APPENDIX Table A.1, Descriptive Statistics, Regression 9.1, Entire Sample

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1

APPENDIX

Table A.1, Descriptive Statistics, Regression 9.1, Entire Sample

Entire sample N Minimum Maximum Mean

Std. Deviation Ginitimes100 491 2570,00 6625,00 4412,4336 910,29134 SW 2911 ,00 1,00 ,3008 ,43722 SWxGDPcap ₂₆₆₃ _,00 _24123,29 _1185,6100 _2832,20937 GDPcap 1952 491,56 24123,29 3924,7125 3662,50675 FemaleinWorkforce 2480 10,60 54,95 37,1650 9,13404 M2/GDP 2507 ,87 189,89 29,0537 18,87295 Inflation 2436 -3,90 198,44 15,1479 20,95918

Real Interest Rate 1352 -89,44 82,47 4,9118 12,98657

Polity2 2891 -10,00 10,00 -1,3952 6,35788

Dummy Gross 491 0 1 ,79 ,409

Dummy Income 491 0 1 ,59 ,491

Dummy Household 491 0 1 ,32 ,465

Valid N (listwise) 244

Table A.2, Descriptive Statistics, Regression 9.1, Separate Regions

South-Asia N Minimum Maximum Mean Std. Deviation Ginitimes100 71 2717,00 5300,00 3427,5980 544,31224 SW 205 ,00 1,00 ,1463 ,31939 SWxGDPcap 205 ,00 3234,66 278,1502 663,96596 GDPcap 180 181,80 4725,25 802,4687 898,22614 Female in Workforce 155 21,80 40,90 32,1692 5,86765 M2/GDP 170 8,13 46,67 28,3585 10,36704 Inflation 170 ,56 17,59 7,8935 3,45721

Polity2 193 -9,40 9,00 2,2166 6,14381

East-Asia & Pacific N Minimum Maximum Mean

Std. Deviation Ginitimes100 107 2570,00 5300,00 3957,6060 680,60774 SW 369 ,00 1,00 ,6045 ,47832 SWxGDPcap 305 ,00 24123,29 4210,8578 5849,36000 GDPcap 297 584,70 24123,29 5381,5743 5266,00203 Female in Workforce 403 30,08 54,95 41,2582 5,95932 M2/GDP 334 3,94 189,89 42,3030 29,71422 Inflation 345 -,18 141,35 9,5768 13,14127

Polity2 432 -9,00 10,00 -,8477 6,21368

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2

Latin-America &

Caribbean N Minimum Maximum Mean Std. Deviation

Ginitimes100 179 3792,00 6366,00 5037,4120 643,41792 SW 902 ,00 1,00 ,3629 ,44956 SWxGDPcap 788 ,00 12371,51 1483,2198 2470,73456 GDPcap 598 2075,56 21234,89 5993,4812 3379,75458 Female in Workforce 744 14,34 49,17 32,7522 7,31212 M2/GDP 825 7,89 93,34 27,4518 12,29016 Inflation 795 -3,90 198,44 18,5487 24,67950

Polity2 850 -9,00 10,00 2,2052 6,27036

Sub-Saharan Africa N Minimum Maximum Mean Std. Deviation

Ginitimes100 97 2590,06 6625,00 4608,2201 926,42032 SW 1107 ,00 1,00 ,1574 ,34410 SWxGDPcap 1086 ,00 8941,35 338,2246 1119,75837 GDPcap 734 491,56 16193,66 2056,4243 2376,48483 Female in Workforce 930 24,94 52,29 43,4595 5,73170 M2/GDP 928 ,87 79,19 21,0197 12,02098 Inflation 876 -3,90 191,34 15,7433 21,85294

Polity2 1120 -9,00 9,00 -3,9964 4,83003

Middle-East &

North-Africa N Minimum Maximum Mean Std. Deviation

Ginitimes100 32 2938,37 5300,00 3967,2663 469,99769 SW 287 ,00 1,00 ,3868 ,47331 SWxGDPcap 238 ,00 5791,42 932,3327 1639,03073 GDPcap 167 633,97 7528,71 3901,8178 1493,61170 Female in Workforce 217 10,60 29,48 21,9245 3,88980 M2/GDP 217 21,89 122,87 51,0635 20,67144 Inflation 210 -1,16 41,13 10,3585 8,42945

Real Interes tRate 78 -10,13 12,89 1,8967 4,78846

Polity2 255 -10,00 2,40 -6,9035 2,55002

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3 Table A.3 List of countries with at least 2 observations

East-Asia and the Pacific Middle-East & North-Africa

China Algeria

Hong Kong Egypt

Indonesia Iran

South-Korea Jordan

Laos Morocco

Malaysia Tunesia

Papua New Guinea Yemen

Philippines

Singapore

Thailand

Vietnam

Latin-America & Caribbean Sub-Saharan Africa

Argentina Botswana

The Bahama’s Burkina Faso

Barbados Cameroon

Bolivia Central African Republic

Brazil Cote d’Ivoire

Chile Djibouti

Colombia Ethiopia

Costa Rica Gabon

Dominican Republic Gambia

Ecuador Ghana El Salvador Guinea Guatemala Guinea-Bissau Guyana Kenya Honduras Lesotho Jamaica Madagascar Mexico Malawi Nicaragua Mauritania Panama Mauritius Paraguay Niger Peru Nigeria

Puerto Rico Rwanda

Trinidad and Tobago Senegal

Uruguay Seychelles

Venezuela Sierra Leone

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4 Table A.4 Descriptive Statistics, Regressions 9.2

