 Latent complementarity in bundles modelsRoy Allen and John Rehbeck Journal of Econometrics, 2022, vol. 228, issue 2, 322-341 Abstract: This paper studies partial identification of latent complementarity in an optimizing model with two goods and binary quantities of each good (buy/do not buy). We provide bounds on the fraction of individuals for whom goods are complements, or substitutes. When utility indices are unknown, we present simple bounds that require only the average structural function (“mean demands”). We show these simple bounds are sharp with only a binary demand shifter. Next, we characterize sharp bounds with richer variation in covariates when utility indices are known, using either the average structural function or structural choice probabilities. In simulations with binary variation in regressors for both goods, we find that the latter bounds coincide. Together, these results indicate that mean demands contain rich information for measuring complementarity without observing whether goods are chosen together. Keywords: Bundles; Complementarity; Partial identification (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:228:y:2022:i:2:p:322-341 DOI: 10.1016/j.jeconom.2021.10.004 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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