| dc.description.abstract | This thesis comprises three chapters.
The first chapter, written with Deivy Houeix, studies search and trust frictions, which 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. Informed by a dynamic model of relational contracting, we run a field experiment leveraging these technological tools to provide exogenous variation in (1) search frictions and (2) trust frictions (adverse selection and moral hazard) in a large international import market. 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 (adverse selection) and incentives (moral hazard) of these new suppliers. Alleviating search frictions is sufficient to increase access to foreign markets: in all treated groups, firms are 26% more likely to have the varieties a mystery shopper requests and the goods sold are 30% more likely to be high quality. However, the trust treatments are necessary for longer-term impact: using both transaction-level mobile payments data and a follow-up survey, we show that 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. 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.
The second chapter, written with Habib Ansari and Dave Donaldson, is motivated by a modern revolution in spatial economic modeling that 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. 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, a gravity-like moment condition, 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) model, 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 distribution that is at least as similar to Frechet as are the types of parametric alternatives that are commonly explored in sensitivity analysis.
The third chapter, written with Tishara Garg, studies regional integration, a major issue both across and within countries. Yet, integration can take many forms, ranging from lowering tariffs to lowering administrative frictions. We provide evidence on the gains to removing administrative frictions using rich microdata on firm-to-firm trade to study a major fiscal integration reform in India. Using an event-study style regression derived from a gravity model, we estimate that the reform increased interstate trade by around 15% on average. We plug this estimate into the model and use it to calculate the aggregate and distributional welfare gains. We find that all but a handful of districts saw welfare gains, with an aggregate welfare increase of around 1%. | |
