World Development Report 1996. Statistical Annex
Table 1a. Basic indicators on population (RR)
Popul Area in Crop Past Crop Past Crop +Total
ation 1000s of land ure land ure PasturArea
sq. km GNP/cap as % as % in in in in
(mill.) mid- Dollars Area Area Ha/ Ha/ Ha/ Ha/
m.-1994 1994 1994 '93 '93 cap cap cap cap
Hong Kong 6.1 1 21,650 nna na 0.000 0.000 0.000 0.002
Singapore 2.9 1 22,500 2 0 0.000 0.000 0.000 0.002
Bangladesh 117.9 144 220 75 5 0.009 0.001 0.010 0.012
Mauritius 1.1 2 3,150 52 3 0.010 0.001 0.010 0.018
Korea, Rep. 44.5 99 8,260 21 1 0.005 0.000 0.005 0.022
***Netherlands 15.4 37 22,010 27 31 0.007 0.008 0.014 0.024
***Belgium 10.1 31 22,870 31 21 0.009 0.006 0.016 0.030
***Japan 125.0 378 34,630 12 2 0.004 0.001 0.004 0.030
Rwanda 7.8 26 80 47 18 0.016 0.006 0.022 0.034
India 913.6 3,288 320 57 4 0.021 0.001 0.022 0.036
Sri Lanka 17.9 66 640 29 7 0.011 0.003 0.013 0.037
El Salvador 5.6 21 1,360 35 29 0.013 0.011 0.024 0.037
Israel 5.4 21 14,530 21 7 0.008 0.003 0.011 0.039
Haiti 7.0 28 230 33 18 0.013 0.007 0.020 0.040
Trinidad and Tobago 1.3 5 3,740 24 2 0.010 0.001 0.010 0.040
***United Kingdom 58.4 245 18,340 27 46 0.011 0.019 0.031 0.042
***Germany 81.5 357 25,580 34 15 0.015 0.007 0.021 0.044
Jamaica 2.5 11 1,540 20 24 0.009 0.011 0.019 0.044
Philippines 67.0 300 950 31 4 0.014 0.002 0.016 0.045
Burundi 6.2 28 160 53 36 0.024 0.016 0.040 0.045
Vietnam 72.0 332 200 20 1 0.009 0.000 0.010 0.046
***Italy 57.1 301 19,300 41 15 0.022 0.008 0.030 0.053
***Switzerland 7.0 41 37,930 11 32 0.006 0.019 0.025 0.059
Pakistan 126.3 796 430 30 6 0.019 0.004 0.023 0.063
Dominican Republic 7.6 49 1,330 30 0 0.019 0.000 0.019 0.064
Nepal 20.9 141 200 17 15 0.011 0.010 0.022 0.067
Czech Republic 10.3 79 3,200 43 11 0.033 0.008 0.041 0.076
Moldova /f 4.4 34 870 67 11 0.052 0.009 0.060 0.077
Armenia /f 3.7 30 680 20 24 0.016 0.019 0.035 0.080
China 1,190.9 9,561 530 h 10 43 0.008 0.035 0.043 0.080
Poland 38.5 313 2,410 48 13 0.039 0.011 0.049 0.081
***Denmark 5.2 43 27,970 60 5 0.050 0.004 0.054 0.083
Nigeria 108.0 924 280 36 44 0.031 0.038 0.068 0.086
Thailand 58.0 513 2,410 41 2 0.036 0.002 0.038 0.088
Albania 3.2 29 380 26 15 0.023 0.013 0.037 0.090
Hungary 10.3 93 3,840 55 13 0.050 0.012 0.062 0.091
Slovak Republic 5.3 49 2,250 34 17 0.031 0.016 0.047 0.092
Portugal 9.9 92 9,320 34 9 0.032 0.008 0.040 0.093
***France 57.9 552 23,420 35 20 0.033 0.019 0.052 0.095
Indonesia 190.4 1,905 880 17 7 0.017 0.007 0.024 0.100
Slovenia 2.0 20 7,040 15 28 0.015 0.029 0.044 0.102
***Austria 8.0 84 24,630 18 24 0.019 0.025 0.044 0.104
Romania 22.7 238 1,270 43 21 0.045 0.022 0.067 0.104
Gambia, The 1.1 11 330 18 9 0.019 0.009 0.028 0.105
Guatemala 10.3 109 1,200 17 23 0.018 0.024 0.042 0.105
Kuwait 1.6 18 19,420 0 8 0.000 0.009 0.009 0.110
