AFR_1996_WDAAF_v01_M DDI_AFR_1996_WDAAF_v02_M

World Bank, Development Economics Research Group (DECRG)

2010-09-15 Nesstar Publisher DDI Document - Version 02 - (04/27/21) This version is identical to DDI_AFR_1996_WDAAF_v01_M but country field has been updated to capture all the countries covered by survey. Version 01 (September 2010) What Does Aid to Africa Finance ? 1970-1996 WDAAF 1996 AFR_1996_WDAAF_v01_M Shantayanan Devarajan, Andrew Sunil Rajkumar and Vinaya Swaroop 2010-09-15 Nesstar Publisher Development Research Group Macroeconomics - Indicators If a donor gives aid for a project that the recipient government would have undertaken anyway, then the aid is financing some expenditure other than the intended project. The notion that aid in this sense may be "fungible," while long recognized, has recently been receiving some empirical support. The paper "What Does Aid to Africa Finance?" focuses on Sub-Saharan Africa—the region with the largest GDP share of aid—and presents results that indicate that aid may be partially fungible, and suggests some reasons why. This database contains data used for the analysis. Burkina Faso Botswana Cameroon Congo, Dem. Rep. Ethiopia Ghana Kenya Liberia Lesotho Madagascar Mauritius Malawi Nigeria Sudan Eswatini Zambia Zimbabwe The database includes data from Botswana, Burkina Faso, Cameroon, Ethiopia, The Gambia, Ghana, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mauritius, Nigeria, Sudan, Swaziland, Zaire, Zambia, and Zimbabwe. Aggregate data [agg] The dataset includes the following: - Population - Infant mortality - Primary and secondary school enrollment - GDP per capita - Concessionary loans - Government expenditure Other [oth] Use of the dataset must be acknowledged using a citation which would include: - the Identification of the Primary Investigator - the title of the survey (including acronym and year of implementation) - the survey reference number - the source and date of download Example: Shantayanan Devarajan et al., World Bank.What Does Aid to Africa Finance? (WDAAF) 1970-1996. Ref. AFR_1996_WDAAF_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date]. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. What_does_aid_to_Africa_finance.NSDstat 471 50 Nesstar 200801 Country Code 471 0 Botswana 26 Burkina Faso 26 Cameroon 26 Ethiopia 26 Gambia, The 26 Ghana 26 Kenya 26 Lesotho 26 Liberia 26 Madagascar 27 Malawi 26 Mauritius 27 Nigeria 26 Sudan 26 Swaziland 26 Zaire 26 Zambia 27 Zimbabwe 26 Year 471 0 1970 1996 1970 18 1971 18 1972 18 1973 18 1974 18 1975 18 1976 18 1977 18 1978 18 1979 18 1980 18 1981 18 1982 18 1983 18 1984 18 1985 18 1986 18 1987 18 1988 18 1989 18 1990 18 1991 18 1992 18 1993 18 1994 18 1995 18 1996 3 agriculture as share of GDP 452 19 5.088 64.419 30.046 12.509 population 468 3 419000 111273000 14231716.607 19741536.395 infant mortality rate 468 3 16.08 200 106.199 37.733 primary school enrolment rate 441 30 13 136 77.077 28.541 secondary school enrolment rate 436 35 1 59 20.765 13.313 total grant disbursement, in 1995 US$ and per capita 468 3 0.452 245.165 36.064 32.687 total concessional loan disbursement, in 1995 US$ and per capita 468 3 -0.0425 174.477 17.773 18.136 total foreign aid disbursement, in 1995 US$ and per capita (=grtdsbp+grlndsbp) 468 3 0.452 269.789 53.837 43.401 total government expenditure, in 1995 US$ and per capita 309 162 7.17 1341.148 235.169 226.659 government expenditure on agriculture, in 1995 US$ and per capita 299 172 0.335 104.603 19.615 19.427 government expenditure on energy, in 1995 US$ and per capita 299 172 0 53.766 3.132 5.975 government expenditure on industry, in 1995 US$ and per capita 298 173 0 58.339 4.426 6.094 government expenditure on transport & communications, in 1995 US$ and per capita 298 173 0 172.427 21.453 23.883 government expenditure on education, in 1995 US$ and per capita 304 167 0.038 294.426 40.054 45.954 government expenditure on health, in 1995 US$ and per capita 304 167 0.0167 68.455 14.903 14.952 principal repayments, in 1995 US$ and per capita 468 3 -53.105 95.878 4.248 8.572 current government expenditure, in 1995 US$ and per capita 309 162 -2417.082 1105.499 155.068 269.432 capital government expenditure, in 1995 US$ and per capita 315 156 0.341 2604.66 90.915 282.687 GDP per capita, in 1995 US$ 446 25 19.097 3059.444 747.375 566.649 number of donors 446 25 4 27 18.72 4.301 concessionary loans to agriculture sector, in 1995 US$ and per capita 468 3 0 72.269 2.274 4.82 concessionary loans to energy sector, in 1995 US$ and per capita 468 3 0 43.756 1.551 3.415 concessionary loans to industry sector, in 1995 US$ and per capita 468 3 0 61.726 1.337 3.977 concessionary loans to transport & communications sector, in 1995 US$ and per ca 468 3 0 133.755 4.757 9.067 concessionary loans to education sector, in 1995 US$ and per capita 468 3 0 14.311 0.698 1.368 concessionary loans to health sector, in 1995 US$ and per capita 468 3 0 6.56 0.228 0.638 concessionary loans to other sectors, in 1995 US$ and per capita 468 3 0 97.64 7.973 11.114 first difference of variable grtdsbp 280 191 -41.689 135.789 0.926 15.126 first difference of variable grlndsbp 280 191 -49.617 77.239 0.398 13.035 first difference of variable aiddsbp 280 191 -60.118 136.04 1.325 19.765 first difference of variable totexpp 281 190 -202.417 207.451 2.938 52.356 first difference of variable agexpp 252 219 -52.542 38.634 0.173 9.226 first difference of variable enexpp 252 219 -22.259 23.694 0.0279 4.437 first difference of variable indexpp 252 219 -48.322 34.422 -0.201 5.368 first difference of variable tacexpp 251 220 -96.369 124.765 -0.0811 15.076 first difference of variable eduexpp 253 218 -35.796 51.461 1.162 10.936 first difference of variable hthexpp 253 218 -15.27 20.093 0.263 3.523 first difference of variable othexpp 249 222 -147.812 135.372 2.057 34.677 first difference of variable curexpp 257 214 -187.5 160.911 2.534 43.4 first difference of variable capexpp 258 213 -134.315 156.541 1.28 26.171 first difference of variable prirepp 280 191 -78.862 95.178 0.232 11.61 first difference of variable cnlnagp 280 191 -41.024 72.269 0.0676 5.739 first difference of variable cnlnenp 280 191 -19.996 22.176 0.0216 3.464 first difference of variable cnlninp 280 191 -36.248 34.368 0.0235 4.603 first difference of variable cnlntacp 280 191 -28.973 31.858 0.14 5.979 first difference of variable cnlnedup 280 191 -11.606 14.101 0.0427 1.753 first difference of variable cnlnhthp 280 191 -2.117 3.591 0.0237 0.453 first difference of variable cnlnothp 280 191 -55.153 70.817 0.0381 11.793