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Statistics and Data Analysis

This analysis conducted by Professor William Greene at Stern School of Business explores the relationship between income distribution, measured by DALE, GINI coefficient, and per capita GDP (GDPC). Using regression analysis, we find that DALE correlates with GINI and GDPC. The regression equations provide insights into how income inequality (GINI) and economic productivity (GDPC) impact overall economic welfare (DALE). The findings highlight the importance of considering both income distribution and education expenditure in assessing economic performance.

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Statistics and Data Analysis

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Presentation Transcript

  1. Statistics and Data Analysis Professor William Greene Stern School of Business IOMS Department Department of Economics

  2. DALE and Per Capita GDP

  3. Income Distribution Matters Regression Analysis: DALE versus GINI, GDPC The regression equation is DALE = 63.8 - 34.5 GINI + 0.000950 GDPC Predictor Coef SE Coef T P Constant 63.768 3.651 17.47 0.000 GINI -34.521 8.550 -4.04 0.000 GDPC 0.00095022 0.00009987 9.52 0.000 S = 9.02618 R-Sq = 46.7% R-Sq(adj) = 46.1%

  4. World Income Distributions http://en.wikipedia.org/wiki/Image:Gini_Coefficient_World_Human_Development_Report_2007-2008.png

  5. Per Capita GDP vs. Income Distribution

  6. What About Education?

  7. Maybe Richer Countries Spend More on Education

  8. How Do We Disentangle All These Effects? Regression Analysis: DALE versus EDUC, GINI, GDPC The regression equation is DALE = 42.3 + 2.65 EDUC - 12.0 GINI + 0.000494 GDPC Predictor Coef SE Coef T P Constant 42.259 3.599 11.74 0.000 EDUC 2.6511 0.2582 10.27 0.000 GINI -12.028 7.197 -1.67 0.096 GDPC 0.00049367 0.00009159 5.39 0.000 The regression equation is DALE = 49.5 + 0.00111 GDPC Predictor Coef SE Coef T P Constant 49.4725 0.9249 53.49 0.000 GDPC 0.00111273 0.00009502 11.71 0.000

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