006).

Gentleman, A. (2007). Stricter law fails to diminish the demand for child laborers in India, New York Times (March 4).

Himmelstrand, K. (1997). Can an AID bureaucracy empower women? In K. Staudt, (ed.), Women, International Development, and Politics (123-135). Philadelphia, PA: Temple University Press.

Horelli, L. and K. Vepsa (1994). In search of supportive structure for everyday life. In I. Altman and A. Churchman (Eds.), Women and the environment. (201-226). New York: Plenum Press.

Hyde, K.A.L. (1993). Sub-Saharan Africa. In E.M. King and M.A. Hill (Eds.), Women’s Education in Developing Countries (211-246). Baltimore MD: The Johns Hopkins University Press.

Kabeer, N. (2003). Gender equality and women’s empowerment. An edited version of Gender Mainstreaming in Poverty Eradication, London: Commonwealth Secretariat.

Kahn, S.R. (1993). South Asia. In E.M. King and M.A. Hill (Eds.), Women’s Education in Developing Countries (211-246). Baltimore MD: The Johns Hopkins University Press.

Kasente, D., Lockwood, M., Vivian, J. and Whitehead, A. (2002). Gender and the expansion of nontraditional agricultural exports in Uganda (35-65). In S. Razavi (Ed.), Shifting Burdens. Bloomfield, CT: Kumarian Press.

Kingdom of Morocco, Ministry of Finance and Privatization (2006). Gender Report. Available from the website of the International Development Research Centre (Canada): http://www.idrc.ca/uploads/user-S/11604177081Moroccan_Gender_Report_English.pdf

Kiritz, N.J. and Mundell, H. (1988). Program Planning and Proposal Writing:Introductory Version. Los Angeles: The Grantsmanship Center.

Koeva, S, and Bould, S. (2007). Women as Workers and as Carers Under Communism and After: The Case of Bulgaria. International Sociology (forthcoming).


Narayan, D., Patel, R., Schafft, K., Rademacher, A., and Koch-Schulte, S. 2000. Voices of the Poor. New York: Oxford University Press.

Phillips, M.M. (2003). The World Bank as privatization agnostic. The Wall Street Journal (July 21, p. A2).

Pal, P. and Ghosh, J. (2007) Inequality in India: A survey of recent trends. In Jomo K.S. (ed. with J. Baudot). Flat World, Big Gaps (327-352). Zed Books: London.

Rowlands, J. (1999). Empowerment Examined. In D. Eade (Ed) Development with Women (141-150). London: Oxfam.

Sachs, J. (2005a). The End of Poverty. The Penguin Group USA.

Sachs, J. (2005b). Preface. In United Nations Millennium Project Taking action:Achieving gender equality and empowering women. London: Earthscan.

Saith, A. (2006). From Universal Values to Millennium Development Goals: Lost in Translation. Development and Change 37(6).

Starrels, Marjorie E., Sally Bould and Leon J. Nicholas. (1994). The Feminization ofPoverty in the United States. Journal of Family Issues 15(4).

Tara, S.N. (1985). Education in a rural environment. New Delhi: Ashish Publishing House.

Thukral, E.G. (2002). Poverty and gender in India. In C. Edmonds and S. Medina (Eds), Defining an Agenda for Poverty Reduction. Vol. 1 (233-253). Manila, Philippines: Asian Development Bank.

UNICEF (2005a) The state of the world’s children, Official Summary. Retrieved September 6, 2005 from http://www.unicef.org/publications/index_24433.html

UNICEF (2005b). Investing in the Children of the Islamic World. UNICEF: New York.

UNICEF (2006). The State of the World’s Children 2007. UNICEF: New York.

United Nations (1999). 1999 World Survey on the Role of Women in Development. New York: United Nations.

United Nations (2000). Families and the World of Work. New York: United Nations.

United Nations (2002). Gender mainstreaming: an overview. New York: United Nations.

United Nations (2003). Putting gender mainstreaming into practice. New York: United Nations.

United Nations (2004). Understanding Poverty from a Gender Perspective. Santiago, Chile: United Nations.

United Nations (2005). Citizen Participation and Pro-poor Budgeting. United Nations: New York.

United Nations Development Program (1995). Human Development Reports. Oxford, England: Oxford University Press.


United Nations Development Program (2005a) Taskforce on Education and Gender Equality, Executive Summary. (pp. 10-25.) Retrieved September 6, 2005 from http://www.mdgender.net/upload/monographs/Task_Force_3

United Nations Development Program (2005b). Human Development Report, 2005 Table 3: Human and Income Poverty. Retrieved September 7, 2005 from http://hdr.undp.org/statistics/data/indicators.cfm?x=24&y=1&z=1

United Nations Millennium Project (2005). Taking action: achieving gender equality and empowering women. London: Earthscan.

United Nations Research Institute for Social Development UNRISD (2005). Gender Equality. Geneva: UNRISD.

United Nations Statistics Division (2004). Statistics and indicators on men and women, Table 5d Economic Activity. Retrieved September 9, 2005 from http://unstats.un.org/unsd/demographic/products/indwm/indwm2.htm

United Nations Statistics Division (2004). Statistics and indicators on men and Women, Table 5e Distribution of the labor force y status in employment. Retrieved September 9, 2005 from http://unstats.un.org/unsd/demographic/products/indwm/ww2005/tab5e.htm

Vinovskis, M.A. (2005). The Birth of Head Start. Chicago: University of Chicago Press.

Weber. Max (1963). Class, Status, Party. In S.M. Miller (Ed.), Max Weber (pp. 42-58). New York: Thomas Y. Crowell.

ENDNOTES

1. The “grandmother” solution was proposed by many economists when an earlier version of this paper was presented at the Cornell University conference ” 75 Years of Development Research” Sponsored by the Program on Comparative Economic Development, Department of Economics, May 7-9, 2004.

2. School quality in terms of textbooks, teachers, buildings etc. does appear to be important for families who are not poor, especially in terms of sending their girls on to secondary education (Hyde, 1993, p. 124ff).

3. Field work at CHECP was done in the Summer of 2003 by the author and three students. There was a meeting with the mothers at the center, as well as observation of the activities of the center. Newsletters of the center were reviewed and are referred to below. Key informants were critical in providing the history of the organization as well as its current situation. Key informants consisted of two board members, one of whom was a founding member, as well as the current director of the organization who also worked in setting up the organization. Interviews were done by telephone with two funding officers from different funding agencies. Clarifications and additional information have been obtained through telephone and e-mail correspondence.A detailed history of the organization was provided by one of current board members who was involved in the founding of CHECP. Information on the situation of the children in those early years was provided by the current director who also worked for


the organization at its inception. This information was corroborated by telephone and e-mail correspondence with a funding officer. Once CHECP was established as an independent NGO a newsletter , News and Views, was occasional produced. After 2000, when funds became tight the newsletter was abandon.

4. This measure results in declaring men and women equal in wage employment where conditions are so poor for women that they are no longer looking for work and thus their problems do not show up in wage employment data (Koeva and Bould, 2007).

5. These conversations took place at the conference on “Secular demographic change: Composition, pressure on land, regional variations, migrations,” organized by the Aligarh Historians Society and the International Commission for Historical Demography, New Delhi, India September 19-20 2005.

6. This is from correspondence with one of the current board members, who was also a founding member.

7. Although the buildings and land were given to CHECP there is now no deed. The land has become much more valuable in the last 20 years. (Personal communication).

8. Mexico has established a goal of universal coverage of child-care and preschool programming from the age of 3 (Cf.www.senado.gob.mx/internacionales/assets/ docs/relaciones_parlamentarias/america/foros/parla_latino/salud5.pdf). For Chile see www.Junji.cl. The situation in Argentina is described in a United Nations publication (United Nations, 2000).

About the Author

Sally Bould, Ph.D. Senior Research Fellow, CEPS, Luxembourg and Professor Emerita of Sociology, University of Delaware where she had been on the Faculty for 30 years. Her fieldwork was supported by the Center for International Studies at the University of Delaware. She has published numerous articles and a book (Eighty-five Plus) in the areas of poverty, family and aging with a focus on policy. Her most recent publications include “The Need for International Family Policy” cited in References, an article on family policy in Bulgaria (with Dr. Stefka Koeva) and an article on the patriarchal family in Bangladesh (with Dr. Sania Sultan Ahmed)

31

CHAPTER 3

POVERTY AND INEQUALITY MAPPING IN DEVELOPING COUNTRIES

Francesca Ballini1, Gianni Betti2 and Laura Neri3

C.R.I.DI.RE. – University of SienaPiazza S. Francesco, 8, 53100 Siena – Italy

Email: [email protected]@[email protected]

ABSTRACT

Poverty and inequality maps - spatial descriptions of the distribution of poverty and inequality - are most useful to policy-makers and researchers when they are finely disaggregated, that is when they represent small geographic units, such as cities, municipalities, districts or other administrative partitions of a country. In order to produce poverty and inequality maps, living standard surveys covering income and consumption are econometrically combined with data from censuses or other sample surveys large enough to allow disaggregation of the poverty and inequality estimates.

Keywords: Poverty mapping, Spatial regression models, Developing countries.


1. INTRODUCTION

The gap between industrialised and less developed countries has increased in the last decades, despite a large number of poverty alleviation interventions have been undertaken by National Governments, Non-Governmental Organisations, Donor Agencies, International Financial Institutions, first of all the World Bank.

One of the main limitation of such interventions consists in the fact that often they do not target specific sub-population and rarely reach poor households.

There is the need to have information on poverty and inequality at a very disaggregated level, i.e. at region, province, municipality, even enumeration areas level. Poverty and inequality mapping is a technique that permits to calculate indicators and their standard errors at local level, so to serve policy makers to better address and target poverty alleviation policies.

Poverty and inequality maps - spatial descriptions of the distribution of poverty and inequality - are most useful to policy-makers and researchers when they are finely disaggregated, i.e. when they represent small geographic units, such as cities, municipalities, districts or other administrative partitions of a country. In order to produce poverty and inequality maps, large data sets are required, which include reasonable measures of income or consumption expenditure and which are representative and of sufficient size at low levels of aggregation to yield statistically reliable estimates. Household budget surveys or living standard surveys covering income and consumption usually used to calculate distributional measures are rarely of such a sufficient size; whereas census or other sample surveys large enough to allow disaggregation have little or no information regarding monetary variables.

Often the required small area estimates are based on a combination of sample surveys and administrative data. In this proposal we aim at performing poverty and inequality mapping primarily using an alternative source of data: data from a Population Census, in conjunction with an intensive small-scale national sample survey.

The methodology adopted in the present work, combines census and survey information to produce finely disaggregated maps, which describe the spatial distribution of poverty and inequality in the country under investigation.

The basic idea is to estimate a linear regression model with local variance components using information from the smaller and richer sample data in conjunction with aggregate information from the Population Census, supplemented by some other data sources present in the country.

The estimated distribution of the dependent variable in the regression model (monetary variable) can therefore be used to generate the distribution for any sub-population in the census conditional to the sub-population’s observed characteristics. From the estimated distribution of the monetary variable in the census data set or in any of its sub-populations, an estimate has to be made of a set of poverty measures, such as the Sen (1976) and the Foster-Green-Thorbecke (Foster et al., 1984) indices and a set of inequality measures such as the Gini coefficient and general entropy measures. To assess the precision of the estimates, standard errors of the poverty and inequality measures need to be computed using an appropriate procedure such as bootstrapping.


Three important aspects of this methodology should be noted at the outset. Firstly, information from the Census is required at micro (household and individual) level; however micro-level linkage between Census and survey data is not required. Secondly, the vector of covariates used in the regression model implies that those variables have to be present in both sources. Thirdly and most importantly, the common variables in the sources must be sufficiently comparable; comparability requires the use of common concepts, definitions and measurement procedures.

The Chapter is made up of seven Sections. After the present introduction, Section 2 describes the theory concerning the models involved in the poverty mapping, models which are then estimated in Section 3, on the basis of the Survey of Living Conditions (SLC) of a developing country – the Commonwealth of Dominica, in the Caribbean. Sections 4 and 5 report poverty and inequality measures and maps disaggregated at national and Parish levels and Village and Enumeration District levels respectively.

Section 6 describes how poor households have been identified and how a participatory assessment has been conducted, while policy recommendations to the Government of the Commonwealth of Dominica are summarised in Section 7.

2. POVERTY MAPPING

The basic idea can be explained in a simple way. Having data from a smaller and a richer data-sample such as a sample survey and a census, a regression model of the target household-level variable, given a set of covariates based on the smaller sample, can be estimated. Restricting the set of covariates to those that can also be linked to households in the larger sample, the estimated distribution can be used to generate the distribution of the consumption expenditure (yh) for the population or sub-population in the larger sample given the observed characteristics. Therefore the conditional distribution of a set of welfare measures can now be generated and the relative point estimates and standard errors can be calculated.

Practically the methodology follows two steps:

a) the survey data are used to estimate a prediction model for the consumption (stage one);

b) simulation of the expenditure for each household of the census and poverty/inequality measures are derived with their relative prediction error (stage two).

The key assumption is that the model estimated from the survey data applies to census observation. Of course the assumption is most reasonable if the survey and census year is the same, unfortunately it is not our case, so when interpreting results we need to consider that the poverty estimates obtained refer to the census year.

2.1 Stage one: a prediction model for consumptionThis step (Stage one) consists in developing an accurate empirical model of a logarithmic transformation of the household per-capita total consumption expenditure (rent and health expenditure excluded). Geographical differences in the level of prices should also be taken into account. In the model the covariates are variables defined in exactly the same way as in the smaller sample data (SLC) and in the census. Denoting by ln chy the


logarithm consumption expenditure of household h in cluster c, a linear approximation to the conditional distribution of ln chy is considered:

ln ln | T Tch ch ch ch ch chy E y x u x u (1)

Previous experience with survey analysis suggests that the proper model being specified has a complex error structure, in order to allow for a within-cluster correlation in the disturbances as well as heteroschedasticity. To allow for a within cluster correlation in disturbances, the error component is specified as follows:

ch c chu (2)

where and are independent of each other and not correlated to the matrix of

explanatory variables. Since residual location effects can highly reduce the precision of welfare measure estimates, it is important to introduce some explanatory variables in the set of covariates, which explain the variation in consumption expenditure due to location. For this reason introducing the means of each covariate into the model covariates may be a good proposal.

Moreover, Elbers, Lanjouw and Lanjouw (2003) propose adopting a logistic model (named as Alpha Model) of the variance ch conditional on a vector z of covariate

(bounding the prediction between zero and a maximum A equal to (1.05)*max( e ch)):

2

2ln 'ch

ch chch

ez r

A e

(3)

Let exp( ' )chz B and using the delta method the household specific variance is

estimated as:

23

1 (1 )ˆ var( )

1 2 (1 )ch

AB AB Br

B B

(4)

The variance of 2 is normally estimated non-parametrically, allowing for

heteroschedasticity in ch (see Appendix 2 of Elbers, Lanjouw and Lanjouw, 2002).

2.2 Stage two: simulation The parameter estimates obtained from the previous step are applied to the census data so as to simulate the expenditure for each household in the census. For each simulation a set of the first stage parameters is drawn from their corresponding distribution simulated at

the first stage: the beta coefficients, , are drawn from a multivariate normal

distribution with mean (the coefficients of the GLS estimation) and variance

covariance matrix equal to the one associated with . Relating to the simulation of the

residual terms ˆc and ,c he , assumption of any specific distributional form is normally

avoided by drawing directly from the estimated residuals: for each cluster the residual


drawn is c and for each household ,c h . The simulated values are based on both the

predicted logarithm of expenditure ,'c hx , and on the disturbance terms c and ,c husing a bootstrap procedure:

, , ,ˆ exp Tc h c h c c hy x (5)

The full set of simulated ,ˆc hy values is used to calculate the expected value of each

of the poverty measures considered. For each of the simulated consumption expenditure distributions a set of poverty and inequality measures is calculated, as is their mean and standard deviation over all the set of simulations.

3. IMPLEMENTATION OF THE METHOD

3.1 Data sources: the 2001 Census and the 2002 Survey of Living ConditionsThe poverty and inequality mapping in the Commonwealth of Dominica was conducted in the period December 2005 – February 2006; the reference year is 2001, the year of the collection of the Population and Housing Census, and is based on 22,359 households and 68,646 individuals.

The Census data set has been revised since the Country Poverty Assessment (June 2003), and the Central Statistical Office (CSO) of the Commonwealth of Dominica released the final version in December 2005. For the present work the authors had indirect access to the Census data through the Central Statistical Office during the two visits in the month of December 2005 and February 2006.

The Survey of Living Conditions was conducted in 2002; as for the Census, the CSO revised the data set releasing an updated version in December 2005. This final version used in the present poverty mapping exercise was based on 938 households. A full description of the construction of the final data set is reported in Betti et al. (2006).

The two sources of data should be fully analysed in order to identify the common concept and to construct the common variable to be compared. The original Census and SLC variables should be transformed in order to get comparable variables.

In principle some variables collected in the SLC survey may present some missing values; in such a case it is useful to impute them in order to avoid the loss of statistical units (and therefore degrees of freedom) in the estimation of the linear regression model with variance components. The imputation procedure proposed here is based on the “sequential regression multivariate imputation” (SRMI) approach adopted by the imputation software (IVE-ware, Raghunathan et al., 2001).

3.2 A prediction model for consumptionThis step consists in estimating the logarithm consumption expenditure model (1) (named Beta Model) allowing for a within-cluster correlation in the disturbances and allowing for heteroschedasticity. The disturbance term is specified as in (2) and it indicates a violation of assumptions for using the OLS in model (1), so a GLS regression is needed.


