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Are Instrumental Variables Really That Instrumental? Endogeneity Resolution in Regression Models for Comparative Studies

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  • Ravi Kashyap

Abstract

We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable method. We show that when performing any comparative study, it is possible to measure the true change in the coefficients under a broad set of conditions. Our results hold, as long as the product of the covariance structure between the explanatory variables and the covariance between the error term and the explanatory variables are equal, within the same system at different time periods or across multiple systems at the same point in time.

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  • Ravi Kashyap, 2022. "Are Instrumental Variables Really That Instrumental? Endogeneity Resolution in Regression Models for Comparative Studies," Papers 2203.14255, arXiv.org.
    • Handle: RePEc:arx:papers:2203.14255
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    File URL: http://arxiv.org/pdf/2203.14255
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    3. Allison J. Sovey & Donald P. Green, 2011. "Instrumental Variables Estimation in Political Science: A Readers’ Guide," American Journal of Political Science, John Wiley & Sons, vol. 55(1), pages 188-200, January.
    4. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(2), pages 222-240, April.
    5. Edward Miguel & Shanker Satyanath & Ernest Sergenti, 2004. "Economic Shocks and Civil Conflict: An Instrumental Variables Approach," Journal of Political Economy, University of Chicago Press, vol. 112(4), pages 725-753, August.
    6. Kahneman, Daniel, 1992. "Reference points, anchors, norms, and mixed feelings," Organizational Behavior and Human Decision Processes, Elsevier, vol. 51(2), pages 296-312, March.
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