The effect of the World Bank's loans on human development

Abstract

This research is conducted to explain the effect of IDA and IBRD loans on HDI given political risk and bank lending factors. In order to reach his objective, the researcher analyzed data for 22 developing countries that is available on Euromoney 94 and World bank 93 annual report. The developing countries are divided into four categories as follows: The Latin American countries category is composed of Bolivia Honduras, Paraguay, El Selvador, Costa Rica, Dominican Republic and Ecuador. It is characterized by having the highest HDI94 average score amounting to 0.64 compared to an average score of 0.508 for the African countries, 0.605 for the Asian countries and 0.4 1 for the only Australasian country. The African countries category is composed of Botswana, Ghana, Kenya, Lesotho, Mauritius, Nigeria and Zimbabwe. . It is characterized by not having ranked first in any of the sample characteristics. The Asian countries category is composed of China, India, Pakistan, Philippines, Sri Lanka, Thailand and Turkey. It is characterized by having taken the highest advantage of IDA loans amounting to $33,838.9 millions followed by $6,145.2 millions for the African countries category, $1.382.8 millions for the Latin American countries category and $113.2 millions for the Australasian country category. The Asian category has also taken the highest advantage of IBRD loans amounting to $61, 61704 millions. The African category has been given $9,285.6 followed by $5,242.5 given to the Latin American category. Five hundreds and thirty one millions of USD is the Australasian category's share of the IBRD loans. The Australasian country category is composed of only Papa New Guinea which is characterized by having the strongest direct access to bank lending. The total amount of bank loans given to this country is $5 millions, followed by $1.12 millions given to the Asian category $730,000 is the African category's share as opposed to $0.59 million for the Latin American countries. Considering the effect of IDA on HDI via bank lending and political risk, the researcher has found that a negative relationship exists between these two variables keeping the effect of other variables constant. This might be reasoned on the basis of the corruption that is characterized by the developed countries. The relationship between political risk and HDI is positive which is acceptable because the better a country is on the political risk score, the better the rank on HDI. So, bank lending which is positively related to the political risk score, leads to better HDI. The R square is equal to .77947 which is highly significant indicating that a relationship exist between the dependent and independent variables. . The negative relationship existing between IDA and HDI is explained as follows: the larger the amount of IDA loans for a specific developing country within the sample, the lower is the HDI score going to be for that country. Some of the reasons, as noted earlier, might be attributed to corruption, which can not be declared as a theory in this thesis before it is tested on a certain representative sample. So, from this perspective, the researcher recommends that future researchers test whether corruption is one of the independent variables leading to a negative relationship between IDA and HDI. Other points of recommendation also include retesting the same subject after a certain period of time (two or three years) since the NDU statistical unit could be directly connected to any source of information in the world through the introduction of the INTERNET system. Therefore, the researcher will have direct access to information from the necessary and required source. Other researchers can also test the change in HDI depending on other variables than IDA or IBRD. They might test the effect Foreign Direct Investment (FDI) on HDI, for example.