Entire sample

Descriptive Statistics

N Minimum Maximum Mean

Std. Deviation region's mean difference with the centered sample mean (=0) Arablelandpw 2426 0 5,98 0,73 0,66 0 Capitalpw 1179 67 27659,60 5533,26 5044,47 0 Avyearsschool 2379 0,06 10,31 3,33 2,03 0 NOEDs 2379 9,12 98,96 72,83 17,99 0 BASEDs 2379 0,31 57,37 18,75 11,45 0 SKILD 2379 0,10 59,10 8,40 8,36 0 NatRes 2352 -45,40 70,92 3,31 21,55 0 SW 2911 0 1 0,30 0,44 0 Valid N (listwise) 709 East-Asia & Pacific Descriptive Statistics

N Minimum Maximum Mean Std. Dev.

region's mean difference with the centered sample mean (=0) Arablelandpw 372 0,00 0,83 0,32 0,22 -0,42 Capitalpw 139 984,00 27659,60 7140,72 5449,63 1607,46 Avyearsschool 369 0,67 10,31 4,63 2,20 1,30 NOEDs 369 9,12 95,71 59,21 19,79 -13,61 BASEDs 369 3,78 52,82 26,90 9,62 8,15 SKILD 369 0,44 59,10 13,87 12,07 5,47 NatRes 396 -18,75 43,95 1,10 12,91 -2,21 SW 369 0,00 1,00 0,60 0,48 0,30 Valid N (listwise) 60 South-Asia Descriptive Statistics

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5

Middle-East & North-Africa

Descriptive Statistics

region's mean difference with the centered

sample mean (=0) N Minimum Maximum Mean Std. Dev.

Arablelandpw 217 0,14 2,23 1,00 0,58 0,26 Capitalpw 69 1436,00 20726,00 5818,43 5390,14 285,18 Avyearsschool 190 0,54 6,99 2,40 1,45 -0,93 NOEDs 190 43,48 95,50 79,68 11,66 6,85 BASEDs 190 2,90 20,12 11,11 4,82 -7,64 SKILD 190 1,02 36,36 9,18 7,54 0,79 NatRes 229 -13,15 58,59 16,24 21,80 12,93 SW 287 0,00 1,00 0,39 0,47 0,09 Valid N (listwise) 29 Latin-America & Caribbean Descriptive Statistics

region's mean difference with the centered sample mean (=0) Arablelandpw 744 0,02 3,44 0,74 0,60 0,01 Capitalpw 489 204,00 21660,00 8156,77 5083,15 2623,51 Avyearsschool 902 1,43 9,02 4,39 1,62 1,07 NOEDs 902 26,22 89,90 64,31 14,45 -8,52 BASEDs 902 7,70 57,37 24,51 10,02 5,76 SKILD 902 1,20 35,18 11,14 6,89 2,75 NatRes 801 -45,40 62,61 1,95 25,27 -1,36 SW 902 0,00 1,00 0,36 0,45 0,06 Valid N (listwise) 412 Sub-Saharan Africa Descriptive Statistics

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6 Table A.5 Regression results; openness and endowments, dependent variable: 100 x Gini

A.5.1 East Asia & Pacific

1. HC= Av Years

schooling B t Sign. 2. HC= NOEDs B t Sign.

(Constant) 3237,68 21,654 0,000 (Constant) 3238,6 21,698 0,000 arabland _200,64 _{2,446 0,015} arabland _203,13 _{2,493 0,013} cappw -0,026 -2,808 0,005 cappw -0,029 -3,203 0,001 NatRes 3,025 2,072 0,039 NatRes 2,93 2,122 0,034 schoolyears -11,69 -1,121 0,263 NOEDs 1,752 1,618 0,106 sw 123,661 1,937 0,053 sw 145,74 2,464 0,014 swXArabland -8,638 -0,029 0,977 swXArabland -15,57 -0,052 0,959 swXCappw 0,031 1,383 0,167 swXCappw 0,039 1,709 0,088 swXnatres 0,194 0,067 0,947 swXnatres 0,502 0,179 0,858 swXschoolyears 1,692 0,06 0,952 swXNOEDs -1,965 -0,69 0,490 Female in Workforce _1,836 _{0,633 0,527} Female In Workforce _1,426 _{0,494 0,621} M2GDP 2,887 5,117 0,000 M2GDP 2,853 5,121 0,000 Inflation -0,074 -0,196 0,845 Inflation -0,136 -0,361 0,719 Polity2 _9,032 _{3,565 0,000} Polity2 _8,558 _{3,386 0,001} DummyGross 130,33 1,429 0,153 DummyGross 131,66 1,446 0,149 DummyIncome 269,32 3,575 0,000 DummyIncome 273,31 3,631 0,000 Dummy Household 388,885 6,452 0,000 Dummy Household 387,03 6,446 0,000

