A Search and Matching Model of Intersectoral Labor Mobility With an Extension of a Deep Q-learning Algorithm

Abstract

The main purpose of this paper is to show that effective law enforcement on shadow economy rises unemployment rate instead of formal employment. To do so, we build a bisector and undirected search and matching model to explain intersector labor mobility by using both wage bargaining and tightness of the labor market. By introducing monitory rates, fiscal policy, and law enforcement, we derive explicit conditions for stable competitive equilibria in the stationary state. An extension of a Deep- Q algorithm is also presented to compute the comparative statics of the model.

Keywords: macroeconomic,reinforcement learning, deep q-learning, artificial intelligences

JEL Classification: E26, J46, J64, K42, O17