Identification and estimation of a search model with heterogeneous consumers and firms

IF 4 3区 经济学 Q1 ECONOMICS Journal of Econometrics Pub Date : 2025-05-01 Epub Date: 2025-01-30 DOI:10.1016/j.jeconom.2025.105956
Mateusz Myśliwski , May Rostom , Fabio Sanches , Daniel Silva Jr , Sorawoot Srisuma
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Abstract

We propose a model of nonsequential consumer search where consumers and firms differ in search and production costs respectively. We characterize the equilibrium of the game. We first show the distribution of search cost can be identified by market shares and prices. Subsequently, we identify the production cost distribution using a similar strategy to Guerre, Perrigne and Vuong (2000) as the firms’ decision problems resemble bidders’ problems in a particular procurement auction. We prove the firm’s cost density can be estimated at the same convergence rate as the optimal rate in Guerre et al. uniformly over any fixed subset on the interior of the support. The uniform convergence rate over any expanding support is slower due to a pole in the price pdf that is a feature of the equilibrium. Our simulation study confirms the theoretical features of the model. Our identification and convergence rate results also apply to two generalizations of the baseline search model that allow for: (i) vertically differentiated products; (ii) an intermediary. We apply the latter model to study loan search using UK mortgage data.
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具有异质消费者和企业的搜索模型的识别和估计
我们提出了一个非顺序消费者搜索模型,其中消费者和企业分别在搜索和生产成本上存在差异。我们描述了博弈的均衡。我们首先证明了搜索成本的分布可以通过市场份额和价格来确定。随后,我们使用与Guerre、Perrigne和Vuong(2000)类似的策略来确定生产成本分配,因为企业的决策问题类似于特定采购拍卖中的投标人问题。我们证明了公司的成本密度可以在任何固定的子集上以与Guerre等人的最优收敛速率相同的收敛速率一致地估计。由于价格pdf中的极点是均衡的一个特征,因此在任何扩展支撑上的统一收敛速度较慢。我们的仿真研究证实了该模型的理论特征。我们的识别和收敛速度结果也适用于基线搜索模型的两种概括,允许:(i)垂直差异化产品;(ii)中介人。我们使用后一种模型来研究使用英国抵押贷款数据的贷款搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Econometrics
Journal of Econometrics 社会科学-数学跨学科应用
CiteScore
8.60
自引率
1.60%
发文量
220
审稿时长
3-8 weeks
期刊介绍: The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.
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