Essays on Dynamic Discrete Choice Economies

This thesis consists of two chapters:

Tax Dynamics for the Long Run

Costs of adjustment delay and complicate behavioral response to tax change. To accommodate such response, we integrate a dynamic discrete choice frame-work into optimal tax theory. We identify long run outcomes with stationary distributions of workers over income-generating states and formulate optimal tax equations in terms of the sensitivity of such distributions to consumption variation. We obtain formulas for these sensitivities that facilitate quantitative evaluation of long run substitution patterns. Novel “inverted” optimal tax equations are derived that establish marginal costs of inducing long run population movements to states as sufficient statistics for optimal taxes. The optimal tax implications of a dynamic quantitative model of occupational choice are analyzed.

Identification and estimation of dynamic matching models with unobserved heterogeneity

We introduce a dynamic model of matching within a competitive market framework that explicitly incorporates time-invariant unobserved heterogeneity on both sides of the market along with endogenous separation and re-matching. In each period, agents make two sequential, forward-looking discrete choices. First, they decide whether to match with a partner or remain unmatched. In the second stage, they are committed to their matching status and face other choice margins. We establish the model’s identification under the assumpton of stationarity in panel datasets where the sampling unit is the household but the measurement unit is the individual, such as the German SOEP.We propose an Expectation-Maximization (EM) algorithm for estimation. Monte Carlo simulations support our theoretical identification results and demonstrate that our model offers a computationally viable framework for studying the economic incentives underlying matching, separation, and re-matching, particularly in settings where unobserved characteristics play a critical role