Human Capital in Growth Regressions: How Much Difference Does Data Quality Make?
为21个OECD国家构建了更准确的教育程度估计，发现数据质量越高，人力资本在增长回归中的系数越大且越显著，并估计出柯布-道格拉斯生产函数中教育年限的系数可能高于0.60。
We construct estimates of educational attainment for a sample of 21 OECD countries. Our series incorporate previously unexploited information and remove sharp breaks in the data that can only reflect changes in classification criteria. We then construct indicators of the information content of our estimates and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model to correct for measurement error bias, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that the value of this parameter is likely to be above 0.60.