WALD_MSE: Stata module to calculate the maximum mean square error (MSE) of a point estimator of the mean

Charles Manski and Max Tabord-Meehan

Statistical Software Components from Boston College Department of Economics

Abstract: wald_mse calculates the maximum MSE of a point-estimator of the mean of a bounded outcome, from a random sample with missing data. The MSE equals regret under square loss, so the maximum MSE is the maximum regret. In the case of bounded outcomes and no missing data, Hodges and Lehmann (1950) derive the estimator with smallest maximum MSE; that is, the minimax-regret estimator. With missing data, the minimax-regret estimator has no known analytical expression and numerical computation appears intractable. wald_mse allows the user to compute the maximum MSE of any proposed estimator with a flexible specification of missing data.

Language: Stata
Requires: Stata version 12
Keywords: mean squared error; MSE; regret; Hodges-Lehmann estimator (search for similar items in EconPapers)
Date: 2017-08-02
Note: This module should be installed from within Stata by typing "ssc install wald_mse". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/w/wald_mse.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/w/wald_mse.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/w/wald_mse_examples.do sample code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/monotone_mean.ado program code (text/plain)

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