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Estimating Returns to Education Using Different Natural Experiment Techniques

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Estimating Returns to Education Using Different Natural Experiment Techniques
 
Identifier https://doi.org/10.7910/DVN/BRDNRF
 
Creator Leigh, Andrew
Ryan, Chris
 
Publisher Harvard Dataverse
 
Description We compare three quasi-experimental approaches to estimating the returns to schooling in Australia: instrumenting schooling using month of birth, instrumenting schooling using changes in compulsory schooling laws, and comparing outcomes for twins. With annual pre-tax income as our measure of income, we find that the naïve (OLS) returns to an additional year of schooling is 13%. The month of birth IV approach gives an 8% rate of return to schooling, while using changes in compulsory schooling laws as an IV produces a 12% rate of return. Finally, we review estimates from twins studies. While these studies have tended to estimate a lower return to education, we believe that this is primarily due to the better measurement of income and schooling in our dataset. Australian twins studies are consistent with our findings insofar as they find little evidence of ability bias in the OLS rate of return to schooling. Our estimates of the ability bias in OLS estimates of the rate of return to schooling range from 9% to 39%. Overall, our findings suggest the Australian rate of return to education, corrected for ability bias, is around 10%, which is similar to the rate in Britain, Canada, the Netherlands, Norway and the United States.
 
Subject Returns to education; Instrumental variables; Compulsory schooling; Twins; Australia
 
Date 2008