Review of Economics and Development Studies Vol.2, No 1, June 2016 55 Volume and Issues Obtainable at Center for Sustainability Research and Consultancy Review of Economics and Development Studies ISSN:2519-9692 ISSN (E): 2519-9706 Volume 2: Issue 1 June 2016 Journal homepage: www.publishing.globalcsrc.org/reads Socioeconomic and Demographic Factors Affecting Individual’s Life Satisfaction in Selected SAARC Countries: A Micro Data Analysis 1 Sofia Anwar, 2 Aisha Asif 1 Professor and chairperson, Department of Economics, Government College University Faisalabad, Pakistan, sofia_eco@gcuf.edu.pk 2 PhD Scholar, Department of Economics, Government College University Faisalabad, Pakistan aieshasif@gmail.com ARTICLE DETAILS ABSTRACT History Revised format: May 2016 Available online: Jun 2016 Life satisfaction is increasingly recognized as a significant dimension of wellbeing. Thus the main b of the objective study will be to explore the association among income, family composition, health, and religion over life satisfaction. In this effort, correlates of the life satisfaction for the SAARC countries Pakistan, India, and Bangladesh analyzed. Micro data from the World Values Survey (WVS) fourth wave (1999 to 2004) for Pakistan, India and Bangladesh was utilized comprising a wide range of information on political, social and cultural values of countries. The multinomial logistic regression was employed to examine the effects of various socioeconomic and demographic factors on life satisfaction. Health, income, shows significant positive factor in determining life satisfaction, however financial satisfaction is overpowered by religious faith especially in India and Pakistan. Employment had a positive impact on individual’s satisfaction in Pakistan and India. Gender, education has insignificant impact on life satisfaction in three countries. Age has insignificant effect on life satisfaction in Pakistan, while shows insignificant impact in India and Bangladesh. Preferences for democracy are associated with life satisfaction in India and Bangladesh. © 2016 The authors, under a Creative Commons Attribution- NonCommercial 4.0 Keywords Determinants of Life Satisfaction, World Values Survey, Pakistan, India, Bangladesh JEL Classification DO3; D60; I31 Corresponding author’s email address: sofia_eco@gcuf.edu.pk Recommended citation: Anwar, S. and Aisha, A. (2016). Socioeconomic and Demographic Factors Affecting Individual’s Life Satisfaction in Selected SAARC Countries: A Micro Data Analysis. Review of Economics and Development Studies, 2 (1) 55-68 DOI: https://doi.org/10.26710/reads.v2i1.124 1. Introduction Life satisfaction is increasingly recognized as a significant dimension of wellbeing (Stiglitz et al., 2009). The expressions ‘happiness’ and ‘Life Satisfaction’ are no explicit conceptions. In the social sciences happiness usually centered on the theme of subjective wellbeing of one’s life as a whole (Veenhoven, 1988). In this demarcation ‘Life Satisfaction’ is synonymous with ‘happiness’. Though some researchers suggested that these terms do tap diverse characteristics of subjective http://www.publishing.globalcsrc.org/reads mailto:sofia_eco@gcuf.edu.pk mailto:aieshasif@gmail.com mailto:sofia_eco@gcuf.edu.pk Review of Economics and Development Studies Vol.2, No 1, June 2016 56 wellbeing. 1 We however, don’t anticipate to enhance contribution to this debate in this research but assumed it might be supportive to mention some references to papers that do confer the explanation of both concepts 2 . This research will emphasis on micro level causes and will not evaluate macro level variables such as economic growth, income inequality, unemployment, inflation, political regime, welfare system, urbanization, safety, climate, and other factors that are generally considered in subjective wellbeing studies (Dolan et al., 2008). Thus the main purpose of the study will be to investigate about the association between family composition, income, health, and religion over life satisfaction. In this effort, correlates of the life satisfaction for the SAARC countries Pakistan, India, and Bangladesh analyzed. This research is based on the cross sectional World Value Survey (WVS) data for the fourth wave (1999-2004). Chapter 1 provides a concise and comprehensive introduction of life satisfaction in Pakistan, Bangladesh, and India. Chapter 2 discusses previous studies related to the concepts and topic. Chapter 3 explains the econometric techniques and methods used for the analysis. Chapter 4 evaluates the descriptive statistics and results of the study and then finally chapter 5 holds conclusions and policy recommendations for the problems addressed in the study. 