Demand Estimation with Flexible Income Effect: An Application to Pass‐Through and Merger Analysis

Shuhei Kaneko and Yuta Toyama

Journal of Industrial Economics, 2025, vol. 73, issue 1, 186-233

Abstract: This article proposes a semiparametric discrete choice model that incorporates a nonparametric specification for income effects. The model allows for the flexible estimation of demand curvature, which has significant implications for pricing and policy analysis in oligopolistic markets. Our estimation algorithm adopts a method of sieve approximation with shape restrictions in a nested fixed‐point algorithm. Applying this framework to the Japanese automobile market, we conduct a pass‐through analysis of feebates and merger simulations. Our model predicts a higher pass‐through rate and more significant merger effects than parametric demand models, highlighting the importance of flexibly estimating demand curvature.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/joie.12406

Related works:
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:bla:jindec:v:73:y:2025:i:1:p:186-233

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0022-1821

Access Statistics for this article

Journal of Industrial Economics is currently edited by Pierre Regibeau, Yeon-Koo Che, Kenneth Corts, Thomas Hubbard, Patrick Legros and Frank Verboven

More articles in Journal of Industrial Economics from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().