Household Resilience and Participation in Markets: Evidence from Ethiopia Panel Data Pasquale Lucio Scandizzo and Sara Savastano * This presentation is

Household Resilience and Participation in Markets: Evidence from Ethiopia Panel Data Pasquale Lucio Scandizzo and Sara Savastano * This presentation is part of a larger study conducted by IFPRI and the World Bank by a team of the University of Rome Tor Vergata, composed by Pasquale L. Scandizzo, Sara Savastano, Federica Alfani. And Adriana Paolantonio.

Resilience and Poverty Resilience it is defined as the ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard (UNISDR) Resilience is a traditional characteristic of agrarian societies, which are mostly poor, but high self-reliant, diversified, flexible and with low levels of cash commitments. Resilience makes poverty a less desperate condition, if it reduces exposure and sensitivity and increases the capacity to cope and rebound from the negative shocks that mostly threaten poor households livelihood

Vulnerability and Market Dependence Sen created a new consensus during the 80s over the need to go beyond increasing agricultural output to ensure food security (access to food rather than supply and availability) More recent work on agrarian communities (AC) shows that access to food is being sought, other than agriculture, through an extended array of activities that make rural households increasingly dependent on the market (Chapman and Tripp, 2004) Pure subsistence is disappearing in ACs: between 40 and 60% of household income comes from wage and self employment, and remittances (Maxwell et al., 1998; Ruel et al., 1998; Ellis and Mdoe, 2003; Chapman and Tripp, 2004) with food expenditure raising to more than 60% of total income (Ruel et al., 1998) De-agrarianization (Bryceson, 2000; 2002) of peasant agriculture implies the discouragement of traditional subsistence modes of production (e.g. diversification, self-reliance and access to food through own production) Poorer households may develop a form of dependence on the market that is not fully sustainable (e.g. vagaries of prices, availability shocks, systemic risk) and which can undermine their self-reliance and the basis of their resilience

Objectives and Contribution In our study we investigate the impact over time on poverty and nutritional shortfalls, and market dependence of several determinants of resilience along the three dimensions of exposure, sensitivity and coping capacity in the rural drylands of Ethiopia The study aims to contribute to a better understanding of the relationship between poverty and resilience by: i. testing hypotheses and providing insights on the relationship between nutrition, poverty and market dependence; ii. investigating the statistical significance and economic size of the impact of variables related to resilience dimensions on the capacity of rural households of being above nutritional and poverty thresholds

The Context Ethiopia is the second-largest country in Africa, with an estimated population of nearly 92 million and a growth rate of 2.6 percent per year. It is a predominantly rural and young society, with 84 percent living mainly in densely populated highland settlements. The urban and the rural population are growing respectively at around 4 and 2.3 percent per year. The proportion of the population under age 15 is 45percent, with only 3.2 percent above age 65.

The Context (cont.d) The present rate of population growth means that Ethiopia adds 2 million people every year, inflating family sizes and increasing the number of dependents. It is the pace and imbalanced distribution of such a growth, that most give rise to concerns. Increasing demographic pressure, mostly in the rural areas, where 84% of the population is concentrated, goes hand in hand with degradation of the environment and natural resources, increased climate variability, and market vulnerability. Population growth in rural areas adds to the growing number of rural residents who are land-short and landless.

The Data of Our Study Our data derive from the Ethiopia Rural Household Survey (ERHS), a unique multi-purpose longitudinal household dataset jointly realized by the Department of Economics at Addis Ababa University, the Centre for the Study of African Economies (CSAE), the University of Oxford and the International Food Policy Research Institute (IFPRI). The data were collected from some 1100 rural households through four rounds of surveys carried out over a period of 15 years (1994, 1999, 2004, and 2009).

The Data of Our Study The surveys cover four of the nine administrative regions in Ethiopia, where the largest proportion of countrys farmers are located and include fifteen woredas (districts) stratified over the three major agricultural systems found in five agro-ecological zones. Although not being nationally representative, the sample is representative of the main farming systems in the country

The Data of Our Study The data include the ox- plough cereal producing areas in the northern and central areas (about 63% of the sample), the enset dominated areas which are typically also suitable for coffee and chat (about 30%) and the hoe-based cereal areas (about 7%) (Dercon and Christiaensen, 2007). For our analysis, we use rounds from 1994, 1999, 2004, and 2009 thus covering a period of fifteen years, including two food price crises (mid-nineties and 2006-2008).

