TY - JOUR AU - Kane,Thomas J. AU - Rouse,Cecilia Elena AU - Staiger,Douglas TI - Estimating Returns to Schooling When Schooling is Misreported JF - National Bureau of Economic Research Working Paper Series VL - No. 7235 PY - 1999 Y2 - July 1999 UR - http://www.nber.org/papers/w7235 L1 - http://www.nber.org/papers/w7235.pdf N1 - Author contact info: Thomas J. Kane Harvard Graduate School of Education Center for Education Policy Research 50 Church St., 4th Floor Cambridge, MA 02138 Tel: 617/496-4359 E-Mail: kaneto@gse.harvard.edu Cecilia E. Rouse Industrial Relations Section Firestone Library Princeton University Princeton, NJ 08544-1013 Tel: 609/258-6478 Fax: 609/258-0549 E-Mail: rouse@princeton.edu Douglas O. Staiger Dartmouth College Department of Economics HB6106, 301 Rockefeller Hall Hanover, NH 03755-3514 Tel: 603/646-2979 Fax: 603/646-2122 E-Mail: douglas.staiger@dartmouth.edu AB - We propose a general method of moments technique to identify measurement error in self-reported and transcript-reported schooling using differences in wages, test scores, and other covariates to discern the relative verity of each measure. We also explore the implications of such reporting errors for both OLS and IV estimates of the returns to schooling. The results cast a new light on two common findings in the extensive literature on the returns to schooling: sheepskin effects' and the recent IV estimates, relying on natural experiments' to identify the payoff to schooling. First, respondents tend to self-report degree attainment much more accurately than they report educational attainment not corresponding with degree attainment. For instance, we estimate that more than 90 percent of those with associate's or bachelor's degrees accurately report degree attainment, while only slightly over half of those with 1 or 2 years of college credits accurately report their educational attainment. As a result, OLS estimates tend to understate returns per year of schooling and overstate degree effects. Second, because the measurement error in educational attainment is non-classical, IV estimates also tend to be biased, although the magnitude of the bias depends upon the nature of the measurement error in the region of educational attainment affected by the instrument. ER -