Working Paper: CEPR ID: DP3587
Authors: Angel de la Fuente; Rafael Domenech
Abstract: We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series 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, 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, after correcting for measurement error bias, the value of this parameter is well above 0.50.
Keywords: Growth; Human Capital; Measurement Error
JEL Codes: C19; I20; O30; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| data quality (L15) | human capital coefficients (J24) |
| measurement error bias (C83) | coefficient of years of schooling (I21) |
| data quality (L15) | size and significance of human capital coefficients (J24) |
| quality of schooling data (I21) | estimated coefficients of human capital (J24) |
| deficiencies in data (C80) | counterintuitive results regarding human capital contribution to economic growth (J24) |
| data deficiencies (C80) | lack of correlation between productivity growth and human capital accumulation (O49) |
| return on investment in education (I26) | substantial (Y20) |