The Role of Macro-Economic Variables for Determining Happiness:
The Empirical Evidence from South Asian Region
MD. Rafiqul Islam Jahangirnagar University
Supervisor: Asrarul Islam Chowdhury Professor, Department of Economics Jahangirnagar University
Abstract
To be happy is a crucial matter for individuals. A person starving cannot be happy unless he or she is a priest.
Rather there is no guarantee that a person with countless wealth is happy. All these uncertainties may possess a generalization in a macro sense. The objective of this paper is to check how much relevant the macroeconomic variables are in the case of happiness determination at a macro level. To determine this, we would go for Random Effect Panel data regression for six countries for nine years. These countries are Bangladesh, India, Pakistan, Sri Lanka, Nepal and Afghanistan. Bhutan and Maldives are omitted for the lack of the availability of data. The time series lie between 2007 to 2015. The chosen macro-economic variables are money supply, labor force size, HDI and GDP components in expenditure approach. According to Forbs citation, Legatum Prosperity Index is used as happiness indicator as GNH dataset is not available. Initial panel regression result has already showed positive evidence toward such determination and this result would encourage macroeconomic policymakers to formulate policy maintaining close relation to happiness.
1. Introduction:
Happiness is an abstract as well as an absurd concept. Happiness and the economic situations are much more correlated. But the extension of this correlation is not yet identified as it ought to be.
A nation’s happiness is much more complex phenomena than the individual’s happiness. But the matter of sorrow that, till now a happiness index is not widely constructed. Though Gross National Happiness index is constructed by GNH Centre Bhutan, it is not just enough sophisticated enough and not found enough to run a regression model. That’s why, the prosperity index is used hereby as an alternative of GNH by following the legacy of a forbs report representing the happiest and saddest country of the world.
1. Literature Review:
Health is wealth is a common proverb used widely. But health status is not positively related with happiness. But people are ready to tradeoff between health and happiness (van de Wetering, van Exel, & Brouwer, 2016). Material well-being that can be more sophisticatedly identified as economic as major proportions but greater psychological well-being as a consequence of the consumption of experiences, compared to consumption of materialistic goods(Muñiz-Velázquez, Gomez-Baya, and Lopez-Casquete 2017). But in short term (Lane 2017) Effect of happiness on time consistency is Positive. When the question of taxation and provision is included, taxation seems to be positively related but provision seems to be negatively related (Albanese et al.
2015). But for inequality, there exists a linkage between perceived fairness of a market economy and preferences for redistribution (Bjørnskov et al. 2013).
Moreover, the nation’s attitude toward happiness is not homogenous rather it varies from nation to nation (Alesina, Di Tella, and MacCulloch 2004). If this nation to nation gap originates from ideological standpoint as in present or as in past, the happiness situation would be more scattered (Djankov, Nikolova, and Zilinsky 2016). But for local perspective, Average local happiness is positively correlated with both R&D intensity and firm investment, after controlling for firm and local area characteristics. This positive relationship may be due to the optimism and longer term perspectives that are typically associated with higher levels of life satisfaction/happiness (Chuluun and Graham 2016). If this underlying reasons go for a war, the happiness would surely be declining (Coupe and Obrizan 2016).
The better sex one can perceive, the happier that person becomes and there exists a positive linkage between these two (Cheng and Smyth 2015). Marriage can be a way of enjoying sex and beauty and sex are strongly co-related with marriage. (Qari 2014) shows that the married for five years or more than five years are comparatively happier than the single. beauty is a promise of happiness as Accounting for a Wide variety of covariates, particularly educational, marital, and labor-market outcomes that might be affected by beauty, the gross effects are roughly halved, with small reductions arising from the impact of beauty on monetary outcomes (Hamermesh and Abrevaya 2013). Rather sex, technology can shape happiness as it is in Turkey (Durahim and Coşkun 2015).
For the first time constructed a cluster of variable consisting with macro and micro level socio economic variable to examine the determinants of happiness and found that income positively influence the probability of being happy and Easterlin paradox is present in Brazil too. But the determinants may not be same and should not be differentiated from country to country for appropriate calculation (Francesco 2010). But sometimes, happiness can go beyond the determinants, it comes to the reality when self-declared happiness becomes associated with real emotional counterpart and ignores nominal differences (Senik 2014).
As previously stated, wealth cannot buy happiness but without wealth happiness is impossible.
But wealth should have a linkage with happiness and (Tsui 2014) tried to formulate this
happiness and result is that absolute income is not responsible as a determinates of happiness but relative income is.
2. Methodology
To show the relevancy of macroeconomic variables for determining happiness a random effect panel data would be run. And in this panel regression model, Happiness would be treated as dependent variable where other macroeconomic variables would be treated as independent variable. Regression co-efficient would inform us the level of determination where confirmation would come from Z test value.
3. Prosperity Index as happiness index:
In 9th JAN, 2013, an article titled as “The Happiest (And Saddest) Countries in The World” is published in Forbes (Helman n.d.) Magazine by its one of the staffs named Christopher Helman.
