Optimal unemployment insurance with monitoring

Monitoring the job-search activities of unemployed workers is a common government intervention. Typically, a caseworker reviews the unemployed worker's employment contacts at some frequency, and applies sanctions if certain requirements are not met. I model monitoring in the optimal unemployment insurance framework of Hopenhayn and Nicolini (1997), where job-search effort is private information for the unemployed worker. In the model, monitoring provides costly information upon which the government conditions the unemployment benefits. In the optimal monitoring scheme, endogenous sanctions and rewards, together with random monitoring, create effective job-search incentives for the unemployed worker. I calibrate the model to the US economy and find that the addition of optimal monitoring to the optimal unemployment insurance scheme decreases the variance of consumption by about two thirds and eliminates roughly half of the government's cost. I also find that compared with the optimal monitoring scheme, US states monitor too much and impose the sanctions over too short a time span. For the US on average, shifting to the optimal monitoring policy would generate savings of about $500 per unemployment spell.