Dealing with regression models’ endogeneity by means of an adjusted estimator for the Gaussian copula approach

IF 9.5 1区 管理学 Q1 BUSINESS Journal of the Academy of Marketing Science Pub Date : 2024-10-30 DOI:10.1007/s11747-024-01055-4
Benjamin D. Liengaard, Jan-Michael Becker, Mikkel Bennedsen, Phillip Heiler, Luke N. Taylor, Christian M. Ringle
{"title":"Dealing with regression models’ endogeneity by means of an adjusted estimator for the Gaussian copula approach","authors":"Benjamin D. Liengaard, Jan-Michael Becker, Mikkel Bennedsen, Phillip Heiler, Luke N. Taylor, Christian M. Ringle","doi":"10.1007/s11747-024-01055-4","DOIUrl":null,"url":null,"abstract":"<p>Endogeneity in regression models is a key marketing research concern. The Gaussian copula approach offers an instrumental variable (IV)-free technique to mitigate endogeneity bias in regression models. Previous research revealed substantial finite sample bias when applying this method to regression models with an intercept. This is particularly problematic as models in marketing studies almost always require an intercept. To resolve this limitation, our research determines the bias’s sources, making several methodological advances in the process. <i>First</i>, we show that the cumulative distribution function estimation’s quality strongly affects the Gaussian copula approach’s performance. <i>Second</i>, we use this insight to develop an adjusted estimator that improves the Gaussian copula approach’s finite sample performance in regression models with (and without) an intercept. <i>Third</i>, as a broader contribution, we extend the framework for copula estimation to models with multiple endogenous variables on continuous scales and exogenous variables on discrete and continuous scales, and non-linearities such as interaction terms. <i>Fourth</i>, simulation studies confirm that the new adjusted estimator outperforms the established ones. Further simulations also underscore that our extended framework allows researchers to validly deal with multiple endogenous and exogenous regressors, and the interactions between them. <i>Fifth</i>, we demonstrate the adjusted estimator and the general framework’s systematic application, using an empirical marketing example with real-world data. These contributions enable researchers in marketing and other disciplines to effectively address endogeneity problems in their models by using the improved Gaussian copula approach.</p>","PeriodicalId":17194,"journal":{"name":"Journal of the Academy of Marketing Science","volume":"238 1","pages":""},"PeriodicalIF":9.5000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Academy of Marketing Science","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11747-024-01055-4","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

Abstract

Endogeneity in regression models is a key marketing research concern. The Gaussian copula approach offers an instrumental variable (IV)-free technique to mitigate endogeneity bias in regression models. Previous research revealed substantial finite sample bias when applying this method to regression models with an intercept. This is particularly problematic as models in marketing studies almost always require an intercept. To resolve this limitation, our research determines the bias’s sources, making several methodological advances in the process. First, we show that the cumulative distribution function estimation’s quality strongly affects the Gaussian copula approach’s performance. Second, we use this insight to develop an adjusted estimator that improves the Gaussian copula approach’s finite sample performance in regression models with (and without) an intercept. Third, as a broader contribution, we extend the framework for copula estimation to models with multiple endogenous variables on continuous scales and exogenous variables on discrete and continuous scales, and non-linearities such as interaction terms. Fourth, simulation studies confirm that the new adjusted estimator outperforms the established ones. Further simulations also underscore that our extended framework allows researchers to validly deal with multiple endogenous and exogenous regressors, and the interactions between them. Fifth, we demonstrate the adjusted estimator and the general framework’s systematic application, using an empirical marketing example with real-world data. These contributions enable researchers in marketing and other disciplines to effectively address endogeneity problems in their models by using the improved Gaussian copula approach.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过高斯共轭方法的调整估计器处理回归模型的内生性问题
回归模型中的内生性是市场营销研究的一个关键问题。高斯共轭方法提供了一种无工具变量(IV)技术,可减轻回归模型中的内生性偏差。以往的研究表明,当把这种方法应用于有截距的回归模型时,会产生很大的有限样本偏差。由于市场营销研究中的模型几乎总是需要截距,这一点尤其成问题。为了解决这一局限性,我们的研究确定了偏差的来源,并在此过程中取得了一些方法上的进步。首先,我们证明了累积分布函数估计的质量会严重影响高斯 copula 方法的性能。其次,我们利用这一洞察力开发了一种调整估计器,提高了高斯协约方法在有截距(和无截距)回归模型中的有限样本性能。第三,作为更广泛的贡献,我们将 copula 估计的框架扩展到了具有连续尺度上的多个内生变量、离散和连续尺度上的多个外生变量以及交互项等非线性因素的模型。第四,模拟研究证实,新的调整估计器优于既有估计器。进一步的模拟还强调,我们的扩展框架允许研究人员有效地处理多个内生和外生回归因子,以及它们之间的交互作用。第五,我们使用一个真实世界数据的实证营销实例,展示了调整估计器和一般框架的系统应用。这些贡献使市场营销和其他学科的研究人员能够利用改进的高斯 copula 方法有效地解决其模型中的内生性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
30.00
自引率
7.10%
发文量
82
期刊介绍: JAMS, also known as The Journal of the Academy of Marketing Science, plays a crucial role in bridging the gap between scholarly research and practical application in the realm of marketing. Its primary objective is to study and enhance marketing practices by publishing research-driven articles. When manuscripts are submitted to JAMS for publication, they are evaluated based on their potential to contribute to the advancement of marketing science and practice.
期刊最新文献
How generative AI Is shaping the future of marketing The impact of analyst stock recommendations on firms’ relative exploration orientation Shifting perspectives: How communicating user innovations’ self-focus enhances adoption There is business like show business! What marketing scholars and managers can learn from 40 years of entertainment science research Expressions of customer rumination in online posts and firm responses
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1