It seems to be reasonable that locations are related to household consumption, and it is plausible that some location effects might remain unexplained even with a rich set of

regressors. For any, given disturbance variance, 2ch , the greater the component due to

the common part c , the less one gains benefits from selecting households belonging to

the same enumeration area within each cluster. Since residual location effects can highly reduce the precision of welfare measure estimates, it is important to introduce some explanatory variables in the set of covariates, which explain the variation in consumption expenditure due to location. For this reason it is suggested that the means of each covariate calculated over the entire census households in each cluster are introduced into the model, as covariates. Means computed at cluster level in the census data set was inserted into the household survey dataset so as to have the possibility of inserting those variables in the first-stage regression specification.

The initial estimate of in equation (1) is obtained from the OLS estimation. With

consistent estimates of the OLS residual ˆchu (first-stage residual) can be decomposed

into uncorrelated components as follows . . ˆˆ ˆ ˆ ˆ( )ch c ch c c chu u u u e , and used to

estimate the variance of ch .

In order to avoid forcing the parameter estimates to be the same for the whole country, preliminarily, separate regression models have been estimated for the urban-semi urban area and for the rural area. Specifying the different models, the whole procedure of poverty mapping has been performed. The results obtained were not reasonable, maybe because of the insufficient sample size in each partition.

After this previous analysis it was decided to perform the analysis considering one model for the whole sample survey.

Considering that the specification of the model has itself be affected by the choice of weighting/no weighting, it is important to decide if it is better to use the weighting system or not. In computing this test, under the null hypothesis, it is assumed that the regressions are homogeneous across strata, weighted and unweighted OLS estimator are unbiased, so the difference between them has an expectation of zero. Computing the variance-covariance matrix of the difference between the weighted and the unweighted OLS estimator the test can be computed. However, the easiest way to test the hypothesis is to run an “auxiliary” regression, where the covariates are the original covariates X and the product between the covariates and the weights (WX=W*X) and to use an F statistic to test the hypothesis H0: g=0 (where g is the vector parameter of the WX matrix). This test is a special case of the Hausman test described in Deaton (1997); it has been applied using the encompassing model (the model having as regressors all the available variables, of course taking the multicollinearity problem into account). The Hausman test performed leads to the rejection of the null hypothesis (see Table 1), so we decided to use the household weights in the model specification.

Table 1:Hausman test of population weights H0: g=0

Empirical F-test DF p-value R2OLS Adj-R2

OLS

23.38 68 <0.0001 0.6468 0.6189


Specifying a multiple linear regression model starting with the encompassing model, we selected a set of significative household covariates; on the basis of those covariates, a set of significative interaction covariates has been inserted. Given that specification, in order to select the location variables, we estimate a regression of the total OLS residuals ˆchu , on cluster fixed effect and select those that best explain the variation at stratum

level. These location variables are then added to the household level variable and to the selected interactions in order to define the final Beta Model; however, in our case, no location variable seems to be significant The results of this estimation step are in Table 2, the adjusted R-square coefficient is quite satisfying, being about 0.62. In that model1 the null hypothesis of homoschedastic errors (White, 1980) has been tested and the hypothesis has not been rejected; in order to have another proof of homoschedasticity of the error component, residual plots have been analysed and the test results have been confirmed. It follows that the estimation of the model for the variance of the idiosyncratic

part of the disturbance 2ch has been skipped. As regard to the estimation of variance

2var( ) , it is important to note that in order to estimate the variance of the location

effect it is necessary to have more than two households within each cluster, otherwise it is not possible to estimate the variance within each cluster. To be surer, at the beginning of the procedure, we decided to re-define the cluster with more than four households per cluster. We can observe that the estimated share of the location component with respect

to the total residual variance represented by Rho= 2 2u accounts for less than 6% of

the total variance, thus it has been decided to eliminate the location effect and thus the total residual chu is reduced to ch .

Having homoschedasticity in the residual, the estimation of the Alpha Model [3] has been skipped; furthermore, not having significant location effect, the GLS estimates are the same as the OLS estimate. Concluding stage one, it is worth looking at of the estimated coefficient parameters (Table 2), in order to understand the effect of the covariates on the transformed equivalent expenditure.

The covariate effects are quite reasonable: the parameters of the dummy variables indicating belonging to between the fourth and tenth decile of the income distribution (DEC4-DEC10) are very significant and have a positive value (most significant are the coefficients of DEC6-DEC10); being owner of the household and having the household rented privately (OWNER_A, OWNER_B) have a positive effect on the housing expenditure; having a household built with brick blocks, wood and concrete (WALL_A and WALL_B), as well as having five or more rooms (ROOMS_5), has a positive effect on the housing expenditure, as well as having gas, LPG and cooking gas (FUEL_A). A set of durable goods has a significant positive effect on the expenditure, particularly: a TV, a dish washer, a telephone, a washing machine, a vehicle.

1 At present, the null hypothesis of omoschedasticity and the significance of the parameters have been tested with both the usual covariance matrix and the heteroschedasticity consistent covariance matrix.


With regard to the head of household characteristics, being a female (SEX), as well as belonging to the age class 55-64 years old (CL_AGE_55_64) has a negative effect on the expenditure; on the other hand, a head of household having a university education (EDU_UNI) has a reasonably positive effect on the expenditure as does a head of household working or having a pension (WORK_PENS).

With regard to the household characteristics, the expenditure increase as the household size increases (the variable AGE2 is also significative, but the parabola has a maximum in AGE equal to 14.7), and the expenditure also increases if the number of household members having less than five years old increases.

The increasing of the number of retired person (NUM_PENS) makes the expenditure lower (the effect is probably connected to the age of retired persons), the increasing age of the eldest son (ELDEST_SON_AGE) also has the same effect. Concluding with the household typology, being single and less than 65 years old makes the expenditure increase (TYPE_FAMD2). As far as the administrative partitions are concerned, living in St. David Parish (PARISH_19) makes the equivalent expenditure lower, this is reasonable given that the Carib territory is enclosed in this Parish. Let’s consider now the interaction variables with positive effects:

o belonging to the tenth decile of the income distribution and having housing with five or more rooms (DEC10_ROOMS_5);

o belonging to the ninth decile of the income distribution and being single and less than 65 years old (DEC9_ROOMS_5_ TYPE_FAMD2);

o living in Paris 19 means belonging to the ninth decile of the income distribution (DEC9_ PARISH_19);

o living in an urban area and having a vehicle at disposal (URBAN_D_VEHICLES).

In the set of the interaction variables, the variable indicating a household belonging to the upper tail of the income distribution and living in Parish 17 has a negative effect (DEC10_ PARISH_17 the significance level of the coefficient is 90%, p-value =0.10).

Table 2:Beta Model: parameter estimates, standard errors and significance levels

VariableParameterEstimate

StandardError

SignificanceLevel (°)

Intercept 8.0000 0.098 ***DEC4 0.1718 0.065 ***DEC5 0.1630 0.066 **DEC6 0.2776 0.067 ***DEC7 0.2834 0.070 ***DEC8 0.4595 0.072 ***DEC9 0.3963 0.082 ***DEC10 0.4830 0.109 ***URBAN_D 0.0425 0.054OWNER_A 0.1357 0.060 **OWNER_B 0.1594 0.072 **WALL_A 0.2077 0.045 ***


Table 2 continued

VariableParameterEstimate

StandardError

SignificanceLevel (°)

WALL_B 0.1561 0.055 ***FUEL_A 0.1465 0.053 ***ROOMS_5 0.0859 0.062TV 0.1682 0.051 **STOVE 0.1554 0.061 ***TELEPHONE 0.2593 0.049 ***WASHING 0.0988 0.043 **VEHICLES 0.3381 0.057 ***SEX -0.0863 0.042 **CL_AGE_55_64 -0.1536 0.052 ***EDU_UNI 0.4038 0.092 ***WORK_PENS 0.2677 0.055 ***SIZE -0.2032 0.031 ***SIZE2 0.069 0.003 **NUM_0_5 0.054 0.036NUM_WORK -0.047 0.029NUM_PENS -0.1391 0.044 ***ELDEST_SON_AGE -0.0042 0.002 **TYPE_FAMD2 0.2190 0.068 ***PARISH_17 -0.1590 0.109PARISH_19 -0.2623 0.067 ***DEC10_ROOMS_5 0.3034 0.128 **DEC9_ TYPE_FAMD2 0.4900 0.186 ***DEC10_ PARISH_17 -0.9144 0.559 ***

DEC9_ PARISH_19 0.9181 0.331 ***DEC10_ NUM_0_5 0.2447 0.090 ***URBAN_D_VEHICLES 0.1709 0.92 *Observations 938 Clusters 117R-squared 0.6382 Adj-R-squared 0.6229Sigma eta 0.1271 RMSE 0.5235

Rho 0.0589 2var( ) 0.000054(°) *** p-value < 0.01

** 0.05 < p-value < 0.01* 0.1 < p-value < 0.05

3.3. Simulation of consumption expenditureThe parameter estimates obtained from the previous step are applied to the census data so as to simulate the expenditure for each household in the census. The simulated values are

based on both the predicted logarithm of expenditure 'chx , and on the disturbance

terms c and ch using bootstrapped methods:


ˆln exp Tch ch c chy x (6)

where ˆ ˆ~ ( , )N .

In the simulation step, the Beta coefficients, are drawn from a multivariate normal

distribution with mean and variance covariance matrix equal to the one associated to

, and for each household the disturbance terms are drawn from a normal distribution

having mean and variance equal to the one estimated on the survey data.

The simulation procedure has been repeated 100 times, each time drawing a new set of coefficients and disturbance terms and finally the simulated consumption expenditure.

Having this information for any given location (Parish, Village, etc…) a set of poverty and inequality measures has been calculated, one for each of the simulated consumption expenditure distributions. Now, the means of the measures, calculated across the simulations, constitute the point estimates of the measures, the standard deviations across the simulation constitute the standard errors of these estimates.

4. RESULTS: MAPS AT NATIONAL AND PARISH LEVEL

4.1. IntroductionThe procedure for estimating the poverty and inequality measures has been applied for the whole of Dominica and disaggregated at four levels:

a) rural – urban level;b) the 10 Parishes and the City of Roseau;c) the 118 Villages;d) the 295 Enumeration Districts;

For any given location, the means constitute the point estimates, while the standard deviations are the bootstrapping standard errors of these estimates.

Tables 3 and 4 report poverty and inequality measures and their bootstrapping errors for the whole of Dominica and are disaggregated at urban – semi urban and rural level, and by the ten Parishes and the town of Roseau.

The disaggregations are very useful for comparing these results to those obtained by the revised version of SLC (Betti el al. 2006) and reported in Table 5.

4.2. Results at National levelThe incidence of Poverty in the Commonwealth of Dominica is very high. About 31% of households and 37% of individuals are below the poverty line. These results are in line with those obtained from the Survey of Living Conditions officially calculated in the Country Poverty Assessment (June 2003), where the corresponding values were 29% for households and 39% for individuals. As expected, the poorest households are also those with more family members. Anyway this gap between household and individuals in the population (census) seems to be smaller than in the survey.

It is clearly evident that the incidence of poverty in Dominica is one of the highest in the Caribbean area. However, the headcount ratio index (HCR) simply measures the


proportion of the population below the poverty line, but does not take the intensity and the severity of poverty into account.

A measure of the intensity of poverty, the Poverty Gap Ratio (FGT(1), described in the Annex of this main Report) is about 11% for households and 14% for individuals.

This figure locates Dominica in an average position among the Caribbean countries; this could be interpreted as meaning that many of the poor families and individuals in Dominica are just below the poverty line. This is confirmed by the severity index (FGT(2) = Poverty Gap squared) which is about 5% for households and 7% for individuals, and by the Gini concentration index among the poor which is about 20% for both households and individuals.

Bearing this information in mind, policy makers should propose anti-poverty strategies so as to bring those many individuals just above the poverty line: noting the figures in Tables 3 and 4, these strategies should be quite inexpensive. For further details see Section 7 on policy recommendations. On the other hand, all the inequality measures (Gini, General Entropy and Atkinson) show large inequality in the consumption distribution, underlining large differences between the poor and the non-poor in the country. When disaggregating the country into urban, semi-urban and rural areas, the incidence, intensity and severity of poverty is increasing from urban to non-urban areas. Anyway, inequality in urban areas is still high, showing the presence of the majority of the very rich households and individuals.

Table 3:Poverty and inequality indices at household level(%); Census, 2001

Partition HCR FGT(1) FGT(2) Gini Ginipov SEN GE(0) GE(1) Atk Eq_conDominica 30.91 10.96 5.33 43.99 19.05 8.76 33.58 34.13 51.87 7286

5.01 2.32 1.32 0.92 1.08 2.26 1.50 1.78 1.39 878Urban 19.89 6.32 2.86 43.18 17.09 4.53 32.38 32.54 52.74 9432

4.16 1.61 0.82 1.08 1.04 1.35 1.66 1.99 1.52 1257Semi urban 27.53 9.29 4.36 43.12 18.06 7.19 32.12 32.64 53.35 7703

4.98 2.15 1.17 0.97 1.03 2.03 1.50 1.84 1.41 922Rural 37.46 13.83 6.90 42.81 19.76 11.72 31.61 32.20 53.89 6123

5.58 2.80 1.66 0.83 1.16 2.93 1.32 1.53 1.32 724St.George (Roseau) 21.24 6.79 3.08 42.87 17.18 4.94 31.80 32.20 53.50 8938

4.39 1.71 0.88 1.08 1.06 1.47 1.64 2.00 1.53 1181Rest of St. George 21.50 7.08 3.28 43.85 17.68 5.14 33.64 33.45 51.31 9322

4.05 1.71 0.92 1.31 1.24 1.46 2.04 2.52 1.74 1168St. John 27.77 9.37 4.39 41.89 17.95 7.25 30.32 30.37 54.86 7440

5.06 2.27 1.26 1.17 1.29 2.14 1.79 2.06 1.81 893St. Peter 31.53 10.75 5.06 39.96 18.10 8.64 27.30 27.43 58.26 6450

5.77 2.56 1.42 1.30 1.43 2.55 1.83 2.36 1.96 785St. Joseph 30.04 10.20 4.81 41.71 18.17 8.10 29.92 30.26 55.50 6999

5.39 2.34 1.28 1.05 1.09 2.29 1.60 1.87 1.61 843St. Paul 22.45 7.40 3.42 44.36 17.62 5.41 34.33 34.39 50.91 9199

4.21 1.72 0.91 1.19 1.03 1.50 1.90 2.25 1.69 1153


Table 3 continuedPartition HCR FGT(1) FGT(2) Gini Ginipov SEN GE(0) GE(1) Atk Eq_conSt. Luke 27.92 9.23 4.26 40.82 17.63 7.17 28.54 28.83 56.91 7126

5.27 2.25 1.21 1.35 1.49 2.11 1.93 2.32 2.14 832St. Mark 36.33 13.41 6.72 42.15 19.90 11.29 30.78 30.75 54.15 6174

5.73 2.81 1.65 1.28 1.39 2.89 1.93 2.37 1.96 747St. Patrick 40.90 15.29 7.70 41.27 20.01 13.37 29.27 29.63 56.11 5511

5.97 3.02 1.81 0.90 1.22 3.30 1.37 1.60 1.49 655St. David 49.86 20.03 10.55 42.31 21.35 18.72 30.61 31.93 55.48 4737

6.32 3.66 2.34 1.16 1.34 4.27 1.77 2.29 1.72 572St. Andrew 37.75 13.69 6.75 41.75 19.35 11.64 29.88 30.41 55.73 5938

5.80 2.87 1.68 0.87 1.19 3.01 1.33 1.62 1.37 699

4.3. Results at Parish levelEven if measures of the incidence of poverty are quite high in every Parish in Dominica, those measures show quite a high local heterogeneity: the Head Count Ratio ranges from 21-22% in St. George and St. Paul (26% for individuals) to 50% in St. David (58% for individuals). These figures are, in some cases, different from the figures from SLC and reported in the Country Poverty Assessment: the main reason could be identified in the fact that estimates based on the Survey are affected by an enormous sampling error, since the sample size is significant for estimates at Country level, but not at Parish level.

