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Measuring socio-economic development – The Local Human Development Index
Piotr Arak, Project Coordinator, UNDP Project Office Poland
PhD Candidate, Institute for Social Policy, University of Warsaw
Manchester, September 6, 2012MANCEPT Workshop on Well-being and Public Policy
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Principles guiding the search for HDI:
• To find a measure that goes beyond income while retaining methodological soundness.
• To limit the number of variables to ensure simplicity and manageability.
• To construct a composite index rather than an extensive set of indicators.
• To merge social and economic indicators (ul Haq 2003).
• Since 1990 the HDI has been gradually refined, but main principles remain unchanged.
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About the Polish project
• Together with the Polish Ministry of Regional Development the UNDP Project Office in Poland is starting a project on a new operational measure of socio-economic development, which methodology will be based on the Human Development Index.
• National level indicators are only useful for international comparisons. They can indicate the specific problems and priorities of a country.
• But computation on a local level is important to reveal the kind of intra-national distribution that is critical for domestic policy-making (EU Funds and regional policy).
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Local Human Development Index• Studies in disaggregated HDI have been initiated in a number of
countries (Akder 1994, Ivanov & Peleah 2011). • Within each country, there are significant disparities, gaps: among
regions, between the sexes, between urban and rural areas. • It’s not about a ranking of municipalities or regions. • It is about the way each of it has achieved its human development
level (e.g. good economic performance at the expense of health or good educational opportunities offsetting delays in other areas).
• An attempt will be also made to make a retrospective analysis of LHDI, going back 6 years. This longitudinal approach would make possible not just monitoring trends over time but also linking the human development outcomes to major political developments, decisions taken
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Goal 1: unveiling the image of Poland
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Goal 2: linking policy inputs with outcomes
• We would be able to say something about the changes happening after accession to the European Union – in link with EU funding.
• Looking for a link between inputs (financial and infrastructural) of public policy and outcomes in the level of human development.
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Possible levels of analysis (1)Level General characteristics Known data issues in Poland
NUTS 2 - Voivodeships (Województwa)
Large territorial formations, with population Administrative units.
Income (GDP data) are availableEducation data are availableHealth data are available
NUTS 3 – Subregion (Podregiony)
Subregional non-administrative units used in Eurostat analyses.
Income (GDP data) are availableEducation data are availableHealth data are available
LAU 1 - Districts and city districts (Powiaty i miasta na prawach powiatu)
Smaller territorial formations, with a large variation of population (from small districts to large cities as the capital city of Warsaw). Administrative units.
GDP not available but computation is possible using taxpayers income dataEducation data are available Health data are limited
LAU 2 - Municipalities (Gminy)
Lowest level territorial formations, administrative units.
Limited data availabilityHDI computation difficult or almost impossible
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Possible levels of analysis (2)• An ideal attemt would be to compute the measure the LHDI at the LAU2
level as it is the closest level of authority to the citizen and the direct influence to their lives.
• Bearing in mind limited availability of appropriate data, we propose that in order to built reliable and valid LHDI, the primary unit of analysis for this study is LAU 1. This choice is further justified by activities pursued at the district level in Polish administrative system – including inter alia secondary education, and provision of health care (more important than at the LAU 2 level).
• Placing our analysis on the level of NUTS 2 wouldn’t allow for a thorough examination of a local policy processes. Limited availability of data at the LAU 2 level impedes reliability of an indicator constructed at this level.
• The economical dimension is only possible to be computed using taxpayers income data.
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The basic level of anaylisis – LAU1
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New approach to regional policy
1. Defining and populating input indicators – the quantitative estimate of the personal, financial, physical and other resources (time is often being disregarded)
2. Defining and populating outcome indicators – the quantitative estimate of the change in the immediate area of intervention (improved access to, use of, better health, education outcomes)
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Potential problems
• Avoid the error of confusing ‘input' indices from policy ‘outcomes'.
• As far as the international HDI treats this factors jointly, at this point we need to focus on dividing the indicators in two separate groups.
• The key is to find sufficient measures enabling computation outcome indicators at the local level, in order to estimate policy effects in the spatial dimension.
• Aside from policy outcomes you need also to take into consideration external factors, which can complement the dimensions of the HDI.
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Methodology• The original HDI methodology suggests that the measurement of
human development should focus on the three essential elements of human life: longevity (health), knowledge (education) and decent living standards (represented by income levels).