N= 17 N= 17

R-Square= 0.304 R-Square= 0.347

3. HC= BASEDs B t Sign. 4. HC=SKILD B t Sign.

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7 A.5.2 South-Asia

1. HC= Av Years schooling B t Sign. 2. HC= NOEDs B t Sign. (Constant) _{3654,148 14,307 0,000 (Constant)} _{3649,9 14,419 0,000} Arabland 36,234 0,174 0,862 Arabland 61,081 0,285 0,776 Cappw -0,032 -1,812 0,072 Cappw -0,025 -1,264 0,208 NatRes _2,565 _{0,45 0,653 NatRes} _1,319 _{0,232 0,817} Schoolyears _45,043 _{1,722 0,087 NOEDs} _{-2,661 -0,886 0,377} sw 376,077 2,427 0,016 sw 381,38 2,446 0,015 swXArabland _1156,273 _{1,388 0,167 swXArabland} _1267,2 _{1,472 0,143} swXCappw _0,05 _{1,27 0,206 swXCappw} _0,038 _{0,894 0,373} swXNatRes _23,06 _{1,003 0,317 swXNatRes} _28,452 _{1,223 0,223} sw X schoolyears -65,609 -1,266 0,207 swXNOEDs 3,012 0,487 0,627 Female in Workforce _{-9,239 -1,457 0,147} Female in Workforce _{-8,748 -1,384 0,168} M2GDP -7,516 -2,706 0,007 M2GDP -7,496 -2,673 0,008 Inflation 2,243 0,376 0,708 Inflation 1,124 0,186 0,853 Polity2 _{-1,291 -0,252 0,802 Polity2} _2,155 _{0,455 0,650} DummyGross _{-77,268 -1,037 0,301 DummyGross} _{-81,87 -1,091 0,276} DummyIncome _652,594 _{6,471 0,000 DummyIncome} _646,43 _{6,352 0,000} Dummy Household _186,546 _{2,083 0,039} Dummy Household _182,47 _{2,016 0,045} N= 28 N= 28 R-Square= _0,293 R-Square= 0,230 3. HC=

BASEDs B t Sign. 4. HC=SKILD B t Sign.

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8 A.5.3 Latin-America & Caribbean

1. HC= Av Years schooling B t Sign. 2. HC= NOEDs B t Sign. (Constant) _4445,785 _45,852 _{0,000 (Constant)} _4448,058 _46,306 _0,000 Arabland _30,015 _1,626 _0,104 Arabland _29,629 _1,6 _0,110 Cappw 0,004 1,441 0,150 Cappw 0,004 1,502 0,133 NatRes _-2,071 _-5,135 _{0,000 NatRes} _-2,084 _-5,162 _0,000 Schoolyears _-18,85 _-2,708 _{0,007 NOEDs} _2,048 _2,659 _0,008 sw 57,987 2,724 0,007 sw 57,07 2,686 0,007 swXNatRes 0,108 0,125 0,901 swXNatRes 0,045 0,052 0,958 swXArabland 57,287 1,426 0,154 swXArabland 63,162 1,576 0,115 swXCappw _-0,001 _-0,091 _{0,928 swXCappw} _-0,000, _-0,004 _0,997 sw X schoolyears 23,552 1,795 0,073 swXNOEDs -1,926 -1,321 0,187 DummyGross _137,59 _1,49 _{0,136 DummyGross} _130,703 _1,415 _0,157 DummyIncome 649,69 9,281 0,000 DummyIncome 644,189 9,197 0,000 Dummy Household -177,744 -4,307 0,000 Dummy Household -176,173 -4,271 0,000 Female in Workforce _0,537 _0,33 _0,741 Female in Workforce _0,869 _0,53 _0,596 M2GDP _-2,734 _-3,218 _{0,001 M2GDP} _-2,723 _-3,208 _0,001 Inflation 0,044 2,3 0,022 Inflation 0,042 2,209 0,027 Polity2 -3,472 -2,128 0,034 Polity2 -3,528 -2,162 0,031 N= ₁₀₀ N= 100 R-Square= _0,212 _R-Square= _0,241 3. HC=

BASEDs B t Sign. 4. HC=SKILD B t Sign.

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9 A.5.4 Sub-Saharan Africa

1.HC= Av Years schooling B t Sign. 2. HC= NOEDs B t Sign. (Constant) 4610,73 52,106 0,000 (Constant) 4571,5 52,312 0,000 arablandpw 15,54 1,273 0,203 arablandpw 12,9 1,048 0,295 cappw _-0,003 _{-0,373 0,709 cappw} _-0,006 _{-0,626 0,532} NatResource _0,294 _{0,561 0,575 NatResource} _0,467 _{0,901 0,368} schoolyears _44,529 _{4,47 0,000 noed} _-5,165 _{-3,61 0,000} sw -23,631 -0,843 0,399 sw -13,05 -0,457 0,648 swXarablandpw _14,178 _{0,303 0,762} swXarablandpw _9,302 _{0,199 0,842} swXnatresource _4,481 _{2,205 0,028 swXnatresource} _4,446 _{2,218 0,027} swXcappw _0,056 _{2,721 0,007 swXcappw} _0,066 _{3,046 0,002} swXschoolyears _-81,07 _{-3,664 0,000 swXnoed} _11,004 _{3,934 0,000} Female in Workforce _-0,025 _{-0,016 0,988} Female in Workforce _0,771 _{0,485 0,628} M2GDP -0,354 -0,443 0,658 M2GDP 0,009 0,011 0,991 Inflation _-0,037 _{-0,549 0,583 Inflation} _-0,043 _{-0,63 0,529} Polity2 -0,045 -0,027 0,978 Polity2 -0,22 -0,132 0,895 DummyGross -120,692 -2,132 0,033 DummyGross -120,5 -2,126 0,034 DummyIncome _391,598 _{5,203 0,000 DummyIncome} _385,09 _{5,11 0,000} Dummy Household 98,699 0,991 0,322 Dummy Household 106,66 1,07 0,285 N= ₁₇ N= 17 R-Square 0,117 R-Square 0,126

3. HC= BASEDs B t Sign. 4. HC=SKILD B t Sign.

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10 A.5.5 Middle-East & North-Africa

1. HC= Av Years

schooling B t Sign. 2. HC= NOEDs B t Sign.