Azerbaijan /f 7.5 87 500 23 26 0.027 0.030 0.057 0.116
Ukraine /f 51.9 604 1,910 59 13 0.069 0.015 0.084 0.116
Croatia 4.8 57 2,560 25 22 0.030 0.026 0.056 0.118
Macedonia, FYR 2.1 26 820 26 25 0.032 0.031 0.062 0.122
Malawi 9.5 118 170 18 20 0.022 0.025 0.047 0.124
Greece 10.4 132 7,700 27 41 0.034 0.052 0.086 0.127
Uganda 18.6 236 190 34 9 0.043 0.011 0.055 0.127
Turkey 60.8 779 2,500 36 16 0.046 0.020 0.067 0.128
Georgia /f 5.4 70 560 14 29 0.018 0.037 0.055 0.129
***Spain 39.1 505 13,440 40 21 0.052 0.027 0.079 0.129
Bulgaria 8.4 111 1,250 39 17 0.051 0.022 0.074 0.131
Togo 4.0 57 320 45 4 0.064 0.006 0.069 0.142
Ghana 16.6 239 410 19 22 0.027 0.032 0.059 0.143
Myanmar 45.6 677 700 15 1 0.022 0.001 0.024 0.148
Costa Rica 3.3 51 2,400 10 46 0.015 0.071 0.087 0.155
Lesotho 1.9 30 720 11 66 0.017 0.103 0.120 0.156
Sierra Leone 4.4 72 160 8 31 0.013 0.051 0.064 0.163
Malaysia 19.7 330 3,480 15 0 0.025 0.000 0.025 0.168
Morocco 26.4 447 1,140 22 47 0.037 0.080 0.117 0.169
Lithuania /f 3.7 65 1,350 46 7 0.081 0.012 0.093 0.175
Egypt, Arab Rep. 56.8 1,001 720 3 5 0.005 0.009 0.014 0.176
Tunisia 8.8 164 1,790 32 23 0.059 0.043 0.102 0.186
Honduras 5.8 112 600 17 14 0.033 0.027 0.060 0.195
Ireland 3.6 70 13,530 13 68 0.026 0.134 0.159 0.197
Ethiopia 54.9 1,097 100 13 41 0.026 0.082 0.108 0.200
Uzbekistan /f 22.4 447 960 11 52 0.022 0.104 0.126 0.200
Belarus /f 10.4 208 2,160 30 15 0.060 0.030 0.090 0.200
Benin 5.3 113 370 17 4 0.036 0.008 0.044 0.211
Jordan 4.0 89 1,440 5 9 0.011 0.020 0.031 0.221
Mexico 88.5 1,958 4,180 13 39 0.029 0.086 0.115 0.221
Kenya 26.0 580 250 8 37 0.018 0.083 0.100 0.223
C“te d'Ivoire 13.8 322 610 12 41 0.028 0.096 0.123 0.233
Senegal 8.3 197 600 12 16 0.029 0.038 0.067 0.238
Tajikistan /f 5.8 143 360 6 25 0.015 0.062 0.077 0.249
Ecuador 11.2 284 1,280 11 8 0.028 0.020 0.048 0.253
Latvia /f 2.5 65 2,320 28 13 0.071 0.033 0.104 0.253
Iran, Islamic Rep. 62.6 1,648 1,940 11 27 0.029 0.071 0.100 0.263
Burkina Faso 10.1 274 300 13 22 0.035 0.060 0.095 0.271
Panama 2.6 76 2,580 9 20 0.026 0.058 0.084 0.289
Estonia /f 1.5 45 2,820 27 7 0.081 0.021 0.102 0.301
South Africa 40.5 1,221 3,040 11 67 0.033 0.202 0.235 0.301
Nicaragua 4.2 130 340 11 46 0.034 0.144 0.178 0.313
Colombia 36.3 1,139 1,670 5 39 0.016 0.122 0.138 0.313
Tanzania /e 28.8 945 140 4 40 0.013 0.131 0.144 0.328
Guinea-Bissau 1.0 36 240 12 38 0.042 0.131 0.173 0.346
United Arab Emirate 2.4 84 22,470 0 2 0.000 0.007 0.007 0.348
Yemen, Rep. 14.8 528 280 3 30 0.011 0.107 0.118 0.357
***United States 260.7 9,364 25,880 20 25 0.072 0.090 0.162 0.359
Zimbabwe 10.8 391 500 7 13 0.025 0.047 0.073 0.363
Cameroon 13.0 475 680 15 4 0.055 0.015 0.070 0.366
Guinea 6.4 246 520 3 22 0.011 0.084 0.096 0.383
Venezuela 21.2 912 2,760 4 20 0.017 0.086 0.103 0.431