Table 4:Poverty and inequality indices at individual level(%); Census, 2001

Partition HCR FGT(1) FGT(2) Gini Ginipov SEN GE(0) GE(1) Atk Eq_conDominica 36.68 13.87 7.07 44.18 20.44 11.69 34.01 34.36 51.28 6438

5.32 2.69 1.62 0.94 1.17 2.80 1.53 1.78 1.41 786Urban 24.82 8.28 3.87 43.05 17.94 6.25 32.15 32.39 53.03 8230

4.86 2.01 1.07 1.13 1.16 1.82 1.73 2.09 1.63 1106Semi urban 32.17 11.48 5.62 43.08 19.18 9.30 32.20 32.38 52.99 6936

5.28 2.46 1.41 0.95 1.13 2.46 1.48 1.74 1.42 844Rural 44.23 17.56 9.22 43.29 21.32 15.72 32.43 32.93 53.00 5376

5.76 3.21 2.02 0.84 1.26 3.57 1.36 1.50 1.36 644St.George (Roseau) 26.41 8.85 4.16 42.58 18.05 6.81 31.34 31.80 53.98 7768

5.12 2.13 1.15 1.07 1.18 1.98 1.62 1.96 1.59 1031Rest of St. George 26.03 9.11 4.40 43.82 18.79 6.92 33.75 33.25 51.00 8289

4.46 2.04 1.15 1.31 1.40 1.83 2.07 2.36 1.93 1048St. John 34.48 12.38 6.06 42.12 19.08 10.20 30.61 30.78 54.73 6432

5.63 2.77 1.64 1.09 1.47 2.83 1.64 1.87 1.67 773St. Peter 36.17 12.80 6.19 39.73 18.76 10.74 27.08 27.34 58.55 5846

6.52 2.96 1.68 1.55 1.58 3.14 2.15 2.93 2.27 717St. Joseph 34.18 12.30 6.05 41.99 19.36 10.16 30.52 30.56 54.58 6447

5.62 2.58 1.48 1.03 1.18 2.66 1.59 1.84 1.68 785


Table 3 continuedPartition HCR FGT(1) FGT(2) Gini Ginipov SEN GE(0) GE(1) Atk Eq_conSt. Paul 26.34 9.06 4.31 44.06 18.35 6.89 33.89 33.81 51.28 8242

4.69 2.03 1.11 1.30 1.14 1.87 2.08 2.41 1.90 1063St. Luke 32.67 11.30 5.40 40.19 18.43 9.19 27.78 27.94 57.60 6332

5.92 2.66 1.49 1.41 1.65 2.64 2.04 2.25 2.45 745St. Mark 43.60 17.28 9.10 42.52 21.41 15.44 31.52 31.76 53.36 5338

6.10 3.32 2.08 1.40 1.59 3.65 2.17 2.65 2.34 662St. Patrick 47.36 19.05 10.11 41.87 21.64 17.51 30.33 30.42 54.78 4905

5.99 3.38 2.17 1.05 1.38 3.90 1.63 1.83 1.72 595St. David 58.53 25.49 14.14 42.49 22.99 25.17 30.82 32.19 55.43 4013

6.22 4.19 2.89 1.14 1.50 5.09 1.77 2.17 1.81 490St. Andrew 43.66 16.92 8.74 42.14 20.76 15.11 30.58 31.01 54.88 5312

5.96 3.22 2.00 0.87 1.33 3.58 1.36 1.56 1.46 632

In fact, in some Parishes, the sample size is just above 20 households, so that the confidence interval of the Head Count Ratio can be so large as to invalidate any inference exercise. Another source of diversity is due to the different reference year: the estimates reported in the present Report are based on Census data and therefore refer to the Year 2001; while there can be little difference between the Head Count Ratio at Country level from 2001 and 2002, probably larger differences can occur when disaggregating at Parish level, since the economic situation changes according to different Parishes.

Table 5:Poverty indices at individual and household level(%); revised SLC, 2002

Code Parish # HHs # Ind % Poor HHs % Poor Ind10 Roseau 209 715 14.7 16.611 Rest of St. George 57 194 23.7 36.812 St. John 68 206 23.6 30.713 St. Peter 23 69 13.5 20.514 St. Joseph 83 243 27.9 35.315 St. Paul 98 360 22.0 31.316 St. Luke 21 69 10.4 17.117 St. Mark 28 79 39.1 52.518 St. Patrick 100 369 40.2 43.719 St. David 92 327 58.8 68.020 St. Andrew 159 529 23.6 27.5Dominica 938 3160 27.0 33.5

Measures of poverty intensity and severity (FGT(1) and FGT(2)) give the same picture of the Parishes as the measure of incidence (Head Count Ratio). On the other hand, the three Parishes of St. George (including Roseau), St. John and St. Paul show quite high inequality with all the measures calculated. This confirms the fact that rich areas are still characterised by high inequality and therefore are still in a process of transition towards further development. Figure 1 shows maps of percentage of


households and individuals in poverty at Parish level. In each map in Figures 1 and 2, the Parishes (or Enumeration Districts) are divided into four groups: the central threshold is usually indicated by the national average, so that it is possible to distinguish the Parishes (or Enumeration Districts) that are better off than the entire Dominica from those that are worst off than the average. Moreover the other two thresholds (the upper and the lower) have been found so that a similar number of Parishes (or Enumeration Districts) is located in the better or lower group.

Figure 1: Percentage of Households and Individuals in Poverty at Parish level.

5. RESULTS: MAPS AT ENUMERATION DISTRICT LEVEL AND DECOMPOSITION OF INEQUALITY

The procedure for estimating the poverty and inequality measures has been applied for the whole of the country, for the Parishes and then disaggregated at Village level and Enumeration District level. The Central Statistical Office has provided the Authors with the software for producing maps at ED level, which are reported later in Figure 2.

Moreover, Table 6 reports decomposition of one of the general entropy class inequality measures (GE(1), Theil Index) into its within area and between area components at various levels of aggregation. By definition, all of the inequality is within group when the group in question is the whole country or is the rural area or urban area,


and all of it is between groups when each household is considered as a separate group. GE(1) index is decomposable so that we are able to distinguish among the inequality due to differences between a certain level of disaggregated areas (Parishes, Villages, Enumeration Districts, etc…) and the inequality due to the differences between households present in the disaggregated area.

Table 6:Decomposition of the GE(1) inequality index (Theil).

Level of DecompositionNumber of Units

Within-Group Inequality

Between-Group Inequality

% Between-Group Inequality

Dominica 1 34.36 0 0Urban - semi urban - rural 3 32.63 1.73 5.0Parishes 10 31.68 2.68 8.0Villages 118 29.68 4.68 13.6Enumeration Districts 295 28.43 5.93 17.2

From Table 6 we can see that in the whole country and in both rural and urban areas, a large portion of the inequality is due to within-group inequality, even when the groups are relatively small, such as Enumeration Districts. Approximately, 8% of the inequality in Dominica is between Parishes, 13,6% between Villages, and 17,2% between Enumeration Districts.

Figure 2: Percentage of Households and Individuals in Poverty at ED level.


6. IDENTIFICATION OF POOR HOUSEHOLDS AND PARTECIPATORY ASSESSMENT

6.1. Identification of poor households and individualsPoverty and inequality measures have been presented for different levels of disaggregation: at rural – urban level, at Parish level, at Village level and finally at Enumeration District level. The method proposed here allows reaching a finer level of disaggregation, up to household level: in fact the method provides simulated household equivalent consumption expenditure for each household of the Census.

Having a set of simulated household equivalent consumption for each household, we are able to compute the average household equivalent consumption for each household; if this value is below the poverty line we can conclude that the household is poor. For the average household equivalent consumption we are able to compute the bootstrap standard error, of course the greater the level of disaggregation considered, the greater the value of the standard error will be. Therefore at household level we can expect to have the largest standard error possible.

6.2. Participatory assessmentIn order to verify the information derived from the quantitative assessment a participatory assessment was conducted. This was in the form of a field test, so as to test the methodology also at household level. The idea of the test was to visit households in some poor villages in the Parishes of St. David (Carib territory) and St. Mark in order to verify if it was reasonable to consider them in a status of poverty.

In order to conduct these field tests, from each village the consultants randomly selected a set of households classified as poor in the quantitative assessment; the selected units were visited at home by the consultants as well as a local researcher from the Ministry of Finance and the National Statistical Office.

The results of the participatory assessment were absolutely consistent with the results of the quantitative assessment: all but one of the households visited showed a real status of poverty. Only one of them did not show real poverty status; however, talking with the household members they explained that the living conditions had recently changed because some members had found a new job. In conclusion, the field test gave very satisfying results even at household level.

7. POLICY RECOMMENDATIONS

Even if the poverty and inequality exercise was completed in February 2006, it should be kept in mind that the reference year for the results is the year 2001, i.e. when the Census information was collected. For this reason the results cannot be used in monitoring poverty and in evaluating the framework for poverty reduction proposed in the Country Poverty Assessment (June, 2003) and undertaken by the Government of the Commonwealth of Dominica and also included in the Growth and Social protection Strategy (GSPS).

The CPA and GSPS have indicated the individual and household categories at risk of poverty and have proposed anti-poverty policies for those categories. The added value of


the poverty mapping exercise consists in assessing WHO those individuals and households are and WHERE they live.

7.1. The medium-term Growth and Social Protection StrategyAccording to the CPA and the medium-term Growth and Social Protection Strategy (GSPS) report, Dominica has an extensive social safety net consisting of several government and NGO-administered programmes. Generally, the CPA found that Dominica’s social protection programmes targeted the poor, directly or indirectly, and were comprehensive in three ways:

- They involve activities that are developmental (i.e. that seek to directly increase individuals’ capability to participate in economic activity), supportive (i.e. that directly address the needs of poor and vulnerable groups) and preventative (i.e. that seek to prevent individuals from becoming poor).

- They cover all relevant sectors: agriculture, small business development, physical infrastructure and housing, education, health and social sectors.

- They target communities, households and individuals including the most vulnerable sub-groups of the poor – the elderly, disaffected youth, the disabled, drug abusers, the indigent, and households with family problems.

7.2. Integration of Poverty Reduction Policies and ProgrammesThe poverty mapping work could be useful for proposing anti-poverty policies or for integrating policies already proposed and undertaken by Poverty Reduction Policies and Programmes. Those policies or programmes could be implemented at least at three levels:

- short term: to individuals or households through economic / monetary support;- medium term: to Enumeration Districts and Villages (projects at local level);- long term: structural changes of the Country (education, training, investments with

an eye on the sustainable growth).

7.2.1. Short term Policies and ProgrammesAt present, the public assistance programme (PA) is co-ordinated by the Social Welfare Division (SWD) and provides support to those individuals who live in households below the Household Indigent Line (HIL). For the year 2002, under this programme, recipients obtained EC$100 per month per family and EC$85 per month per child. A process of eligibility exists that includes a home visit and other examinations by SWD staff to ensure that applicants satisfy SWD criteria. Even if the CPA report has estimated that in Dominica about 10,000 individuals are indigent, this programme covers not more that 2,500 people (CPA, p. 107).

In order to improve the SWD criteria and to ensure a large coverage of the programme among the indigents, results from the poverty mapping could be used:

- first of all, to be eligible for the programme, an individual should belong to a household with a estimated consumption expenditure below the HIL;

- secondly, an informative campaign should be conducted in order to better inform potentially indigent people how, when and where to apply.


Alternatively, given its fiscal realities (GSPS) the Government could launch a new programme, the Household Direct Support Programme (HDSP):

Food supply (hot meals) to 1000 - 2000 households with very low consumption estimated with the poverty mapping exercise (after checking by means of a visit by government authorities) and with a large number of children present.

7.2.2. Medium term Policies and ProgrammesGiven the rich set of poverty and inequality measures provided by the poverty mapping, which are disaggregated at Village and Enumeration District level, the Government of the Commonwealth of Dominica could launch a new Programme, the Village (or Enumeration District) Direct Support Programme (VDSP or EDDSP):

- single out the 10 - 20 poorest Villages (Enumeration Districts) according to the HCR estimates produced by the poverty mapping exercise;

- single out the main characteristics and problems of the area (i.e. lack of schools, high unemployment rate, etc…) on the basis of information collected in the Census data or in other alternative sources;

- propose ad hoc projects for each village (ED) according to the characteristics of the area.

The information from the poverty mapping could also be used for monitoring Programmes undertaken by the Government. In fact some Programmes target some restricted areas on the basis of criteria or socio-economic indicators not necessarily related to poverty or just not up to date.

One example consists in the Small Project Assistance Team (SPAT), a community development NGO that has been providing support for socio-economic projects for the past 25 years, with some discontinued periods. In year 2001 SPAT’s main programme, the Community Animation Programme (CAP), was still covering four communities with socio-economic indicators (updated at year 1996) below the national average: Petite Savanne, Dublanc/ Bioche, Grand Fond and Grand Bay.

According to the poverty mapping 2001 HCR estimates (see Section 5 above), Petite Savanne, Grand Fond and Grand Bay villages experienced more than 50% of individuals in poverty, whereas in the Village of Dublanc/ Bioche less than one individual out of four lives in poverty.

The recommendation of this report is to invite the SPAT to continue its activities and to take into account the results produced by the poverty mapping at Village and Enumeration District level in order to launch new small projects.

Another medium-term Programme should also aim at attracting back into Dominica young people who have been educated abroad, so as not to loose investment in human resources. With the coming into effect of the CSME, Dominica will need to retain and attract highly skilled individuals. It will not only need those to function now in this competitive environment but will also need their specialised knowledge as it moves towards a knowledge economy.


7.2.3. Long term Policies and ProgrammesLong term policies and programmes should be based on structural changes of the Country, particularly on education, training, employment and investments, with an eye to the sustainable growth.

This should be in line with the most important strategy to be implemented by the GSPS, i.e. the promotion of (sustainable) economic growth and job creation.

The Government should therefore continue to undertake the Basic Needs Trust Fund (BNTF) with the support of the Caribbean Development Bank. The BNTF plays and will continue to play in the future a very important role with regard to:

- economic and social infrastructure necessary for development;- basic services or enhancement of;- skills training to increase productivity and income.

Everything possible should also be done to implement the Dominica Social Investment Fund (DSIF). DSIF will not only provide direct cash support to individuals, households and communities at risk of poverty, but will also provide opportunities for employment and sustainable development.

REFERENCES

Betti G., Ballini F. and Neri L. (2006). The Survey of Living Conditions in the Commonwealth of Dominica: a revision, Working Paper # 65, Dipartimento di Metodi Quantitativi, Università di Siena.

Country Poverty Assessment (2003). Final Report, Caribbean Development Bank. Government of the commonwealth of Dominica, Halcrow, June 2003.

Deaton A. (1997). The Analysis of Household Surveys: A Microeconometric Approach to Development Policy. John Hopkins Press and The World Bank: Washington, D.C.

Elbers C., Lanjouw J.O. and Lanjouw P. (2002). Micro-level Estimation of Welfare, Working Paper n. 2911. The World Bank: Washington, D.C.

Elbers C., Lanjouw J.O. and Lanjouw P. (2003). Micro-level Estimation of Poverty and Inequality. Econometrica, 71, 355-364.

Foster J., Greer J. and Thorbecke E. (1984). A Class of Decomposable Poverty Measures. Econometrica, 52, 761-766.

Raghunathan T.E., Lepkowski J., Van Voewyk J. and Solenberger P. (2001). A Multivariate Technique for Imputing Missing Values Using a Sequence of Regression Models. Survey Methodology, 27, 85-95.

Sen A. (1976). Poverty: An Ordinal Approach to Measurement. Econometrica, 44, 219-231.

White H. (1980). A Heteroschedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroschedasticity. Econometrica, 48, 149-170.


About the Authors

Francesca Ballini is member of the “Centro Interdipartimentale di Ricerca sulla Distribuzione del Reddito” (C.R.I.DI.RE.), University of Siena, Italy. She has worked for several projects for the World Bank, Eurostat and the European Commission, and has been closely involved with the development of the EU Statistics on Income and Living Conditions (EU-SILC).

Gianni Betti is Associate Professor in Statistics and Economics and member of the “Centro Interdipartimentale di Ricerca sulla Distribuzione del Reddito” (C.R.I.DI.RE.), University of Siena, Italy. He has worked for several projects for the World Bank and European Commission, and has been closely involved with the development of the EU Statistics on Income and Living Conditions (EU-SILC).

Laura Neri is Researcher in Statistics and Economics and member of the “Centro Interdipartimentale di Ricerca sulla Distribuzione del Reddito” (C.R.I.DI.RE.), University of Siena, Italy. She has worked for several projects for the World Bank and the European Commission, and has been closely involved with the development of the EU Statistics on Income and Living Conditions (EU-SILC).

51

CHAPTER 4

TACKLING THE RELATIONSHIP BETWEEN PRISONER RE-ENTRY AND POVERTY

Monica L.P. RobbersMarymount University

2807 North Glebe Road, Arlington VA 22207, USAEmail: [email protected]

ABSTRACT

Each year some 650,000 people are released from various correctional facilities in the United States (DOJ, 2006). Problems that inmates encounter upon their release are plentiful and complicated. More than half of those released are repeat offenders, one quarter have substance abuse problems, 12 percent are homeless, and 14 percent are mentally ill (Harrison and Beck, 2006). All of these variables are well established in research as contributing to poverty (see Reiman, 2001, and Wilheim, 2003, fordiscussion). When an offender reenters society with few legitimate options and few social supports, the cycle of poverty and crime begins again.

This chapter examines the relationship between prisoner reentry and poverty. The reentry process is described along with assessment of reentry programs from various jurisdictions that demonstrate potential for reducing poverty. This includes programs established to serve special populations. Critical success factors from programs are identified and the chapter concludes with recommendations for practitioners, policy-makers, and researchers.

Keywords: crime, incarceration, poverty, prisoners, reentry.


INTRODUCTION

According to the Department of Justice, some 650,000 people are released from various parts of the correctional system each year in the United States (DOJ, 2006). More than half of these individuals are “frequent fliers” in the criminal justice system, about one quarter are substance abusers, 12 percent are homeless, and 14 percent are mentally ill (Harrison and Beck, 2006). All of these variables are well established in research as contributing to poverty (see Reiman, 2001, and Wilheim, 2003, for discussion). Although the cyclical nature of crime and poverty is also well established, there has not been not much written about offender reentry and poverty, despite a 2004 Federal mandate on reentry programs recognizing the link between reentry and poverty. When an offender reenters society with few legitimate options and few social supports, the cycle of poverty and crime begins again.

