Conlon, Christopher. <br/><br/>
Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP / 
Christopher Conlon, Jeff Gortmaker. 
 - Cambridge, Mass.  National Bureau of Economic Research  2023. 
 - 1 online resource:  illustrations (black and white); 
 - NBER working paper series  no. w31605 .
 - Working Paper Series (National Bureau of Economic Research)  no. w31605. .
<br/><br/> August 2023. 
<br/><br/> We provide 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 best 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. 
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<br/><br/><br/>System requirements: Adobe [Acrobat] Reader required for PDF files. <br/>Mode of access: World Wide Web. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Estimation: General<br/>Methodological Issues: General<br/>General<br/>Consumer Economics: Empirical Analysis<br/>General<br/>Food &bull; Beverages &bull; Cosmetics &bull; Tobacco &bull; Wine and Spirits