Wages and Hours: Estimating Vector Autoregressions with Panel Data

Abstract

This paper considers estimation and testing of vector autoregression coefficients in panel data, and uses the techniques to analyze the dynamic properties of wages and hours among American males. The model allows for non- stationary individual effects, and is estimated by applying instrumental variables to the quasi—differenced autoregressive equations. Particular attention is paid to specifying lag lengths and forming convenient test statistics. The empirical results suggest that the wage equation contains at most a single lag of hours and wages, and that one cannot reject the hypothesis that lagged hours may be excluded from the wage equation. Our results also show that lagged hours is important in the hours equation, which is consistent with alternatives to the simple labor supply model that allow for costly hours adjustment or preferences that are not time separable.