(Constant) _4150,42 _59,23 _0,000 (Constant) _{4146,78 58,56} _0,000 Arabland 40,094 1,947 0,052 Arabland 41,889 2,024 0,044 NatRes 1,153 2,707 0,007 NatRes 1,118 2,624 0,009 schoolyears 0,061 0,008 0,993 NOEDs -0,353 -0,394 0,694 sw 41,24 2,074 0,039 sw 37,84 1,881 0,061 swXArabland _62,849 _1,224 _0,222 swXArabland _{66,317 1,294} _0,196 swXNatRes 2,735 2,473 0,014 swXNatRes 2,653 2,395 0,017 swXschoolyears _24,529 _1,243 _0,215 swXNOEDs _{-3,321 -1,306} _0,193 DummyGross -507,55 -13,64 0,000 DummyGross -509,16 -13,68 0,000 DummyIncome 1593,61 15,789 0,000 DummyIncome 1594,97 15,8 0,000 DummyHousehold -275,2 -3,702 0,000 Dummy Household -276,14 -3,715 0,000 FemaleinWorkforce 3,948 1,706 0,089 Femalein Workforce 4,067 1,745 0,082 M2GDP _{-0,919 -1,959} _0,051 M2GDP _{-0,968 -2,098} _0,037 Inflation 2,402 2,343 0,020 Inflation 2,441 2,373 0,018 Polity2 1,294 0,389 0,697 Polity2 0,889 0,269 0,788 N= ₁₈ N= ₁₈ R-Square= 0,486 R-Square= 0,428

3. HC= BASEDs B t Sign. 4. HC=SKILD B t Sign.

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11 Table A.6

Data sources:

Gini-values

Branko Milanovic, ”Worlds Apart: Measuring International and Global

Inequality”, Princeton: Princeton University Press, 2005.

http://econ.worldbank.org/projects/inequality

Educational data

Barro, R.J. and Lee, J-W (2000) “International Data on Educational

Attainment: Updates and Implications.” CID Working Paper no. 42

(April).

http://www.cid.harvard.edu/ciddata/ciddata.html

Polity score

Centre for International Development and Conflict Management

(CIDCM), PolityIV Project.

http://www.cidcm.umd.edu/polity/

Capital per worker

Easterly, W. and Ross Levine, “It’s not factor accumulation: stylized

facts and growth models” , Mimeo, World Bank and U. of Minnesota,

September 1999.

http://www.nyu.edu/fas/institute/dri/dataset/Micro%20Time%20Series.

xls

Sachs-Warner

Wacziarg, R. and Welch, K.H. 2003. "Trade Liberalization and

Indicator

Growth:New Evidence." NBER Working Paper No. 10152.

M2/GDP

World Development Indicators 2006

Inflation rate

World Development Indicators 2006

Real Interest rate

World Development Indicators 2006

Arable land

World Development Indicators 2006

Exports and Imports of ores and metals

World Development Indicators 2006

Exports and Imports of fuels

World Development Indicators 2006

GDP PPP 2000

World Development Indicators 2006

Woman in labour force (% of total)

World Development Indicators 2006

Labour force

World Development Indicators 2006

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12 Table A.7.1.1, Correlation Matrix, Regression 9.1, Entire Sample

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Table A.7.1.2 Correlation-matrix, regression in section 9.2; Entire Sample. All endowment variables are centered

