# A comparison of happiness between India and South Africa

The previous sections discussed results for happiness and life satisfaction in India and South Africa when each country was considered in isolation. This section turns to a comparison of happiness between the two countries in the context of a model in which the happiness equation is estimated on data pooled across India and South Africa. Within this pooled dataset, the variable C was used to define the respondents’ country: for N respondents, indexed i = 1, . . . , N, С, = 1 if respondent i was from India and C, = 2 if respondent i was from South Africa.

Following this, every component of the vector of determining variables, x, in the happiness equation, was allowed to interact with the country variable, C:

If, for example, education is a component of the vector x then, in equation (2.3), the effect of a particular educational achievement on happiness would be contingent on the respondent’s country: the same educational level could affect happiness differently depending on whether the respondent was Indian or South African. Within the context of this “interaction” model, it is possible to test whether the inter-country difference in the effect of a particular variable category (say, university education) on happiness was significantly different from zero.

Table 2.5 shows the results of comparing the PPs of being happy between India and South Africa. The first row of this table shows that the PP of being happy, computed over the 16,879 respondents in the pooled sample, was 84.2% for India and 81.1% for South Africa. As discussed earlier, these PPs were computed by, first, assuming that all the 16,879 respondents were Indian and, second, by assuming they were all South African, the values of the other variables remaining unchanged, at their observed sample values, between these two scenarios. Thus, the two PPs, 84.2% and 81.1%, were entirely the product of a “country effect” since nothing else was altered between the two scenarios. The statistical significance of the difference between these two probabilities could be tested by dividing the difference by its standard error to arrive at the associated г-value: the г-value of 3.4 suggested that the PP of being happy was significantly higher in India than in South Africa.

The next two rows in Table 2.5, under the rubric Social Group, compare the PPs of being happy of, respectively, dominant and subordinate group persons in India and South Africa. The two PPs for the dominant group - 85.8% and 89% for, respectively, India and South Africa - were computed by regarding all the 16,879 respondents as from the dominant group (i.e., FC if they were Indian and Whites if they were South African) and then, first, assuming

 Predicted Probability of Being Very or Quite Happy India South Africa Difference Standard Error z -Value All Persons 0.842 0.811 -0.030»* 0.009 -3.4 Social Group Dominant (FC/Whites) 0.858 0.890 0.032** 0.015 2.2 Subordinate (non-FC/non- Whites) 0.839 0.797 -0.042** 0.010 -4.3 Gender Male 0.843 0.801 -0.042** 0.010 -4.1 Female 0.840 0.823 -0.017 0.012 -1.4 Friends Not Very/At All Important 0.817 0.791 -0.026* 0.015 -1.7 Rather Important 0.855 0.823 -0.033** 0.011 -3.0 Very Important 0.843 0.813 -0.030** 0.011 -2.6 Religion Not Very/At All Important 0.804 0.783 -0.021 0.018 -1.2 Rather Important 0.829 0.814 -0.015 0.013 -1.1 Very Important 0.854 0.816 -0.038** 0.010 -3.8 Health (self-assessed) Good/Very Good 0.943 0.894 -0.048** 0.009 -5.2 Fair 0.862 0.830 -0.032** 0.012 -2.7 Poor 0.654 0.661 0.007 0.019 0.4 Age 15-30 Years 0.799 0.813 0.014 0.013 1.0 30-45 Years 0.857 0.800 -0.057** 0.011 -5.0 45-60 Years 0.868 0.814 -0.054** 0.014 -3.8 60+ Years 0.859 0.847 -0.012 0.023 -0.5 Marital Status Married/Living Together 0.848 0.821 -0.028** 0.009 -3.0 Divorced/Separated/ Widowed 0.839 0.796 -0.043 0.028 -1.6 Single Never Married 0.828 0.796 -0.032 0.021 -1.5 Number of Children None 0.866 0.813 -0.053** 0.016 -3.4 1-2 0.853 0.814 -0.039** 0.012 -3.1 3+ 0.810 0.807 -0.004 0.014 -0.3 Education Elementary Education (partial/complete) 0.814 0.804 -0.010 0.013 -0.8

{Contniued)

34 Subjective well-being

Table 2.5 (Continued)

