Dynamic Financial Constraints: Distinguishing Mechanism Design from Exogenously Incomplete Regimes
We formulate and solve a range of dynamic models of information-constrained credit that allow for moral hazard and unobservable investment. We compare them to full insurance and exogenously incomplete financial regimes (autarky, saving only, and borrowing and lending in a single asset). We develop computational methods based on mechanism design, linear programming, and maximum likelihood to estimate, compare, and statistically test these alternative theoretical models of financial constraints. Our methods work with both cross-sectional and panel data and allow for measurement error and unobserved heterogeneity. Empirically, we find that using consumption, income, and investment data jointly, or using intertemporal data, improves the researcher’s ability to distinguish across the financial regimes relative to using consumption or investment data alone, especially in the presence of high measurement error. We estimate the models using data on Thai households running small businesses. We find that, overall, the borrowing and saving only regimes provide the best fit using joint data on consumption, investment, and income. However, there is evidence that family networks are helpful in consumption smoothing as in a moral hazard constrained regime and that there are regional differences in the best fitting regime (higher-wealth, near Bangkok vs. rural agricultural areas).