Problems inmates encounter upon release are both plentiful and complicated. Some 11 percent of inmates have learning disabilities compared with about three percent in the general population, and only half of inmates have high school diplomas compared to about three quarters of all American adults (BJS, 2003). Finding housing upon reentry is one of the most difficult challenges for an ex-offender. These individuals typically do not have the financial means or social networks to obtain lease agreements. Further, criminal history is often used to exclude ex-offenders from leases. Government housing may also be difficult for ex-offenders to obtain given section eight providers can deny housing to anyone whose past criminal history may endanger the lives of other residents; the broad nature of this statement leads to varied interpretations usually at the expense of ex-offenders (Travis and Waul, 2003). Finding employment is also problematic. Most parolees are unemployed, and in some states, such as California, the percentage of unemployed parolees is as high as 90 percent (Mears, Lawrence, Solomon, and Waul, 2002). Thus, living below the poverty line is common among ex-offenders.

This chapter focuses on the relationship between offender reentry and poverty, and addresses the effects this relationship has on families and the community. The chapter includes an overview of offenders and reentry, a review of research on reentry, and some discussion of the relationships between crime, poverty, race, and reentry. The bulk of the chapter will be devoted to how poverty can be reduced by reentry programs, and programs from around the United States will be highlighted. Included will be an examination of the special needs of female ex-offenders, and some examples of gender specific programs.

The chapter will conclude by offering critical success factors of reentry programs for reducing poverty based on lessons from the field and current research, and will provide resources for practitioners, policy-makers and researchers who wish to explore the topic further.

DEFINING REENTRY

Reentry occurs when individuals are released from local, state, and Federal facilities. Reentry can be supervised, such as mandatory parole, or unsupervised. Although release from local jails occurs frequently, offenders in these types of institutions typically do not serve long sentences and their transition back to society can be uneventful. This chapter


will focus mainly on individuals who are released from state and Federal institutions, as their sentences tend to be much longer and their reentry thus more challenging.

With few exceptions, release from state or Federal incarceration involves some type of supervision. Commonly this is in the form of parole, the length of which is determined by various legal mechanisms. Parole is considered a form of after-care in which ex-offenders are required to check in with their parole officer to ensure they are complying with the conditions of their release. Mandatory meetings may vary; typically, an ex-offender may meet with his or her parole officer once a month. Intensive supervision parole occurs in some jurisdictions where the ex-offender is required to meet with the parole officer as frequently as once per week. Other conditions of release may include mandatory counseling, substance abuse treatment, community service, and victim restitution.

RECENT TRENDS IN SENTENCING

The Bureau of Justice Statistics (BJS) estimates more than 95 percent of all prisoners housed in state facilities will be released from prison at some point, and about 80 percent of these will be released conditionally. Among those who are released conditionally, only about 41 percent of offenders will complete their release successfully without recidivating (BJS, 2006). This means 59 percent of those released are not prepared for successful reentry or do not have the tools, such as employment contacts or housing, to succeed outside of the prison environment.

In a report addressing the political, economic, and social consequences of reentry, Petersilia (2000) writes the numbers of people reentering society after serving long sentences is unsurpassed. She argues changes to parole, such as increased caseloads for parole officers, decreased resources, and optional rehabilitation, are contributing to increased failure rates. She also argues the rehabilitation philosophy of indeterminate sentencing, which is the practice of sentencing an offender to a range of time that ultimately depends on the offender’s behavior and progress toward rehabilitation, has been undercut by prison overcrowding, resulting in frequent early releases of unprepared individuals.

One factor contributing to poverty among those reentering society, is often offenders must be paroled into the communities in which they resided before incarceration. In many cases, these communities are the very ones that do not have the resources to provide employment, housing and healthcare opportunities for ex-offenders, and eventually, ex-offenders may be left with few legitimate options. Perhaps unwittingly, this has a larger effect on certain groups in society than others. Black Americans, for example, are disproportionately poor, unemployed, and come from urban areas where there are few opportunities. They are also disproportionately represented in the nation’s prison system. It appears the correctional system perpetuates poverty by releasing individuals into the same circumstances that led to initial incarceration. Despite high recidivism rates ofbetween 65 and 80 percent, prison programs of various types are actually on the decline. Mears et al., (2002) report in 1991, 43 percent of inmates were part of some kind of educational program. However, by 1997, only 35 percent of inmates were participating in programs. Pre-release programs are offered to about 10 percent of inmates nationally (BJS, 2003).


The American public seems to be in favor of offering different types of programs to prisoners to a point. Linton (1998) writes most Americans favor basic education programs for inmates, but do not support free higher education for inmates. Such an attitude was reflected in the Government’s eradication of inmate Pell Grants in 1994. Similarly, Linton also reports generally, the public are in favor of inmates developing computer skills, but not when the inmates have access to more advanced technology than children do in public school systems. A study conducted by the Hart research group (2002) suggests about two thirds of Americans feel prison programs are essential for today’s inmates, particularly programs educating prisoners, and those providing life and job skills. This suggests most people realize the majority of inmates will reenter society at some point, and the public sees current reentry efforts as inadequate.

EXISTING RESEARCH ON REENTRY

Much of the work conducted on reentry has been completed by The Urban Institute, a non-partisan, non-profit, think tank, located in Washington D.C. In 2001, The Urban Institute began a longitudinal study of prisoner reentry in four states, Maryland, Ohio, Texas, and Illinois. The purpose of the study was to ascertain what services were being provided to offenders; both pre and post release, experiences of prisoners upon release, and what factors determined successful reentry.

The study indicates services pre and post release vary dramatically, and researchers maintain this is indicative of what is happening around the US. In Illinois, prisoners may attend a Pre-Start program, designed to provide inmates with basic information such as how to find a job, how to obtain photographic identification, where to find housing and healthcare, help with substance abuse, and tips for re-establishing personal relationships (La Vigne, Visher and Castro, 2004, p. 2).

Although the Pre-Start program addresses important issues, it does not appear to be translating into successes in the community. La Vigne et al (2004) tracked 400 males released from Illinois prisons in 2001, and almost all of these had participated in the Pre-Start program. Upon release, less than one quarter of the program participants obtained referrals for employment, and less than 10 percent received referrals for housing. Four to eight months after release, less than one third were employed, although more (44 percent) had had some employment during that period. Those who were employed were in the construction, maintenance, food services and warehouse / shipping industries. The average wage for the group was $9 per hour. These results suggest actual work programs may be more beneficial for ex-offenders.

In addition to high unemployment rates, existing debts and other financial obligations among ex-offenders are also contributing to poverty among the Illinois group; a situation common among ex-offenders. Of the ex-offenders in Illinois, 20 percent stated they owed money upon release, whether that was restitution, court fines and fees, or child support. More than three quarters of the group said they relied on income from family members, spouses or friends, and about one third reported receiving some type of state financial assistance.

A factor frequently overlooked in literature on reentry is what happens during the moment of release. Variables such as the time offenders are released, what they are given


at release time, and whether they have a release plan, are critical factors in determining the success of reentry and avoidance of both poverty and recidivism. For example, in most states, offenders are released with minimal financial resources, ranging from $20 to $200 and some type of transportation voucher, such as a bus or train ticket. Many states do not offer offenders clothing upon release; they provide only what the offender was wearing at intake. Many states require a housing plan from offenders being released, but these plans are not always verified. Logic dictates if an offender is released back into society in the middle of the night, with nowhere to live or sleep and with only $20 in hand, that offender is going to be homeless very quickly.

In a study conducted by researchers at the Vera Institute of prisoners released from the New York City Department of Corrections, researchers interviewed prisoners 24 to 48 hours after release to ascertain expectations, financial support, etc. Follow-up interviews occurred weekly for a period of four weeks (Nelson, Deess and Allen, 1999).

More than half of the respondents in this group of 66 indicated they were re-entering the community alone. Almost all arrived in the city after 1am, having left prisons in the afternoon. Most also went from public transportation to stores selling alcohol. Respondents who had served long sentences reported being confused about the transportation system, being lost in the city, and general confusion about how things worked. The study concluded simple changes can be made to the release process, such as changing the time when people are released, and making sure family and friends are there to meet ex-offenders so they have somewhere to go for their first night. Prison programs also need to educate offenders about the nuances of the city and how things, such as transportation systems, work prior to their release (Nelson, Deess, and Allen, 1999).

THE INTER-RELATIONSHIPS BETWEEN POVERTY, RACE, CRIME, AND PRISON

Although reentry and reducing poverty is the focus of this chapter, it would be remiss not to briefly address the inter-relationships between poverty, race, crime and prison. How crime rates and victimization rates vary by race is one of the most controversial issues in criminal justice.

Examining the statistics alone, African Americans make up about 13 percent of the adult population in the US, yet according to the UCR, they comprise 34 percent of property crime arrests and 34 percent of violent crime arrests. Examining arrest rates for homicide, African Americans are eight times more likely than whites are to be arrested for a homicide (see Barkan, 2005, p. 69). Further, a young African American male is the most likely victim of a violent crime in the US today.

Criminologists have examined these cross-cultural differences in crime rates and victimization rates for many years, and have arrived at a multitude of theories and explanations. Simply put, crime cannot be evaluated without taking into account social conditions. Young African Americans have a higher unemployment rate than whites, making crime a more tempting activity. More African Americans also live in areas where there are high poverty rates and this environment may foster criminal activity. Much has also been written about the lack of positive male African American role models, as currently the majority of African American households are female headed. Experiences


of prejudice and racism may also contribute to higher crime rates among African Americans (see Barkan, 2005).

Criminologists have also looked at police and policing practices when evaluating the relationship between race and crime. Many argue police target African Americans because police think African Americans are more likely to be involved in crime. This serves as a self-fulfilling prophecy, but serves as the rationale behind racial profiling. Further, African Americans are more likely to be arrested, charged, tried and convicted than other minority groups for many reasons, such as poor legal representation, lack of legal resources, and distrust of the justice system (see Reiman, 2001). The result is the poorest people in the US are the ones who end up in the nation’s prisons; the prison system is effectively the national poorhouse, so it is no wonder that upon release, ex-offenders return to lives of poverty (see Reiman, 2001 for discussion).

CHALLENGES TO EMPLOYMENT

The majority of offenders reenter society with little financial support and very few have employment secured. Their choices are to find a job, try to receive unemployment benefits (which can be challenging without a fixed address), or return to crime. The Department of Labor estimates an unemployed ex-offender is three times more likely to return to prison than an employed ex-offender is (DOL, 2007).

In a study of reentry, Rose, Clear, and Ryder (2002) write employment for ex-offenders is typically unstable, low paying, and part-time, thus, ex-offenders rarely qualify for health and other benefits. The result of this is many ex-offenders have to work more than one job to stay afloat or keep their families afloat. Many ex-offenders simply cannot make enough money to keep themselves and their families above the poverty line.

The reticence of employers to hire ex-offenders is a national issue. In a study conducted of US employers some time ago, Holzer (1996 cited in Holzer 2003) found 65 percent would not knowingly hire an ex-offender and between 30 and 40 percent indicated, they had checked the criminal records of their employees. Today, it is rare to apply for a job that does not ask for criminal history. Even if an employer has a policy of hiring ex-offenders, many ex-offenders do not know how to find a job, may not have a work history, and may lack work skills.

There are some programs established to alleviate this problem. In New York City, The Center for Employment Opportunities (CEO) is available for non-violent, ex-offenders immediately after release. Ex-offenders come to this program from boot camps, work release programs, probation and parole. The goal of CEO is to help ex-offenders locate and keep jobs. The CEO program was originally developed by the Vera Institute of Justice in 1978, and became independent of the institute in 1996.

The CEO program begins by holding an orientation and classes for ex-offenders immediately upon release. The orientation describes the CEO program and runs for one day. Following this is a four-day life skills and job readiness program designed by researchers at Columbia University for populations difficult to employ. The program covers how to search for a job, job interviews, and required paperwork for employment. The life skills portion of the program addresses practical concerns such as obtaining Medicaid, social security cards, driver’s license, housing, child-care, appropriate


clothing, opening a bank account, balancing a checkbook and a multitude of other essential skills (Finn, 1998).

Once ex-offenders have completed the class and if they have not yet secured employment, they are placed on day laborer crews. Thus, the CEO program is providing employment for ex-offenders only one week after they have been released. The day laborer crews instill good work habits, such as punctuality and teamwork, provide work skills, and most importantly, provide ex-offenders with an income that keeps them out of immediate poverty and bolsters their self-esteem. Ex-offenders can work on laborer crews for up to 12 weeks. Following this, the CEO program helps place the ex-offenders in permanent positions and provides follow-up services for the ex-offenders.

Program participants who violate the rules of employment, such as arriving late or not bringing the appropriate gear, are given one warning and action is taken, such as pay being docked. A second violation results in a mandatory disciplinary meeting with program administrators, during which time the participant is re-evaluated. A third violation results in termination. Program participants who commit serious acts, such as stealing, during the program are automatically terminated (Finn, 1998).

The CEO program is paid for by the work the crews do, and by Federal matched funds. Crews work on various types of construction projects, work on highways, roads, and parks, and do a variety of other landscaping and maintenance work. The CEOprogram also offers benefit to those employers who employ ex-offenders on a permanent basis once they have left the CEO program. Employers are eligible for tax benefits, and any of their employees can attend the CEO’s substance abuse programs free of charge (regardless of whether the employees are ex-offenders). Because ex-offenders placed with employers are proven reliable workers, the CEO program is also fostering a healthy attitude in the local community regarding hiring ex-offenders; more employers are likely to hire an ex-offender because of this program.

Evaluation of the CEO program is on going, although results to date indicate 70 percent of participants are place in permanent jobs. Given nationwide employment rates for ex-offenders are between 20 and 30 percent, the CEO program is a great success in reducing poverty among ex-offenders.

HOUSING

Finding housing upon reentry is one of the most difficult challenges for an ex-inmate. Prisoners do not have the financial means or social networks to obtain lease agreements. Further, criminal history is often used to exclude prisoners from leases. Government housing may also be difficult for ex-inmates to obtain given section eight providers can deny housing to anyone whose past criminal history may endanger the lives of other residents. Criminal history is very broadly defined as any drug related activity, violent activity or other criminal activity (Travis and Waul, 2003).

A number of other states have developed innovative ways of dealing with the high risk of homelessness among ex-inmates. In Hawaii, a prisoner will not be released to parole supervision unless he or she has an approved place to live. Inmates are given a furlough in order to find housing, and the Hawaii Paroling Authority estimates it takes about two months for an offender to secure housing (Wilhelm, 2003). The time is


considerably longer for sex offenders and other high-risk offenders who face additional legal restraints.

Inmates in Illinois are assured housing upon release. The Department of Corrections secured Federal funds to establish a placement resource unit charged with finding inmates short-term housing and employment for those inmates at risk of becoming homeless. There is also some funding available to be used as rent assistance (Wilhelm, 2003).

In the state of California, inmates who have completed a drug rehabilitation program in prison are eligible for up to six months of housing upon release, and housing is linked to further substance abuse programming. California has some 160,000 inmates, 75,000 of which are involved in some type of substance abuse program. Wilhelm writes inmate motivation for these programs is heightened dramatically by knowledge of after care and community resources connected to the program (2003).

Inmates released in Baltimore County, Maryland, can enroll in job training programs and then utilize a reentry program that helps find ex-inmates employment. Housing is guaranteed two months and is subsidized by wages or stipends earned by the ex-inmates. Wilhelm (2003) observes the director of this program initially thought about one third of inmates being released would need services from the reentry program, although in reality the number is about half.

In the state of Virginia, inmates can participate in project SOAR (Supporting Offenders After Release), a program run in conjunction with religious organizations in the community that helps current and inactive parolees transition back into the community by offering life skills training (such as teaching offenders how to find housing and balance a checkbook), mentoring, and referrals to community resources. Offenders begin the program during their last few months of incarceration and continue participation upon release. What is especially beneficial for program participants is the assignment of a mentor to each offender in the program. Mentors undergo training in the Virginia Department of Corrections and are subject to a background investigation. The mentor resides in the same area the offender will live, and upon release, works one-on-one with ex-offenders to help them re-establish themselves in the community. Having a mentor not only means the ex-offender has someone to turn to for advice and assistance, but the mentor can also serve as a sponsor or reference for the ex-offender, and in many cases have helped the ex-offender locate employment. This program is voluntary for ex-offenders, and faith-based organizations volunteer to provide the program.

Project SOAR is being offered at 13 of Virginia’s correctional institutions at the current time (VADOC, 2007). There currently is no assessment of this program in place.

MISSOURI’S PARALLEL UNIVERSE PROGRAM

In 1993, an innovative program called the Parallel Universe was implemented in Missouri prisons. This program was implemented in response to the realization that 97 percent of Missouri’s inmates were going to be released into society at some point, and they could only be contributing members of society if they were given the tools to do so (Schiro, 2000).

The Parallel Universe operates under the assumption prison life should reflect life on the outside as much as possible to cultivate skills that will ensure success. This meant the


entire prison system, including management, had to be overhauled. Inmates are required to make life-altering decisions about employment and education options, just as they would on the outside. During work hours, offenders either attend school, or go to work, just as they would on the outside. They are also paid according to their education level, trade or skill, as they would be paid on the outside, thus providing additional motivation for inmates to be involved in continuing education. The work and school component of the program is called “Buns out of Bed.” All inmates are required to obtain photo identification prior to attending school or working, pay social security, participate in health insurance, and file tax returns. These are simple practical skills and tools the inmates need to be successful on the outside, yet are frequently overlooked by the correctional system.

During non-work hours, inmates volunteer and participate in recreational activities. Substance abuse treatment programs are also plentiful, with facilities able to treat more than 2,700 inmates each year. Every inmate is also required to participate in a recidivism prevention program designed to provide inmates with tools to help them resist re-offending.

Most of the offenders in Missouri state prisons also complete a reparation program, where inmates may participate in victim – offender mediation, restitution plans, or victim-impact classes. These programs are designed for inmates to develop a realistic understanding of the harm caused by their crimes, and for them to take responsibility for them.

