Boot, T. and Juodis, A. (2025). Uniform inference in linear error-in-variables models: Divide-and-conquer Econometric Reviews, 44(3):335--355.
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Affiliated author
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Publication year2025
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JournalEconometric Reviews
It is customary to estimate error-in-variables models using higher-order moments of observables. This moments-based estimator is consistent only when the coefficient of the latent regressor is assumed to be nonzero. We develop a new estimator based on the divide-and-conquer principle that is consistent for any value of the coefficient of the latent regressor. In an application on the relation between investment, (mismeasured) Tobin{\textquoteright}s q and cash flow, we find time periods in which the effect of Tobin{\textquoteright}s q is not statistically different from zero. The implausibly large higher-order moment estimates in these periods disappear when using the proposed estimator.