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 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...

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...

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...

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...