Spatial Pseudo Panel Data Models with an Application to Mincer Wage Equations

Abstract

The studies using Mincer equations are generally applied to cross-sectional
data at the micro-level. There are however limited studies conducted with macro
or panel data for wage equations. Pseudo panel data methods can be applied
to empirical studies by creating cohorts from repeated cross-sectional data in
the absence of genuine panel data. Difference in both the human and labour
resources according to the spatial positions may also affect the prediction of the
wage equations. We aim to introduce the application of spatial pseudo panel
models by creating cohorts according to the birth years of employees and regions
in which they live from the Turkish household labour survey for the period 2010–
2015. As a result, we find that the spatial autocorrelation model is appropriate
for wage equations of Turkey. We also find that return of education on wages is
11% while return of experience on wages is 4%.