In this article, he used prosperity index to identify the happiest and saddest country in the world.
And this legacy has been followed strictly hereby to see the impact of happiness. The main pillars of this index are Economic Quality, Business Environment, Governance, Education, Health Safety & Security, Personal Freedom, Social Capital and Natural Environment.
Prosperity index and Rank in south Asian region:
In this parameter, Afghanistan is on the worst situation and the Sri Lanka owns the best position similarly. Sri Lanka holds top position and on the contrary, Afghanistan holds the lowest position. And the midst position is held by Nepal, India, Bangladesh and Pakistan. Another interesting thing is that war affected country and mostly burdened with militant problem is likely on the second worst position. And that country is Pakistan. Bangladesh and India, two neighboring countries, are on the mid position according to the average rule. Hereby these two country is country of stable growth. For instances, the GDP growth rate of Bangladesh for last five consecutive years is roughly on average is of six percentages. And India’s economic growth is also similar to this. Both Nepal and Sri Lanka were war affected regions in recent Past. Sri Lanka after the war with LLTE has turned back with every positive change in most indicators.
And the same case is true for Nepal. Nepal has a long history of prolonged war with Maoist
Revolt against the monarchy of Nepal. And finally, this revolt came to an end with democratic reform of Nepal.
Selected Macro-Economic Variables:
In this paper, we have especially taken the GDP components variable in expenditure method as macro-economic variables with several additional variables too.
In expenditure method,
Gross Domestic Product=Consumption+Investment+Government Expenditut+Net Export In this paper, Household final consumption, Government expenditure (current US$), Net export and Investment are taken to represent the components of GDP,
Where,
C=H ousehold final consumption , I=Investment G=Government Expenditure∧X=Net export
But along with this GDP component variable in expenditure method, following variables, some variables are included by considering its physical importance. And they are Money Supply, GDP growth, Labor force total and Inflation rate. But due to extreme association with total GDP, this variable has not taken into consideration for analysis.
Government Expenditure: Bangladesh is on the third position where Sri Lanka is on the fourth position. Interestingly, the total area of Bangladesh is more than that of Sri Lanka. Afghanistan and Nepal are on the bottom on the context of government expenditure. Nepal is the smallest country among six countries. But case of Afghanistan on this parameter is misleading for total area hypothesis. Afghanistan is third largest country among these six ones. But its position is fifth on the context of government expenditure. One remainder comes hereby about the capability case of Afghanistan. As it is struggling with war as a form of War on Terror. And this war on terror that continues almost for a decade has decreased the spending capacity of Afghanistan. Otherwise, there exists a possibility of working total area hypothesis hereby once again.
Investment: India is on the first position on the terms of Investment expenditure. The war porn country Afghanistan is on the bottom of this indicator. Bangladesh and Pakistan are on the second and third position. Last three countries are consecutively Sri Lanka, Nepal and Afghanistan.
Net Export: Net export is the difference between total export and total import. And this negative trend is common to all six countries but the magnitude of being negative is not same.
Import: The import condition depends upon the internal productivity condition of a country.
India and Pakistan holds first and second position consecutively. And on the bottom Afghanistan and Nepal exists consecutively. Bangladesh and Sri Lanka remains on the middle consecutively.
Export: Unlike export condition, the import condition depends upon internal demand and also capability of meeting up this demand through domestic production. Nepal and Afghanistan remains the lowest position where India’s and Pakistan’s situation is opposite. Middle situation is held by Bangladesh and Sri Lanka consecutively.
Net export: Afghanistan and Bangladesh are on the top position in this indicators. The case of Afghanistan is the result of low exporting capability where the case of Bangladesh is probably the self-sufficiency as its growth in major indicators is praiseworthy in recent time. Pakistan and Nepal exist on the midst of these six. Sri Lanka and India remains on the border line. The position of every country is the result of self-sufficiency.
Money Supply: The largest economy would have more circulation than others and it is a natural role. The largest two economies such that India and Pakistan possess top position consecutively.
And that is the reasons for which Bangladesh and Sri Lanka are on the middle position. And the bottom position is hold by Nepal and Afghanistan consecutively.
Total GDP: Approaches for GDP calculation are revenue aspect, expenditure aspect and total production aspect. Theoretically, the result derived from every approach should be equal but empirically for not. On the scale of GDP size, India and Pakistan is the largest. Nepal and Afghanistan places to the bottom. Bangladesh and Sri Lanka holds mediaeval place.
Total labor: India is the largest country in the Indian subcontinent in the sense of population and the same scenario is present to the labor size contribution too. Pakistan is the second largest country in the sense of population but it goes third for labor size contribution.
Inflation: lower inflation level is assumed to be positive and lowest inflation rate possessed by India has taken first place where Bangladesh is the preceding ones. Afghanistan and Nepal is on the middle position where Sri Lanka and Pakistan are on the least position Sometimes, Inflation is used as a strategy for fostering growth and development for an economy but the consequences are not praiseworthy always.
