Job Market Paper

Relational Frictions along the Supply Chain: Evidence from Senegalese Traders (with Deivy Houeix)

Search and trust frictions have historically made it hard for small firms in lower-income countries to buy inputs from foreign markets. The growth in smartphone ownership and social media usage has the potential to alleviate these barriers. We run a field experiment leveraging these technological tools to provide exogenous variation in both search and trust frictions in a large international import market. The design is informed by a dynamic relational contracting model featuring sequential search for suppliers and trust frictions in the form of adverse selection and moral hazard. In our search treatment, we connect a randomly selected 80% of 1,862 small garment firms in Senegal to new suppliers in Turkey. We then cross-randomize two trust treatments that provide additional information about the types and incentives of these new suppliers. Alleviating search frictions is sufficient to increase access to foreign markets: in all treated groups, firms are 25% more likely to have the varieties a mystery shopper requests and the goods sold are 32% more likely to be high quality. However, the trust treatments are necessary for longer-term impact: these groups are significantly more likely to develop the connections into relationships that persist beyond the study. These new relationships lead to increases in medium-run profit and sales, particularly among wholesalers in the upper tail. Finally, we use the treatment effects to estimate the model and evaluate counterfactuals where we set various combinations of the frictions to zero, finding that the largest gains come from eliminating adverse selection.

Publications

Losing Prosociality in the Quest for Talent? Sorting, Selection, and Productivity in the Delivery of Public Services.  With Nava Ashraf, Oriana Bandiera, and Scott S. Lee.  American Economic Review 2020, 110(5): 1355–1394 

We embed a field experiment in a nationwide recruitment drive for a new health care position in Zambia to test whether career benefits attract talent at the expense of prosocial motivation. In line with common wisdom, offering career opportunities attracts less prosocial applicants. However, the trade-off exists only at low levels of talent; the marginal applicants in treatment are more talented and equally prosocial. These are hired, and perform better at every step of the causal chain: they provide more inputs, increase facility utilization, and improve health outcomes including a 25 percent decrease in child malnutrition.

Online Appendix   Data and Replication Files

AEA Highlights (Short Summary)

Working Papers

Quantifying the Sensitivity of Quantitative Spatial Models (with Habib Ansari and Dave Donaldson)

A modern revolution in spatial economic modelling aims to answer quantitative counterfactual questions by using models that feature micro-level heterogeneity. This heterogeneity is then often assumed to come from particular parametric families — such as Frechet in Eaton and Kortum’s (2002) Ricardian model, or Pareto in applications of Melitz’s (2003) monopolistic competition model. While these parametric choices greatly enhance the tractability of model simulations, it is unknown how sensitive the answers to counterfactual questions are to these assumptions of convenience because there are infinitely many alternative distributions of heterogeneity to be evaluated. We overcome this challenge by building a general trade model that leverages recent advances in the robustness literature. Our method calculates sharp bounds on the values of model counterfactuals that could obtain — while still exactly matching all aggregate trade data points and satisfying equilibrium constraints — under all possible distributions of underlying heterogeneity that lie within a given divergence from a chosen reference distribution. Applying this method to the Eaton and Kortum (2002) and Melitz (2003) models, we find that the gains from trade in these models could be several times larger or smaller than they appear to be under standard benchmark distributions, even if heterogeneity is drawn from a relatively similar distribution.

Draft coming soon!