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Censored Regressors and Expansion BiasRoberto RigobonMassachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER) Thomas M. StokerMassachusetts Institute of Technology (MIT) - Sloan School of Management December 2003 MIT Sloan Working Paper No. 4451-03 Abstract: We show how using censored regressors leads to expansion bias, or estimated effects that are proportionally too large. We show the necessity of this effect in bivariate regression and illustrate the bias using results for normal regressors. We study the bias when there is a censored regressor among many regressors, and we note how censoring can work to undo errors-in-variables bias. We discuss several approaches to correcting expansion bias. We illustrate the concepts by considering how censored regressors can arise in the analysis of wealth effects on consumption, and on peer effects in productivity.
Number of Pages in PDF File: 28 Keywords: Censored Regressors, Expansion Bias JEL Classification: C40 working papers seriesDate posted: December 9, 2003Suggested CitationContact Information
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