2. Review of Literature What can we acquire from the prior literature? Evidently, there is a wide literature gap on the significance of country-level dynamics of life satisfaction, as many researchers do not exhibit adequate attention in observing the susceptibility of their empirical conclusions regarding the presence of additional factors to their regressions. That’s why, it is hard to conclude whether the described significances in a specific regression are really dependable and the factors are significantly associated to life satisfaction. Previous studies recommend a U- shaped curve among life satisfaction and age. Younger and older age group respondents tend to be satisfied than middle aged respondents (Ferrer-i-Carbonell & Gowdy, 2007). Other studies find a different shape of relation (Baird et al., 2010), but nevertheless, agree, that age is an important determinant of life satisfaction. There is no agreement among scientist whether gender is an important variable in life satisfaction and happiness studies. Some scientists find a significant relation (Alesina et al., 2004). Most of studies also consistently showed a strong impact of health on subjective wellbeing. Both physical and mental health has a strong positive effect on life satisfaction (Dolan et al., 2008). Marriage or close relations usually were associated with more life satisfaction. Many studies found positive relation between being in close relation and higher life satisfaction scores (Helliwell, 2003). According to several studies Separation with a partner due to divorce or death causes the lowest level of life satisfaction. Studies find that impact of having children may vary depending on other factors. If other factors are negative (low income, no partner, poor health), children may further lower the life satisfaction (Alesina et al., 2004; Frey and Stutzer, 2000). Haller and Hadler (2006) concluded that children’s influence is insignificant. Still other authors observed a positive relation between having children and life satisfaction (Angeles, 2010). There was no general consent on the influence of education on life satisfaction. Some studies revealed positive impact with increasing life satisfaction in higher education groups (Blanchflower & Oswald, 2004; Ferrante, 2009), others debated that education effect is associated to income and 1 Among them are Diener et al. (2010); Fischer (2009), McKennel and Andrews (1980) and Saris and Andreenkova (2001), 2 Life satisfaction is hypothesized by certain researchers as a subgroup of happiness (Davis and Fine-Davis 1991). Some others see happiness and life satisfaction as two distinct sections of Subjective well-being (Zapf et al. 1987). In the latter perspective, happiness is a psychological state formed by negative and positive experiences and events in life. Life satisfaction, on the other hand, is abstracted as more of a cognitive assessment that is rather reliant on social evaluations with compare to groups as well as on the individual’s expectations, hopes and desires . Review of Economics and Development Studies Vol.2, No 1, June 2016 57 health and therefore the latter should be controlled in order to determine the sole power of education (Bukenya et al., 2003; Degutis & Urbonavicius, 2013). There was no reasonable answer whether type of work is significant in determining life satisfaction. Few studies proposed that self-employed respondents have a tendency to be satisfied with life (Blanchflower & Oswald, 2008), however this connection clearly needs more examination. There was a consistent agreement that unemployment negatively affects life satisfaction (Brereton et al., 