Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP

Christopher Conlon and Jeff Gortmaker

No 31605, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We delineate a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995)-style estimates of differentiated products demand systems. We extend recommended practices for BLP estimation in Conlon and Gortmaker (2020) to the case with micro data and implement them in our open-source package PyBLP. Monte Carlo experiments and empirical examples suggest that incorporating micro data can substantially improve the finite sample performance of the BLP estimator, particularly when using well-targeted summary statistics or “optimal micro moments” that we derive and show how to compute.

JEL-codes: C13 C18 C30 D12 L0 L66 (search for similar items in EconPapers)
Date: 2023-08
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