2001年-世界发展银行全球_Where_Has_All_the_Education_Gone__25页_608kb

Summary of "Where Has All the Education Gone?"

Core Content

This article by Lant Pritchett explores the relationship between educational expansion and economic growth, challenging the widely held belief that increasing education levels directly boost productivity and economic output. Using cross-national data, the author finds that while education is associated with higher wages at the micro level, there is no consistent positive link between educational capital growth and output per worker at the macro level. Instead, the results suggest that the growth impact of education is often negative or insignificant, raising questions about the presence of externalities and the broader development impact of education.

Main Points

• No Association Between Education and Growth: Cross-national data show no positive correlation between increases in educational attainment and output per worker growth. This indicates that the growth impact of education is not as strong as expected, even though it has a clear positive effect on individual wages.

• Negative Externalities and the Micromacro Paradox: The findings suggest that education may have negative externalities at the macro level, creating a "micromacro" paradox. While education increases individual wages, it may not translate into aggregate economic growth due to various structural and institutional factors.

• Three Possible Explanations for the Paradox:

  1. Institutional Environment: In some countries, the institutional framework may lead to socially wasteful or counterproductive uses of educated labor, such as income redistribution (e.g., piracy metaphor), which may not enhance productivity.
  2. Diminishing Marginal Returns: As the supply of educated labor increases while demand remains stagnant, the rate of return to education may fall rapidly, reducing its impact on growth.
  3. Low Educational Quality: If the quality of education is poor, years of schooling may not translate into meaningful human capital gains, despite higher wages due to signaling effects.

Key Information

• Educational Capital and Wages: The article discusses how the share of wages attributable to human capital can be estimated using wage premia across different educational attainment levels. It highlights that the human capital share of the wage bill is estimated to be between 0.35 and 0.7 across regions, with OECD countries showing the highest at 0.73 under one assumption.

• Educational Capital Stock: Using microeconomic data, the author constructs a measure of educational capital stock, assuming the wage increment to education is constant or follows a specific pattern. The formula for the growth rate of educational capital is derived from the natural logarithm of the wage premium function.

• Growth-Accounting Regressions: The author performs growth-accounting regressions using data from Barro and Lee (1993) and Nehru and others (1995). The results show that the coefficient for educational capital growth is consistently negative and statistically insignificant, while the coefficient for physical capital (CUDIE) is positive and significant.

• TFP and Educational Capital: In the TFP regression, the coefficient for educational capital is also negative and statistically significant, even when assuming different factor shares. This suggests that educational capital may not contribute positively to total factor productivity (TFP) growth.

• Robustness of Results: The findings are robust across different samples, data sources, and estimation techniques. The negative coefficient on education is not due to measurement error or failure to account for school quality.

Methodology and Data

• Data Sources: The author uses two cross-national time-series datasets to estimate educational capital and physical capital growth. These include:

  • Barro and Lee (1993): Estimates educational attainment based on census or labor force data.
  • Nehru and others (1995): Uses a perpetual inventory method to estimate the stock of schooling for the labor force-aged population.

• Growth Equations: The article uses the augmented Solow model, which incorporates educational capital and physical capital into the production function. The model assumes constant returns to scale and estimates the growth of GDP per worker as a function of the growth of educational and physical capital.

• Regression Results:

  • The coefficient for educational capital growth is -0.049 (insignificant).
  • The coefficient for CUDIE (physical capital) is 0.524 (highly significant).
  • In TFP regressions, the coefficient for educational capital is -0.338 (statistically significant), indicating a negative impact on TFP growth.

• Robustness Checks: The results are consistent across different samples and data sources. The negative coefficient remains even when excluding certain regions or using alternative weighting schemes.

Conclusion

Pritchett concludes that while education is beneficial at the individual level, its macroeconomic impact on growth is often limited or negative. The failure to observe a strong positive relationship between education and growth challenges the conventional wisdom that education is a key driver of economic development. The article emphasizes the importance of institutional and structural factors in determining the effectiveness of education in promoting growth, suggesting that the development impact of education varies widely across countries.