A Transformed Random Effects Model with Applications
نویسندگان
چکیده
This paper proposes a transformed random effects model for analyzing non-normal panel data where both the response and (some of) the covariates are subject to transformations for inducing flexible functional form, normality, homoscedasticity and simple model structure. We develop maximum likelihood procedure for model estimation and standard error calculation, along with a computational devise which makes the estimation procedure feasible in cases of large panels. We give model specification tests which take into account the fact that parameter values for error components cannot be negative. We illustrate the model and methods with two applications: state production and wage distribution. The empirical results strongly favor the new model to the standard ones where either linear or log-linear functional form is employed.
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