See legend below 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 1,00 0,03- 0,10 0,28- 0,30 0,27- 0,28- 0,25- 0,30- 0,07- 0,16- 0,15- 0,16 0,12- 0,15- 0,18- 0,24- 0,05 0,21- 0,13- 0,09- 0,15- 2 0,03- 1,00 0,28 0,61 0,62- 0,48 0,64 0,21 0,15- 0,07- 0,10 0,20 0,18- 0,06 0,26 0,31- 0,23 0,08 0,37 0,33 0,44 0,00 3 0,10 0,28 1,00 0,09- 0,08 0,08- 0,04- 0,05- 0,06- 0,13- 0,07- 0,05- 0,04 0,03- 0,05- 0,09- 0,10- 0,07 0,01- 0,10- 0,18- 0,03- 4 0,28- 0,61 0,09- 1,00 0,97- 0,90 0,86 0,51 0,12- 0,06- 0,23 0,38 0,38- 0,23 0,44 0,09- 0,44 0,04 0,39 0,32 0,32 0,04- 5 0,30 0,62- 0,08 0,97- 1,00 0,93- 0,87- 0,51- 0,12 0,05 0,21- 0,37- 0,38 0,25- 0,43- 0,12 0,44- 0,03- 0,39- 0,29- 0,30- 0,03- 6 0,27- 0,48 0,08- 0,90 0,93- 1,00 0,64 0,44 0,09- 0,03- 0,07 0,21 0,24- 0,21 0,21 0,02- 0,33 0,00 0,40 0,25 0,25 0,10 7 0,28- 0,64 0,04- 0,86 0,87- 0,64 1,00 0,49 0,14- 0,06- 0,33 0,50 0,49- 0,25 0,63 0,22- 0,50 0,06 0,30 0,27 0,28 0,07- 8 0,25- 0,21 0,05- 0,51 0,51- 0,44 0,49 1,00 0,17- 0,02- 0,15 0,38 0,39- 0,35 0,34 0,03- 0,34 0,04- 0,24 0,13 0,03 0,04- 9 0,30- 0,15- 0,06- 0,12- 0,12 0,09- 0,14- 0,17- 1,00 0,04 0,11- 0,24- 0,27 0,22- 0,25- 0,04 0,11- 0,02 0,09 0,06 0,02 0,12- 10 0,07- 0,07- 0,13- 0,06- 0,05 0,03- 0,06- 0,02- 0,04 1,00 0,18 0,14- 0,12 0,11- 0,10- 0,01 0,18- 0,02- 0,03 0,07- 0,09- 0,04 11 0,16- 0,10 0,07- 0,23 0,21- 0,07 0,33 0,15 0,11- 0,18 1,00 0,65 0,65- 0,48 0,67 0,14 0,07 0,05- 0,02 0,04 0,15 0,06- 12 0,15- 0,20 0,05- 0,38 0,37- 0,21 0,50 0,38 0,24- 0,14- 0,65 1,00 0,97- 0,84 0,87 0,16 0,34 0,07- 0,04 0,15 0,20 0,00 13 0,16 0,18- 0,04 0,38- 0,38 0,24- 0,49- 0,39- 0,27 0,12 0,65- 0,97- 1,00 0,89- 0,86- 0,15- 0,32- 0,07 0,03- 0,12- 0,17- 0,02- 14 0,12- 0,06 0,03- 0,23 0,25- 0,21 0,25 0,35 0,22- 0,11- 0,48 0,84 0,89- 1,00 0,53 0,19 0,20 0,06- 0,02- 0,07 0,11 0,08 15 0,15- 0,26 0,05- 0,44 0,43- 0,21 0,63 0,34 0,25- 0,10- 0,67 0,87 0,86- 0,53 1,00 0,06 0,37 0,06- 0,07 0,14 0,19 0,04- 16 0,18- 0,31- 0,09- 0,09- 0,12 0,02- 0,22- 0,03- 0,04 0,01 0,14 0,16 0,15- 0,19 0,06 1,00 0,24- 0,02- 0,03- 0,03 0,08- 0,09- 17 0,24- 0,23 0,10- 0,44 0,44- 0,33 0,50 0,34 0,11- 0,18- 0,07 0,34 0,32- 0,20 0,37 0,24- 1,00 0,07- 0,02 0,02 0,04 0,02- 18 0,05 0,08 0,07 0,04 0,03- 0,00 0,06 0,04- 0,02 0,02- 0,05- 0,07- 0,07 0,06- 0,06- 0,02- 0,07- 1,00 0,07 0,03 0,01- 0,10- 19 0,21- 0,37 0,01- 0,39 0,39- 0,40 0,30 0,24 0,09 0,03 0,02 0,04 0,03- 0,02- 0,07 0,03- 0,02 0,07 1,00 0,11 0,17 0,02 20 0,13- 0,33 0,10- 0,32 0,29- 0,25 0,27 0,13 0,06 0,07- 0,04 0,15 0,12- 0,07 0,14 0,03 0,02 0,03 0,11 1,00 0,52 0,14 21 0,09- 0,44 0,18- 0,32 0,30- 0,25 0,28 0,03 0,02 0,09- 0,15 0,20 0,17- 0,11 0,19 0,08- 0,04 0,01- 0,17 0,52 1,00 0,39 22 0,15- 0,00 0,03- 0,04- 0,03- 0,10 0,07- 0,04- 0,12- 0,04 0,06- 0,00 0,02- 0,08 0,04- 0,09- 0,02- 0,10- 0,02 0,14 0,39 1,00

1= Arable land per worker 7= % Higher educated (SKILD) 13= SW x NO-EDs 19= Polity 2

2= Capital per worker 8= Sachs-Warner indicator (SW) 14= SW x BAS-EDs 20= Dummy Gross

3= Natural Resources 9= SW x Arable land per worker 15= SW x SKILD 21= Dummy Income

4= Average years of school attainment 10= SW x Natural Resources 16= % Females in workforce 22= Dummy Households

5= % Uneducated (NO-EDs) 11= SW x Capital per Worker 17= M2 / GDP

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14 Table A.7.2.1, Collinearity statistics, Variance Inflation Factors (VIF), Regressions 9.1

Entire sample East-Asia & Sub-Saharan

Collinearity Statistics Pacific Collinearity Statistics Africa Collinearity Statistics

Tolerance VIF Tolerance VIF Tolerance VIF

(Constant) (Constant) (Constant)

SW 0,50 1,98 SW 0,32 3,12 SW 0,45 2,20

GDPcap 0,55 1,83 GDPcap 0,11 8,78 GDPcap 0,76 1,31 SWxGDPcap 0,32 3,09 SWxGDPcap 0,12 8,24 SWxGDPcap 0,39 2,54 Female in Workforce 0,92 1,08 Female in Workforce 0,77 1,30 Female in Workforce 0,92 1,08 M2/GDP 0,73 1,37 M2/GDP 0,54 1,84 M2/GDP 0,76 1,31 Inflation 0,94 1,06 Inflation 0,88 1,13 Inflation 0,65 1,54 Real Interest Rate 0,95 1,05 Real Interest Rate 0,89 1,12 Real Interest Rate 0,62 1,62 Polity2 0,92 1,09 Polity2 0,93 1,08 Polity2 0,91 1,10 DummyGross 0,73 1,38 DummyGross 0,75 1,34 DummyGross 0,90 1,11 DummyIncome 0,62 1,62 DummyIncome 0,59 1,68 DummyIncome 0,62 1,62 DummyHousehold 0,83 1,20 DummyHousehold 0,69 1,44 DummyHousehold 0,63 1,58 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

Latin-America & South-Asia Middle-East &

Caribbean Collinearity Statistics Collinearity Statistics North-Africa Collinearity Statistics

SW 0,33 3,06 SW 0,07 13,65 SW 0,30 3,31

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15 Table A.7.2.2 Collinearity statistics, Variance Inflation Factors (VIF), Regression 9.2