With good behavior, offenders in the Parallel Universe can also participate in decisions affecting their incarceration. Taken together, all the program components are designed to foster an attitude offenders can lead productive lives chosen by their own decisions; an often liberating experience. For example, earning a GED equates to earning a greater wage. Learning a trade means greater likelihood of employment.

Since the Parallel Universe has been implemented, more than 98 percent of inmates are involved in school, work or both, and none of these inmates is homeless. Between 1994 and 1999, institutional employment increased by 65 percent, and only one quarter did not hold a GED (although many were working on them). The state has also reported a drop in felony recidivism rates of one-third (Schriro, 2000). The program is now being used as a model for other states.

NEW YORK CITY’S PROJECT GREENLIGHT

Project Greenlight was established in the Queensboro Correctional Facility in New York in 2002. Designed to reduce recidivism, program administrators also expected to improve employment rates among those released, reduce homelessness, reduce substance abuse, and increase family support networks for ex-offenders and increase community support and services for ex-offenders. The program was the result of collaboration between the Vera Institute of Justice, The New York State Department of Correctional Services and the New York State Division of Parole, and consisted of a 60-day program provided for inmates at the Queensboro facility.

The program offered in Greenlight was an intense mix of classes and services for inmates about to be released in the proceeding two months. Classes covered job


preparation and development, which included interview skills and workplace behavior; substance abuse relapse prevention; practical skills, such as banking, time management, and transportation system navigation; cognitive skills training, such as delayed gratification and problem-solving; homelessness prevention, which included information about transitional housing and how to secure permanent housing; and community and family support, including parole information.

In addition to the above topics, each inmate received a release plan designed by Greenlight counselors tailored to fit their individual needs and expectations. Part of this plan matched inmates with appropriate social services and other community groups on the outside.

The program was evaluated, using a control group of inmates who were also released into New York City directly from prison and who had not participated in Greenlight. Results of the evaluation revealed participants in Greenlight were recipients of more community based services than non-participants, and were significantly less likely to report substance abuse. However, the evaluation also revealed there were no differences between the two groups on time spent in homeless shelters or time spent employed, two critical factors in reducing poverty. Further, the short-term recidivism rates, including arrests for new felonies and misdemeanors and parole violations, among Greenlightparticipants were higher than those who had not gone through the program.

In subsequent discussions of this project, some valuable lessons have been raised and have been used by other reentry programs. For example, participants in Greenlight were forced into participating in the program during their last two months of incarceration as a condition of their release. Other evaluations of reentry programs have indicated offenders who volunteer for programs are more motivated to succeed, and it takes several months for offenders to embrace a program. Initially, program participants can be reluctant to fully participate and may be hostile and skeptical. The classes in Greenlight were also large, as there were only four counselors in the program. Thus, many of the offenders may not have learned what they should have. It is also possible Greenlight participants had much higher expectations of their lives outside of prison, and when those expectations were not met, they became increasingly frustrated (Brown and Campbell, 2005, p.10).

Other lessons from Greenlight have centered on the evaluation process itself. This program ran for only one year, and results of the program may have changed during the second and third years as the program became more established. Accounting for other variables in the evaluation, such as crime rates in communities where offenders reentered, also need to be further examined. In any event, Greenlight has provided valuable lessons for other reentry programs.

PROJECT RIO

Project RIO (Reintegration of Offenders) has been a very successful post-release program in Texas, run under the management of the Texas Workforce Commission (TWC). The project was begun in 1991 and by 1998, had 150,000 graduates from 61 prisons and has involved some 20,000 employers (Anon, 1998).


Project RIO is designed to decrease recidivism rates by finding employment for parolees prior to their release. This means inmates have no time to ponder the futility of life once they are released. In cases where employment is not found before release, offenders attend seminars and training sessions until employment is found. In addition to the work program, Project RIO also targets employment readiness and helps offenders with attitude, appearance, and ultimately, self-esteem.

Evaluations of the program have indicated 66 percent of RIO participants who are minorities are employed after release, compared with only 30 percent of minorities who do not complete the program. Financially, the program saves Texas a great deal of money. Texas spends an average of $34,000 per year per inmate and Project RIO costs $400 per year per inmate. Given the lower recidivism rates for completers, project RIO saves Texas some $10 million each year in potential re-incarceration costs. Further, there are also financial benefits for employers. The Opportunity Tax Credit allows employers to earn up to $2,100 tax credit per qualified ex-offender during the first year of employment. Second, free fidelity bonding is available for each parolee hired (TWC, 2007).

Project RIO has also been extended to youth offenders in Texas. Under the direction of the Texas Youth Commission, the program follows a four-cornerstone approach to education and treatment. The four cornerstones are correctional therapy, education, work and discipline training. The youth RIO program aims to improve individual accountability and provide skills for more responsible decision-making. The program is also phase-progressive, so juveniles have to meet set criteria before moving onto the next phase of the program. There is a rewards system of privileges built into the program to encourage success (TWC, 2007).

SPECIAL CONCERNS OF FEMALES AND REENTRY

The number of female incarcerated in the United States has increased on average, some 4.6 percent each year since 1995, which is double the rate for males. Currently, about seven percent of all individuals incarcerated are women (Harrison and Beck, 2006). The vast majority of these women are serving sentences for non-violent offenses, such as property crimes and drug related offenses; as many as one in three women incarcerated are serving sentences for drug offenses. These women disproportionately represent low income, low educated, minority groups. Two thirds of incarcerated women report having children under the age of 18 years (Covington, 2001). In 2000, it was estimated there were 2.3 million children in the US with incarcerated parents (Mumola, 2000).

After one or both income-earning parents are incarcerated, families are often left in dire financial circumstances. For the most part, incarcerated parents are unable to provide financial assistance to their families, and instead, rely on families for assistance. Approximately seven percent of inmates in the US are employed by their respective prison systems, but wages are not enough to help families survive (Travis and Waul, 2003). For example, Pryor (2005) writes the average minimum state prison wage in 2002 was $0.89, and the maximum was $2.93. In the Federal system, hourly wages started at $0.15 and ended at $1.15 per hour (p. 5). This is not enough to provide financial assistance to a single person, let alone a family.


The effects of incarceration thus go well beyond offenders, especially if they happen to be parents. If the mother is incarcerated, often children are sent to live with other relatives or placed in foster care, initiating a host of additional problems. In 2000, BJSreported less than half of all mothers incarcerated in state facilities had any personal contact with their children since being incarcerated. Children with incarcerated mothers are at risk of increased poverty, increased physical and metal health problems and increased likelihood of involvement in the criminal justice system, thus perpetuating an inter-generational cycle of incarceration and poverty (Travis, 2005).

There are some key differences in characteristics of male and female offenders, which translate to differences in approaches to reentry. These are typically mental health issues, substance abuse issues and trauma (Covington, 2002). It is well established in psychology, sociology and medical literature females are more likely to self-medicate and self-mutilate when faced with life stressors than males, and the relationship between substance abuse and psychiatric illness is also well established. Coupled with a very high proportion of abuse, female offenders often require more complex forms of treatment than male offenders do.

Tackling reentry for female offenders is thus a difficult task. Covington (2002) suggests reentry programs should begin for women at the beginning of her sentence rather than toward the end, and must involve a myriad of services. In addition to the usual employment, housing, and substance abuse services, women about to reenter society also need assistance with child reunification. For many incarcerated women, the knowledge their children are in foster care, living with a relative, or have been separated from them is motivation enough for them to successfully complete their sentences. Child reunification is complicated and requires coordination with psychological services, child services agencies, as well as physical services for housing, healthcare, schooling, and childcare.

Research on females and reentry suggests wrap-around models, which involve multiple agencies in a coordinated program are the most successful in helping women transition successfully back into the community (Covington, 2002). There are numerous examples of such programs around the United States. One example is the non-profit organization called Our Place, located in Washington D.C. Established in 1999, this organization offers in-prison and post-release programs designed for women. One of the unique problems incarcerated women from the District of Columbia face, is incarceration in other states, such as Connecticut, Florida, and West Virginia, making family and community relationships much more difficult to maintain. Our Place offers a family transportation program to help family members visit women incarcerated in other states. The also offer pre-release programs for women that include multiple agency resources, and HIV / AIDS prevention and education. The latter is extremely important given the very high rates of HIV in the District of Columbia.

Post-release, Our Place offers transitional housing programs, employment placement, referrals for medical, mental health, and substance abuse services for women and their children. In evaluations of Our Place, participants consistently say finding housing is the most challenging hurdle they face upon reentry, and without transitional housing, they would instantly be homeless. Our Place also offers other very practical programs for women re-entering the community. For example, free legal services are available to help


newly released women with everything from immigration issues to child custody, a Saturday Our Kids program is provided to offer relief to caregivers and expose children to recreation activities, and a weekly support group is available for newly released women. The support group is a place where women can share their experiences with others and swap information and resources. It is also a place where program administrators can learn about need areas upon reentry.

One of the most popular services offered by Our Place is a clothing boutique that provides second hand business attire for released women who are entering the workforce. Again, this is a very practical yet simple approach to helping ex-offenders from spiraling into poverty. Women who have been incarcerated for any length of time are unlikely to have the resources needed to purchase business attire for employment interviews and subsequent jobs.

Other gender specific programs offer mental health treatment options for female offenders and ex-offenders. Some studies have indicated as many as 80 percent of female offenders have been exposed to some type of abuse in their lifetimes (Covington, 2002). Abuse is not limited to personal experience; it includes witnessing abuse. For survivors of any type of abuse, Post Traumatic Stress Disorder (PTSD) is a likely consequence and requires treatment if the survivor is going to lead a productive life outside of correctional facilities.

An example of a program that does offer mental health services is the TAMAR(Trauma, Addictions, Mental health and Recovery) program currently offered for women in local and some state facilities in Maryland. This program provides interagency services for women who are in need of trauma, victimization, substance abuse and mental illness treatment. Participants in this program receive therapy and counseling in both individual and group settings. The program continues for women post-release, offering service referrals and support groups. A newer component of TAMAR is TAMAR’s children, a program offering services to pregnant and post-natal women and their infants. Again, the focus is on mental health and specifically an intervention called the Circle of Security (COS) in which mother – baby bonds are emphasized. The goal of the program is to foster healthier families, break the cycle of abuse, and break the cycle of incarceration and related issues, such as poverty. At the end of the fiscal year in 2000, the recidivism rate among women who had completed the TAMAR program was less than three percent (www.reentrypolicy.org).

CONCLUSION AND CRITICAL SUCCESS FACTORS

The criminal justice system in the United States has long been torn between retribution and rehabilitation. No matter which ideology one ascribes to, the reality of the situation is, most of the individuals incarcerated in the nation’s prisons are going to be released at some point. In the next three years, it is expected about two million people will be released from state facilities alone. As a society, we need to address whether we want these people to succeed. Surely, it is more cost-effective to work toward making ex-offenders contributing members of society than it is to capitulate ex-offenders into poverty and the resulting crime cycle.


Reentry is the key to keeping ex-offenders and their families out of poverty. This chapter has reviewed current research on reentry and has highlighted numerous reentry programs from around the United States. This section of the chapter takes lessons from these programs and provides some critical success factors for reentry programs.

Before tackling specifics of reentry programs, there are some more general principles that need to be addressed if reentry is going to be successful. For example, the thinking reentry falls under the umbrella of the nation’s correctional facilities is too narrow a focus. There needs to be a realization reentry begins in the correctional system, but incorporates the community and the community’s agencies, government, non-profit, for profit and religious organizations. Second, we may also need to revisit sentencing guidelines. Current research suggests drug offenders are disproportionately incarcerated and their substance abuse problems often are the catalyst for criminal activity. Addressing substance abuse may be more useful than incarceration for some of these individuals.

Programs reviewed in this chapter indicate numerous small changes can be implemented to assist in reentry and ultimately keeping ex-offenders from falling into poverty and recidivism. Examples of small changes are changing the time and method of actual release for offenders, offering used clothing boutiques for ex-offenders who are trying to get into the job market, and ensuring offenders have family or friends greeting them upon release.

When implementing specific reentry programs, research suggests programs need to begin at least six months prior to release. This way, offenders can gradually make full use of the program resources. Results from Project Greenlight indicated programs implemented just two or three months prior to release do not allow for the time it takes for offenders to overcome skepticism and embrace a program.

One of the most important lessons learned from current reentry programs is the needed emphasis on transitional services, particularly housing and employment. If these two staples are not provided in some way, ex-offenders have almost no chance of avoiding poverty and recidivism. Further, programs must also focus on social networking. While housing and employment provide ex-offenders with financial stability and self-worth, social networks provide emotional support, and much needed social relationships. Numerous studies on reentry also indicate communities where ex-offenders are likely to be released are urban areas with few resources, thus economic development and planning are needed components.

This chapter has also highlighted the special needs of female ex-offenders. Research on female populations indicates reentry programs need to offer a broad array of social services, including mental health and medical services for women and their children. Programs also need to include parenting skills classes and legal services, such as immigration and child services advocacy. Covington (2002) also is a proponent of culture specific programs that consider cultural awareness and related cultural community resources.

In addition to the above, Mears et al., (2002) suggest correctional programs carefully match offender needs with program offerings; target offender needs that can be changed and may contribute to crime or limit complete reentry success, such as anti-social


behaviors; provide programs that are integrated into other prison programs to avoid redundancy; rely on existing program designs and implementation of programs; and involve researchers and practitioners in the programming planning, implementation, andevaluation.

The Department of Justice reentry mandate offers discretionary funds and block grants for communities to develop reentry programs. The initiative outlines a three-stage model for programs. Stage one is titled protect and prepare, and incorporates institution based programs for incarcerated offenders. Stage two is control and restore, and incorporates community based transition programs. Stage three is sustained support, and incorporates community based long-term support programs. DOJ cites assessment centers, reentry courts, supervised or electronically monitored boarding houses, mentoring programs and community correction centers as examples of programs that would qualify for funding. This initiative is indicative of the changing view of corrections, specifically education and other programs are a vital part of transitioning offenders back into society and keeping them out of poverty and away from recidivism.

REFERENCES

Anonymous (1998). RIO: A program for ex-offenders that works! Alternatives to Incarceration, 4(5), 13-17.

Baer, D. et al. (2006). Understanding the challenges of prisoner reentry: Research findings from the Urban Institute’s prisoner reentry portfolio. The Urban Institute Justice Policy Center, Washington D.C.

Brazzell, D. (2007). Reentry Mapping Brief: Informing and encouraging communities through reentry mapping. The Urban Institute Justice Policy Center, Washington D.C.

Brown, B., and Campbell, R. (Eds) (2005). Smoothing the path from prison to home: A roundtable discussion on the lessons of Project Greenlight. Vera Institute of Justice, New York.

Bureau of Justice Statistics (2003). Education and Correctional Populations. Washington D.C., Department of Justice. NCJ 195670.

Covington, S. (2002). A woman’s journey home: Challenges for female offenders and their children. Institute for Relational Development, The Urban Institute, Washington D.C. Available on-line at: http://www.urban.org/UploadedPDF/410630_FemaleOffenders.pdf

Department of Justice (2006). Reentry in the United States. http://www.reentry.gov/Accessed December 5, 2006.

Department of Labor (2007). Prisoner reentry: Issues and answers. http://www.dol.gov/cfbci/images/Prisoner_Reentry.pdf Accessed March 8, 2007.

Finn, P. (1998). Successful job placement for ex-offenders: the Center for Employment Opportunities. Program Focus, National Institute of Justice, Washington D.C. NCJ 168102.


Finn, P. (1999). Washington States’ corrections clearinghouse: A comprehensive approach to offender employment. Program Focus, National Institute of Justice, Washington D.C. NCJ 174441.

Gillece, J. (2002). Leaving jail: service linkage and community reentry for mothers with co-occurring disorders. The GAINS Center Series, Delmar, New York. Available online at: http://www.gainscenter.samhsa.gov/pdfs/Women/series/LeavingJail.pdf

Harrison, P.M., and Beck, A.J. (2006). Prisoners in 2005. Bureau of Justice Statistics Bulletin. Bureau of Justice Statistics, Washington D.C.

Hart Research Group (2002). Changing public attitudes toward the criminal justice system: Summary of Findings. Peter D. Hart Research Associates Inc.

Henderson, M.L., and Hanley, D. (2006). Planning for quality: A strategy for reentry initiatives. Western Criminology Review, 7 (2), 62-78.

Holzer, H.J. (2003). Employment barriers facing ex-prisoners. Paper prepared for the Urban Institute Reentry Roundtable: Employment Dimensions of Reentry: Understanding the Nexis between Prisoner Reentry and Work, New York.

Johnson, R. (1987). Hard Time: Understanding and reforming the prison. Pacific Grove, CA: Brooks/Cole.

La Vigne, N.G., Visher, C., and Castro, J. (2004). Chicago prisoners’ experiences returning home. The Urban Institute, Washington D.C.

Linton, J. (1998). Inmate education makes sense. Corrections Today, 60(3), 18-18.

MacLellan, T.M. (2005). Improving prisoner reentry through strategic policy innovations. National Governors Association Center for Best Practices, Washington D.C.

Mears, D.P., Lawrence, S., Solomon, A., and Waul, M. (2002). Prison-based programming: What it can do and why it is needed. Corrections Today, 64(2) 66-73.

Mumola, C. (2000). Incarcerated parents and their children. Bureau of Justice Statistics Special Report, August, NCJ 182335.

Nelson, M., Deess, P., and Allen, C. (1999). The first month out: Post-incarceration experiences in New York City. Vera Institute of Justice, New York City.