Kyrgyz Republic /f 4.5 199 630 7 47 0.031 0.209 0.240 0.444
Madagascar 13.1 587 200 5 41 0.022 0.184 0.206 0.448
Lao PDR 4.7 237 320 3 3 0.015 0.015 0.030 0.499
***Sweden 8.8 450 23,530 7 1 0.036 0.005 0.041 0.512
Mozambique 15.5 802 90 4 56 0.021 0.290 0.311 0.518
Brazil 159.1 8,512 2,970 6 22 0.032 0.118 0.150 0.535
Chile 14.0 757 3,520 6 18 0.032 0.097 0.130 0.541
Peru 23.2 1,285 2,110 3 21 0.017 0.116 0.133 0.553
Uruguay 3.2 177 4,660 7 77 0.039 0.432 0.471 0.561
Finland 5.1 338 18,850 8 0 0.053 0.000 0.053 0.664
***Norway 4.3 324 26,390 3 0 0.022 0.000 0.022 0.747
New Zealand 3.5 271 13,350 14 51 0.109 0.396 0.504 0.776
Argentina 34.2 2,767 8,110 10 52 0.081 0.421 0.502 0.809
Zambia 9.2 753 350 7 40 0.057 0.327 0.384 0.818
Paraguay 4.8 407 1,580 6 54 0.051 0.459 0.510 0.850
Algeria 27.4 2,382 1,650 3 13 0.026 0.113 0.139 0.869
Oman 2.1 212 5,140 0 5 0.000 0.051 0.051 1.013
Papua New Guinea 4.2 463 1,240 1 0 0.011 0.000 0.011 1.103
Turkmenistan /f 4.4 488 1,270 3 74 0.033 0.820 0.853 1.108
Russian Federation 148.4 17,075 2,650 8 5 0.092 0.058 0.150 1.151
Saudi Arabia 17.8 2,150 7,050 2 56 0.024 0.676 0.700 1.208
Mali 9.5 1,240 250 2 25 0.026 0.326 0.352 1.302
Congo 2.6 342 620 0 29 0.000 0.385 0.385 1.327
Niger 8.7 1,267 230 3 7 0.044 0.102 0.145 1.451
Bolivia 7.2 1,099 770 2 24 0.030 0.364 0.395 1.518
Kazakstan /f 16.8 2,717 1,160 13 70 0.210 1.131 1.342 1.616
Central African Rep 3.2 623 370 3 5 0.058 0.096 0.154 1.926
Chad 6.3 1,284 180 3 36 0.061 0.735 0.796 2.042
Gabon 1.3 268 3,880 2 18 0.041 0.370 0.411 2.057
***Canada 29.2 9,976 19,510 5 3 0.171 0.102 0.273 3.411
Botswana 1.4 582 2,800 1 45 0.040 1.814 1.854 4.031
***Australia 17.8 7,713 18,000 6 54 0.259 2.334 2.594 4.323
Mauritania 2.2 1,026 480 0 38 0.000 1.759 1.759 4.630
Namibia 1.5 824 1,970 1 46 0.055 2.514 2.569 5.466
Mongolia 2.4 1,567 300 1 80 0.066 5.303 5.370 6.629
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e. In all tables, GDP and GNP cover mainland Tanzania
f. Estimates for economies of the former Soviet Union are preliminary,
their classification will be kept under review
[This table was processed by Dr. Robinson Rojas, from tables 9 and 11,
World Development Report, 1996]
==========================================
Low-income econom. 3,182.2 40,391 380 w 13 w 31 w0.017 0.039 0.056 0.127
Exc. China&India 1,077.7 27,543 360 w 8 w 30 w0.020 0.077 0.097 0.256
Middle-income econ.1,569.9 61,263 2,520 w 10 w 23 w0.039 0.090 0.129 0.390
Lower-middle-inc. 1,096.9 40,594 1,590 w 11 w 18 w0.041 0.067 0.107 0.370
Upper-middle-inc. 472.8 20,669 4,640 w 7 w 32 w0.031 0.140 0.170 0.437
Low- & middle-inc. 4,752.2 101,655 1,090 w 11 w 26 w0.024 0.056 0.079 0.214
Mid.East&N. Africa 266.7 11,021 1,580 w 6 w 24 w0.025 0.099 0.124 0.413
Sub-Saharan Africa 571.9 24,274 460 w 7 w 33 w0.030 0.140 0.170 0.424
