Continuous Outcomes Stochastically Mismeasured As Discrete Random Variables: A Maximum Likelihood Approach

J. S. Butler; Kathryn H. Anderson

doi:10.1080/03610928408828809

Continuous Outcomes Stochastically Mismeasured As Discrete Random Variables: A Maximum Likelihood Approach

J. S. Butler, Kathryn H. Anderson

Research output: Contribution to journal › Article › peer-review

Abstract

In an economic model of retirement behavior, a continuous dependent variable was required; the variable could only be estimated discretely with error, however. Parameter estimates using this dependent variable and ordinary least squares regression are inefficient. In this paper, we develop a maximum likelihood procedure which adjusts for this heteroscedasticity.

Original language	English
Pages (from-to)	2005-2012
Number of pages	8
Journal	Communications in Statistics - Theory and Methods
Volume	13
Issue number	16
DOIs	https://doi.org/10.1080/03610928408828809
State	Published - Jan 1 1984

Keywords

dependent variables
heteroscedastic residuals
maximum likelihood discretely measured
retirement behavior

ASJC Scopus subject areas

Statistics and Probability

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10.1080/03610928408828809

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title = "Continuous Outcomes Stochastically Mismeasured As Discrete Random Variables: A Maximum Likelihood Approach",

abstract = "In an economic model of retirement behavior, a continuous dependent variable was required; the variable could only be estimated discretely with error, however. Parameter estimates using this dependent variable and ordinary least squares regression are inefficient. In this paper, we develop a maximum likelihood procedure which adjusts for this heteroscedasticity.",

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Continuous Outcomes Stochastically Mismeasured As Discrete Random Variables: A Maximum Likelihood Approach

Abstract

Keywords

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