Test of Sectoral Shifts Hypothesis Based on Robust Measures of Dispersion and Skewness

Abstract

Sectoral shifts hypothesis states that sectoral reallocation of labor demand has a significant effect on the fluctuation of unemployment rate even in the absence of aggregate shocks. Many studies have found strong evidence supporting the hypothesis. In those studies, classical measures of dispersion and skewness of the cross-sectional distribution of estimated sectoral shocks have been used to represent the effect of sectoral shifts on aggregate unemployment rates. However, it is well known that classical measures of moments are strongly affected by the presence of outliers. Consequently, the test of sectoral shifts hypothesis can be distorted by the presence of a few outliers. This paper examines the presence of outliers in the sectoral shocks estimated from the U.S. industrial data, and tests the sectoral shifts hypothesis based on alternative robust measures of the dispersion and skewness. We find strong evidence of the presence of outliers. However, it turns out that sectoral shifts hypothesis is still strongly supported when robust measures of dispersion and skewness are used as a measure of sectoral shifts. We also find that even in the absence of aggregate shocks the natural rate of unemployment fluctuates significantly over time due to sectoral shifts.