Working Paper: CEPR ID: DP4637
Authors: Rob Alessie; Miguel Portela; Coen N. Teulings
Abstract: The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations constructed from enrolment data. We discuss a methodology for correcting the measurement error. The standard attenuation bias suggests that using these corrected data would lead to a higher coefficient. Our regressions reveal the opposite. We discuss why the measurement error yields an overestimation. Our analysis contributes to an explanation of the difference between regressions based on 5 and on 10-year first-differences.
Keywords: Education; Growth; Measurement Error
JEL Codes: I20; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| perpetual inventory method (C69) | systematic measurement errors (C83) |
| systematic measurement errors (C83) | biased GDP growth regressions (E20) |
| measurement error (C20) | overestimation of the impact of education on GDP growth (I25) |
| education measurement errors (I21) | GDP growth (O49) |
| corrected education data (I20) | lower coefficient on changes in education in GDP regressions (I25) |
| education (I29) | GDP growth (O49) |