Demand estimation with infrequent purchases and small market sizes

B-Tier
Journal: Quantitative Economics
Year: 2023
Volume: 14
Issue: 4
Pages: 1251-1294

Authors (5)

Ali Hortaçsu (University of Chicago) Olivia R. Natan (not in RePEc) Hayden Parsley (not in RePEc) Timothy Schwieg (not in RePEc) Kevin R. Williams (not in RePEc)

Score contribution per author:

0.402 = (α=2.01 / 5 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We propose a demand estimation method that allows for a large number of zero‐ sale observations, rich unobserved heterogeneity, and endogenous prices. We do so by modeling small market sizes through Poisson arrivals. Each of these arriving consumers solves a standard discrete choice problem. We present a Bayesian IV estimation approach that addresses sampling error in product shares and scales well to rich data environments. The data requirements are traditional market‐level data as well as a measure of market sizes or consumer arrivals. After presenting simulation studies, we demonstrate the method in an empirical application of air travel demand.

Technical Details

RePEc Handle
repec:wly:quante:v:14:y:2023:i:4:p:1251-1294
Journal Field
General
Author Count
5
Added to Database
2026-02-02