there is enough cross-sectional variation of the observed states.

We describe identification conditions for dynamic discrete choice models that include unobserved state variables that are correlated across individuals and across time periods. The proposed framework extends the standard literature on the structural estimation of dynamic models by incorporating...

The estimation of production functions suffers from an unresolved identification problem caused by flexible inputs, such as intermediate inputs. We develop an identification strategy for production functions based on a transformation of the firm's short-run first order condition that solves the...

The panel data literature on deterrence and capital punishment contains a wide range of empirical claims despite the use of common data sets for analysis. We interpret the diversity of findings in the literature in terms of differences in statistical model assumptions. Rather than attempt to...

We present a new approach to the estimation of production functions that allows for richer patterns of firm heterogeneity than can be accommodated under the proxy variable methods of and Olley/Pakes and Levinsohn/Petrin. In particular, we show that the economics of the firms static input choice...

We estimate a dynamic model of default for a cohort of Colombian debtors between 1997 and 2004, which was a period of unprecedented financial stress in Colombia. We develop a methodological framework based on a fully dynamic behavioral model that accounts for both cross-sectional and aggregate...