Individual welfare analysis: Random quasilinear utility, independence, and confidence bounds

Junlong Feng and Sokbae (Simon) Lee

No 25/24, CeMMAP working papers from Institute for Fiscal Studies

Abstract: We introduce a novel framework for individual-level welfare analysis. It builds on a parametric model for continuous demand with a quasilinear utility function, allowing for heterogeneous coefficients and unobserved individual-good-level preference shocks. We obtain bounds on the individual-level consumer welfare loss at any confidence level due to a hypothetical price increase, solving a scalable optimization problem constrained by a novel confidence set under an independence restriction. This confidence set is computationally simple and robust to weak instruments, nonlinearity, and partial identification. The validity of the confidence set is guaranteed by our new results on the joint limiting distribution of the independence test by Chatterjee (2021). These results together with the confidence set may have applications beyond welfare analysis. Monte Carlo simulations and two empirical applications on gasoline and food demand demonstrate the effectiveness of our method.

Date: 2024-12-13
New Economics Papers: this item is included in nep-dcm and nep-upt
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.cemmap.ac.uk/wp-content/uploads/2024/1 ... onfidence-bounds.pdf (application/pdf)

Related works:
Journal Article: Individual welfare analysis: Random quasilinear utility, independence, and confidence bounds (2025)
Working Paper: Individual Welfare Analysis: Random Quasilinear Utility, Independence, and Confidence Bounds (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:azt:cemmap:25/24

DOI: 10.47004/wp.cem.2024.2524

Access Statistics for this paper

More papers in CeMMAP working papers from Institute for Fiscal Studies Contact information at EDIRC.
Bibliographic data for series maintained by Dermot Watson ().