We present a model of endogenous institutional change that rationalizes reforms that have taken place in the context of economic crisis and drastic political change. Most of the reforms have been initiated by powerholders, even though they have ended worse off relative to the status quo. The...

We propose a criterion of approximate incentive compatibility, strategy-proofness in the large (SP-L), and argue that it is a useful second-best to exact strategy-proofness (SP) for market design. Conceptually, SP-L requires that an agent who regards a mechanism's “prices” as exogenous to...

We are motivated by the unique migration experience of Israel of a supply-side shock triggering skilled immigration and the concurrent decline in welfare-state redistribution. This paper develops a model, which can provide an explanation for the mechanism through which a supply-side shock...

Will politics lead to over-building or under-building of transportation projects? In this paper, we develop a model of infrastructure policy in which politicians overdo things that have hidden costs and underperform tasks whose costs voters readily perceive. Consequently, national funding of...

Two heterogeneous agents contribute over time to a joint project, and collectively decide its scope. A larger scope requires greater cumulative effort and delivers higher benefits upon completion. We show that the efficient agent prefers a smaller scope, and preferences are time-inconsistent: as...

Why did the most prosperous colonies in the British Empire mount a rebellion? Even more puzzling, why didn't the British agree to have American representation in Parliament and quickly settle the dispute peacefully? At first glance, it would appear that a deal could have been reached to share...

We study the problem of measuring group differences in choices when the dimensionality of the choice set is large. We show that standard approaches suffer from a severe finite-sample bias, and we propose an estimator that applies recent advances in machine learning to address this bias. We apply...