Using household survey data from Ethiopia, this paper evaluates the impact of agricultural cooperatives on smallholders' technical efficiency. We used propensity score matching to compare the average difference in technical efficiency between cooperative member farmers and similar independent farmers. The results show that agricultural cooperatives are effective in providing support services that significantly contribute to members' technical efficiency. These results are found to be insensitive to hidden bias and consistent with the idea that agricultural cooperatives enhance members' efficiency by easing access to productive inputs and facilitating extension linkages. According to the findings, increased participation in agricultural cooperatives should further enhance efficiency gains among smallholder farmers. Impact des coopératives agricoles sur l'efficacité technique des petits exploitants: Analyse empirique en EthiopieA partir de données d'enquêtes de ménages en Ethiopie, cet articleévalue l'impact des coopératives agricoles sur l'efficacité technique des petits exploitants. Les auteurs utilisent la méthode dite propensity score matching pour comparer la différence moyenne d'efficacité technique entre membres de coopératives agricoles et fermiers indépendants. Les résultats montrent que les coopératives agricoles sont efficaces pour fournir des services de support qui contribuent significativementà l'efficacité technique de leurs membres. Ces résultats sont insensiblesà des biais cachés et confirment l'idée que les coopératives agricoles augmentent l'efficacité des membres en facilitant l'accèsà des inputs productifs et les liaisonsà distance. Les résultats indiquent qu'intensifier la participation dans les coopératives agricoles accroitrait les gains d'efficacité des petits agriculteurs.

We show analytically and empirically that non-classical measurement errors (NCME) in the two key variables in a hypothesized relationship can bias the estimated relationship between them in any direction. Furthermore, if these measurement errors are correlated, correcting for either NCME alone can aggravate bias in the parameter estimate of interest relative to ignoring mismeasurement in both variables, a 'second best' result with implications for a broad class of economic phenomena of policy interest. We use numerical simulation to illustrate the parameter space over which a second best approach of not correcting one variable's NCME dominates correcting it. We then illustrate these results empirically by demonstrating the implications of mismeasured agricultural output and plot size for the long-debated (inverse) relationship between size and productivity. Our data from Ethiopia show large discrepancies between farmer self-reported and directly measured values of crop output and plot size. These NCME are strongly, negatively correlated with the true variable values and strongly, positively correlated with one another. In these data, correlated NCME generate a strong but largely spurious estimated inverse size-productivity relationship. And in line with our analytical result, correcting for just one source of NCME aggravates the bias in the parameter estimate of interest. JEL Codes: C81, O12, Q12, Q15

International humanitarian organizations have expressed substantial concern about the potential for increases in food insecurity resulting from the COVID‐19 pandemic. We use a unique panel survey of a representative sample households in Addis Ababa to study both food security and food consumption during the pandemic. In contrast to some other countries in the region, Ethiopia never went into a full lockdown severely restricting movement. Despite subjective income measures suggesting a large proportion of households have been exposed to job loss or reduced incomes, we find that relative to a survey conducted in August and September of 2019, food consumption and household dietary diversity are largely unchanged or slightly increased by August 2020. We find some changes in the composition of food consumption, but they are not related to shocks found in previous phone surveys conducted with the same households. The results therefore suggest the types of subjective questions about income typically being asked in COVID‐19 phone surveys may not appropriately reflect the magnitude of such shocks. They also imply, at least indirectly, that in the aggregate food value chains have been resilient to the shock associated with the pandemic.

It has now become almost a stylized fact that sustained agricultural growth is central to rapid poverty reduction and economic development. Yet, world poverty is largely concentrated in the agrarian societies, which have the potential for agricultural productivity growth. This is particularly true for Sub-Saharan African countries, where the gaps between potential and actual yields remain high. Minimizing this gap through the promotion of modern inputs-such as fertilizer and modern seeds-has been at the core of almost all development strategies in Ethiopia. Among other initiatives, the country has promoted microfinance institutions and member-owned financial cooperatives to alleviate credit constraints of the smallholder farmers. This paper analyzes the impacts of these institutions. Using household survey data and a propensity-score-matching technique, we examine the effects that institutional financial services have on farmers' adoption of agricultural technology in Ethiopia. The results suggest that access to institutional finance has a significant positive impact on both the adoption and extent of technology use. However, when impacts are disaggregated by type of financial institution and farm size, heterogeneities are observed. In particular, financial cooperatives have a greater impact on technology adoption than microfinance institutions, and the results appear to vary depending on farm size and types of inputs. The paper concludes with implications for policies to promote adoption of modern agricultural inputs.

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