BID Brown Bag Seminar: Noncognitive Skills and Labor Market Outcomes: A Machine Learning Approach
|Speaker:||Winfried Pohlmeier, University of Konstanz|
|Date: ||Tuesday 30 May 2017|
|Location: ||Bateman Lecture Theatre, Building One|
We study the importance of noncognitive skills in explaining differences in the labor market performance of individuals by means of machine learning techniques. Unlike previous empirical approaches centering around the within-sample explanatory power of noncognitive skills our approach focuses on the out-of-sample forecasting and classi_cation qualities of
noncognitive skills. Moreover, we show that machine learning techniques can cope with the challenge of selecting the most relevant covariates from big data with a whopping number of
covariates on personality traits. This enables us to construct new personality indices with larger predictive power.
In our empirical application we study the role of noncognitive skills for individual earnings and unemployment based on the British Cohort Study (BCS). The longitudinal character
of the BCS enables us to analyze predictive power of early childhood environment and early cognitive and noncognitive skills on adult labor market outcomes. The results of the analysis show that there is a potential of a long run inuence of early childhood variables on the earnings and unemployment.