Paul T. Scott
NYU Stern School of Business
Kaufman Management Center, 7-77
New York University
New York, NY 10012
Information about this author at RePEc
NBER Working Papers and Publications
|December 2016||Estimating market power Evidence from the US Brewing Industry|
with Jan De Loecker: w22957
While inferring markups from demand data is common practice, estimation relies on difficult-to-test assumptions, including a specific model of how firms compete. Alternatively, markups can be inferred from production data, again relying on a set of difficult-to-test assumptions, but a wholly different set, including the assumption that firms minimize costs using a variable input. Relying on data from the US brewing industry, we directly compare markup estimates from the two approaches. After implementing each approach for a broad set of assumptions and specifications, we find that both approaches provide similar and plausible markup estimates in most cases. The results illustrate how using the two strategies together can allow researchers to evaluate structural models and identify problema...
|September 2015||Identification of Counterfactuals in Dynamic Discrete Choice Models|
with Myrto Kalouptsidi, Eduardo Souza-Rodrigues: w21527
Dynamic discrete choice models (DDC) are nonparametrically not identified. However, the non-identification of DDC models does not necessarily imply non-identification of their associated counterfactuals. We provide necessary and sufficient conditions for the identification of counterfactual behavior and welfare for a broad class of counterfactuals. The conditions are simple to check and can be applied to virtually all counterfactuals in the DDC literature. To explore how robust counterfactuals can be to model restrictions in practice, we consider a numerical example of a monopolist’s entry problem, as well as an empirical application of agricultural land use. For each case, we provide relevant examples of both identified and non-identified counterfactuals.