Parke, R.D. and K.A. Clarke-Stewart (2003). The effects of parental incarceration on children: Perspectives, Promises and Policies. In J. Travis and M. Waul (Eds). Prisoners once removed: The impact of incarceration and reentry on children, families and communities. The Urban Institute Press, Washington D.C.

Petersilia, J. (2000). When prisoners return to the community: Political, economic and social consequences. Sentencing and Corrections: Issues for the 21st Century, No. 9. National Institute of Justice, Washington D.C. NCJ 184253.

Pryor, F.L. (2005). Industries behind bars: An economic perspective on the production of goods and services by US prison industries. Review of Industrial Organization, 27, 1-16.

http://www.reentrypolicy.org (2007). Accessed April 2, 2007.


Reiman, J. (2001). The Rich get Richer and the Poor get Prison: Ideology, Class, and Criminal Justice (6th ed.) Allyn and Bacon: Boston, MA.

Rose, D., Clear, T., and Ryder, J. (2002). Drugs, incarcerations, and neighborhood life. The impact of reintegrating offenders into the community. U.S. Department of Justice: National Institute of Justice: Washington D.C.

Schriro, D. (2000). Correcting corrections: Missouri’s Parallel Universe. Sentencing and Corrections: Issues for the 21st Century, No. 8. National Institute of Justice, Washington D.C. NCJ 181414.

Texas Workforce Commission (2007). http://www.twc.state.tx.us/svcs/rio.htmlAccessed March 2, 2007.

Travis, J. (2005). But they all come back: Facing the challenges of prisoner reentry. The Urban Institute: Washington D.C.

Travis, J. and Waul, M. (2003). Prisoners once removed: The impact of incarceration and reentry on children, families and communities. The Urban Institute Press, Washington D.C.

Virginia Department of Corrections (2007). Website Accessed March 10, 2007.

Wilhelm, Daniel F. (2003). Issues in brief: Preventing homelessness among people leaving prison. Vera Institute of Justice, New York.

OTHER RESOURCES

Criminal Justice Policy Foundation http://www.cjpf.org/

Department of Justice Reentry Page http://www.reentry.gov/

Department of Labor Reentry Page http://www.dol.gov/cfbci/Ready4Work.htm

Housing and Reentry from NPR http://www.npr.org/news/specials/housingfirst/whoneeds/ex-offenders.html

Joint Fix: Programs for Reentry Success http://www.jointfx.com/

Michigan Department of Corrections Reentry Information http://www.michigan.gov/corrections/0,1607,7-119-9741_33218---,00.html

National Criminal Justice Reference Service http://www.ncjrs.gov/

New Jersey Institute for Social Justice http://correctionssentencing.blogspot.com/2007/03/great-reentry-resource.html

Planning for Reentry Initiatives http://wcr.sonoma.edu/v07n2/62-henderson/henderson.pdf

The Sentencing Project http://www.sentencingproject.org/

The Urban Institute’s Crime and Justice Group http://www.urban.org/justice/index.cfm

Vera Institute of Justice http://www.vera.org/


About the Author

Monica L.P. Robbers, Ph.D., is an associate professor and chair of the Department of Sociology and Criminal Justice at Marymount University in Arlington, Virginia. Dr. Robbers has recently published research addressing correctional programming, felony disenfranchisement, and the relationships between crime and the media.

67

CHAPTER 5

IMMIGRANT WOMEN AND THE LABOR MARKET

Sandy D. Alvarez1

Dept of Sociology and Anthropology, Shippensburg University429 Grove Hall, 1871 OLD MAIN

Shippensburg, PA 17257Email; [email protected]

ABSTRACT

The importance of the immigrant women’s role in the American labor market is worth noting due to both the magnitude of their participation and the effect it has on immigrant and host community alike. Their experiences and acceptance of cultural beliefs of the host community have affected their participation in the labor market. Whereas Cuban women participated in the labor market as a means of helping their family to regain some of their prior socioeconomic status they experienced in Cuba, their participation in the labor was expected to end when their husbands were able to succeed in their own ventures.

This study examines the role of immigrant women in the labor market and the challenges they face as they try to assist their families in attaining success in their host community.

Keywords: Assimilation, Cuban Americans, Education Performance and Attainment, Public Services, Immigrant Communities,

1 Sandra D. Alvarez is an assistant professor of Sociology and Anthropology at Shippensburg

University in Pennsylvania. Her research interests include social inequality, women and their status roles, human development indicators associated with immigration. Immigrants and public services. Her teaching interests encompass women and status, population problems and immigration.


Prior research exploring immigrant women’s participation in the labor market has been limited to an analysis of the public sphere of employment. Much of this research has focused on the wage gap and the limited employment opportunities without examining the social context within which choices, such as where to work and whether to work, are made. Personal choices to work within or outside the enclave are often complex and consider factors in the private sphere as much as the public sphere.

Portes and Stepick (1993:127) identified three conditions required for an ethnic enclave economy to develop: (1) a stable market that small firms can control by offering to the immigrant community culturally defined goods and services not available outside the enclave; (2), privileged access to a pool of cheap labor through networks within the community; and, (3) access to capital. The availability of a protected market and cheap labor give the incipient ethnic enterprises an “edge” over firms in the mainstream economy, provided they have sufficient access to capital (Portes and Stepick, 1996: 126).

They argued that these conditions exist in Miami’s Little Havana. Overlooked by their analyses was the extent to which women’s labor played a role on the development and continuation of the enclave economy.

Moreover, the importance of the immigrant women’s role in the American labor market is worth noting due to both the magnitude of their participation and the effect it has on immigrant and host community alike. Fernandez-Kelley and Garcia (1997) contend that the effect these women have on host communities may be reflective of their prior experiences in their country of origin. They compare the cases of Cuban women in Miami and Mexican women in Los Angeles. Their experiences and acceptance of cultural beliefs of the host community have affected their participation in the labor market. Whereas Cuban women participated in the labor market as a means of helping their family to regain some of their prior socioeconomic status they experienced in Cuba, their participation in the labor was expected to end when their husbands were able to succeed in their own ventures. This was unlike the experiences of Mexican women. Their participation in the labor market was not viewed as temporary but as a continuing need to assist in the family’s survival (Fernandez-Kelley and Garcia, 1997). Moreover, the issue of remittances is also likely to effect participation in the labor market. Women’s role in care taking of the elderly whether in the United States or abroad may further compound the need to stay employed.

It is the intent of this research to analyze the extent to which the labor market experiences of the Cuban women in this study are similar to those of Cuban or Mexican women in Fernandez-Kelley and Garcia’s (1997) study. They rely on data collected previously to make their claim that the motivation of Cuban women to remain in the labor force was temporary and conditional upon the ability of their husbands to prosper financially, with the husband’s financial success allowing them to return to their previous duties within the household. I suggest Cuban American women today are very different from their predecessors they have higher educational status (Table-1). They are motivated to work for a variety of different reasons, many of which are more similar to the Mexican American women in Fernandez-Kelley and Garcia’s research (1997).

Immigrating Mexican women are more likely to be economically disadvantaged within the labor market due to lower levels of education and lower labor force


participation levels. Yet their increased presence in the labor market can bolster their family’s economic resources enough to ameliorate poverty conditions (Greenless and Saenz, 1999). These authors propose an alternative model for examining the role of immigrant women in the labor market. Their theoretical model suggests that Awomen=s employment is influenced by their personal (individual level) capital resources, household budgetary requirements (for individual married couples) that affect decisions for home or work production, and employment opportunities available (Saenz and Greenless, 1999: 355). Each of these factors are expected to influence the employment of the Cuban-American women as well.

In other words, women prioritize caregiving to their family ahead of personal goals, while men focus on their employment objectives. The consequence for women when they place family ahead of career is often in lower wage jobs with little or no benefits (Hondagneu-Sotelo, 1994). They come in contact with the state in order to assist their family. For example, women are most likely to apply for social service programs such as Head Start to provide childcare so that they may work to assist the family financially, but are involved in the program to help their children succeed in the program. The career in the family usually regarded as most important is the husbands’. These employment patterns illustrate to family members the hierarchy of roles. This hierarchy in turn perpetuates the patriarchal subordination. The subordination however, predates the migration. Young women from the beginning, often offer little to the decision making in the migration process yet have the most to lose.

Gilbertson’s (1995) analysis of immigrant women working within an enclave economy points to another aspect of the labor market experiences many immigrant women have: co-ethnic exploitation in ethnic enclave economies. This is consistent with the findings of Sanders and Nee (1987), who posit that there exists an inherently exploitative relationship between the co-ethnic worker and their co-ethnic employer based upon the needs of the enterprises to have a readily accessible and abundant cheap labor pool. Although Sanders and Nee (1987) did not focus on women, Gilbertson does. She contends that women within the enclave are likely to be exploited due to discrimination, occupational segregation and work/family conflicts that result in lower wages and a more narrow range of opportunities for women than men in an enclave economy.

Zhou and Logan (1989) contend that Chinese women workers in New York City had no measurable earnings return on their previously attained human capital. Their participation within the enclave economy was based not only on the income they could provide to support their family’s needs. They also had to consider how their paid work would affect child care and other responsibilities they usually have in the household division of labor. Consequently, although wages outside the enclave were generally higher, those jobs often did not provide the hours and flexibility found with enclave employment (Zhou and Logan, 1989).

The researchers, Shumway and Cooke (1996) found that when women migrate they lose social networks that often came in the form of family and friends. In the host community, they confront barriers of language and culture that may facilitate isolation. This isolation can work to create more dependence on husbands’ taking autonomy away from the wife, increasing the dynamic of patriarchal relations within the household.


However, once immigrant women begin working and adding income to the family coffers their value often begins to change (Table-2). It is possible for them to gain social independence, as they reconstruct their role as wife, partner and equal contributor. This does not negate their on-going duties to care for children and the home but does increase their self perception as contributors nearly equal to that of their spouse.

Although the cultural expectations are present, immigrant women are not necessarily monolithic in nature. Whereas many immigrant women will adhere to cultural norms and feel the burden of exploitation and subordination, not all immigrant women will.

Coleman(1988) posits that social capital must be defined in terms of functions. Similar to other forms of capital, social capital occurs within social structures and can be productive. In other words, social capital can facilitate achievement and motivate to a specific end that without it would not be possible. “Unlike other forms of capital, social capital inheres in the structure of actors and among actors (Coleman, 1988, p.98).”

An important aspect of social capital, is the transference of information that occurs within social structures(Coleman, 1988). How social actors access this information through and information channel can be a fundamental to the function of social capital. Coleman goes further to consider aspects of prescriptive norms and social capital. In this respect, social capital may act as a norm that discourages self interests or acts in the interests of the collectivity(Coleman, 1988).

“All social relations and social structures facilitate some forms of social capital; actors establish relations purposefully and continue them when they continue to provide benefits (Coleman, 1988, p105).” Simply put, social capital in the family and in the community can play a part in furthering the creation of human capital (Coleman, 1988).

Whereas the earlier waves of Cuban exile males were able to utilize forms of social capital such as multifamily pooling of resources, and access to association loans, women were not given these opportunities. Moreover, Cuban women were discouraged from pursuing capital for business ventures due to their expected work in the household that would exclude them from seeking other opportunities.

The experiences of Cuban immigrant women within the enclave demonstrated a different outcome. They are less likely to access various forms of social capital in compared to their male counterparts. Due to patriarchal relations, they are more likely to utilize public services and access social capital and create social networks through the assistance of state institutions such as Head Start program.

Table-1:Foreign-Born Populations by Selected Characteristics: 2005

Total NaturalizedNot US Citizen

2000-March 2005

Persons 25 years old and over 28, 446 12, 375 16, 072 4, 620

Not high school graduate 9, 249 2, 617 6, 631 1, 480

High school graduate/ 11, 571 5, 744 5, 827 1, 635


some college

Bachelor's degree 4, 818 2, 534 2, 283 956

Advanced degree 2, 809 1, 479 1, 331 548

US Census National Statistical Abstract, 2007

Table-2:Foreign-Born Populations by Selected Characteristics: 2005

POVERTY STATUS IN 2004 \3

At or below poverty level 6, 006 1, 328 4, 678 2, 006

Above poverty level 29, 109 12, 168 16, 941 5, 882

US Census National Statistical Abstract, 2007

REFERENCE

Alvarez, Sandra (1994). The Effects of Politics on an Ethnic Enclave as a Social Movement. Master’s Thesis. Central Missouri State University. Warrensburg, Mo.

Britton, Dana (2000). The Epistemology of Gendered the Organization. Gender and Society. 14, 3, 418-434.

Card D. (1990). The Impact of the Mariel Boatlift on the Miami Labor Market. Industrial and Labor Relations Review. 43, 2, 245-257.

Celano, M.J. and F.B. Tyler (1991). Behavioral Acculturation of Vietnamese Refugees in the United States. Journal of Social Psychology. 131, 3, 373-385.

Cobas, Jose and I. De Ollos (1989). Family Ties, Co-Ethnic Bonds, and Ethnic Entrepreneurship. Sociological Perspectives. 32, 3, 403-411.

Coleman, James S. (1988). Social Capital in the Creation of Human Capital, American Journal of Sociology, 94, Issue Supplement: Organization And Institutions: Sociological and Economic Approaches to the Analysis of Social Structure, 95-120.

Duignan, Peter and Lewis H. Gann (Ed.) (1998). The Debate In the United States over Immigration. Stanford, CA: Hoover Institution Press.

Eisenstadt, S.N. (1953). Analysis of Patterns of Immigrant Absorption. Population Studies. 7, 2, 167-180.

Eisenstadt, S.N. (1954). Reference Group Behavior and Social Integration: An Exploratory Study. American Sociological Review. 19, 2, 175-185.

Fernandez-Kelley, Maria Patricia and Anna M.Garcia. In Romero, Mary, Pierrette Hondagneu-Sotelo, and Vilma Ortiz (Ed.) (1997). Challenging Fronteras: Structuring Latina and Latino Lives in the U.S. New York: Routledge, 215-227.

Frankenhoff, C.A. (1985). Cuban, Haitian Refugees in Miami: Public Policy Needs Growth from Welfare to Mainstream. Migration Today. 13, 3, 7-13.


Fuentes, Frank; Cantu, Virginia D. and Stechuk, Robert A. (1996). Migrant Head Start: What Does it Mean to Involve Parents in Program Service? Children Today. 24(1), 16-18.

Gilbertson, Greta A. (1995). Women’s Labor and Enclave Employment: The Case of Dominican and Colombian Women in New York City. International Migration Review. 29, 3, 111, 657-670.

Greenless, Clyde S. and Rogelio Saenz (1999). Determinants of Employment of Recently Arrived Mexican Immigrant Wives. International Migration Review. Summer, 29, 3, i2, 354-371.

Grenier, Guillermo and Alex Stepick, III. (1992). Miami Now: immigration, ethnicity, and social change. Gainesville: University of Florida.

Head Start Bureau (1999). Preparing your Child for Head Start. Washington, D.C: Government Printing Office.

Head Start Bureau (2000). Facts about Head Start: Recent Research. Washington, D.C: Government Printing Office.

Hondagneu-Sotelo, Pierrette (1994). Gendered Transitions: Mexican Experiences of Immigration. Berkeley: University of California.

Jensen, Leif, Alejandro Portes and Jimy M. Sanders (1992). The Ethnic Enclave and the Entrants: Patterns of ethnic enterprise in Miami before and After Mariel. American Sociological Review. 57, 3, 411-414.

Jones, Delmos (1993). The Culture of Achievement-Among the Poor: The Case of Mothers and Children In a Head Start Program, Critique of Anthropology. 13, 3, 247-266.

Kelson, Gregory A. and Debra L. DeLaet (1999). Gender and Immigration. New York: New York University.

Lamphere, Louise, Alex Stepick, and Guillermo Grenier (1994). Newcomers in the Workplace: immigrant and the restructuring of the U.S. economy. Philadelphia: Temple University.

Lowe, Lisa (1998). Work, Immigration, Gender: New Subject of Cultural Politics. Social Justice. 25, 3, 73, 31-49.

Matthei, Linda Miller (1996). Gender and International Labor Migration: A Networks Approach. Social Justice. 23, 3, 38-54.

Mora, Marie T. and Alberto Davila (1998). Gender, Earnings, and the English Skill Acquisition of Hispanic Workers in the United States, Economic Inquiry. 36, 4, 631-645.

Nee, Victor, Jimy M. Sanders, and Scott Sernau (1994). Job Transitions in an Immigrant Metropolis: Ethnic Boundaries and the Mixed Economy, American Sociological Review. 59, 6, 849-872.


Pedraza, Silvia (1991). Women and Migration: The Social Consequences of Gender, Annual Review of Sociology. 17, 303-325.

Pedraza-Bailey, Silvia (1985). Cuba’s Exiles: Portrait of a Refugee Migration, International Migration Review, 19, (Spring), 4-34.

Perez, Lisandro (1986). Immigrant Economic Adjustment and Family Orientation: The Cuban Success Story, International Migration Review, 20, 4-20.

Portes, Alejandro (1987). The Social Origins of the Ethnic Enclave Economy. Sociological Perspectives. 30, 340-372.

Portes, Alejandro and Robert L. Bach (1985). Latin Journey: Cuban and Mexican Immigrants in the United States. Berkeley: University of California.

Portes, Alejandro and Ruben Rumbaut (1996) (2nd Ed) Immigrant America: A Portrait. Berkeley: University of California.

Portes, Alejandro and Leif Jensen (1989). The Enclave and the Entrants: Patterns of Ethnic Enterprise In Miami Before and After Mariel. American Sociological Review. 54, 6, 929-949.