HDI: The position of India and Sri Lanka is on the top on the basis of HDI. In this region, the human development condition is on the peak. Bangladesh and Pakistan remains on the middle where the bottom position has been captured by both Nepal and Bangladesh.
Overall Ranking of the countries of South Asian Countries:
On the overall ranking table, India and Bangladesh stands for the first and second position respectively. And middle position is held by Pakistan and Sri Lanka. Other two countries are on the bottom position.
4. Modelling:
In this paper, prosperity index would be treated as dependent variable where others macro- economic indicators would be considered as independent variable. A regression would be run to find out the impact of these macro-economic indicators on happiness determination. To find out that, in this paper, we would treat happiness as a function of GDP components in expenditure method, Money Supply, GDP growth, Labor force total and Inflation rate. So we can write,
Happiness=f (Consumption , Investment , Government Expenditure , Net Export , Money Supply , GDP growth , Labor force total, Inflation rate , HDI)
Let assume,
Investment=〖x〗1, Government Expenditure=〖x〗2, Net Export=〖x〗3,Money Supply=〖x〗4,GDP growth=〖x〗5, Labor force total=〖x〗6, Inflation rate=〖x〗7,HDI=〖x〗8
¿Happiness=H
So we can write this in following simplest format,
H=f(〖x〗1,〖x〗2,〖x〗3,〖x〗4,〖x〗5,〖x〗6,〖x〗7,〖x〗8)
but behind this, least happiness can exist when every single value of xi becomes zero and that is defined by α and named as intercept coefficient.
Rather this modelling is not bible itself and the power of not being explained by above specified variables should not be ignored. And the same case is true for the adjustment of model specification error. These are to be tried to be explained through this variable as named as error term or more sophistically residuals. And defined by u. And lastly the model is thought to be linear as this is for both simplicity and no more complex formation may not be present hereby at all. So now here it comes the time of econometric specification. And by econometric specification, the final model becomes
H=β0+β1x1it+〖β2x〗2it+〖β3x〗3it+β4〖x〗4it+β5〖x〗5it+β6〖x〗6it+β7〖x〗7it+β8〖x〗8it+μit 5. Result and its Interpretation:
This is panel data regression model as stated before. In this model cases are the countries and year is considered as time. According to hausman specification test, we should use random effect model. Random effect model shows that investment money supply, GDP size. Labor force and inflation rate are relevant to happiness determination. But Government expenditure (billion), Net Export (Billion) and Inflation Rate are not significant. As Prob > chi2 = 0.0000, the model fits overall.
After omitting the insignificant variables, when the regression is run another set of coefficients are obtained inward. And these shows us the level of dependency of happiness upon other variables. Every single unit rise in dependent variable can affect happiness by .1088096 units for investment, .0008233 for money supply, -.0898485 for total GDP size, 55.34147 for labor force and 55.84205 for HDI. And regardless of this, the minimum prosperity index is 17.532 .
So this paper suggests that Happiness is positively dependent on Investment, Money Supply, labor force total where total GDP is negatively dependent.
6. Concluding Remarks:
Happiness is a complex thing and also does not necessarily depend on only macro-economic variable only. But this paper has attempted to build a model to find out dependency of being happy as a nation over macro-economic variables. Limitation of this paper lies on to not to
include other variables. In real world, happiness is undefined but a nation wills to be happy as well as economic wellbeing. This paper suggests that policy makers should make policy in such a way that economic progress can maximize happiness too.
Annex:1 Ranks of south Asian countries in rank
Count ry
Prosperi ty Index
Government Expenditure
Household Final consumption
Inves tmen t
Net Expo
rt
Money Supply
Total GDP
Total labor
Inflati on rate
H D I
Ave rag e
Overal l Rank
India 3 1 1 1 6 1 1 1 1 2 1.8 1
Pakist an
5 2 2 3 5 2 2 3 6 4 3.4 3
Bangl adesh
4 3 3 2 3 3 3 2 2 3 2.8 2
Sri Lank
a
1 4 4 4 5 4 4 5 5 1 3.7 4
Afgha nistan
6 5 5 6 2 6 5 6 3 6 5 6
Nepal 2 6 6 5 1 5 6 4 4 5 4.4 5
Annex 2: Regression Result (Random Effect Model)
Prosperity Index Regression
Coefficient
Z test Regression Coefficient after omitting the insignificant variable.
Government expenditure (billion) 0.1442578 Not Significant
Net Export (Billion) 0.089409 Not
Significant
Investment (Billion) 0.2623193 Significant 0.1088096
Money Supply (Billion) 0.0011891 Significant .0008233
Total GDP (Billion) -0.2372287 Significant -.0898485
Labor Force total (Billion) 44.50854 Significant 55.34147
Inflation Rate 0.0767887 Not
Significant
Prosperity Index Regression Coefficient
Z test Regression Coefficient after omitting the insignificant variable.
HDI 52.83568 Significant 55.84205
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