Statistics from the Panel Suggest Slight Improvements of Average Conditions Unit20042009 Number of household members Nb.5.755.74 Share of adult females in the household %25.0826.38 Share of children in the household %30.9627.27 Share of elderly in the household %9.0510.24 Age of household head Years50.7452.72 Years of schooling of household head Years1.361.78 Total value of consumption US$1007.21950.85 Total amount of land used by the household ha1.451.52

Exposure to negative shocks has been reduced, except for drought 19942009 Non poorPoorNon poorPoor HH having experienced too much rain or flood in last 15 yrs. 13%18%4%1% HH having experienced. frost in last 15 yrs. 17%30%17%11% HH having experienced pest or disease on livestock in last 15 yrs. 4%9%5%3% HH having experienced lack of demand of agricultural products in last 15 yr 12%23%15%12% HH having experienced output prices shocks in last 15 yrs. 52%67%30%61% HH having experienced drought in last 15 yrs. 12%13%18%22% Max shortfall in the previous 5 years over rainfall st. dev. of the previous 5 yrs. 1.0951.2151.361.29 Aridity index0.6020.6340.6080.642

The extent and the depth of poverty have undergone significant changes Resilience and development make poverty a dynamic phenomenon, as people can enter and exit poverty permanently or temporarily in their lifetime. Thus, snapshot poverty measures may be misleading, because they may exaggerate or underestimate the impact of poverty over a lifetime. More reliable indicators of poverty are lifetime poverty measures or composite measures that combine snapshot and lifetime poverty indexes.

Most Households Tend to Move In and Out of Poverty Aggregate ClassificationClassification % In Monetary Terms %in Nutritional Terms Non resilient Persistent negative6,327,39 Hit, no rebound15,1914,65 Swinging22,5831,59 Resilient Hit, with rebound14,6511,29 Stable exit14,2517,74 Persistent positive27,0117,34 Total 100

The depth of poverty also significantly changes over time Poverty as Income Shortfall VariableMinMeanMax Snapshot Poverty Index Average p.c. Gap ($ per year)-491.175.891.7 Delta=Increase in Average p.c. Gap-297.32.0447.0 Lifetime Index Average($ per year)-494.276.190.7 Delta-24.13.74.4 Composite Index Average ($ per year)-492.675.991.2 Delta-155.92.9212.6

Calorie shortfalls are negative on average, but change over time Poverty as Calorie Shortfall MinMeanMax Snapshot Poverty Index Average p.c. Gap (Kcal/pc/day)-1879.4-244.31280.4 Delta-1591.3-11.71207.2 Lifetime Index Average(Kcal/pc/day)-1999.9-214.71351.3 Delta-968.0-29.5962.3 Composite Index Average (Kcal/pc/day)-1939.7-229.51315.8 Delta-1279.6-20.61084.7

Market dependence and poverty seem to be associated Market dependence goes hand in hand with coping strategies However, in the long-term, it also seems to be associated with movements towards and persistence into under-nourishment (and poverty)

The Econometric Analysis The Econometric Analysis aimed to test the relationships between important outcome variables (poverty, undernutrition, food consumption and life satisfaction) and the main components of resilience (exposure, sensitivity and coping capacity). Taking into account their simultaneous determination, the results showed significant correlations of outcomes with many household indicators of resilience. Correlations were particularly significant and robust for a smaller set of key variables, such as family size, weather shocks, market dependence and wealth.

Some Robust Results from the Econometric Analysis

Family size (population growth) appears to be the single, most important poverty factor An increase of 1% in family size is associated with an increase in % Estimated Elasticity Probability of being poor2.24 Probability of being under-nourished2.08 Snapshot poverty gap3.29 Lifetime poverty gap0.62 Composite poverty gap0.87 Snapshot calorie gap1.67 Lifetime calorie gap0.50 Composite calorie gap0.60

Increase in Family Size (Accelerating Population Growth) is Also an Important Factor of Increasing Poverty An increase of 1% in the rate of increase in family size is associated with an increase in % Estimated Elasticity Increase in Snapshot poverty gap0.90 Increase in Lifetime poverty gap0.43 Increase in Composite poverty gap0.66 Increase in Snapshot calorie gap2.20 Increase in Lifetime calorie gap0.98 Increase in Composite calorie gap1.59

