OLS and Tobit Estimates: When is Substitution Defensible Operationally?
AbstractField data are used to illustrate that, other things constant, regression results using Ordinary Least Squares (OLS) converge to Tobit estimates as the number of zeros in the regressand decrease. Tobit estimates are theoretically superior to OLS estimates when using censored data. However, if little difference exists between OLS and Tobit estimates, OLS may be operationally acceptable. OLS may even be optimal in a bounded rationality sense because the extra cost of using Tobit analysis may be less than the extra benefits from a very slight increase in accuracy.
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Bibliographic InfoPaper provided by University of Queensland, School of Economics in its series Economic Theory, Applications and Issues Working Papers with number 90519.
Date of creation: May 2002
Date of revision:
Bounded rationality; censored data; Ordinary Least Squares; Tobit; regressand; willingness to pay studies.; Public Economics;
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