• Because of the differences in the indices used in the LHDI, we propose to use the computation method prior to the 2011 HDI revival. In general the aim would be to transform a raw variable, into a unit-free index between 0 and 1 (which allows different indices to be added together).
• Special effort must go into developing a simple quantitative measure to capture the many aspects of human life with sufficient data available at the local level (LAU1).
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Dimensions and indicators of the “outcome” Local HDI
Dimensions of development Economical Educational Health
Human Development Indicators
Average total taxpayers income
Share of children enrolled in pre-school education (3-5)
Life expectancy
Agricultural income based on conversion hectares
Average result of the middle school exam
Infant mortality rate
Sold production of industry
Share of people with tertiary education
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Dimensions and indicators of the “input” Local HDI
Dimensions of development Economical Educational Health
Human Development Indicators
Budget of the local government per capita
Student-teacher ratio
Average waiting time for outpatient specialty care
EU funds distribution per capita
Local government expenditures on education per student
Percentage of medical emergency trips that exceeded the maximum amount of time specified by law
Population per primary care physician
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Single Local HDI may be not enough
• Fakuda Parr (2003) and Pinenda (2012) state that from the HDI’s inception, it was explicitly recognized that the concept of human development is larger than what can be measured by the index.
• This creates certain policy challenges, since there may be situations where human progress may mask deterioration in other key aspects not covered in the index.
• For example, civic activity, environment pollution, sustainability of development, social cohesion, labour market conditions and digital engagement could be worsening at the same time as the HDI moves upward.
• This means that the UNDP must regularly update its methodologies and indicators, as well as try out different indices to better capture certain aspects of human development (Pineda 2012).
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Single Local HDI may be not enough
• The welcomed revision of the HDI in 2010 gave new indicators such as the education index, because the formerly used literacy indicator is losing meaning, since many countries have reached the upper limit.
• The HDI fails to capture important aspects of human development and the focus of the Human Development Report Office in recent years has been on refining the measurement of existing indicators, rather than on the inclusion of new dimensions.
• But in case of Poland we are going to take into account additional contextual measures, useful in exploring the concept of human development.
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Context dimensions and indicators to human development
Dimension
Sustainable development
and sustainability of
development
Poverty and social
exclusionLabout market Civic activity Digital
engagement
Indicator Percentage of treated sewage
The share of beneficiaries of
social assistance in
population
Employment (but the data are gathered only during census)
Voter turnout in recent local
elections
Share of tax declarations
sent by internet
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Reveiling the whole picture
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Main data sources:
• National Statistical Office, • National Health Service, • Ministry of Health,• Ministry of Finance, • Ministry of Regional Development, • Ministry of Labour and Social Policy, • Public Electoral Commission.
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What is more needed?
• A framework for measuring subjective well-being – maybe an internet site gathering information?
• Well-being as an contextual measure? • Subjective social capital – trust in other people. • What could be the basis? A study done every 2-years
on a group of 20 thou people (Social Diagnosis) or a study on Social Cohesion conducted by the NSO (social trust and well-being questions) both not representative for the LAU1 level but computation and correlation can be done on the NUTS2 level.
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The connection with well-being
• HDI falls into the objective category, as it reflects people’s objective circumstances, basing on observable, quantitative statistics.
• Conversely, subjective indicators are based on the individual’s perception of his/her status (e.g. level of happiness).
• The word “happiness” is often used in a general way. It does help to focus thinking and look for measures that count what matters in human life, which is not available in the vast datasets of statistical offices and governmental agencies.
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Happiness and human development• There is an interest in finding out how happy people are, such
subjective measures will be of little help unless they can be combined with sufficient other information to build an understanding of what makes for better lives (Helliwell, Layard, Sachs 2012).
• Both approaches have their strengths and weaknesses, and should be complementing each other, but incorporation of subjective measures on the local level remain a considerable challenge.
• Nonetheless, a possible follow-up to this project could be targeted specifically at the measurement of subjective well-being, since it captures best how people rate the quality of their lives.
• What could be done is computation of the indicators listed with representative indicators of social capital and happiness on the NUTS2, and on the LAU1 level having in mind the quality of data.
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Happiness and human development as a policy goal
• Keeping happiness as a clear policy objective is important but difficult and risky. Focusing just on subjective perceptions is not sufficient.
• A robust “happiness and human development index” should be a combination of status and perception indicators.
• Designing such indicators is the minor challenge. • The difficult – and most important – part is changing
policies from a consumption-driven to “meaningful life driven” pattern. This entails a fundamental shift in values of the policymakers – something extremely difficult – but not impossible.
