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Faculty of Economics

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Bhattacharya, D.

Nonparametric welfare analysis for discrete choice


Abstract: We consider empirical measurement of equivalent variation (EV) and compensating variation (CV) resulting from price change of a discrete good using individual-level data when there is unobserved heterogeneity in preferences. We show that for binary and unordered multinomial choice, the marginal distributions of EV and CV can be expressed as simple closed-form functionals of conditional choice probabilities under essentially unrestricted preference distributions. These results hold even when the distribution and dimension of unobserved heterogeneity are neither known nor identified, and utilities are neither quasilinear nor parametrically specified. The welfare distributions take simple forms that are easy to compute in applications. In particular, average EV for a price rise equals the change in average Marshallian consumer surplus and is smaller than average CV for a normal good. These nonparametric point-identification results fail for ordered choice if the unit price is identical for all alternatives, thereby providing a connection to Hausman–Newey's (2014) partial identification results for the limiting case of continuous choice.

Keywords: Binary choice, Multinomial choice, Ordered choice, Applied welfare analysis, Compensating variation, Equivalent variation, Unobserved heterogeneity, Unrestricted heterogeneity, Nonparametric identification

Author links: Debopam Bhattacharya  

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