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Multicollinearity in the Presence of Errors-in-Variables Can Increase the Probability of Type-I Error

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  • John Komlos

Abstract

Multicollinearity, especially in combination with errors-in-variables, can increase the likelihood of a Type-I error by inflating the value of the estimated coefficients by more than it magnifies their standard errors, thereby increasing the likelihood of obtaining statistically significant results. This anomalous result may be due to an interaction effect between errors-in-variables and multicollinearity.

Suggested Citation

  • John Komlos, 2019. "Multicollinearity in the Presence of Errors-in-Variables Can Increase the Probability of Type-I Error," CESifo Working Paper Series 7459, CESifo.
    • Handle: RePEc:ces:ceswps:_7459
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    References listed on IDEAS

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    1. Chatelain, Jean-Bernard & Ralf, Kirsten, 2014. "Spurious regressions and near-multicollinearity, with an application to aid, policies and growth," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39(A), pages 85-96.
    2. Chatelain, Jean-Bernard, 2010. "Can statistics do without artefacts?," MPRA Paper 42867, University Library of Munich, Germany.
    3. Carl Mela & Praveen Kopalle, 2002. "The impact of collinearity on regression analysis: the asymmetric effect of negative and positive correlations," Applied Economics, Taylor & Francis Journals, vol. 34(6), pages 667-677.
    4. Arturs Kalnins, 2018. "Multicollinearity: How common factors cause Type 1 errors in multivariate regression," Strategic Management Journal, Wiley Blackwell, vol. 39(8), pages 2362-2385, August.
    5. Komlos, John & A'Hearn, Brian, 2019. "Clarifications of a Puzzle: The Decline in Nutritional Status at the Onset of Modern Economic Growth in the United States," The Journal of Economic History, Cambridge University Press, vol. 79(4), pages 1129-1153, December.
    6. Atems Bebonchu & Bergtold Jason, 2016. "Revisiting the statistical specification of near-multicollinearity in the logistic regression model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 199-210, April.
    7. Brian A'Hearn & John Komlos, 2015. "The Decline in the Nutritional Status of the U.S. Antebellum Population at the Onset of Modern Economic Growth," CESifo Working Paper Series 5691, CESifo.
    8. Bodenhorn, Howard & Guinnane, Timothy W. & Mroz, Thomas A., 2017. "Sample-Selection Biases and the Industrialization Puzzle," The Journal of Economic History, Cambridge University Press, vol. 77(1), pages 171-207, March.
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    2. Thomas B. Marvell, 2025. "A Test for Endogeneity in Regressions," EERI Research Paper Series EERI RP 2025/05, Economics and Econometrics Research Institute (EERI), Brussels.

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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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