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Optimal Estimation of Discrete Choice Demand Models with Consumer and Product Data / Paul L. E. Grieco, Charles Murry, Joris Pinkse, Stephan Sagl.
- Format:
- Book
- Author/Creator:
- Grieco, Paul L. E.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w33397.
- NBER working paper series no. w33397
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2025.
- Summary:
- We propose a conformant likelihood estimator with exogeneity restrictions (CLEER) for random coefficients discrete choice demand models that is applicable in a broad range of data settings. It combines the likelihoods of two mixed logit estimators--one for consumer level data, and one for product level data--with product level exogeneity restrictions. Our estimator is both efficient and conformant: its rates of convergence will be the fastest possible given the variation available in the data. The researcher does not need to pre-test or adjust the estimator and the inference procedure is valid across a wide variety of scenarios. Moreover, it can be tractably applied to large datasets. We illustrate the features of our estimator by comparing it to alternatives in the literature.
- Notes:
- January 2025.
- Print version record
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