Structural and stochastic poverty, shocks, and resilience capacity in rural Ethiopia

Abstract

Whilst structurally poor households fall below the income and asset poverty line, stochastically poor households fall below the income poverty line but above the asset poverty line. This distinction suggests different challenges for the households in dealing with shocks and building the resilience to make a lasting escape from poverty. Accordingly, we examine the effect of shocks on structural and stochastic poverty, transitions, and the role of resilience as a mechanism for dealing with shocks and stochastic and structural poverty using the Ethiopian Socioeconomic Survey data. We find that recurrent and concurrent shocks adversely impact structural and stochastic poverty, whilst resilience capacities can curb poverty as shocks intensify. Access to irrigation, literacy, good vegetation cover, and non-farm economic activities help eradicate both structural and stochastic poverty. Rainfall variability, drought, conflict, input and output price volatility, and idiosyncratic shocks all drive both structural and stochastic poverty. However, the critical implication for policy is that reducing structural and stochastic poverty requires enhancing resilience capacity. This will require promoting symbiotic rural–urban links and rural revitalization to ensure a balanced mix of development. The findings suggest that two distinct sets of policies are required to protect against falling into poverty and sustain movements out of poverty, namely harmonizing cargo net and safety net policies.

Keywords:

• shocks
• poverty
• cox proportional hazard
• panel data
• rural Ethiopia

PUBLIC INTEREST STATEMENT

Stochastic events in Ethiopia are the worst setback in poverty reduction. Relief efforts are aimed to respond to crises by protecting the life and livelihoods after a shock. As such, these interventions deal for a large part with coping strategies and trying to strengthen the absorptive capacity.. In contrast, development efforts mostly aimed at addressing long-term issues of societal changes and deal with incremental adjustment and transformational changes. Resilience is introduced to transcend the pitfalls of earlier interventions. “An ounce of prevention is worth a proud of cure” - Economics of resilience. Despite its added-value, resilience needs to be embodied in a more rigorous empirical analysis. To design appropriate poverty reduction policies, reformulating poverty analysis toward the third-generation measures (structural and stochastic) is overwhelming. The empirics also underscore the need for a forward-looking and dynamic framework that consistently predicts future poverty. This paper examines how resilience mediates the relationship between shocks and structural and stochastic poverty.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. The two-stage stratified sampling technique was applied taking into account diversities in agro ecological factors for rural areas and major urban towns for the urban survey. In the first stage, the four most populous regions and a combination of the remaining regions as a fifth category were stratified, from which CSA enumeration areas (EAs) were selected with probability proportional to size. The number of EAs covered by the survey begins with 333 in the first round and grown to 433 (290 rural, 43 small town and 100 major urban areas) subsequently. In the second stage, 12 households in each EA were randomly selected. Out of the 3,969 households in first 2011/12, the later waves respectively re-interviewed 3,776 and 3,699 rural households (CSA and World Bank, 2017).

2. It entails a total of 6 dwelling characteristics, 31 household durables, and 4 household means of production. Variables with low standard deviations or an asset that all households own or no one owns that would exhibit no variation between households and would be zero weighted that would carry a low weight from the PCA were excluded.

3. Since the coefficients of each covariates are relative to the reference group (structural non-poor), the standard interpretation of the multinomial logit is that for a unit change in the predictor variable (For example, resilience capacity), the logit of the outcome relative to the referent group is expected to change by its respective parameter estimate given the variables in the model are held constant.

4. Normalized Difference Vegetation Index is a simple index that allows immediate recognition of problems in farm areas. It is used as a proxy for water stress problems (vulnerability to drought) or land productivity or the state of land degradation Zhang and Zhang (2019). Its values range between −1 and 1, and each value corresponds to a different agronomic situation, regardless of the crop. A better NDVI implies strong vegetation cover and responses to environmental change, less vulnerable to drought (Tonini et al., 2012) and have more production, and resilient properties of the landscapes and their constituent. The greening in vegetation in the rain-fed agricultural areas is strongly linked to living in a more productive land which can be attributed to improved productivity.

5. However, it is not necessarily the case in rural Ethiopia that children are an unsustainable economic burden for a household; rather, it is the combination of children with respect to their timing in a household’s life cycle and income generating capacity which influences the downward mobility of the stochastic non-poor.

Additional information

Funding

This manuscript received no financial grant from any funding agency.

Notes on contributors

Dereje Haile

Dereje Haile is an Assistant Professor of Development Studies. Ample experience with a demonstrated history of working in the higher education, he has research interests in the economics of poverty, food and nutrition insecurity, destitution, resilience, climate change, agricultural productivity, technology adoption, conflict and migration, to address questions that are relevant for sustainable development.

Abrham Seyoum

Abrham Seyoum is an Associate Professor of Development Economics at Addis Ababa University. He has been involved in various research projects in the areas of agricultural and development economics, agricultural productivity, commercialization, poverty and vulnerability, resilience, food security, and destitution. He authored and co-authored numerous journal articles.

Alemu Azmeraw

Alemu Azmeraw is an Associate Professor of Sociology and Development Studies at Addis Ababa University. He has extensive research and teaching experience in the areas of rural transformation, sustainable development, qualitative research methodology, climate change, value chain analysis, poverty, food and nutrition security, destitution, and policy analysis.