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Research Institute for Quantitative Studies in Economics and Population

Abstracts of Research Reports: 2014

  1. A Shortcoming of the Conventional Approach to Statistical Explanation for Wage or Income Variation: Offering a Better Alternative

    by Kao-Lee Liaw and Ji-Ping Lin

    In explaining wage or income by personal attributes (e.g. educational attainment, age, and ethnicity) in a regression model, many researchers choose to use the log of wage or income asthe dependent variable and then to estimate the unknown coefficients by some version of theleast-squares method. We call this approach the conventional approach.

    Using the micro data of the 2005-2007 American Community Survey and Taiwan's 2001-2010 Manpower Utilization Survey, we show that the conventional approach has the serious shortcoming of under-predicting the observed wage structure in the space spanned by the values of the explanatory variables. In addition to revealing the reason for the under-prediction problem and linking the severity of this problem to wage variability, we present a nonlinear approach that does not have this shortcoming. We also offer a SAS module for carrying out the estimation task in the nonlinear approach.

Last updated: August 26, 2014
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