Educational Attainment and Income Inequality

in Southeast Missouri

Kang H. Park

Professor of EconomicsSoutheast Missouri State University

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. Domazlicky’s 2005 article.

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

Descriptive Statistics

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

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

edmean13.00012.50012.00011.50011.00010.500

22000

20000

18000

16000

14000

12000

10000

capita

LinearObserved

edsd3.8000003.6000003.4000003.2000003.0000002.8000002.600000

22000

20000

18000

16000

14000

12000

10000

capita

LinearObserved

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 0.413F-value 15.40 14.22 12.62

Regression of income on education variablesN=34

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.

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 0.371F 29.19 43.30 7.03 10.74

Regression of income inequality on income and education variablesN=34

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.

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.