Portes, Alejandro and Julia Sensenbrenner (1993). Embeddedness and Immigration: Notes on the Social Determinants of Economic Action, American Journal of Sociology, 98, 6, 1320-1350.

Portes, Alejandro and Alex Stepick (1985). Unwelcome Immigrants: The Labor Market Experiences of 1980 (Mariel) Cuban and Haitian Refugees in South Florida. American Sociological Review, 50, 4, 493-514.

Portes, Alejandro and Alex Stepick (1993). City on The Edge: the Transformation of Miami. Berkeley: University of California.

Rivera-Batiz, Francisco, Selig L. Secher and Ira N. Gang (Ed.) (1991). U.S. Immigration Policy Reform in the 1980’s: A Preliminary Assessment. New York: Praeger.

Romero, Mary, Pierrette Hondagneu-Sotelo, and Vilma Ortiz (Ed.) (1997). Challenging Fronteras: Structuring Latina and Latino Lives in the U.S. New York: Routledge.

Sanders, Jimy M. and Victor Nee (1987). Limits of Ethnic Solidarity in the Enclave Economy. American Sociological Review. 52, 6, 745-767.

Schoeni, Robert (1998). Labor Market Outcomes of Immigrant Women in the United States: 1970-1990. International Migration Review. Spring, 32, 1, 57-68.

Shumway, J. Matthew and Thomas J. Cooke (1998). Gender And Ethnic Concentration and Employment Prospects for Mexican-American migrants. Growth and Change, Wntr, 29, 1, 23-44.

U.S. Bureau of the Census (2005). 2000 Census of Population, General Population Characteristics. Washington, D.C.: U.S. Government Printing Office.


Walby, Silvia (1996). In Moghadam, Valentine. [Ed.] Patriarchy and Economic Development: women’s positions in at the end of the twentieth century. New York: Oxford University Press, 3-26.

Zhou, Min and Carl Bankston, III. (1998). Growing up American: How Vietnamese Children Adapt to Life In the United States. New York: Russell Sage Foundation.

Zhou, Min and John R. Logan (1989). Returns on Human Capital in Ethnic Enclaves: New York City’s Chinatown. American Sociological Review. 54, 5, 809-820.

75

CHAPTER 6

MEASUREMENT OF POVERTY IN PAKISTAN: A NEW METHOD

Munir AhmadNational College of Business Administration & Economics

Lahore, PakistanEmail: [email protected]

ABSTRACT

It is generally considered that population and poverty go hand in hand. In this paper, we show that population is not an important poverty parameter. We measure the poverty on the basis of eight factors of population and housing data (1998) and show that illiteracy is the most important poverty parameter.


1. INTRODUCTION

Pakistan is a poor country and poverty seems endemic. The poverty line is internationally defined on the basis of purchase of bundle of basic needs including food, fuel, housing and clothing. It translates into a daily income of between US$ 1/- and US$ 2/-. The poverty line for Pakistan was 46% in 1985-86 and 34% in 1995. (World Bank, 2002). We saw an unprecedented population growth, technological advancement and poverty during the 20th century. The world witnessed an increase of population from 1.6 billion to 6.1 billion persons in 100 years (UN 2001a, b) and corresponding growth of per capita income of US$ 300/- to US$ 20,000/- (DeLong, 1998). Both population and per capital income growth exerted direct impact on global poverty. World Bank and Asian Development Bank support Pakistan in conducting research on rural poverty reduction in 2004, but it has not helped yet in poverty reduction. Policy makers should not work for poverty eradication to earn financial support from aid giving agencies. It seems, they provide only lip services and paper work.

Pakistan is facing various types of problems in improving the quality of life of its population. The causes of these problems are inequitable economic growth, widespread poverty, low literacy and unfriendly social structure. Poverty is associated with the increasing pressure of population and low literacy rate. One of the major concern is the housing facilities. One definition of poverty is that a person is assumed poor if he/she does not have basic package of goods services and rights. The second definition is that of economic deprivation, viz. misdistribution of welfare schemes, social inequality and unemployment. Since a household is built-up on individual persons, then poor persons would mean poor households. In this paper, poverty is defined on household level. A household is poor if it has large family size with small number of rooms per housing unit, has kacha house made of mud mired with grass fibers, has no access to clean water etc. i.e. a household is housing-facilities deprivation. The poverty reduction policy should not be concentrated on population viz. job availability, and income, but depends on some basic requirements of housing infrastructure especially in rural areas. The basic needs of growing population is dependent on sufficient size of a housing unit to house the family, housing structure, source of drinking water, source of light, cooking fuel, housing facilities like a good, kitchen, bath room and latrine.

Good housing is one of the basic human needs. The estimated housing backlog is about 4.30 million housing units (Population Census Organization, 2001), Government of Pakistan formulated a policy in 2001 to deal with the small population living in katcha houses abadies in rural and urban areas. Katchi abadies have highly inadequate housing facilities. As defined, a housing unit with no electricity, no access to clean water, no gas for cooking, no kitchen, no bath room and no toilet are important poverty parameters and puts residents in physical and psychological stresses and mental depression.

In this paper the poverty is more linked with the illiteracy than the population growth. Poverty exists when an individual has no access to income, jobs and good housing structures. Absence of and lack of access to basic facilities is used to measure poverty. It is essential to integrate demographic and housing facility factors into poverty assessments. This is a new dimension of assessment of poverty. We believe that the definitions and methods used in this study have not been addressed by earlier economists and demographers.


2. HOUSING CHARACTERISTICS

Estimation of standard of living index comprising the following household facilities in addition to other factors has been made by Banerjee and Roy (2002). Since the majority of poor people live in rural areas, organizations interested in poverty reduction should invest in rural development and agricultural productivity, roads to markets, schools and health care centers. If one can identify poverty ridden areas, strategic planning can be adopted to reduce poverty. We have defined the poverty on the basis of

i) average household size,ii) average number of rooms per housing unit,iii) katcha houses, iv) access to pond water only,v) sources of light (kerosene oil),vi) source of cooking fuel (wood and kerosene oil), andvii)absence of housing facilities i.e. no kitchen, no bath room and no latrine.

In this paper, we assume, but not limited to, the above factors as poverty parameters which are the minimal needs that separate households in to poor and non poor. Poverty involves all characteristics like a katcha house with no kitchen, no bathroom, no toilets, no access to safe and clean water etc.

Population growth is considered as a single most important factor worldwide forpoverty but this factor is not evident from Pakistan data, instead illiteracy has become the most effective single factor for poverty in Pakistan. In Pakistan, growth rate has the weakest link with poverty. The ecological correlations among literacy rate, population growth rate and quality of housings in Punjab, Pakistan have been calculated and are exhibited in the following diagram (Fig. 1):

Fig. (1): Correlation Analysis of Socio-demographic factors and quality of housings, Punjab, 1998 source: Ahmad et al. (2003).


3. ODDS RATIO

Odd ratios has now been used in many areas and which shows the degree of links between two characteristics of factors. In this section, we study odd ratio for rural-urban differentials. Suppose we consider katcha houses as 1 and non-katcha houses as 0 and rural area as 1 and urban (non-rural) as 0, then we compute odd ratio for a specimen 2x2 table (Table-1).

Table-1:2x2 Table for Katcha Housing Structure for Pakistan

(Prop.) Katcha housing structures

(1)

(Prop.) Non-katcha housing structures

(0)Rural (1) 43.8 N1 56.2 N1 100 N1Urban (0) 10.7 N2 89.3 N2 100 N2

43.8 N1+10.7 N2 56.2 N1+89.3 N2 100 (N1+N2)

The odd ratio 48.8 89.3

6.5356.2 10.7

,

where N1 and N2 are the number of housing units in rural and urban areas respectively.

The value of odd ratio for katcha housing structure versus rural area is 6.53 which shows that in Pakistan the probability of rural population to have katcha housing units is 6.5 times more than the probability of urban population to be using katcha house. A person in rural area has 6.5 more chance of having a katcha house than a person living in urban area.

The Table-2 below gives odd ratios for the poverty parameters for Pakistan and the provinces of Pakistan.

Table-2:Odd Ratios of Inducing Stress Parameters by Provinces in Pakistan

Name of Area

KatchaHousing

Structure

Usage of Pond Water

Source of

Light

CookingFuel Used

NoKitchen

No Bath

Room

No Latrine

Punjab 7.00 2.76 8.26 6.47 2.78 8.01 21.46Sindh 11.16 1.93 11.97 35.27 5.23 13.28 20.79NWFP 2.21 4.66 10.89 12.78 2.08 3.76 8.06Balochistan 3.54 4.81 9.99 8.37 3.91 5.37 10.55Source: Ahmad, et al. (2003)

4. A METHOD OF MEASURING POVERTY

We have considered eight factors that contribute to poverty. A person or a family is assumed to be a poor if it does not a large house, reasonable number of rooms, brick cement pacca-housing structures. The family does not have access to good drinking water. It does not have electricity, gas, kitchen, latrine, bathroom etc.


We find index of each factor that contribute to poverty. Suppose KHiRI is defined as

the proportion of number of housing units with katcha (KH) housing structures in ith rural area:

KHiRI =

Number of housing units with katcha housing structures in rural area

Number of housing units with non-katcha (pacca + semi-pacca) housing structures in rural area

Similarly KHiUI and KH

iTI have been defined for urban and total areas of the ith

district. Each of these indices will be larger than zero i.e. ( ) 0iRI . Such indices are

obtained for each of the factor that contribute to poverty. These proportions are pooled to obtain one index for each district or area. The pooled index is the average (Geometric Mean) of the poverty indices:

1

Ikk j

iR iRj

I I

, k = 8 is the number of poverty factors, (1)

where

j = 1 denotes average house hold sizej = 2 denotes katcha housing structurej = 3 denotes access to pond waterj = 4 denotes use of kerosene oil and ‘other’ source of lightj = 5 denotes use of wood & kerosene oil as source of cooking fuelj = 6 denotes ‘no’ kitchen facilityj = 7 denotes ‘no’ bath room facilityj = 8 denotes ‘no’ latrine facility.

The formula (1) provides an index for the ith area.

The Poverty Indices for Pakistan and Provinces based on population census data (PCO, 2000) are given at Table-3.

Table-3:Poverty Indices by Provinces and Rural-Urban Areas

Area Rural Urban Total

Pakistan 50.82 13.46 40.03Punjab 45.01 11.99 36.08Sindh 53.82 10.28 35.83NWFP 48.28 15.61 43.84Balochistan 62.36 22.69 55.21

The general poverty index is 40% for Pakistan, 51% for rural Pakistan and about 14% for urban Pakistan. The index involves all characteristics of a poor person who has a


katcha house with no kitchen, no bathroom, no toilets and does not have access to safe and clean water, uses wood/kerosene oil as cooking fuel and kerosene oil as source of light. These factors are also strongly linked with very low literacy rate. One of the main results is that 40% to 50% of population is living in sub-standard conditions and can be recognized as living below poverty line.

In Punjab, 36% of people live below poverty line, 45% in rural areas and 12% of population is living in dilapidated conditions in urban Punjab. In Punjab, the poorest division is Bahawalpur Division with percentages of 52. Sindh is a little better province where 35.8% of people live under shabby conditions, 53.8% of poor people live in rural Sindh. The highest level of poverty is in rural Mirpur Khas Division which has about 53% of people living in sub-standard conditions. Karachi Division being urban in nature has the lowest percentage of poor people. NWFP is the second poor province with 44% people having low quality of life. D.I. Khan is the worst hit division in the province with GES value of 53%. Balochistan is the poorest province with 55% poor people. In Balochistan, Nasirabad Division is the poorest of all. It has more than 75% living in dilapidated conditions. (Ahmad, 2005).

5. ACKNOWLEDGEMENT

The author is indebted to Prof. Akhlaq Ahmed and Dr. Suleman Aziz Lodhi for suggestion that improve the text of the paper and to Mr. Zahoor Ahmad for computing the poverty indices. The author is grateful to Mr. M. Iftikhar, Mr. M. Imtiaz and Mr. Saif-ur-Rehman ISOSS Secretaries for the type set.

6. REFERENCES

Portes, Alejandro and Alex Stepick (1993). City on The Edge: the Transformation of Miami. Berkeley: University of California.

Ahmad, M. (2005). Census based analysis of population and environmental issues. Unpublished manuscript. Islamic Countries Society of Statistical Sciences (ISOSS) and National College of Business Administration and Economics (NCBA&E), Lahore. Pakistan.

Ahmad, M. and Akhlaq Ahmad (2002). Census Data Analysis of Population and Environment Issues. Presented to Conference on Population, Population Association of Pakistan, Lahore, Pakistan.

Ahmad, M., Ahmad A. and Afzal, S. (2003). Population Environment. Chapter 19, 383-409. In Kemal A.R. Irfan, M and Mahmood, N. (2003)(editors). Population of Pakistan. Pak. Institute of Development Economics, Islamabad, Pakistan.

Asian Development Bank (2004. Pakistan for rural poverty reduction drives. www.org/media/articles/2004/4839.

Banerjee, S.K. and Roy, T.K. (2002). Parental Consanguinity and offspring Mortality: The Search for Possible Linkage in the Indian Context. Asia-Pacific Population Journal, Vol. 17(1), 17-38.


DeLong, J.B. (1998). Estimating World GDP, one million B.C. – present. http://www.j-bredford-delong.net/TCEN/1998-draft/world-GDP/Estimating-World-GDP.html.

Government of Pakistan (1997). Pakistan Country Profile. http://www.un.org/dpesd/earthsummit

Pace Nedanovski (2001). Poverty Measurement in Transitional Circumstances: Methodological Aspects. CPM 45.1, Proc. ISI, 91-92.

Population Census Organization, (2001). District Census Reports, Statistics Division, Government of Pakistan, Islamabad.

Preston, S.H. (2001). Demography: Measuring and Modeling Population Processes. Blackwell Publishers Ltd., Oxford, U.K.

UN (2001a). Results of the Eighth United Nations Inquiry among Governments on Population and Development. Sales No. E.01.XIII.2, UN Publications, N.Y. USA.

UN (2001b). Population, Environment and Development. The Concise Report. ST/ESA/SER.A/202, UN Publications, N.Y. USA.

World Bank (2002). Pakistan Development Policy Review; A New Dawn? Report No. 23 916-Pak.

About the Author

Munir Ahmad, born in Sialkot, studied in Murray College, Sialkot, Institute of Statistics, University of the Punjab, Lahore, and taught at University of the Punjab, Karachi University, Karachi and Michigan Tech. University, Houston, Michigan, USA. He did his post graduate degree at Aberdeen University, Aberdeen, UK and Ph.D. from Iowa State University, USA. He is the author of more than 150 research papers published in national and international journals. He is currently working as Rector. National College of Business Administration and Economics and Professor of Statistics in the School of Business Administration and Economics. His area of research is statistics, population, data neural network, and various management sciences.

81

CHAPTER 7

POVERTY: A NEW TARGET FOR TECHNOLOGYAn Analysis on Poverty reduction with the help of Technology

Khalil AhmedNational College of Business Administration & Economics

Lahore, PakistanEmail: [email protected]

ABSTRACT

Technology is a rapidly evolving assistant to human in scientific and social sectors. Though this innovative assistance is available to human since centuries, but 21st century is prominent due to the swift expansion and advancement in technology borders. Either it’s the field of medical science or engineering; exploration of new space frontiers or insights of computation, technology is providing research, development and deployment resources. In an extreme contrast, poverty exists with same characteristics of growth and effectiveness on human lives, although poverty is a many centuries old entity in human culture, but 21st century is prominent in timeline due to the engraving effects of poverty on human lives. This paper analyses some of the technologies effective to eradicate or reduce poverty.

Keywords: Poverty, ICT, GRT, Policy Designing


INTRODUCTION

The advancement in technology becomes one of the most prominent features of last century in history. In 20th century, world faced the advantages and also devastating effects of technology on environment, culture, politics, science and most importantly human lives. Maddison (2001) calculated this effect by evaluating the growth of world per capita GDP due to the industrial revolution. It shows that GDP increased by a factor of 24 from 0.05 per cent per annum in 1000-1820 to 1.21 per cent a year from 1820 to the present. This global progress is not reaching many areas of the world due to the absence of coherence between technology and governance strategy. By the rise of new millennium, it became very clear that in some parts of the world rapid progress is linked with not only technology but also equally dependent on relevant and supportive strategy to reduce poverty. Eradication of poverty through technology is highly dependent on selection of suitable technology which requires skill and literacy, in other words technology as a poverty reduction tool needs a dedicated incubator which provides and implements suitable rules and supportive measures to make technology successful.

Current phase of technological advancements is not only the further refinement in various areas but this phase is also focused on new scenarios of technology usage specially related to socio-economic systems. In current technology layer connectivity turns into wide range wireless communication, information processing turns into knowledge management and sharing, general applications are turning into intelligent evolving programs, technology is now becoming a strong analytical and development tool in social sciences. In this new sector, the most difficult target for technology is the deeply rooted and multi-dimensional entity named “Poverty”. It is growing and living in human culture for so long and in so many ways that its eradication or alleviation needs technological, political, governmental and social efforts, technology can provide products, ways and means, processes to reduce the incursion of poverty in human lives but that is not possible without collective and strategic plans.

Technology cannot work in isolation, it work effectively within social systems, especially for poverty reduction the contribution of technology requires institutional, government and social collaboration. Like in People’s Republic of China (PRC), poverty alleviation program started in late 70s and it incorporated rural area reforms, policies for farmers, irrigation systems, skill based training programs and financial support to buy technology. The outcomes of PRC’s poverty reduction efforts are also interconnected as technology and poverty, the way technology can reduce poverty, similarly reduction in poverty can enhance the people’s capability to use technology. Lipton (2001) explained that technological advances in agriculture lead to improvements in health and human productivity, declining mortality and fertility rates, increased investment in children’s education and enhanced human capabilities to develop and use new techniques.

