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An MPEC Estimator for the Sequential Search Model

Shinji Koiso, Suguru Otani

arXiv 6 Sep 2024 · Econometrics

arXiv:2409.04378 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper proposes a constrained maximum likelihood estimator for sequential search models, using the MPEC (Mathematical Programming with Equilibrium Constraints) approach. This method enhances numerical accuracy while avoiding ad hoc components and errors related to equilibrium conditions. Monte Carlo simulations show that the estimator performs better in small samples, with lower bias and root-mean-squared error, though less effectively in large samples. Despite these mixed results, the MPEC approach remains valuable for identifying candidate parameters comparable to the benchmark, without relying on ad hoc look-up tables, as it generates the table through solved equilibrium constraints.

Citation extraction

9
references
24
in-text mentions
9
distinct cited
0
self-citations
2,189
main-text words

appendix boundary found by appendix_command · 84% of the source is main text. Read the extracted text to check this.

Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Ursu, Seiler and Honka (2023) The Sequential Search Model: A Framework for Empirical Research0.9619589%
2Weitzman (1979) Optimal Search for the Best Alternative0.81142100%
3Su and Judd (2012) Constrained optimization approaches to estimation of structural models0.73732100%
4Lu, Luo and Xiao (2014) An MPEC estimator for misclassification models0.64422100%
5Kim, Albuquerque and Bronnenberg (2010) Online demand under limited consumer search0.51121100%
6Dubé, Fox and Su (2012) Improving the numerical performance of static and dynamic aggregate discrete choice random coefficients demand estimation0.40511100%
7Elberg, Gardete, Macera and Noton (2019) Dynamic effects of price promotions: Field evidence, consumer search, and supply-side implications0.40511100%
8Jiang, Chan, Che and Wang (2021) Consumer search and purchase: An empirical investigation of retargeting based on consumer online behaviors0.40511100%
9Morozov (2023) Measuring benefits from new products in markets with information frictions0.40511100%

Showing the top 9 of 9 scored citations.