Charles Gauthier, Sebastiaan Maes, Raghav Malhotra
arXiv 1 Mar 2023 · Theoretical Economics
arXiv:2303.01231 · PDF · DOI · OpenAlex · Extracted main text
We propose a nonparametric method for estimating the distribution of consumer welfare from cross-sectional data with no restrictions on individual preferences. First demonstrating that moments of demand identify the curvature of the expenditure function, we use these moments to approximate money-metric welfare measures. Our approach captures both nonhomotheticity and heterogeneity in preferences in the behavioral responses to price changes. We apply our method to US household scanner data to evaluate the impacts of the price shock between December 2020 and 2021 on the cost-of-living index. We document substantial heterogeneity in welfare losses within and across demographic groups. For most groups, a naive measure of consumer welfare would significantly underestimate the welfare loss. By decomposing the behavioral responses into the components arising from nonhomotheticity and heterogeneity in preferences, we find that both factors are essential for accurate welfare measurement, with heterogeneity contributing more substantially.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Jerry A Hausman and Whitney K Newey (2016) Individual heterogeneity and average welfare | 0.874 | 9 | 4 | 67% |
| 2 | Xavier Jaravel and Danial Lashkari (2023) Measuring growth in consumer welfare with income-dependent preferences: Nonparametric methods and estimates for the United States | 0.874 | 5 | 2 | 100% |
| 3 | David Baqaee, Ariel T Burstein, and Yasutaka Mori (2022) A new method for measuring welfare with income effects using cross-sectional data | 0.811 | 4 | 2 | 100% |
| 4 | Sarah K. Burns and James P. Ziliak (2016) Identifying the elasticity of taxable income | 0.811 | 4 | 2 | 100% |
| 5 | Pablo D Fajgelbaum and Amit K Khandelwal (2016) Measuring the unequal gains from trade | 0.811 | 4 | 2 | 100% |
| 6 | Jon Gruber and Emmanuel Saez (2002) The elasticity of taxable income: evidence and implications | 0.811 | 4 | 2 | 100% |
| 7 | Stefan Hoderlein and Enno Mammen (2007) Identification of marginal effects in nonseparable models without monotonicity | 0.794 | 6 | 4 | 50% |
| 8 | Jerry A Hausman (1981) Exact consumer's surplus and deadweight loss | 0.737 | 3 | 3 | 67% |
| 9 | Yrjö O Vartia (1983) Efficient methods of measuring welfare change and compensated income in terms of ordinary demand functions | 0.737 | 3 | 3 | 67% |
| 10 | Stefan Hoderlein and Anne Vanhems (2018) Estimating the distribution of welfare effects using quantiles | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 61 scored citations.