The World Development Report 2000/2001 states that poverty is a pronounced deprivation in well-being, it also accepts that traditional view of poverty as encompassing not only material deprivation (measured by an appropriate concept of income or consumption) but also low achievements in education and health. Poverty is linked with hunger, insufficient clothing, lack of shelter, inadequate medical facilities and most of all


illiteracy. Out of world’s 6 billion people, 2.8 billion live on less than $2 a day, and 1.2 billion live on less than $1 a day (World Bank, 2000). Technology advancements have improved more in the past century than in the rest of history, in East Asia the number of people living on less than $1 a day fell from around 420 million to around 280 million between 1987 and 1998 while in South Asia, Africa and Latin America, the number of poor people has raised. In the countries of Central Asia and Europe in transition, poverty has increased more than twenty fold (World Bank, 2000).

Poverty is a universal entity, growing along with humans in almost every part of the world, largely we linked it with economy but that’s not it, poverty is multi-dimensional and can affect political, social and cultural structures. With the increase in world’s population, the challenge of poverty reduction is also becoming stronger, it is not dependent on government policies only, and as the nature of poverty is multi-dimensional therefore it requires reduction plans and efforts from various channels. European industrial revolution generated a thought stream to refine and improve the production along with product; the innovation was separation of product and production. The domain of product included marketing, customer and services, while production included human resource, supply chain management and quality assurance. Information sharing and communication gradually became the most demanding success factor in the industry. Information and Communication Technologies (ICT) is now the hub for business and non-business digitalization in form of fast communication and accurate information exchange. ICT, the latest “general purpose technology” is one of the tools to support strategies and models for poverty alleviation.

ICT’s progress may well be divided into two phases, one is e-commerce emergence and second is knowledge portals. Initially ICT contributed as a communication and information bridge between the participants of urban business and economic structures.The growing demand for ICT resulted into new economic terminologies i.e. B2C (Business-to-Consumer) and B2B (Business-to-Business), new quality standards introduced like ISO9000, CMM-Levels (Capability Maturity Model) but e-commerce failed to get same response in rural areas due to the problems in adoptability. ICT needs skilled labor therefore its effects in rural areas were less or rather negative due to the increased demand in skilled labor instead of unskilled workers.

For poverty reduction, the most important and sensitive factor is the selection of suitable technology according to the situation, economy and adoption/diffusion rate of technology. Considering the poverty alleviation a goal, suitable technology varies according to the situation, a technology product can be a right solution to provide direct benefits to poor e.g. medicine, HYVs (high yielding crop varieties), Pesticides, in other scenarios process based technologies can be suitable to reduce poverty gradually e.g. irrigation systems.

Green Revolution Technologies:Technology’s initial focus was on agriculture under the domain named “Green

Revolution Technologies” (GRTs), as most of the poor depend on land, Spillance indicates that there are almost 1.05 billion farmers in the developing countries. These people are facing the worst affects of poverty and its consequences in form of malnourishment, child labor, illiteracy and inadequate health care. Liu Yanhua examined


the green revolution in People’s Republic of China, he divided the 20 years history of anti-poverty campaign in three phases i.e. Poverty alleviation through systemic reforms in rural areas, A well planned, well organized, large scale campaign and tracking the key issues confronted by poverty regions.

The process of helping the poor through science and technology brought many advanced technologies and ideas, measures and ways of modern management to the poverty regions. They were used together with traditional productivity factors in poverty areas. This caused gradual reform in the means of production, expansion of labor objectives and improvements in labor quality. As the functioning of the productive system changed and strengthened step by step, regional technological advances and economic development were promoted. Measure to help the poor through science and technology turned out to be a major channel for speeding the work on poverty reduction (Liu Yanhua).

In agriculture, technology is providing various products and processes, few of the products are HYVs, pesticides, and veterinary health other than the modern equipment.Green revolution technologies improved the productivity by focusing on high-yielding crop varieties (HYVs) and better irrigation systems. In rural areas, better productivity means major affects on economy and poverty reduction with individual and collective growth, better health care, education and further capability to enhance usage of technology. GRTs affects on poverty reduction are visible in Lipton (2001), showing that reduction in malnutrition has occurred in much of Asia and Latin America as well as parts of Africa. The percentage of children under five who were malnourished reduced from 71 to 53 during 1977 and 1993 (WDI, 2000). It was also observed in GRTs that technology adoption was initiated by wealthy farmers and gradually effects trickled down to the remaining social participants.

Huang and Rozelle (1996) analyzed the poverty reduction through technology in PRC, they studied the adopters of new technology in comparison with the farmers who were non-adopters of high-yielding crop varieties. Their study shows that technology had 60 per cent contribution in growth rate during 1975 and 1990, and 22.3 per cent growth was due to the institutional reforms and policies. Lin (1999) researched the other side of the GRTs, his focus was on how the growth affects total income in both adopter and non-adopter cases. The non-adopters of technology invested their resources in other income generating options. The study was based on household survey data for five counties of Hunan province in PRC, which had one of the highest adoption rates of HYV’s in the world. Only one county was consistent not to use technology, but they rationally chose other areas where they can earn higher/equal returns. The study shows that the trade off in technology adoption decision seems to be between HYV’s and non-farm income i.e. planting HYV’s has a significant positive effect on farm income and a significantly negative effect on non-farm income, at the same time, adoption has no significant effect on total household income, while such variable as size of land, number of employed household members, and average years of schooling do.

The study shows that education played a vital role in the adoption of green revolution technologies, though it never effect the productivity itself but the decision and planning for technology adoption are deeply linked with education. People with few years of


schooling were more open towards technological experimentation, productivity growth, pesticides, fertilizers and veterinary health care. Pomp and Burger (1995) share their findings to support the same idea. Their study shows that education levels significantly affect decisions by farmers to grow diversified crops, and that other farmers are more likely to follow the lead of educated adopters than of uneducated ones, suggesting greater trust in their entrepreneurial judgment.

Technology itself can come up with a direct product or an indirect process for poverty reduction but the one significantly important factor is the adoption of that particular product or process by the poor, if the poor are uneducated than their capacity to make adoption decisions will be influenced by traditions and other cultural factors. For improved productivity, investment in HYV’s is suitable but that will not reduce poverty in a collective approach, it may affect few farmers or adopters only, the affect will trickledown to less wealthy non-adopters slowly therefore to alleviate or reduce poverty, investment in educating farmers is more significant. Educated farmer can take entrepreneurial decisions not only on HYV’s adoption, but also on proper irrigation, affective pesticides, and better fertilizers.

There is good reason to suppose that agricultural productivity gains matter more to poverty reduction than do productivity gains in other sectors of the economy. First and foremost, this derives from the heavy weight of food items in the consumption baskets of the poor. Food in general and staples in particular represent over 70 per cent and 50 per cent, respectively, of the consumption expenditures of the dollar poor. Second, the poor are much more likely than the non–poor to make a living from agriculture and/or other rural employment. About two–thirds of the world’s 1.3 billion poor people live in rural areas, and most are employed in agriculture. Third, the poor depend heavily on labor income, and for a given growth in output the agricultural sector tends to employ more labor than other sectors, both directly and indirectly (in the form of labor–intensive rural non–farm services) (Lipton, 2001).

De Janvry et al. (2000) shows the effects of agricultural technology on poverty reduction using a computable general equilibrium model with rural economies and poverty characteristics for Africa, Asia, and Latin America, defined as a ten per cent gain in agricultural total factor productivity. In Africa, the benefits to the poor accumulate directly to smallholders in terms of improved own consumption and income, in Asia they accrue mostly to agricultural laborers in terms of higher wages and greater off–farm employment opportunities; in Latin America they accrue mostly in the form of cheaper food prices for the rural and urban poor. The effects were not immediate, and much early literature suggested that the benefits would accrue primarily to better–off farmers.

In PRC, poverty reduction plan expanded over twenty years, introduced various technological changes gradually, and supported these changes with relevant macro and micro level policies related to training, education and social laws. It clearly shows that poverty reduction through technology needs a dedicated plan not only to cover technology implementation but also to support implementation with economic and social reforms. Chinese anti-poverty campaign shows strategy refinement during implementation cycle, it started with a poverty relief plan but converted into a process development for poverty reduction. Its initial focus was on industry development but


gradual policy refinement converted the focus over agriculture development with technology. Initial approach was to help and reduce poverty in poor areas but after policy infra-structure this emphasis changed into helping poor families. Green revolution technologies provided processes to reduce poverty and further micro level focus was facilitated by technological products and ICTs.

Information and Communication Technologies: ICT is a technology which is applicable in various sectors with multiple dimensions,

these dimensions spread the direct or indirect link and influence between ICT and economy. Due to the generic nature of ICT, it covers the complete cycle of economy i.e. structuring, manufacturing, process, production and intermediate linkage therefore its one dimension is serving customer-end while the other dimension is penetrating in material and management science. ICT is not only influencing the new projects/product but it also improves the performance of existing activities, from operations to top-level strategy designing, ICT is providing multiple ways and tools to generate accuracy and speed.Initially the concept of ICT was limited to CAD/CAM and SCM systems, but now the application domains of ICT are expanding with every passing day. Its highly economical internet-based communication structure or very complex B2B/B2C solution, its fast information exchange or strict operational monitoring, ICT is providing strategies, tools, systems and frameworks to enhance productivity and control. Economy support of ICT is not limited to corporate sector only, in poverty reduction and community development programs, ICT is playing a vital role to provide timely information exchange, analytical data modeling and its transfusion into multi-dimensional prediction/forecasting structures make it possible to incorporate intelligent information and communication technology (IICT) for community development and poverty reduction. Specifically for poverty reduction it is critical to make analytical decisions at right time i.e. decisions/plans based on situation history, culture, skill-set and environment. A decision/plan without considering aforementioned parameters may fail or may not produce the expected results; these parameters are significant because poverty is deep rooted with environment and its reduction plans need to be linked with local culture considering local skill-set and economic history e.g. in industrial zones of poor countries, ICT can enhance the production by reducing the overheads, by increasing the product quality and by squeezing the processes to a bare minimum level. ERP is one of the examples, it provides communication, information exchange along with business process re-engineering and analytical data processing, it also reduces the processes within a specific domain which helps in eliminating additional processes and linkages between irrelevant processes. One important thing needs to be mention here that implementation of any strategy/tool of ICT does not mean the elimination of human manpower, rather these strategies and tools enhances the productivity and performance of same human capital on macro level, while on micro level it also provides skill enhancement and knowledge growth of individuals which ultimately influences the poverty reduction in a significantly positive manner.

In developing and under-developed countries the access to technological benefits becomes the most difficult issue, urban areas are swift in accessing the ICT’s outcomes but rural areas especially distant and far away from the markets, are still facing a havoc of poverty. In physical structures, poor countries are significantly far behind in segments


like transportation, commodities storage/transfer and security, therefore the poor in distant remote areas slipped out of the poverty reduction cycle. To some extend same applied on telecommunication but with some important differences. If roads are not sufficient to link the remote areas with the economically strong markets then at least telecommunication lines may provide a link for remote areas and their poor inhabitants to seek a suitable link for their skills and products. One may argue that ICT is not a perfect solution for poverty reduction; it is a more suitable tool for urban communities to pool their resources and knowledge for further growth and progression furthermore, ICTs are particularly well suited to advanced capitalist economies with large service sectors that generate heavy demands for information processing, management and sharing. The important point here is that in developed economies their markets work reasonably efficiently, with low transaction costs. Developing economies, on the other hand, have pervasive market imperfections and, presumably, high transaction costs. There is little systematic evidence to support this hypothesis but much of the anecdotal kind (cf. Goldstein and O’Connor, 2000, for a survey). Assuming it is so, then ICTs (in particular, internet–based e-commerce/e-business) have greater efficiency than in the developed countries. The significance of this for the poor appears ambiguous.

Up to some extend its true, but due the generic nature of ICT, it proved to be a useful and effective tool for poverty reduction but requires careful craftsmanship and dedicated resources backed by customized strategies and plans. ICT support for poverty reduction can be categorized in two basic levels;

- A non–trivial contribution that ICTs could make to help the poor is in realizing cost savings through rationalization of government functions. Areas of considerable wastage in many countries include non–competitive procurement (e.g. of vaccines and medicines, school textbooks, building materials and construction services), poor storage, poor inventory management and erroneous demand projections, most of which are amenable to amelioration through ICT use (Bloom et al., 2000).

- Provision of accurate information at right time which poor people needs to make right decisions, though we tend to think that time is fast paced and valuable in urban areas only but in actual a peasant is more sensitive and conscious about making a decision for his crop at right time, perhaps timing is more crucial and elementary parameter in rural life. With the condition of literacy and basic infra-structure, ICT do provides information and communication whether by telephone or the internet. Linking time factor with information makes ICT a transitory information mechanism, a transitory process which can assist poor people in making critical decisions related to their small businesses. In poor areas one wrong decision results into an increase in the growth rate of poverty therefore it is critical to assist poor people in making right and timely decisions which indirectly support the reduction in poverty. ICT improvise the communication between producer and consumer, it eliminates the concept of middlemen who manipulates information, and disintermediation will result in cost saving for both consumer and producer.


Technology is one of the effective and supportive mediums to reduce poverty but asshown in GRT and ICT that technological support for poverty alleviation is not executable in isolation, it requires a balanced synchronization with a relevant policy and it also requires time for solution stability and expansion therefore inference of technology in the designing of poverty alleviation strategies and plans can utilize the role of technological tools more effectively in the process of poverty reduction.

REFERENCES

Bloom, D.E., River Path Associates and Fang, K. (2000). Social Technology and Human Health. Background Paper for Human Development Report 2001, United Nations Development Programme, NY, processed.

Bruno, M., Ravallion, M. and Squire, L. (1998). Equity and Growth in Developing Countries: Old and New Perspectives on the Policy Issues, in V. Tanzi and K–Y. Chu (eds.).

Byerlee, D. (1996). Modern Varieties, Productivity, and Sustainability. World Development, 24(4).

Coase, R. (1937). The Nature of the Firm. Economica, 4, November.

DE Janvry, A.; Graff, G.; Sadoulet, E. and Zilberman, D. (2000). Technological Change in Agriculture and Poverty Reduction. A Concept Paper for the World Development Report on Poverty and Development, 2000/01, World Bank, Washington, D.C.

DE Janvry, A.; Graff, G.; Sadoulet, E. and Zilberman, D. (1999). Agricultural Biotechnology and Poverty: Can the Potential Be Made a Reality? University of California, Berkeley.

Dollar, D. and Kraay, A. (2000). Growth is Good for the Poor. Development Research Group, World Bank, Washington, D.C.

Fan, S., Hazell P. and Thorat, S. (1999). Linkages between Government Spending, Growth, and Poverty in Rural India. Research Report 110, International Food Policy Research Institute (IFPRI), Washington, D.C.

Goldstein, A. and O’Connor D. (2000). E-Commerce for Development: Prospects and Policy Issues. OECD Development Centre Technical Paper No. 161, October.

Lipton, M. (2001). Reconnecting Agricultural Technology to Human Development.Background Report for UNDP Human Development Report 2001.

Lipton, M. (1999). Reviving Global Poverty Reduction: What Role for Genetically Modified Plants? Sir John Crawford Memorial Lecture, CGIAR International Centers Week, Washington, D.C., 28 October.

Lipton, M. and Longhurst, R. (1989). New Seeds and Poor People. Johns Hopkins University Press, Baltimore.

Maddison, A. (2001). The World Economy: A Millennial Perspective, Development Centre Studies, OECD, Paris.


Martin, W. and Mitra, D. (2001). Productivity Growth and Convergence in Agriculture and Manufacturing. World Bank Development Group, Washington, D.C.

Panagariya, A. (2000). E-Commerce, WTO and Developing Countries. World Economy,23(8).

Pomp, M. and Burger, K. (1995). Innovation and Imitation: Adoption of Cocoa by Indonesian Smallholders. World Development, 23(3).

Pradhan B.; Sahoo K.A. and Saluja, M.R. (1999). A Social Accounting Matrix for India, 1994-95. Special Article, Economic and Political Weekly, Mumbai, India.

Qaim, M.; Krattiger A. and Braun, J. Von (eds.), (2001). Agricultural Biotechnology inDeveloping Countries: Towards Optimizing the Benefits for the Poor, Kluwer Academic Publishers, Dordrecht.

Quibria, M.G. and Tschang, T. (2000). Information & Communication Technology & Poverty: An Asian Perspective. Asian Development Bank Institute, 25 November, processed.

Ravallion, M. (2000). Growth, Inequality and Poverty: Looking Beyond the Averages.Development Research Group, World Bank, Washington, D.C., 20 September.

Sen, B. (2001). Poverty in Bangladesh: A Review, processed, downloaded from http://www.sdnbd.org/sdi/international_day/poverty/povertyinbd–bids.htm.

World Bank (2001). World Development Indicators 2000-01. CD-ROM, Washington, D.C.

About the Author

Khalil Ahmed is a specialist in implementing automation initiatives in organizations, particularly the Services Sector. He has over 16 years of progressively senior work experience in Development, Implementation, Management Consulting and Corporate Training with local and multinational companies. His experience of Management using technology gives him an edge to deliver more workable automation solutions. His research interests are in the areas of machine learning, artificial intelligence and neural networks.

Documents

Poverty Reduction: Policies and Global Integration