A consistent finding in the development literature is that average non-farm labor productivity is higher than average farm labor productivity. These differences in average productivity are sometimes used to promote policies which advance the non-farm sector. In this paper, we analyze the...

This study models producer protection legislation that would grant growers the right to claim damages (PPLD) if their contracts are prematurely terminated. In the absence of contracting frictions that prevent contractors from redesigning contracts to accommodate exogenous policy changes, PPLD...

In this article, we present a first empirical reflection on 'smart development', its measurement, possible 'drivers' and 'bottlenecks'. We first provide cross-national data on how much ecological footprint is used in the nations of the world system to 'deliver' a given amount of democracy,...

We investigate the economic relevance and the composition of gifts within a firm where output is contractible. We develop a structural econometric model that identifies workers' optimal reaction to monetary gifts received from their employer. We estimate the model using data from two separate...

We present results from a field experiment testing the gift-exchange hypothesis inside a tree-planting firm paying its workforce incentive contracts. Firm managers told a crew of tree planters they would receive a pay raise for one day as a result of a surplus not attributable to past planting...

Agents operating in illegal markets cannot resort to the justice system to guarantee property rights, to enforce contracts, or to seek protection from competitors' improper behaviors. In these contexts, violence is used to enforce previous agreements and to fight for market share. This...

In this paper we propose the use of machine learning methods to estimate inequality of opportunity. We illustrate how our proposed methods - conditional inference regression trees and forests - represent a substantial improvement over existing estimation approaches. First, they reduce the risk...

We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...

We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...

We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data generation processes (DGPs) based on actual data. We consider 24...