 Predicted Probability of Being Very or Quite Happy India South Africa Difference Standard Error z - Value Secondary Education Vocational 0.882 0.825 -0.058 0.015 -3.9 Secondary Education University 0.845 0.812 -0.033 s* 0.013 -2.5 University Education (partial/complete) 0.848 0.809 -0.039s'* 0.019 -2.0 Economic Status Full-Time Employed 0.817 0.833 0.016 0.015 1.1 Part-Time Employed 0.837 0.783 -0.053 s* 0.021 -2.6 Self-Employed 0.866 0.809 -0.058 s* 0.020 -2.8 Housewife 0.879 0.817 -0.062 s* 0.018 -3.5 Student 0.862 0.848 -0.014 0.019 -0.8 Unemployed 0.816 0.768 -0.048 s* 0.019 -2.6 Retired/Other 0.873 0.845 -0.028 0.021 -1.4 Social Class Upper/Upper Middle 0.891 0.876 -0.016 0.013 -1.2 Lower Middle 0.877 0.850 -0.027[1] 0.011 -2.4 Working Class 0.825 0.840 0.016 0.014 1.1 Lower Class 0.791 0.709 -0.082[1] 0.018 -4.6

Source: Own calculations from WVS Longitudinal.

Note: Logit estimates based on 16,879 observations: 5,580 from India and 11,299 from South Africa. FC = Forward Caste.

significant difference between the two countries in the predicted likelihood of women being happy. In terms of social relations (as represented by the importance of friends), the PP of happiness was greater in India than in South Africa for all three categories of importance - not at all important, somewhat important, and very important. In terms of religiosity, the PP of happiness was greater in India than in South Africa for those for whom religion was very important; there was no significant difference between the countries for the two other categories of importance - not at all important and rather important.

Health and education both offered better prospects for happiness in India than in South Africa. The PP of being happy was greater in India than in South Africa for persons in good health (Table 2.5: 94.3% vs. 89.4%) and in fair health (Table 2.5: 86.2% vs. 83%), but there was no significant difference between India and South Africa in the PP of being happy for those in poor health. In respect of education, except for those whose highest educational attainment was elementary education (or less), the PP of being happy, for persons at every educational level, was greater in India than in South Africa.

Being married had a greater positive effect on happiness in India than in South Africa - the PP of being happy for married persons was significantly higher in India than in South Africa. With respect of the other marital states - divorced/separated/widowed or never married - there was, however, no significant difference between the two countries in their PPs of being happy. Not having children or not having more than two children had a greater positive effect on happiness in India than in South Africa: the PP of being happy for childless persons or persons with no more than two children was significantly higher in India than in South Africa. For persons with three or more children, there was, however, no significant difference between the two countries in their PPs of being happy.

The very young and the very old were as likely to be happy in India as in South Africa - there was no significant difference between India and South Africa in the PP of being happy for those between the ages of 15 and 30 years or those whose ages were 60 years or older. For the intermediate age groups (30-45 and 45-60), however, the PP of being happy was significantly higher in India than in South Africa.

While there was no difference between the two countries in the PP of being happy for those in full-time employment, this probability was significantly higher in India than in South Africa for four categories of economic status: part-time employees, the self-employed, housewives, and the unemployed. In terms of social class, the PP of being happy for those in the lowest social class and in the lower middle class was significantly higher in India than in South Africa (Table 2.5: 79.1% vs. 70.9% and 87.7% vs. 85%, respectively), but for the other two social classes - upper/upper middle and working - there was no significant difference between the countries in this probability.

• [1] Difference is significant at 5% level; * Difference is significant at 10% level. that they were all Indian and, second, by assuming they were all South African, the values of the other variables remaining unchanged, at their observedsample values, between these two scenarios. Thus, the two PPs, 85.8% and89%, were entirely the product of a “country effect”, underpinned by a dominant group base. The г-value of 2.2 suggested that the predicted probabilityof being happy for dominant group persons was significantly higher in SouthAfrica (where the dominant group was Whites) than in India (where the dominant group was the FCs). Conversely, the next row of Table 2.5 shows thatthe predicted probability of being happy for subordinate group persons - thatis, a “country effect”, underpinned by a subordinate group base - was significantly lower in South Africa (79.7%) than in India (83.9%). The predicted likelihood of men being happy was significantly higher inIndia than South Africa (Table 2.5: 84.3% versus 80.1%) but there was no
• [2] Difference is significant at 5% level; * Difference is significant at 10% level. that they were all Indian and, second, by assuming they were all South African, the values of the other variables remaining unchanged, at their observedsample values, between these two scenarios. Thus, the two PPs, 85.8% and89%, were entirely the product of a “country effect”, underpinned by a dominant group base. The г-value of 2.2 suggested that the predicted probabilityof being happy for dominant group persons was significantly higher in SouthAfrica (where the dominant group was Whites) than in India (where the dominant group was the FCs). Conversely, the next row of Table 2.5 shows thatthe predicted probability of being happy for subordinate group persons - thatis, a “country effect”, underpinned by a subordinate group base - was significantly lower in South Africa (79.7%) than in India (83.9%). The predicted likelihood of men being happy was significantly higher inIndia than South Africa (Table 2.5: 84.3% versus 80.1%) but there was no

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