Entire sample

Collinearity Statistics Collinearity Statistics

Tolerance VIF Tolerance VIF

(Constant) (Constant) arablandpw 0,75 1,33 arablandpw 0,74 1,34 cappw 0,76 1,32 cappw 0,74 1,35 NatResource 0,90 1,11 NatResource 0,90 1,11 schoolyears 0,58 1,72 noed 0,56 1,80 sw 0,72 1,40 sw 0,71 1,41 swXarablandpw 0,82 1,21 swXarablandpw 0,81 1,23 swXnatresource 0,91 1,10 swXnatresource 0,91 1,10 swXcappw 0,76 1,31 swXcappw 0,74 1,35 swXschoolyears 0,60 1,67 swXnoed 0,57 1,74 FemaleinWorkforce 0,83 1,20 FemaleinWorkforce 0,84 1,20 M2/GDP 0,72 1,39 M2/GDP 0,73 1,37 Inflation 0,97 1,03 Inflation 0,98 1,02 Polity2 0,83 1,20 Polity2 0,83 1,21 DummyGross 0,72 1,38 DummyGross 0,72 1,38 DummyIncome 0,61 1,65 DummyIncome 0,61 1,64 DummyHousehold 0,83 1,21 DummyHousehold 0,83 1,21 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

Tolerance VIF Tolerance VIF

(16)

16 Table A.7.2.3 Collinearity statistics, Variance Inflation Factors (VIF), Separate Regions,

Regressions 9.2

East-Asia & Sub-Saharan

Pacific Africa

Tolerance VIF Tolerance VIF

(Constant) (Constant) arablandpw 0,60 1,67 arablandpw 0,45 2,21 cappw 0,03 34,78 cappw 0,71 1,41 NatResource 0,45 2,23 NatResource 0,42 2,38 schoolyears 0,19 5,31 schoolyears 0,62 1,60 sw 0,23 4,44 sw 0,48 2,08 swXarablandpw 0,35 2,84 FemaleinWorkforce 0,78 1,28 swXnatresource 0,48 2,07 M2/GDP 0,71 1,42 swXcappw 0,03 32,17 Inflation 0,88 1,13 swXschoolyears 0,16 6,13 Polity2 1,19 FemaleinWorkforce 0,56 1,80 DummyGross 0,90 1,11 M2/GDP 0,70 1,43 DummyIncome 0,62 1,62 Inflation 0,76 1,32 DummyHousehold 0,63 1,58 Polity2 0,67 1,49 swXarablandpw 0,46 2,19 DummyGross 0,70 1,43 swXnatresource 0,41 2,43 DummyIncome 0,55 1,82 swXcappw 0,62 1,61 DummyHousehold 0,68 1,47 swXschoolyears 0,61 1,63 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

Latin-America & South-Asia Middle-East &

Caribbean North-Africa

Collinearity Statistics Collinearity Statistics Collinearity Statistics

arablandpw 0,67 1,48 arablandpw 0,17 5,87 arablandpw 0,31 3,23 cappw 0,65 1,53 cappw 0,26 3,79 NatResource 0,43 2,30 NatResource 0,70 1,43 NatResource 0,57 1,76 schoolyears 0,39 2,54 schoolyears 0,49 2,04 schoolyears 0,17 5,79 sw 0,54 1,86

sw 0,50 2,01 sw 0,03 28,61 swXarablandpw 0,34 2,92

swXarablandpw 0,94 1,06 swXarablandpw 0,06 16,62 swXnatresource 0,51 1,98 swXnatresource 0,77 1,29 swXnatresource 0,19 5,33 swXschoolyears 0,51 1,98 swXcappw 0,73 1,38 swXcappw 0,43 2,32 FemaleinWorkforce 0,61 1,64 swXschoolyears 0,39 2,57 swXschoolyears 0,48 2,08 M2/GDP 0,43 2,30 FemaleinWorkforce 0,57 1,74 FemaleinWorkforce 0,26 3,82 Inflation 0,61 1,64 M2/GDP 0,67 1,50 M2/GDP 0,39 2,56 Polity2 0,45 2,21 Inflation 0,95 1,06 Inflation 0,72 1,40 DummyGross 0,82 1,22 Polity2 0,68 1,48 Polity2 0,28 3,54 DummyIncome 0,92 1,09 DummyGross 0,68 1,47 DummyGross 0,58 1,72 DummyHousehold 0,88 1,14 DummyIncome 0,66 1,51 DummyIncome 0,32 3,11 Dependent Variable: Ginitimes100 DummyHousehold 0,94 1,06 DummyHousehold 0,39 2,54

Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

(17)

17 Table A.7.2.4 Variance Inflation Factors with intolerable variables left out.

East-Asia Pacific South-Asia

Tolerance VIF Tolerance VIF

(18)

18 Table A.8.1, Regression results South-Asia without GDP per Capita variable due to

collinearity concerns.

South-Asia Unstandardized Coefficients t Sig. Collinearity Statistics B Tolerance VIF (Constant) 3453,06 23,37 0,00 SW 330,91 2,88 0,00 0,10 9,57 SWxGDPcap -0,09 -1,64 0,10 0,12 8,68 FemaleinWorkforce -5,94 -1,84 0,07 0,52 1,92 M2/GDP -6,87 -3,94 0,00 0,52 1,92 Inflation 3,90 0,96 0,34 0,86 1,16

Real Interest Rate 2,97 0,82 0,41 0,92 1,09

Polity2 1,41 0,59 0,56 0,69 1,45

DummyGross -51,02 -0,99 0,32 0,62 1,61

DummyIncome 597,36 8,49 0,00 0,34 2,92

DummyHousehold 172,15 2,76 0,01 0,42 2,37

Dependent Variable: Ginitimes100

(19)

19 Table A.8.2 Regression results East-Asia & Pacific without interaction term between

Sachs-Warner and Capital

per Worker due to collinearity concerns

1. HC= Av Years

schooling B t Sig. 2. HC= NOEDs B t Sig.

