Educational Attainment and Income Inequality in Southeast Missouri

1
Educational Attainment and Income Inequality in
Southeast Missouri

• Kang H. Park
• Professor of EconomicsSoutheast Missouri State
  University

2
Introduction

• Human capital theory
• Educational spending is an investment because it
  increases worker productivity.
• Human capital theory is used to explain income
  differentials.
• This study examines the effects of educational
  variables on income and income inequality in
  Southeast Missouri, using the 2000 US census data
  covering 34 Southeast Missouri counties.
• Gini index from B. Domazlickys 2005 article.

3
Descriptive Statistics
Variable Minimum Maximum Mean Standard deviation
EDMEAN 10.98 (Pemiscot) 12.94 (Pulaski) 11.79 0.388
EDSD 2.52 (Miller) 3.61 (Pemiscot) 2.90 0.260
EDCV 0.206 (Camden) 0.328 (Pemiscot) 0.247 0.029
Household Income (HINCOME) 28,978 (Shannon) 47,221 (Camden) 36,170 4,578
Family Income (FINCOME) 11,492 (Shannon) 55,283 (Cape Girardeau) 41,401 5,329
Per Capita Income (CAPITA) 11,492 (Shannon) 20,197 (Camden) 14,520 1,768
Poverty Rate (POVERTY) 8.2 (Ste. Genevieve) 30.4 (Pemiscot) 18.2 5.21
Gini Index (GINI) 0.336 (Pulaski) 0.481 (Pemiscot) 0.404 0.033
EDMEAN Average years of schooling EDSD
Standard deviation of years of schoolingEDCV
Coefficient of variation of years of schooling,
EDSD/EDMEANGini Index (GINI) measure of income
inequality
4
(No Transcript)
5
Southeast Missouri Data Southeast Missouri Data Southeast Missouri Data

County edmean edsd edcv pop Hincome Fincome capita poverty Gini
Butler 12.047 2.971714 0.246677 40867 38000 45157 15721 18.6 0.4477
Bollinger 11.471 2.858834 0.249223 12029 35413 40371 13641 13.8 0.3586
Camden 12.7955 2.631408 0.205651 37051 47221 53000 20197 11.4 0.4152
Cape_Girardeau 12.912 3.042582 0.23564 68693 46272 55283 18593 11.1 0.3834
Carter 11.6235 3.104086 0.267053 5941 33143 36064 13349 25.2 0.4207
Crawford 11.77 2.670108 0.226857 22804 37726 43356 14825 16.3 0.3883
Dent 11.5805 2.941226 0.253981 14927 35513 40333 14463 17.2 0.3935
Douglas 11.782 2.840713 0.241106 13084 34605 37864 13785 17.5 0.3956
Dunklin 11.2735 3.315 0.294062 33155 33066 38139 13351 24.5 0.4262
Howell 12.04 2.684033 0.222926 37238 34427 39418 13959 18.7 0.4127
Iron 11.5035 3.06586 0.266492 10697 35415 41637 14227 19 0.4303
Laclede 12.047 2.572438 0.213533 32513 39479 43191 15572 14.3 0.3962
Madison 11.585 2.838624 0.245026 11800 32092 36949 13215 17.2 0.3992
Maries 11.929 2.738115 0.229534 8903 38570 44031 15662 13.1 0.3496
Miller 12.07 2.524602 0.209155 23564 37978 43535 15144 14.2 0.3673
Mississippi 11.1955 3.364215 0.300497 13427 32139 37976 13038 23.7 0.445
New_Madrid 11.2 3.419156 0.304087 19760 35027 40467 14204 22.1 0.4292
Oregon 11.7195 2.790444 0.238103 10344 30635 35257 12812 22 0.4256
Ozark 11.8 2.641091 0.222567 9.542 33776 38289 14133 21.6 0.4281
Pemiscot 10.9835 3.607001 0.328402 20047 32372 37861 12968 30.4 0.4809
Perry 11.735 2.773194 0.236318 18132 42693 50072 16554 9 0.3455
Phelps 12.803 3.130931 0.244547 39825 38894 46519 16084 16.4 0.3942
Pulaski 12.937 2.692144 0.208096 41165 40442 43527 14586 10.3 0.336
Reynolds 11.5025 2.760879 0.240024 6689 31450 36064 13065 20.1 0.3812
Ripley 11.344 3.097861 0.273084 13509 31464 35420 12889 22 0.417
StFrancois 12.036 2.730266 0.226842 55641 38872 44270 15273 14.9 0.3816
SteGenevieve 11.841 2.6289 0.2201 17842 46289 51897 17283 8.2 0.3524
Scott 11.863 2.858032 0.24092 40422 39705 45570 15620 16.1 0.3951
Shannon 11.5465 2.659815 0.230357 8324 28978 33638 11492 26.9 0.4416
Stoddard 11.5795 3.036908 0.262266 29705 35859 41462 14656 16.5 0.4062
Texas 11.898 2.746514 0.230838 23003 33219 37797 13799 21.4 0.427
Whashington 11.3565 3.006616 0.264748 23344 34980 39980 12934 20.8 0.4225
Wayne 11.1665 3.136637 0.280897 13259 31928 36766 13434 21.9 0.429
Wright 11.798 2.84702 0.241314 17955 32144 36461 13135 21.7 0.4064
6
(No Transcript)
7
Regression of income on education variables N34
Dependent Variable Income Dependent Variable Income Dependent Variable Income
Per Capita Income Household Income Family Income
Intercept -18816 (-2.334) -42875 (-2.015) -58864(-2.311)
EDMEAN 2690 (5.084) 6597 (4.723) 7881(4.714)
EDSD 561 (0.565) 442 (0.169) 2540 (0.809)

Adjusted R2 0.466 0.445 0.413
F-value 15.40 14.22 12.62
Numbers in parentheses are t-values. The
variable is significant at the 0.01 level and
The variable is significant at the 0.05 level.
8
(No Transcript)
9
(No Transcript)
10
Regression of income inequality on income and
education variables N34
Dependent Variable Dependent Variable Dependent Variable Dependent Variable
Poverty Rate Poverty Rate Gini Index Gini Index
Intercept 289.81(6.206) 260.21 (5.518) 1.02 (2.305) 0.82 (1.841)
LnCapita -30.88 (-5.277) -27.10 (-5.784) -0.08 (-1.415) -0.06 (-1.317)
EDMEAN -0.149 (-0.098) -0.003 (-0.215)
EDSD 7.68 (3.603) 0.059 (2.905)
EDCV 70.97 (3.826) 0.58 (3.339)

Adjusted R2 0.719 0.720 0.354 0.371
F 29.19 43.30 7.03 10.74
LnCapita natural logarithm of per capita
incomeNumbers in parentheses are t-values.
The variable is significant at the 0.01 level and
The variable is significant at the 0.05 level.
11
Summary

• A higher levels of income and education have an
  equalizing effect on income distribution
• The dispersion of schooling has a disequalizing
  effect on income distribution.
• Both LnCapita and EDSD (or EDCV) are
  statistically significant in explaining the
  poverty rate.
• only EDSD(or EDCV) can explain the Gini index
  well.