2008; Luechinger, 2010; Winkelmann & Winkelmann, 2004). Financial situation, Income of the household is one of the most often used variables, which impact on life satisfaction is measured. Most of the studies found that there is a positive correlation among individual income and life satisfaction (Clark et al., 2007; Dorn et al., 2007; Jagodzinski, 2010; Malesevic & Perovic, 2010; Verbic & Stanovnik, 2006). While others conclude that perception of financial status (or valuation of financial situation) has more predictive influence than actual income per se even if it is highly related to the latter (Haller & Hadler, 2006; Wildman & Jones, 2002). Still, there was a common agreement that income is a significant determinant and even if it is not used in analysis directly, it is used as a control variable when measuring effects of other factors. Trust in other people is related to higher life satisfaction by majority of studies. Helliwell (2003), Helliwell and Putnam (2004) analyzing World Values Survey data concluded that life satisfaction positively associated to trust level. Though the direction of relation is not always clear. Furthermore, even trust in public institutions such as government, police and legal system is also positively associated with higher life satisfaction (Helliwell & Putnam, 2004; Hudson, 2006). In this case it is also not clear whether trust is a predictor of life satisfaction or vice versa. Confirmation from numerous researches also supports the notion that greater life satisfaction is related to religiousness. This relation between life satisfaction and religion is found irrespective of their confession (Helliwell, 2006; Heliwell & Putnam, 2004). 3. Data and Methodology 3.1. Data Micro data from the World Values Survey (WVS) fourth wave (1999 to 2004) for Pakistan, India and Bangladesh was utilized comprising a wide range of information on political, social and cultural values of countries. The total sample size for three countries is 5502 observations (Pakistan (2000), India (2002), Bangladesh (1500). 3.2. Definition of Variables As there is an absence of detailed applied studies on life satisfaction in Pakistan, India and Bangladesh, thus the opted explanatory variables in the existing model are established on the prior research in other economies. Life satisfaction measured using the World Values Survey question; “All things considered, how satisfied are you with your life as a whole these days? Please use this card to help with your answer”. Answers are recorded on a 10-point scale (1= dissatisfied, 10 = satisfied), for the purposes of this analysis it has been re-scaled 1= Highly Satisfied, 2 = Quite satisfied and 3 = Dissatisfied. Independent Variables & their description used in the study for life satisfaction model are depicted in Table 1. 3.3. Methodology The multinomial logistic regression was employed to examine the effects of various socioeconomic and demographic factors on life satisfaction. Review of Economics and Development Studies Vol.2, No 1, June 2016 58  JPr (Y =a,b) Y = ln = α + β (Z)(a, b)j(a, b)i a, b ijPr (Y =c) j=1 .……………………………… (1) Where; Y= dependent variable while N= a, b, c are the three different categories of life satisfaction. Multinomial logit model estimates the log odd ratio like the logit model. pr(Life Satisfaction = Highly Satisfied) Ln = β + β X + β X .......+ β X 0 1 1 2 2 k kpr(Life Satisfaction = Dissatisfaction) ………………… (2) pr(Life Satisfaction =Quite Satisfaction) Ln = β + β X + β X .......+ β X 0 1 1 2 2 k kpr(Life Satisfaction = Dissatisfaction) ………………….. (3) The coefficients of logistic regression show, for a unit change (i>0 increase and i<0 decrease) in explanatory variable; changes in the log odds of dependent variable keeping all other variables constant (Hoffmann, 2004). The exponential coefficient of beta presents changes in the odd ratio of the dependent variable in a particular category of the reference category, related to one unit change of the subsequent explanatory variable. A positive sign of the coefficient indicates that the chances of that category are more than the reference category. Table1: Variables & their Description Used in