What Does Happiness Is Still Subjective?
As what previous researchers has discussed, happiness is still subjective. Every person may have different definition of happiness. This study was to examine and understand further the relationship between factors that have influence towards the happiness. Empirical evidences have determined many factors that are believed to have influence on happiness level and this study would focus on the commonly used factors. Income, education, and air pollution are the factors that were chosen and put to the test as to understand the relationship with the happiness level. The findings would be useful for some parties (e.g. governments, universities, and further researchers). Data were collected from various credible sources and ordinary least square
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This result is consistent with Howell and Howell (2008) where they said income is more significant in small and developing countries. However, income being insignificant in least-developed countries is contradicting with what Veenhoven (1996) found. Perhaps because they prioritize to feed and shelter their family over earning higher income. The fulfillment curve (Graph 1) might help to explain of why income being insignificant in developed countries. Majority of the people in rich nations have reached ‘enough’ point. Thus any extra spending from this point will become overconsumption and would have small contribution to the overall …show more content…
Followings are the limitations of the study which followed by the possible solutions that can be done, by further researchers on this area, to avoid them:
• The nature of this study is cross-sectional where it focuses on one particular time period. Thus, the scope is too narrow and results might only reflect that particular year. Further researchers should do more details analysis with wider scope of period. Thus, it may give more accurate outcome.
• The study only focused on the effect of income, education, and air pollution to happiness level, the R2 appeared to be quite low. On top of that, the serial correlation, both positive and negative, existed in the study. These problems were perhaps due to omitted variables. As this study included variables that are often included in the previous study, for further studies, more variables should be included as to explain the variance in happiness.
• The included variables might have unit root which causes them to be non-stationary. A non-stationary variable will cause spurious regression which makes it less reliable. Hence, further researchers should do unit root test (e.g. Augmented Dickey Fuller Test) which then can be followed to test the short-run and long-run causality with the dependent variables using cointegration test (e.g. Engle Granger and
This result is consistent with Howell and Howell (2008) where they said income is more significant in small and developing countries. However, income being insignificant in least-developed countries is contradicting with what Veenhoven (1996) found. Perhaps because they prioritize to feed and shelter their family over earning higher income. The fulfillment curve (Graph 1) might help to explain of why income being insignificant in developed countries. Majority of the people in rich nations have reached ‘enough’ point. Thus any extra spending from this point will become overconsumption and would have small contribution to the overall …show more content…
Followings are the limitations of the study which followed by the possible solutions that can be done, by further researchers on this area, to avoid them:
• The nature of this study is cross-sectional where it focuses on one particular time period. Thus, the scope is too narrow and results might only reflect that particular year. Further researchers should do more details analysis with wider scope of period. Thus, it may give more accurate outcome.
• The study only focused on the effect of income, education, and air pollution to happiness level, the R2 appeared to be quite low. On top of that, the serial correlation, both positive and negative, existed in the study. These problems were perhaps due to omitted variables. As this study included variables that are often included in the previous study, for further studies, more variables should be included as to explain the variance in happiness.
• The included variables might have unit root which causes them to be non-stationary. A non-stationary variable will cause spurious regression which makes it less reliable. Hence, further researchers should do unit root test (e.g. Augmented Dickey Fuller Test) which then can be followed to test the short-run and long-run causality with the dependent variables using cointegration test (e.g. Engle Granger and