East Asia&Pacific 1,734.7 16,367 860 w 12 w 34 w0.011 0.032 0.043 0.094
South Asia 1,220.3 5,133 320 w 45 w 10 w0.019 0.004 0.023 0.042
LatinAmerica&Carib 470.9 20,505 3,340 w 7 w 29 w0.030 0.126 0.157 0.435
Europe&CentralAsia 487.4 24,354 2,090 w 13 w 16 w0.065 0.080 0.145 0.500
High-income econ. 849.9 31,824 23,420 w 12 w 25 w0.045 0.094 0.139 0.374
World 5,601.3 133,478 4,470 w 11 26 w0.026 0.062 0.088 0.238
===================================================================
REGRESSION ANALYSIS:
Independent variable : Total Area per capita
Dependent variable : Cropland per capita
Regression Output:
Constant 0.0256
Std Err of Y Est 0.0314
R Squared 0.1884
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) 0.01457
Std Err of Coef. 0.00264
====================================================
Independent variable : Total Area per capita
Dependent variable : Pasture land per capita
Regression Output:
Constant -0.082
Std Err of Y Est 0.2757
R Squared 0.7846
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) 0.50573
Std Err of Coef. 0.02316
========================================================
Independent variable : Total Area per capita
Dependent variable : Crop plus Pasture land per capita
Regression Output:
Constant -0.056
Std Err of Y Est 0.2754
R Squared 0.7944
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) 0.5203
Std Err of Coef. 0.02313 20
=========================================================
Independent variable : Total Area per capita
Dependent variable : Income per capita
Regression Output:
Constant 5536.4
Std Err of Y Est 8479.7
R Squared 0.002
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) -361.4
Std Err of Coef. 712.061
=========================================================
Independent variable : Cropland per capita
Dependent variable : Income per capita
Regression Output:
Constant 4997.5
Std Err of Y Est 8480.4
R Squared 0.0018
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) 10273.2
Std Err of Coef. 21223.9
===========================================================
Independent variable : Pasture land per capita
Dependent variable : Income per capita
Regression Output:
Constant 5527.7
Std Err of Y Est 8468.3
R Squared 0.0046
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) -973.49
Std Err of Coef. 1245.44
================================================================
Independent variable : Cropland and Pasture land per capita
Dependent variable : Income per capita
Regression Output:
Constant 5543.1
Std Err of Y Est 8470.5
R Squared 0.0041
No. of Observations 133
Degrees of Freedom 131
X Coefficient(s) -897.32
Std Err of Coef. 1218.44
==============================================rrojas/1996
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