Enterprise Dynamics and Finance: Distinguishing Mechanism Design from Exogenously Incomplete Markets Models

Joint with: Alex Karaivanov

We formulate and solve a range of dynamic models of information-constrained credit markets that allow for moral hazard and unobservable investment. We compare them to the exogenously incomplete markets environments of autarky, saving only, and borrowing and lending in a single

asset. We develop computational methods based on mechanism design theory, linear programming, and maximum likelihood techniques to structurally estimate, compare and

statistically distinguish among the competing theoretical models of credit market imperfections. Our methods can be applied with both cross-sectional and panel data and allow for measurement error and unobserved heterogeneity in initial conditions. The models match major stylized facts from the empirical literature on firm dynamics as listed by Cooley and Quadrini (2001). Empirically, we find that using consumption, cashflow and investment data jointly or using dynamic data improves the researcher’s ability to distinguish across the various model regimes relative to using consumption or investment only data, especially in the presence of high measurement error. We also estimate our models using data on Thai households running small businesses. We find that the borrowing and saving only frameworks provide the best fit when using joint data on

consumption, cashflow and investment.

For more information, contact Petra Todd.