(Constant) 3321,17 23,35 0,00 (Constant) 3342,10 23,48 0,00 arablandpw 178,87 2,67 0,01 arablandpw 179,03 2,64 0,01 cappw -0,01 -2,67 0,01 cappw -0,02 -2,95 0,00 NatResource 3,48 2,78 0,01 NatResource 3,30 2,75 0,01 schoolyears 3,33 0,32 0,75 noed 0,35 0,33 0,74 sw 69,80 1,63 0,10 sw 72,75 1,71 0,09 swXarablandpw -65,81 -0,75 0,45 swXarablandpw -75,59 -0,86 0,39 swXnatresource -0,12 -0,05 0,96 swXnatresource 0,49 0,21 0,84 swXschoolyears -30,28 -1,39 0,16 swXnoed 1,96 0,90 0,37 FemaleinWorkforce 2,63 1,07 0,29 FemaleinWorkforce 2,07 0,84 0,40 M2/GDP 2,94 6,05 0,00 M2/GDP 2,86 5,97 0,00 Inflation -0,06 -0,18 0,86 Inflation -0,11 -0,34 0,74 Polity2 9,18 4,40 0,00 Polity2 9,09 4,36 0,00 DummyGross 133,95 1,72 0,09 DummyGross 136,64 1,75 0,08 DummyIncome 271,99 4,21 0,00 DummyIncome 273,17 4,22 0,00 DummyHousehold 392,82 7,63 0,00 DummyHousehold 391,85 7,59 0,00 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

3. HC= BASEDs 4. HC=SKILD B t Sig. B t Sig. (Constant) 3398,12 24,01 0,00 (Constant) 3276,40 23,23 0,00 arablandpw 206,50 3,01 0,00 arablandpw 167,19 2,54 0,01 cappw -0,02 -4,58 0,00 cappw -0,01 -2,10 0,04 NatResource 3,27 2,79 0,01 NatResource 3,95 3,31 0,00 based -3,09 -1,76 0,08 skilld 4,53 1,88 0,06 sw 64,13 1,44 0,15 sw 56,98 1,39 0,16 swXarablandpw -87,12 -0,98 0,33 swXarablandpw -86,87 -0,99 0,32 swXnatresource 0,88 0,38 0,71 swXnatresource -0,31 -0,13 0,90 swXbased 0,88 0,24 0,81 swXskild -10,88 -2,48 0,01 FemaleinWorkforce 1,16 0,48 0,63 FemaleinWorkforce 3,55 1,45 0,15 M2/GDP 2,83 5,88 0,00 M2/GDP 2,83 5,98 0,00 Inflation -0,21 -0,66 0,51 Inflation 0,04 0,13 0,90 Polity2 8,94 4,31 0,00 Polity2 10,02 4,73 0,00 DummyGross 135,34 1,73 0,08 DummyGross 134,29 1,72 0,09 DummyIncome 272,41 4,21 0,00 DummyIncome 277,32 4,30 0,00 DummyHousehold 393,84 7,63 0,00 DummyHousehold 384,23 7,46 0,00 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

(20)

20 Table A.8.3, Regression results South-Asia without interaction term between Sachs-Warner

and Arable Land

per Worker due to collinearity concerns

1. HC= Av Years

(Constant) 3477,77 21,04 0,00 (Constant) 3440,19 20,41 0,00 arablandpw -35,59 -0,26 0,80 arablandpw -31,35 -0,22 0,82 cappw -0,02 -2,47 0,01 cappw -0,02 -2,08 0,04 NatResource -2,19 -0,60 0,55 NatResource -3,67 -1,00 0,32 schoolyears 41,79 2,43 0,02 noed -3,00 -1,50 0,13 sw 100,40 1,01 0,31 sw 138,15 1,33 0,18 swXnatresource -3,65 -0,56 0,57 swXnatresource -2,04 -0,30 0,76 swXcappw 0,01 0,31 0,76 swXcappw 0,00 -0,06 0,95 swXschoolyears -49,65 -1,64 0,10 swXnoed 2,51 0,76 0,45 FemaleinWorkforce -6,02 -1,38 0,17 FemaleinWorkforce -5,83 -1,32 0,19 M2/GDP -6,69 -3,35 0,00 M2/GDP -6,73 -3,33 0,00 Inflation 3,51 0,84 0,40 Inflation 2,42 0,57 0,57 Polity2 -3,17 -0,90 0,37 Polity2 0,18 0,05 0,96 DummyGross -66,01 -1,26 0,21 DummyGross -68,58 -1,29 0,20 DummyIncome 636,43 8,91 0,00 DummyIncome 630,62 8,74 0,00 DummyHousehold 183,31 2,87 0,00 DummyHousehold 177,00 2,75 0,01 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

(21)

21 Table A.8.4, Regression results Latin-America & Caribbean without interaction term between

Sachs-Warner

and Capital per Worker for comparability purposes with East-Asia & Pacific

1. HC= Av Years

(Constant) 4451,83 49,36 0,00 (Constant) 4451,2 49,69 0,00 arablandpw 26,89 1,57 0,12 arablandpw 25,98 1,52 0,13 cappw 0,00 1,52 0,13 cappw 0,00 1,57 0,12 NatResource -2,06 -5,39 0,00 NatResource -2,08 -5,42 0,00 schoolyears -20,29 -2,99 0,00 noed 2,16 2,91 0,00 sw 33,45 1,38 0,17 sw 40,53 1,70 0,09 swXarablandpw 52,66 1,39 0,16 swXarablandpw 58,12 1,54 0,12 swXnatresource 0,04 0,05 0,96 swXnatresource 0,00 0,00 1,00 swXschoolyears 23,01 1,99 0,05 swXnoed -1,91 -1,49 0,14 FemaleinWorkforce 0,51 0,33 0,74 FemaleinWorkforce 0,81 0,53 0,6 M2/GDP -2,73 -3,41 0,00 M2/GDP -2,73 -3,41 0,00 Inflation 0,04 2,43 0,02 Inflation 0,04 2,34 0,02 Polity2 -3,44 -2,24 0,03 Polity2 -3,50 -2,27 0,02 DummyGross 137,85 1,58 0,11 DummyGross 130,87 1,50 0,13 DummyIncome 648,78 9,83 0,00 DummyIncome 643,59 9,75 0,00 DummyHousehold -178,06 -4,57 0,00 DummyHousehold -176,66 -4,54 0,00 Dependent Variable: Ginitimes100 Dependent Variable: Ginitimes100

