Distributional assumptions and a test of the dual labor market hypothesis

Recent application of the switching regression model to allocate workers into the primary and secondary labor markets is considered to be the best solution to the classification problem of the empirical testing of the dual labor market theory. In such models, normality of the error terms is assumed. This paper adopts the switching regression model to test the dual labor market theory by assuming different distributions of the error terms. The test results strongly support the dual labor market theory regardless of the assumption one makes about the error terms. However, the results indicate that different distribution can lead to different percentage distributions of workers in the two segments. In particular, the normal distribution generates more workers in the primary segment than the non-normal distributions. Therefore, care must be taken not to generalize the type of industries or occupations that fall under the primary and secondary segments. First version received: October 2000/Final version received: March 2002 RID="*" ID="*"  I would like to thank Kevin Lang, Robert Marshall, and two anonymous referees for their helpful comments. I am grateful for comments received from the session participants of the Western Economic Association International Conference, San Francisco, CA, June 28–July 2, 1996, and the Midwest Economic Association Conference, Kansas City, 1997. I thank George Bonney, the Chief Statistician of Fox Chase Cancer Center, Philadelphia for his comments. Any remaining errors are my responsibility. I gratefully acknowledge financial support from Penn State Research and Development Grant, 1995.