|
|
|
|
| LEADER |
02781nmm a2200469 u 4500 |
| 001 |
EB001826109 |
| 003 |
EBX01000000000000000992555 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
180614 ||| eng |
| 020 |
|
|
|a 9781475595741
|
| 100 |
1 |
|
|a Coady, David
|
| 245 |
0 |
0 |
|a Income Inequality and Education Revisited
|b Persistence, Endogeneity, and Heterogeneity
|c David Coady, Allan Dizioli
|
| 260 |
|
|
|a Washington, D.C.
|b International Monetary Fund
|c 2017
|
| 300 |
|
|
|a 23 pages
|
| 653 |
|
|
|a Population & demography
|
| 653 |
|
|
|a Distribution: General
|
| 653 |
|
|
|a Education and Inequality
|
| 653 |
|
|
|a Demographic Economics: General
|
| 653 |
|
|
|a Income distribution
|
| 653 |
|
|
|a National Government Expenditures and Education
|
| 653 |
|
|
|a Aggregate Factor Income Distribution
|
| 653 |
|
|
|a Education
|
| 653 |
|
|
|a Population and demographics
|
| 653 |
|
|
|a Estimation
|
| 653 |
|
|
|a Demography
|
| 653 |
|
|
|a Education: General
|
| 653 |
|
|
|a Econometric models
|
| 653 |
|
|
|a Population
|
| 653 |
|
|
|a Macroeconomics
|
| 653 |
|
|
|a Estimation techniques
|
| 653 |
|
|
|a Income inequality
|
| 653 |
|
|
|a Econometrics
|
| 653 |
|
|
|a Econometrics & economic statistics
|
| 700 |
1 |
|
|a Dizioli, Allan
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b IMF
|a International Monetary Fund
|
| 490 |
0 |
|
|a IMF Working Papers
|
| 028 |
5 |
0 |
|a 10.5089/9781475595741.001
|
| 856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2017/126/001.2017.issue-126-en.xml?cid=44854-com-dsp-marc
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 330
|
| 520 |
|
|
|a This paper presents new results on the relationship between income inequality and education expansion—that is, increasing average years of schooling and reducing inequality of schooling. When dynamic panel estimation techniques are used to address issues of persistence and endogeneity, we find a large, positive, statistically significant and stable relationship between inequality of schooling and income inequality, especially in emerging and developing economies and among older age cohorts. The relationship between income inequality and average years of schooling is positive, consistent with constant or increasing returns to additional years of schooling. While this positive relationship is small and not always statistically significant, we find a statistically significant negative relationship with years of schooling of younger cohorts. Statistical tests indicate that our dynamic estimators are consistent and that our identifying instruments are valid. Policy simulations suggest that education expansion will continue to be inequality reducing. This role will diminish as countries develop, but it could be enhanced through a stronger focus on reducing inequality in the quality of education
|