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You are not alone: social capital and risk exposure in rural Ethiopia


This paper examines the impact of shocks on food security and the insurance role of social capital and informal social networks. In particular, by combining household panel data, weather data, self-reported shocks and detailed social capital information, the paper investigates the insurance role of social capital against covariate and idiosyncratic shocks. Our results suggest that both covariate and idiosyncratic shocks increase the prevalence of food insecurity. However, households with a higher stock of social capital were able to smooth consumption. We also found that food consumption is not insured through social capital when a shock affects the whole risk-sharing network. Moreover, we show that formal policy interventions such as access to consumption credit and safety nets are the only effective ways of insuring food consumption when a shock affects the entire risk-sharing network.

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Fig. 1


  1. 1.

    Iddirs are informal institutions established for providing mutual aid during death of members (Dercon et al. 2006).

  2. 2.

    A shock is considered as idiosyncratic if the effect is confined to the household and covariate if it affects at least some other residents in the village. In the survey the following questions were used to determine a given shock as covariate and idiosyncratic: “How widespread was the shock? i) only affected my household, ii) affected some households in this village, iii) affected all households in this village, iv) affected this village and other nearby villages

  3. 3.

    These data were made available by the Economics Department, Addis Ababa University, and the Centre for the Study of African Economies, University of Oxford and the International Food Policy Research Institute. Funding for data collection was provided by the Economic and Social Research Council (ESRC), the Swedish International Development Agency (SIDA) and the United States Agency for International Development (USAID); the preparation of the public release version of these data was supported, in part, by the World Bank, AAU, CSAE, IFPRI, ESRC, SIDA and USAID

  4. 4.

    Our measure of non-food consumption excludes expenditure on health and medical care. Expenditure on health and medical care was deducted from non-food consumption. Previous studies on health shocks by Gertler, Levine and Moretti 2006; Gertler and Gruber 2002; De Weerdt and Dercon 2006; Islam and Maitra 2012; Asfaw and von Braun 2004 also used similar measurement of non-food consumption.

  5. 5.

    We assumed health shocks to be exogenous for the following reasons: Our measurement of health shocks can be regarded as being transitory and unpredictable. Our identification strategy relied heavily on this assumption. In addition, since we used fixed effects, any time invariant unobserved household characteristic (e.g., early childhood nutrition) that may affect consumption and health outcomes were eliminated. However, time-varying unobservable factors may affect both health and consumption outcomes. For example, wealthy farmers may have better health outcomes (through the purchase of health inputs, including better nutrition and healthcare) and consumption. However, in our measurement of consumption, we excluded health expenditures. Though we tried to address the issue of identification using fixed effects, we acknowledge that identification might still be a problem with health shocks. While the consistency of the results reported in this paper supports the absence of consumption smoothing against health shocks, the results may need to be interpreted with caution.

  6. 6.

    However, the problem of reverse causality between (food) consumption and health shocks may extend beyond the correlation between rainfall shocks and health shocks. This would be an important area of future research and is beyond the scope of this paper.

  7. 7.

    Measuring the interaction effect between market shocks and social capital is beyond the scope of this paper. Theoretically, market shocks may not adversely affect food security and hence the role that social capital may play cannot be specified a priori.

  8. 8.

    Using the 2004 rounds of ERHS data, Dercon et al. (2005) reported that experiencing a health shock reduces consumption growth by 9 %.

  9. 9.

    Note that, we did not include an interaction term between market shocks and social capital variables as the social capital proxies we considered here are not designed to serve against market shock

  10. 10.

    First stage regression results are presented in Table 9, Appendix I


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The research project has been financially supported by the Dr. Hermann Eiselen Ph.D. Grant from the Foundation fiat panis and the publication is an output of the scholarship from the Food Security Center from the University of Hohenheim, which is part of the DAAD (German Academic Exchange Service) program “exceed” and is supported by DAAD and the German Federal Ministry for Economic Cooperation and Development (BMZ).

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Correspondence to Tesfamicheal Wossen.

Appendix I

Appendix I

First stage regression results.

Table 9 First stage regression results

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Wossen, T., Di Falco, S., Berger, T. et al. You are not alone: social capital and risk exposure in rural Ethiopia. Food Sec. 8, 799–813 (2016).

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  • Consumption
  • Social capital
  • Insurance
  • Shocks
  • Ethiopia

JEL classification

  • C23
  • D12
  • D71
  • O12