Family Background Variables as Instruments for Education in Income Regressions: A Bayesian Analysis

Abstract The validity of family background variables instrumenting education in income regressions has been much criticized. In this paper, we use data from the 2004 German Socio-Economic Panel and Bayesian analysis to analyze to what degree violations of the strict validity assumption affect the estimation results. We show that, in case of moderate direct effects of the instrument on the dependent variable, the results do not deviate much from the benchmark case of no such effect (perfect validity of the instrument's exclusion restriction). In many cases, the size of the bias is smaller than the width of the 95% posterior interval for the effect of education on income. Thus, a violation of the strict validity assumption does not necessarily lead to results which are strongly different from those of the strict validity case. This finding provides confidence in the use of family background variables as instruments in income regressions.

[1]  David A. Jaeger,et al.  Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak , 1995 .

[2]  T. Lancaster An Introduction to Modern Bayesian Econometrics , 2004 .

[3]  S. Comi,et al.  Education and Earnings Growth: Evidence from 11 European Countries , 2000 .

[4]  M. Blackburn,et al.  Are Ols Estimates of the Return to Schooling Biased Downward? Another Look , 1993 .

[5]  A. Deaton Instruments of Development: Randomization in the Tropics, and the Search for the Elusive Keys to Economic Development , 2009 .

[6]  Matt Dickson,et al.  Economic Returns to Education: What We Know, What We Don't Know, and Where We Are Going Some Brief Pointers , 2011 .

[7]  Family Background Variables as Instruments for Education in Income Regressions: A Bayesian Analysis , 2010 .

[8]  Peter E. Rossi,et al.  Plausibly Exogenous , 2008, Review of Economics and Statistics.

[9]  T. Bayes An essay towards solving a problem in the doctrine of chances , 2003 .

[10]  H. Oosterbeek,et al.  Wage effects of an extra year of basic vocational education , 2007 .

[11]  J. Behrman Schooling in developing countries: Which countries are the Over- and underachievers and what is the schooling impact? , 1987 .

[12]  James J Heckman,et al.  Comparing IV with Structural Models: What Simple IV Can and Cannot Identify , 2009, Journal of econometrics.

[13]  G. Brunello Absolute Risk Aversion and the Returns to Education , 2001 .

[14]  Eric Zivot,et al.  Bayesian and Classical Approaches to Instrumental Variables Regression , 2003 .

[15]  H. D. Webbink Causal Effects in Education , 2005 .

[16]  Lennart F. Hoogerheide,et al.  Education and entrepreneurial choice: An instrumental variables analysis , 2010 .

[17]  Lennart F. Hoogerheide,et al.  Natural conjugate priors for the instrumental variables regression model applied to the Angrist–Krueger data , 2006 .

[18]  Lennart F. Hoogerheide,et al.  A Class of Adaptive EM-Based Importance Sampling Algorithms for Efficient and Robust Posterior and Predictive Simulation , 2011 .

[19]  Gert G. Wagner,et al.  The German Socio-Economic Panel Study (SOEP) - Evolution, Scope and Enhancements , 2007 .

[20]  Philip A. Trostel,et al.  Estimates of the economic return to schooling for 28 countries , 2002 .

[21]  César Camisón,et al.  Direct and indirect effects of education on job satisfaction: A structural equation model for the Spanish case , 2009 .

[22]  M. Praag,et al.  Schooling, Capital Constraints and Entrepreneurial Performance , 2005 .

[23]  M. Blackburn,et al.  Omitted-Ability Bias and the Increase in the Return to Schooling , 1991, Journal of Labor Economics.

[24]  J. Angrist,et al.  Does Compulsory School Attendance Affect Schooling and Earnings? , 1990 .

[25]  Lennart F. Hoogerheide,et al.  On the Shape of Posterior Densities and Credible Sets in Instrumental Variable Regression Models with Reduced Rank: An Application of Flexible Sampling Methods Using Neural Networks , 2005 .

[26]  Peter E. Kennedy A Guide to Econometrics , 1979 .

[27]  Jan Goebel,et al.  Using Geographically Referenced Data on Environmental Exposures for Public Health Research: A Feasibility Study Based on the German Socio-Economic Panel Study (SOEP) , 2011 .

[28]  H. Patrinos,et al.  Returns to investment in education: a further update , 2002 .

[29]  Zvi Griliches,et al.  Education, Income, and Ability , 1972, Journal of Political Economy.

[30]  S. Paternostro,et al.  Returns to Education in the Economic Transition: A Systematic Assessment Using Comparable Data , 2007 .

[31]  David Card Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems , 2000 .

[32]  Boyan Jovanovic,et al.  An Estimated Model of Entrepreneurial Choice under Liquidity Constraints , 1989, Journal of Political Economy.

[33]  Joshua D. Angrist,et al.  Identification of Causal Effects Using Instrumental Variables , 1993 .

[34]  Richard V. Burkhauser,et al.  The English language public use file of the German Socio-Economic Panel , 1993 .

[35]  H. Patrinos Quality of Schooling, Returns to Schooling and the 1981 Vouchers Reform in Chile , 2008 .

[36]  Inmaculada García-Mainar,et al.  Education returns of wage earners and self-employed workers: Portugal vs. Spain , 2005 .

[37]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.