Kevin Lang

Professor

Department of Economics, Boston University; NBER; IZA

NLS user since 1980

Citations
  • Bond, T. and Lang, K. “The Evolution of the Black-White Test Score Gap in Grades K-3: The Fragility of Results.” Review of Economics and Statistics, (December 2013): 1468-79.
  • Lang, K. and Manove, M., “Education and Labor Market Discrimination,” American Economic Review, 100 (June 2011): 1467-96.
  • Lang, K. and Zagorsky, J. “Does Growing Up with An Absent Parent Really Hurt?” Journal of Human Resources, 36 (Spring 2001): 253-73.
  • Kahn, S. and Lang, K. “Constraints on the Choice of Work Hours: Agency vs. Specific Capital,” Journal of Human Resources, 27 (Fall 1992), 661-678.
  • Lang, K. and Ruud, P. “Returns to Schooling, Implicit Discount Rates and Black-White Wage Differentials” The Review of Economics and Statistics 68 (February 1986): 41-47.
  • Bond, T.N. and Lang, K. “The Black-White Education-Scaled Test-Score Gap in Grades K-7,” National Bureau of Economic Research Working Paper No. 19243, July 2013.
What I learned from NLS data

Much of my work using various NLS data sets has been concerned with racial disparities. My more recent papers establish the conditions under which we can make meaningful statements about the evolution of the test-score gap in elementary and middle school. One paper shows that this is sensitive to scaling, while the more recent approach argues for a particular approach to scaling and reestablishes that the gap is large and constant from kindergarten through grade 7. My very early work suggested that conditional on background characteristics, blacks and whites made similar decisions regarding when to end schooling, while my more recent work extends the analysis and establishes that conditional on a number of possible confounding factors, blacks complete more education than otherwise similar whites. I also have quite separate papers that find that the adverse effects of growing up with one parent absent have been greatly exaggerated due to inadequate controls for other differences, and a paper that uses the NLSY79 to show that the pattern of constraints on the choice of working hours is inconsistent with Lazear's agency model.

Why I chose NLS data

The longitudinal information combined with the breadth of the questions asked makes the NLS suitable for a wide range of investigations. The ability to span generations through the CNLSY has been particularly useful for some of my recent research.