The Effect of Pseudo-Exogenous Instrumental Variables on Hausman Test

Jeong, Jinook; Yoon, Byung‐Ho

doi:10.1080/03610910903447833

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…In employing an instrumental variable one is able to mitigate estimation inconsistency, but estimates lose efficiency (become less accurate) and their finite‐sample bias increases. Even if the instruments are uncorrelated with the disturbances at the population level, there will be a “nuisance correlation” in any finite sample of the population, which results in a bias toward the OLS estimator (Jeong and Yoon, 2010). These nuisance correlations can be expected to be even worse with weak instruments, as small effects are subject to greater sampling variability.…”

Section: The Empirical Aspectmentioning

confidence: 99%

Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations

Ketokivi

McIntosh

2017

J of Ops Management

313

239

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In this paper, we examine the problem of endogeneity in the context of operations management research. Whereas the extant literature has focused primarily on the statistical aspect of the problem, a comprehensive treatment requires an examination of theoretical and pragmatic considerations as complements. The prevailing problem with the focus on statistical techniques is that the standards tend to be derived from idealizations: the correlation between a regressor and a disturbance term must be exactly zero, or the analysis will be invalid. In actual empirical research settings, such a knife-edge assumption can never be satisfied, indeed it cannot even be directly tested. Idealizations are useful in helping us understand what it would take to eliminate endogeneity, but when applied directly and unconditionally, they lead to unreasonable standards that may unnecessarily stifle substantive inquiry. We believe that it is far more productive and meaningful to ask: "What can we realistically expect empirical scientists to be able to achieve?" To this end, we cover and revisit some of the general technical material on endogeneity, paying special attention to the idiosyncrasies of operations management research and what could constitute reasonable criteria for addressing endogeneity in empirical operations management studies.

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Section: The Empirical Aspectmentioning

confidence: 99%

Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations

Ketokivi

McIntosh

2017

J of Ops Management

313

239

View full text Add to dashboard Cite

show abstract

“…In addition, we employ the Hausman test [12] to investigate the potential endogeneity issue within the model. The results of the test show that we do not have sufficient evidence to reject the null hypothesis, indicating the absence of an endogeneity issue.…”

Section: Diagnostic Testsmentioning

confidence: 99%

The Impact of Financial Technology Development on Money Laundering Risks

Wang

2023

Advances in Economics, Business and Management Research

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The rapid advancement of financial technology has introduced increased complexity into the global landscape of anti-money laundering. This study seeks to examine the influence of a country's financial technology development on money laundering risks, and whether such impact varies between developing and developed countries. To support our research, we collected data from a sample of 20 economies spanning the time frame of 2012 to 2022, and employed principal component analysis and lagged variables within a multiple linear regression framework. The results indicate that the development of financial technology initially increases money laundering risks in the short term but eventually leads to a reduction in these risks in the long term. Furthermore, this effect is more pronounced in developing countries compared to developed countries. These findings contribute novel insights to the research exploring the role of financial technology in the realm of anti-money laundering.

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“…It is possible that a suspected endogenous variable (i.e., those are considered as endogenous based on theory and literature) can be approximately exogenous (we explain this term in details in section 3.3). In this case, OLS regression is more efficient because the widely used 2SLS estimator is naturally biased in finite samples (Cameron and Trivedi, 2005, p. 108) while the OLS estimator is not (Baum, 2006; Jeong and Yoon, 2010). If the literature and/or theory suggest that endogeneity may be a concern, endogeneity tests should be performed to examine the extent of endogeneity.…”

Section: Addressing Endogeneity: Om Literaturementioning

confidence: 99%

Addressing endogeneity in operations management research: Recent developments, common problems, and directions for future research

Ding

Peng

et al. 2018

J of Ops Management

195

166

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Addressing endogeneity can be a challenging task given the different sources of endogeneity and their impacts on empirical results. While premier business journals typically expect authors to rigorously address endogeneity, this expectation is relatively new to many Operations Management (OM) scholars, as exemplified by a recent editorial in Journal of Operations Management that calls for more rigorous treatment for endogeneity. This study serves two purposes. First, we summarize recent OM literature with respect to the treatment for endogeneity by reviewing studies published in leading OM journals between 2012 and 2017. The review provides evidence that endogeneity problems have received increasing attention from OM scholars. However, we also find some common problems that may render the chosen techniques for addressing endogeneity less effective and potentially lead to biased analysis results. Second, since instrumental variable regression is the most prevalent technique for dealing with endogeneity in the OM literature according to our review, we provide an empirical illustration tailored to OM researchers for using instrumental variable regression in the post‐design (data analysis) phase. Using variables from a publicly available healthcare dataset, our analysis sheds light on the importance of examining instruments' quality and triangulating results based on more than one test/estimator.

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The Effect of Pseudo-Exogenous Instrumental Variables on Hausman Test

Abstract: This paper investigates the potential problem of 'pseudo-exogenous' instruments in regression models. We show that the performance of Hausman test is deteriorated when the instruments are asymptotically exogenous but endogenous in finite samples, through Monte Carlo simulations.

Cited by 9 publications

References 8 publications

Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations

Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations

The Impact of Financial Technology Development on Money Laundering Risks

Addressing endogeneity in operations management research: Recent developments, common problems, and directions for future research

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