the Study Variables (Abbreviation s) Description SHS Self-reported satisfaction level of individual with health status GEN Gender AGE Age in Years (( Divided in three different age groups in WVS) EDU Education in Years ( Divided into different education groups in WVS) EMP Employment status INC Income Level ( Divided in three Income Groups in WVS) ITMC Interaction Term Married Not Having, Having Child TMPL Thinking about Meaning and Purpose of Life PTP Perception about Trust on other People ITFSR Interaction Terms between Financial Satisfactions and Religiousness of a person SDEMO Self-reported level of satisfaction with democracy RPCA-10 Respondent ‘First Choice National Aspects (aims of the country in the coming ten years) Achieving economic growth as the "country's first priority in the next ten years” If a person agree with statement = 1, Otherwise = 0 Achieving economic stability as the "country's first priority in the next ten years": Fighting against rising prices "country's first priority in the next ten years" Fight against crime: "country's first priority in the next ten years" 4. Results and Discussions Review of Economics and Development Studies Vol.2, No 1, June 2016 59 Tables 2 and 3 present overall results of multinomial regression model. As estimated, health shows important positive factor in determining life satisfaction. Those who reported very good health and average health have a higher level of life satisfaction contrast to those who reports a poor health status. Previous researches showed a strong correlation between life satisfaction and psychological and physical health (Veenhoven, 1991). Results are consistent with the studies of (Blanchflower, 2008; Cid et al., 2007; Frey & Stutzer, 2002; Graham, 2008; Hussien & Heshmat, 2009). Gender has insignificant impact on life satisfaction in three countries. In the study of life satisfaction, gender considered as an insignificant factor (Easterlin, 2003; Cheah & Tang, 2013). Age has insignificant effect on life satisfaction in Pakistan and Bangladesh, while shows significant impact in India. Prior Studies pointed out that age was insignificant in determining life satisfaction as individuals would amend their goals and purposes as they matured (Diener et al., 1993; Cheah & Tang, 2013). As compere to both age has significant effect on dissatisfaction in India. If a person belongs to 30-49 mid-age group then he has .486 times chances to report unsatisfied. Some studies claimed that the relationship between age and satisfaction was U-shape, where individuals tended to feel happier in their very young age and old age compared to when they were in their mid-age (Blanchflower & Oswald 2007; Clark & Oswald, 1996; Clark, 2002; Helliwell, 2003; Frey & Stutzer, 2002). Review of Economics and Development Studies Vol.2, No 1, June 2016 60 Table 2: Socioeconomic and Demographic Variables Affecting the Probability of Highly Satisfied in Selected SAARC Countries (Dissatisfied= reference category) Independent Variables Pakistan India Bangladesh B Odd ratios B Odd ratios B Odd ratio s Intercept - 0.47 4 - 1.041 SHS Very Good Health=1 2.60 7* 13.55 7 1.674 * 5.333 1.41 9* 4.13 1 Good Health =2 1.55 2* 4.721 0.64^ 1.897 0.78 4* 2.19 Poor/Fair Health=3 Reference Category GEN Male=1 - 0.31 7 0.728 - 0.131 0.877 0.06 7 1.06 9 Female=0 Reference Category AGE 15-29 Years=1 - 0.16 1 0.851 - 0.722 ^ 0.486 - 0.29 9 0.74 2 30-49 Years =2 -0.14 0.869 - 0.676 ^ 0.509 -0.16 0.85 2 Above 50 Years = 3 EDU Lower Educated =1 - 1.41 9* 0.242 - 0.426 0.653 0.37 5 1.45 5 Educated =2 - 0.68 2 t 0.506 0.101 1.106 0.58 6 t 1.79 6 Highly Educated =3 Reference Category EMP Unemployed=1 - 0.19 1 0.826 - 1.096 * 0.334 - 0.10 9 0.89 6 Retired/Student Housewife=2 0.36 1 1.435 0.195 1.215 0.49 6 t 1.64 2 Employed=3 Reference Category INC Lower Income Group =1 - 1.16 7 t 0.311 0.033 1.034 - 1.50 5 0.22 2 Middle Income Group =2 0.11 8 1.125 - 0.279 0.756 - 0.83 7^ 0.43 3 High Income Group =3 Reference Category ITMC Married Having No Child=1 - 0.09 2 0.912 0.241 1.273 - 0.70 5 0.49 4 Married With 1-2 Kids =2 0.20 8 1.232 0.709 t 2.032 - 0.66 0.51 3 Review of Economics and Development Studies Vol.2, No 