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...

This paper explores the role of model uncertainty in explaining the different findings in the literature regarding the effect of shall-issue right-to-carry concealed weapons laws on crime. In particular, we systematically examine how different modeling assumptions affect the results. We find...

We study the determinants of youth crime using a dynamic discrete choice model of crime and education. We allow past education and criminal activities to affect current crime and educational decisions. We take advantage of a rich panel dataset on serious juvenile offenders, the Pathways to...

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 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...

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...