Modeling and Quantifying Industry Dynamics under Aggregate Uncertainty

In this thesis, I empirically investigate the selection process and the evolution of an industry in response to aggregate shocks.In the first essay (Chapter 2), I develop a new way to quantify the effects of import competition on intra-industry patterns of job creation and destruction and productivity. It is based on a dynamic stochastic industry model with monopolistically competitive productmarkets, heterogeneous firms, and endogenous entry and exit. First,Colombian panel data on metal product producers are used to identifythe model's parameters. Then several counterfactual trade policyexperiments are conducted. In addition to quantifying the effects ofopenness on job turnover patterns, the model delivers predictions onthe associated changes in the aggregate productivity, the nature ofthe transition process when openness changes, and the role of hiringand firing costs in shaping firms' responses.In the second essay (Chapter 3), which is co-authored with J. Tyboutand R. Bond, we analyze the firm-level consequences of acrisis-prone environment in the presence of capital marketfrictions. Balance of payments crises and banking crises are commonin developing countries. Often they feed off one another, creatingdramatic swings in the real exchange rate, real interest rates, andexpectations about regime sustainability. We quantify the effects ofthese crises on industrial sector productivity distributions, sizedistributions and borrowing patterns. To do so, we first develop anindustrial evolution model in which capital market imperfectionslink firms' ability to borrow to the wealth of their owners. Then wefit our model to firm-level panel data and macro data from Colombiathat span the debt-crisis period of the 1980s. Finally, using theestimated parameters, we simulate industrial evolution patternsunder alternative assumptions about the stochastic processes forexchange rates and interest rates.