Modeling and quantifying industry dynamics under aggregate uncertainty

by Utar, Ha?le.

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 product markets, heterogeneous firms, and endogenous entry and exit. First, Colombian panel data on metal product producers are used to identify the model’s parameters. Then several counterfactual trade policy experiments are conducted. In addition to quantifying the effects of openness on job turnover patterns, the model delivers predictions on the associated changes in the aggregate productivity, the nature of the transition process when openness changes, and the role of hiring and firing costs in shaping firms’ responses. In the second essay (Chapter 3), which is co-authored with J. Tybout and R. Bond, we analyze the firm-level consequences of a crisis-prone environment in the presence of capital market frictions. Balance of payments crises and banking crises are common in developing countries. Often they feed off one another, creating dramatic swings in the real exchange rate, real interest rates, and expectations about regime sustainability. We quantify the effects of these crises on industrial sector productivity distributions, size distributions and borrowing patterns. To do so, we first develop an industrial evolution model in which capital market imperfections link firms’ ability to borrow to the wealth of their owners. Then we fit our model to firm-level panel data and macro data from Colombia that span the debtcrisis period of the 1980s. Finally, using the estimated parameters, we simulate industrial evolution patterns under alternative assumptions about the stochastic processes for exchange rates and interest rates. iii