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The results of the regression are demonstrated in table 2. The coefficient of male is 0.011. This indicates that the number of doctor visits increases if the individual is male by 0.011. The value is not statistically significant at 10, 5 and 1 percent level of significance since the probability is greater than the critical values in each of the alpha value.
The regression results are illustrated in the table 3 in the appendix. The male coefficient is 14.89. This coefficient is positive which indicates that males spend 14.89 more on private medical services than the females. The value is statistically significant at the 1 percent level of significance since the probability value is very low. This means that there statistical significance that the level of private expenditure on medical services is highly influenced by gender.
The coefficient of number of visits to the doctor in the past years is -0.562. This has been indicated in table 4 below. The coefficient is negative which indicates that there are an inverse relation between the number of visits to the doctor in the past years and health status. When the endogenous variable increases by one unit, the health status will decline by 0.562 units. The coefficient is statistically significant at 1 per cent level of significance indicating that the number of visits to the doctor in the past years is a good indicator of changes in health status.
A casual interpretation exists when there is a cause and effect reaction on the regression results (Wayne A. Woodward, 2011). This means that there is a two way impact of the variables. In this case, no casual interpretation exists. This is because the number of doctor visits in the past affects the present health status negatively and on the other hand, health status in the present cannot affect the number of doctor visits in the past.
Male: The coefficient of the male is -3.987. This means that when an individual is male, the health status
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