Women who have sex at an early age have been argued to engage more in risky sexual activity and have been found to meet a higher risk of HIV infected. Therefore, to measure the effect the variable age at first intercourse is included in the analysis. Religion To measure the effect of religion, a dummy variable is being used. The dummy variable takes the value one if the respondent is catholic and zero otherwise. The reason for not including a dummy variable for each religion that exists within the country is because most of the respondents were Catholics or Protestants, only 0.43% of the respondents were Muslims and 1.03% belonged to other religions. Inequality To measure expenditure inequality, and test for the IIH, the Gini coefficient for each of the provinces is used. A Gini coefficient is a statistical measure of inequality and can take any value between zero and one, with zero implying total equality and one total inequality (Nilsson, 2009). According to the IIH, the relationship between inequality and the dependent variable, HIV status, is believed to be positive. Expenditures According to the RIH, the relationship between average expenditure and HIV status is believed to be negative. In order to measure expenditures, the logs of average expenditures of each province are included in the model. Male circumcision Men who are circumcised have been found to have a lower risk of being HIV infected than men who are not. Since risk of HIV infection is affected by the male women’s infection rate, a variable for the mean male circumcision in each province has been included in the analysis. Density Population density is often used as an indication of living standard and has previously been found to be negatively correlated with HIV prevalence. To measure population
Women who have sex at an early age have been argued to engage more in risky sexual activity and have been found to meet a higher risk of HIV infected. Therefore, to measure the effect the variable age at first intercourse is included in the analysis. Religion To measure the effect of religion, a dummy variable is being used. The dummy variable takes the value one if the respondent is catholic and zero otherwise. The reason for not including a dummy variable for each religion that exists within the country is because most of the respondents were Catholics or Protestants, only 0.43% of the respondents were Muslims and 1.03% belonged to other religions. Inequality To measure expenditure inequality, and test for the IIH, the Gini coefficient for each of the provinces is used. A Gini coefficient is a statistical measure of inequality and can take any value between zero and one, with zero implying total equality and one total inequality (Nilsson, 2009). According to the IIH, the relationship between inequality and the dependent variable, HIV status, is believed to be positive. Expenditures According to the RIH, the relationship between average expenditure and HIV status is believed to be negative. In order to measure expenditures, the logs of average expenditures of each province are included in the model. Male circumcision Men who are circumcised have been found to have a lower risk of being HIV infected than men who are not. Since women’s risk of HIV infection is affected by the male infection rate, a variable for the mean male circumcision in each province has been included in the analysis. Density Population density is often used as an indication of living standard and has previously been found to be negatively correlated with HIV prevalence. To measure population
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