Drought is the second most important poverty factor An increase of 1% in the incidence of (self reported) drought is associated with an increase in % Estimated Elasticity Probability of being poor0.66 Probability of being under-nourished0.25 Snapshot poverty gap1.50 Lifetime poverty gap0.21 Composite poverty gap0.35 Snapshot calorie gap0.37 Lifetime calorie gap0.17 Composite calorie gap0.16

Drought appears also important as a factor of increasing poverty over time An increase of 1% in the incidence of (self reported) drought is associated with an increase in % Estimated Elasticity Increase in Snapshot poverty gap0.70 Increase in Lifetime poverty gap0.36 Increase in Composite poverty gap0.53 Increase in Snapshot calorie gap1.21 Increase in Lifetime calorie gap0.55 Increase in Composite calorie gap0.88

Accumulated wealth is the most important factor of poverty reduction An increase of 1% in the value of accumulate wealth is associated with a reduction in % Estimated Elasticity Probability of being poor1.26 Probability of being under-nourished0.64 Snapshot poverty gap1.32 Lifetime poverty gap0.45 Composite poverty gap0.49 Snapshot calorie gap0.30 Lifetime calorie gap0.15 Composite calorie gap0.16

Greater farm size is associated with small reduction of poverty An increase of 1% in farm size is associated with a decrease in % Estimated Elasticity Probability of being poor0.04 Probability of being under-nourished0.04 Snapshot poverty gap0.18 Lifetime poverty gap0.03 Composite poverty gap0.07 Snapshot calorie gap0.09 Lifetime calorie gap0.10 Composite calorie gap0.08

Income from livestock is associated with lower probability of being poor An increase of 1% in income from livestock is associated with a decrease in % Estimated Elasticity Probability of being poor0.37 Probability of being under-nourished0.18 Snapshot poverty gap0.13 Lifetime poverty gap0.01 Composite poverty gap0.03 Snapshot calorie gap0.04 Lifetime calorie gap0.01 Composite calorie gap0.01

Greater market consumption goes hand in hand with greater poverty An increase of 1% in the share of food market consumption (in calories) is associated with an increase in % Estimated Elasticity Probability of being poor (abs. value)0.44 Probability of being under-nourished (absolute value) 0.16 Snapshot poverty gap (share)0.53 Lifetime poverty gap (share)0.23 Composite poverty gap (share)0.25 Snapshot calorie gap (share)0.02 Lifetime calorie gap (share)0.15 Composite calorie gap (share)0.10

Increasing market consumption is associated with increasing poverty An increase of 1% in the rate of increase in the share of food market consumption is associated with an increase in % Estimated Elasticity Increase in Snapshot poverty gap0.70 Increase in Lifetime poverty gap0.36 Increase in Composite poverty gap0.53 Increase in Snapshot calorie gap1.21 Increase in Lifetime calorie gap0.55 Increase in Composite calorie gap0.88

Food market consumption is a strategy to copewith with poverty and adverse shocks Elasticities: % Increases in Market Calorie Consumption in Response to a 1% increase in : Per capita total calorie consumption planned 0.966 Crop price ratio (consumer/producer)-0.003 Household members are under- nourished (1=yes, 0=no) 0.019 Drought shock in the previous five years (1=yes, 0=no) 0.082 Avg. rainfall shortfall in the previous five years measured at PA level 0.054 Rainfall coefficient of variation (since 1983) 4.756 Ratio of food to non food expenditure at time t-1 0.043 Off-farm employment ratio0.048

Food market consumption is a strategy to cope with poverty and adverse shocks (cont.d) Elasticities: % Increases in Market Calorie Consumption in Response to a 1% increase in : Debt load ratio (household over village)0.004 Household has storage facilities (1=yes, 0=no) -0.254 PA food supply-0.033 Cultivated land-0.015 Nb. of plots with flat slope-0.119 Nb. of ploughs owned-0.030 Per capita gross wealth accumulation-0.020 Age of household head0.011 Female household head (1 = yes, 0=no)-0.009 Share of children and elderly in the household 0.054