1, June 2016 61 7 t Married With 3-4 Kids=3 - 0.75 4^ 0.47 0.527 1.694 - 0.50 5 0.60 4 Married & Above 4 Kids=4 - 0.74 9 0.473 - 0.355 0.701 - 0.36 4 0.69 5 Single =5 Reference Category TMPL Thinking About Meaning & Purpose Of Life=1 0.59 4^ 1.812 0.75* 2.117 1.25 7 3.51 6 Never Think About It =2 Reference Category PTP Can Be Trusted=1 0.69 4* 2.002 0.061 1.063 - 0.28 2 0.75 5 Can’t Be Trusted =2 Reference Category ITFSR Financially dissatisfied and religious =1 - 2.09 5* 0.123 - 2.101 * 0.122 - 3.09 7 0.04 5 Financially Quite satisfied and religious =2 - 1.58 7* 0.205 0.913 * 2.492 - 0.40 3 0.66 8 Financially Highly Satisfied and religious =3 - 0.98 ^ 0.375 3.671 * 39.29 9 3.16 2 23.6 17 Financially Satisfied and Not Religious = 4 Reference Category SDEMO Satisfied=1 - 0.03 7 0.963 1.131 * 3.1 0.67 9^ 1.97 2 Not Satisfied =2 Reference Category RPCA- 10 A stable economy - 0.13 5 0.874 0.138 1.148 0.28 8^ 1.33 4 Achieving high level of economic growth 0.15 7 1.17 - 0.066 0.936 0.24 2 t 1.27 4 Fight against rising prices 0.22 5 1.252 - 0.173 0.841 0.07 8 1.08 2 Fight against crime - 0.05 7 0.944 - 0.226 ^ 0.798 0.07 7 1.08 Source: Author’s own calculation from World Value Survey (1999-2004). ^, *, t indicate coefficients are significant at 1, 5 and 10 percent level respectively Education increases the chance to being satisfied with life in Pakistan and India. If a person lower educated he has .242 and .62 times chances to being dissatisfied as compare to highly educated person in Pakistan and India respectively. If a person was middle educated then he had .50 times chances to being dissatisfied with life in Pakistan. In Bangladesh a person who fall in middle educated group has more chances to being highly satisfied than dissatisfied person. Some studies found a positive relationship between each additional level of education and life satisfaction and life satisfaction (Blanchflower & Oswald, 2004); while others found that middle level education is related to the highest life satisfaction (Stutzer, 2004). However, there is some evidence that education has more of a positive impact on low-income countries (Clark & Oswald, 1994; Clark et Review of Economics and Development Studies Vol.2, No 1, June 2016 62 al., 1996; Fahey & Smyth, 2004; Ferrer-i-Carbonell, 2005). Result is consistent with (Clark & Oswald, 1996; Frey & Stutzer 2002; Helliwell, 2003). People with higher income were more-happy in Pakistan, India and Bangladesh. Individuals with lower income levels had .31times and .56 times probability of being satisfied with life in Pakistan and Bangladesh respectively. Individuals with middle-income group had .75 times and .433 times chances to being dissatisfied with life in Pakistan and India respectively. Results were consistent with (Blanchflower & Oswald, 2004; Clark & Oswald, 1996; Easterlin 2001; Headey et al., 2008; Hussien & Heshmat, 2009; Stevenson & Wolfers, 2008). Studies conclude that changes in real incomes correlated with changes in life satisfaction (Clark et al., 2005; Ferrer-i-Carbonell, 2005; Ravallion & Lokshin, 2002; Senik, 2004; Winkelmann & Winkelmann, 1998). The models revealed that employment had a positive impact on individual’s satisfaction in Pakistan and India. Housewives, retired individuals or students appeared to be happier in Bangladesh. Unemployed person .51 times and 0.75 times chances to being in the group of dissatisfied from life than an employed person in Pakistan and India respectively. If a person is housewives, retired individuals or students then he had 1.64 times likelihood towards highly satisfaction with life in Bangladesh. Results were consistent with (Clark & Oswald, 1994; Hussien & Heshmat, 2009; Winkelmann & Winkelmann, 1998). Marital status and presence of children were also correlates of life satisfaction. Couples reported significantly higher satisfaction level than those who are not currently married or single (Blanchflower & Oswald, 2008; Di Tella et al., 2001; Frey & Stutzer, 2006). Parental satisfaction increases with the life satisfaction of their adult children also suggests that parents have selfless feelings towards children (Francesconi, 2002; Schwarze & Winklemann, 2005). Married couples having 1-2 children has more chances to dissatisfy with life rather a single person. These results are reliable with previous findings that having children reduces satisfaction. Simply adding the number of children in the household to the list of explanatory variables of life satisfaction will typically show negative or null effects (Di Tella et al. 2003; Alesina et al. 2004; Clark 2006). This well- known result has encouraged authors to conclude that having children makes people less happy. If married couples have more than three children then they have 2.42 times chances to dissatisfy with life. Clark & Oswald (2002) found a negative effect of third or higher order children on satisfaction. It was evident that a person who was ponder about meaning and purpose of life has 1.8 and 2.17 times chances to being satisfied rather who often or not thinking about it in Pakistan and India. People who often think about the meaning and purpose of life would be more satisfied with life (Duff and Ivlevs, 2012; Haller and Hadler, 2006). Likewise the people who trust on others, they were more satisfy in Pakistan and Bangladesh than a person who cannot trust on others and more likely to befall in the group of unsatisfied individuals. These results are contrary with previous findings (Helliwell, 2003; Helliwell & Putnam, 2004). Financial satisfaction and religiosity are important determinants of life satisfaction status of an individual. Faith on God or some super power positively influenced satisfaction. It is observed that as the financial satisfaction of a religious person increases the chances of being satisfy increases or vice versa. If a religious person was financially dissatisfied, then he was more satisfy than financially satisfied but not religious person in both India and Pakistan. Some studies concluded that religion ensures life satisfaction in stressful events like unemployment and divorce. Religious persons of all religious sects undergo less psychological destruction and harm from unemployment than the nonreligious (Clark & Lelkes, 2005). Table 3: Socioeconomic and Demographic Variables Affecting the Probability of Quite Satisfaction in Selected SAARC Countries Review of Economics and Development Studies Vol.2, No 1, June 2016 63 (Dissatisfied= reference category) Independent Variables Pakistan India Bangladesh B Odd ratio s B Odd ratios B Odd ratios Intercept 0.55 -0.18 -1.17 SHS Very Good Health=1 1.60* 4.99 0.81 * 2.24 -0.15 0.86 Good Health =2 0.91* 2.47 0.79 * 2.20 -0.01 0.99 Poor/Fair Health=3 Reference Category GEN Male=1 - 0.049 0.95 2 0.21 4 1.239 - 0.295 0.744 Female=0 Reference Category AGE 15-29 Years=1 0.39 1.47 -0.61 0.54 0.61 1.84 30-49 Years =2 0.056 1.05 7 - 0.55 2 0.576 0.352 1.422 Above 50 Years = 3 EDU Lower Educated =1 - 0.67^ 0.51 - 0.47 1^ 0.624 - 0.395 0.674 Educated =2 - 0.446 0.64 - 0.14 5 0.865 - 0.101 0.904 Highly Educated =3 Reference Category EMP Unemployed=1 - 0.355 t 0.70 1 -0.24 0.787 - 0.165 0.848 Retired/Student Housewife=2 - 0.191 0.82 6 - 0.02 9 0.971 0.418 t 1.519 Employed=3 Reference Category INC Lower Income Group =1 0.098 1.10 3 - 0.20 2 0.817 - 0.564 ^ 0.569 Middle Income Group =2 0.213 1.23 7 - 0.17 4 0.841 -0.31 0.733 High Income Group =3 Reference Category ITMC Married Having No Child=1 0.413 1.51 1 0.03 3 1.033 0.178 1.195 Married With 1-2 Kids =2 0.335 t 1.39 7 0.26 4 1.302 -0.23 0.795 Married With 3-4 Kids=3 0.068 1.07 0.13 3 1.142 - 0.158 0.854 Married & Above 4 Kids=4 0.226 1.25 4 - 0.60 4 0.547 - 0.155 0.856 Single =5 Reference Category TMPL Thinking About Meaning & Purpose Of Life=1 0.183 1.20 1 0.57 9* 1.784 - 0.081 0.922 Review of Economics and Development Studies Vol.2, No 1, June 2016 64 Never Think About It =2 Reference Category PTP Can Be Trusted=1 0.302 ^ 1.35 2 0.11 4 1.121 0.805 * 2.237 Can’t Be Trusted =2 Reference Category ITFSR Financially dissatisfied and religious =1 - 1.27* 0.28 - 0.68 6* 0.504 - 1.629 * 0.196 Financially Quite satisfied and religious =2 - 0.918 ^ 0.39 9 2.06 8* 7.909 1.837 * 6.276 Financially Highly Satisfied and religious =3 - 0.211 0.80 9 1.18 4^ 3.266 0.736 2.087 Financially Satisfied and Not