(22)

22 Table A.9.1 Kurtosis and Skewness for Regressions 9.1

Entire sample East-Asia & Pacific South-Asia

Kurtosis Skewness Kurtosis Skewness Kurtosis Skewness

sw -1,84 -0,20 -1,64 -0,64 0,70 1,49 GDPcap 5,31 1,84 2,56 1,71 2,46 1,08 swxGDPcap 4,58 1,82 1,37 1,33 5,62 2,26 FemaleinWorkforce -0,55 -0,22 -1,58 0,00 -0,07 1,05 M2/GDP 2,68 1,56 -0,80 0,31 -1,19 -0,32 Inflation 10,86 2,93 -0,54 0,49 1,51 0,51

Real Interest Rate 6,15 0,57 -0,77 -0,04 0,04 -0,25

Polity2 -1,64 -0,12 -0,91 0,66 0,94 -1,54

DummyGross 0,30 -1,52 4,65 -2,55 -2,06 -0,31

DummyIncome -1,94 -0,28 -0,75 -1,13 -1,46 0,81

DummyHousehold 0,88 1,69 -1,92 0,39 -0,55 1,22

Middle-East &

North-Africa Sub-Saharan Africa

Latin-America & Caribbean

sw -1,09 -0,99 -1,60 0,57 -1,07 -0,80 GDPcap 0,83 -1,02 10,75 3,07 1,33 0,84 swxGDPcap -1,89 -0,34 6,05 2,56 0,04 0,46 FemaleinWorkforce 0,29 -0,34 -0,64 -0,45 -0,39 0,40 M2/GDP -0,80 0,74 2,53 1,40 0,45 0,53 Inflation 1,08 1,29 3,61 1,97 7,35 2,17

Real Interest Rate 0,54 -0,66 2,85 -1,52 2,78 0,63

Polity2 -0,01 0,87 -0,17 1,00 0,56 -1,36

DummyGross -0,76 -1,19 -1,62 -0,67 6,91 -2,96

DummyIncome . . 1,21 1,78 1,41 -1,84

(23)

23 Table A.9.2 Kurtosis and Skewness for Regressions 9.2

Entire sample East-Asia & Pacific South-Asia

sw -1,86 0,08 sw -0,04 -1,37 sw 3,29 2,06

arablandpw 1,64 1,05 arablandpw -1,62 -0,11 arablandpw -1,14 -0,36 cappw -0,36 0,81 cappw 1,65 0,90 cappw -0,59 1,03 NatResource 0,44 -0,03 NatResource 2,59 -0,83 NatResource -1,33 0,14 noed -0,39 -0,01 noed -0,60 -0,19 noed -0,83 -0,26 based -0,19 0,11 based 1,86 -1,21 based -0,92 0,45 skilld -0,13 0,55 skilld -0,85 0,66 skilld -0,73 -0,34 schoolyears 0,04 -0,15 schoolyears -0,94 0,00 schoolyears -0,03 -0,69 swXarablandpw 2,12 0,16 swXarablandpw -0,08 -0,67 swXarablandpw 4,54 -1,99 swXnatresource 1,92 -1,06 swXnatresource 0,24 0,50 swXnatresource 3,05 -1,83 swXcappw 1,25 0,73 swXcappw -0,78 -0,09 swXcappw 0,99 -1,35 swXschoolyears -0,09 0,79 swXschoolyears -0,97 0,06 swXschoolyears -0,08 0,60 swXnoed 0,47 -0,82 swXnoed -0,15 -0,72 swXnoed 1,84 -0,59 swXbased 1,60 0,99 swXbased -1,15 -0,36 swXbased 2,45 0,65 swXskild 0,79 1,01 swXskild 1,47 1,50 swXskild -0,27 0,31 FemaleinWorkforce -0,53 0,19 FemaleinWorkforce -1,76 -0,50 FemaleinWorkforce -1,11 0,49 M2/GDP 2,88 1,34 M2/GDP -0,63 0,55 M2/GDP -1,43 0,00 Inflation 9,08 2,67 Inflation -0,70 0,55 Inflation 1,15 0,66 Polity2 -1,04 -0,73 Polity2 -0,42 -0,41 Polity2 5,85 -2,59 DummyGross 0,42 -1,55 DummyGross . . DummyGross -2,14 0,15 DummyIncome -1,56 -0,67 DummyIncome 1,67 -1,87 DummyIncome -1,73 0,63 DummyHousehold -0,90 1,06 DummyHousehold 1,67 -1,87 DummyHousehold -1,46 0,81

Middle-East & North-Africa Sub-Saharan Africa Latin-America & Caribbean

sw -1,74 0,47 sw -2,13 0,04 sw -1,81 -0,19

arablandpw -0,31 -0,19 arablandpw -0,75 0,81 arablandpw 1,79 0,99 cappw -3,73 0,40 cappw -0,38 0,87 cappw -0,94 0,41 NatResource 1,88 1,50 NatResource 0,07 1,35 NatResource -0,40 -0,26

noed -2,37 0,17 noed -1,06 0,37 noed -0,52 -0,08