Greater off farm employment is associated with greater poverty An increase of 1% in off farm employment ratio is associated with an increase in % Elasticity Probability of being poor0.09 Probability of being under-nourished0.08 Snapshot poverty gap2.39 Lifetime poverty gap0.09 Composite poverty gap0.53 Snapshot calorie gap0.68 Lifetime calorie gap0.13 Composite calorie gap0.20

The most important factors for lifetime nutritional paths Elasticity estimates: % variation of increases in poverty indexes in response to 1% variation in: Family size Incidence of drought (at least once) Market share of food cons. Accumulated wealth Land Age of HH head Persistent negative1.0480.0850.191-0.369-0.633-0.722 Hit no rebound0.8420.0680.153-0.296-0.508-0.58 Swinging0.3040.0250.055-0.107-0.184-0.21 Hit with rebound-0.212-0.017-0.0390.0750.1280.146 Stable exit-0.587-0.048-0.1070.2060.3540.404 Persistent positive-0.966-0.079-0.1760.340.5840.666

The most important factors for lifetime poverty paths Elasticity estimates: % variation of increases in poverty indexes in response to 1% variation in: Family size Incidence of drought (at least once) Market share of food cons. Accumulated wealth Land Age of HH head Persistent negative0.7490.1410.391-0.315-0.588-0.479 Hit no rebound0.8120.1530.424-0.342-0.637-0.520 Swinging0.430.0810.224-0.181-0.337-0.275 Hit with rebound-0.02-0.004-0.010.0080.0160.013 Stable exit-0.424-0.08-0.2210.1780.3320.271 Persistent positive-0.792-0.149-0.4130.3330.6210.507

A Plausible Interpretation of the Results Family size increases are one of the main consequences of rapid population growth; They put a strain on resource -constrained rural communities (minimal farm size, low accumulated wealth); In response to these factors, especially when hit by a shock (e.g. droughts), households turn to markets for food and off farm employment; But this strategy tends to reduce self-reliance and may ultimately increase both the extent and the depth of poverty

Resilience is a dynamic property Resilience appears to be dynamically related to the attempts to break free of the poverty cycle, which appears to be a non linear phenomenon, characterized by a significant turning point. Most of the negative effects measured for the various factors by the econometric analysis, such as family size, lack of assets and natural adversities, act by frustrating households efforts to exit permanently from under-nutrition and poverty conditions. Once the critical threshold of economic performance is successfully crossed, the same factors constitute significant handicaps, and reduce the probability that households will maintain their economic accomplishments.

Conclusions and Policy Implications Development and resilience make poverty a dynamic condition, with many households changing status, in terms of income and consumption shortfalls, in the course of their lifetime. Development policies should aim to enhance the main factors that allow poor households to permanently exit poverty, such as higher access to land and other natural resources and better opportunities to accumulate savings, and invest in livestock and other forms of wealth.

Conclusions and policy implications Population growth and land scarcity are hindering economic development in Ethiopia and are the major obstacles to poverty reduction in the rural areas. Their combined effect forces poor rural households to increasingly use purchases from the market and off farm employment as a way to smoothen consumption and cope with adverse shocks. While these may be effective coping strategies, higher dependence on the market reduces self-reliance, and is one of the main determinants of farmers sensitivity to the risk of under-nutrition and poverty in the subsequent periods.

Conclusions and policy implications We conclude that food markets do play a crucial role in ensuring flexibility and consumption smoothing, but, together with other forms of market dependence, they may also be a source of instability and further risks, especially for the less self-reliant households. A new class of less resilient poor may be created by unchecked population growth, increasing scarcity of land and capital, higher dependence on the market for food, employment and credit services. Policies to reduce poverty and enhance development must address this process, by expanding the agriculture resource base and by assisting the rural communities in a gradual transition to greater market integration.

Conclusions and Policy Implications A larger resource base for the growing rural population should thus be provided, by increasing access to land and other production factors, mobilizing land markets and increasing incentives for on farm investment. Because of the importance of droughts and other shocks, crop insurance and safety nets appear also important policy instruments. A new set of capabilities for households and institutions also appears to be needed to manage the transition to a more integrated market economy.

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Household Resilience and Participation in Markets: Evidence from Ethiopia Panel Data Pasquale Lucio Scandizzo and Sara Savastano * This presentation is