Religious = 4 Reference Category SDEMO Satisfied=1 0.091 1.09 6 0.54 6* 1.726 0.407 ^ 1.502 Not Satisfied =2 Reference Category RPCA- 10 A stable economy 0.322 ^ 1.38 0.22 4* 1.251 0.165 1.18 Achieving high level of economic growth - 0.15^ 0.86 2 0.03 1.031 0.207 t 1.23 Fight against rising prices - 0.112 0.89 4 - 0.12 7 0.881 - 0.024 0.976 Fight against crime - 0.022 0.97 8 - 0.17 ^ 0.839 0.042 1.043 Source: Author’s own calculation from World Value Survey (1999-2004). ^, *, t indicate coefficients are significant at 1, 5 and 10 percent level respectively The widespread reviews on life satisfaction depicts that religiosity is a key aspect that influence life satisfaction of an individual. There is a positive association among life satisfaction and religiosity (Ellison, 1991; Robbins & Francis, 1996; Ferriss, 2002; Lelkes, 2006; Elliott & Hayward, 2009). Results indicate that satisfaction in financial conditions coupled with religious faith express profound results in attaining life satisfaction and peace of mind. But financial satisfaction is overpowered by religious faith especially in India and Pakistan. Few studies have explored the direct effect of holding a particular political view (Frey & Stutzer, 2000; Graham & Pettinato, 2001; Inglehart & Klingemann, 2000). It found that preferences for democracy are associated with life satisfaction in India and Bangladesh. Frey and Stutzer (2000) reported that direct democratic institutions in Switzerland (one of the wealthiest countries in the world) contribute positively to the life satisfaction. Regarding the plan of the country in the coming ten year, the model results show that those who choose high level of economic growth, fighting against high prices, achieving economic stability, fight against crime as first and second choice were not satisfied. This might be explain by the fact that many people in sample tend to feel dissatisfied with the government performance and they did not feel that there is any progress in the economy or growth in GDP. Results are consistent with (Hussien & Heshmat, 2009). V. Conclusion and Recommendations Review of Economics and Development Studies Vol.2, No 1, June 2016 65 The study revealed that life satisfaction not much influenced by demographic and Socio- economic factors such as age, gender and employment status found to have trivial effect on the life satisfaction level. The satisfaction with health status, satisfaction with life, satisfaction with financial situations, income level, satisfaction with democracy, had a substantial positive influence life satisfaction level. As the satisfaction with the health status had a positive effect on individual’s life satisfaction this suggests expansion and more investment in healthcare facilities in these developing countries. Marriage contributed positively to happiness, while separation and divorced did the opposite. This gives insight towards the power of family institution and its crucial role in psychological development of family members and social development of society. The results related to the education level showed that Life satisfaction was not associated with high level of education. Therefore, programs that emphasis on causing improved education structure alone might not be very effective in conveying more life satisfaction to the public rather awareness related to social ethics, methods of reducing the stresses should also be focused A positive association was found between income level and life satisfaction. Individuals with higher income levels were contented with their economic situations had more likelihood of being happy. But at the same time employed were dissatisfy .This suggests that policies to increase the job opportunities, encourage business environment are highly required but at the same time focus should be there to reduce work stress of employed persons. Increasing the income level is one of the first priorities on the government agenda. The development in infrastructure will increase public satisfaction with living conditions, quality of life and financial satisfaction and as a result, their life satisfaction. 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