Socio-Economic and Psychological Well-Being: An Analytical Study for Sustainable Policy-Making

It is in the heart of human existence to be happy and the sole purpose of human communities is to work towards reaching for the highest of people’s well-being. A detailed analysis of the historical foundations of the concept of "well-being" demonstrates that how people perceive it depends on the development and needs of the period. From the Greeks to Enlightenment to Industrialization the self-understanding of well-being changed from being virtuous to knowledgeable to finding happiness in wealth. Malleable time brings changing perceptions and therefore, a need for novel interpretation has arisen. The world must redefine development while taking sustainability into account as a result of growing industrialization, unchecked resource extraction, unmet human needs and desires, and a lack of logical rationale. To do so, a balanced and multidimensional well-being approach is the need of the hour. There are two perspectives which are prevalent even today one is, Behavioural Economics/welfare economics (Hedonic) and other is socio-psychological approach (Eudaimonia), but are researched separately. The present paper tries to link both by assuming that, on the one hand, hedonic well-being (Income and Financial well-being) keeps people materialistically happy and, on the other hand, eudaimonic (Socio-psychological well-being) makes them live a satisfactory and mentally sound life. Our aim is to provide a simple way to measure holistic well-being for knowledgeable and sustainable policy-making, as the time demands. Knowledgeable policymaking means understanding the state of total well-being before designing policies. Sustainable policy-making means after a deep understanding of what people want (to feel satisfied in life) building policies that take care of people’s quality of life, future generation needs and environmental concern [1]. The present paper tries to distinguish social, psychological and financial well-being clearly and distinctly. The hedonic perspective is measured by income level and financial well-being scale, whereas the eudaimonic perspective is measured by social and psychological well-being scales. As the question of life satisfaction and happiness became the main agenda of many major Governments of the world, the need to define more realistic social and psychological well-being indicators surfaced. From the 1960s to the 1980s a major upsurge in the empirical study of subjective well-being, with both the social and psychological elements was seen [2-5]. At around 1990 there was a minute thrust in economic research on subjective well- being. Both interests are still prevalent and expanding exponentially.

The concept of economic well-being was first introduced in the academic literature by Easterlin et al. [6] in their 1990 paper titled “How have American baby boomers fared? Earning and economic well-being of young adults, 1964-1987”. There was shift from an objective approach to a subjective approach, which focused on the behavioural aspects of financial well-being [7]. It was not until 2009 that the topic of financial well-being research became widespread, and researchers began studying its impact on overall life satisfaction, academic success, psychological and physical health, and normative expectations [8, 9]. Subsequently, many different studies have attempted to define and measure financial well-being, financial capabilities, and financial behaviours among different groups, including college students, American women, Malaysian college students, and consumers [10-13].

Bradburn attempted to differentiate psychological wellbeing from social/general wellbeing, despite there being many locus classicus that define and measure human wellbeing in general and social wellbeing in particular [14]. Subsequent researchers built on Bradburn's work and added new dimensions to the concept. However, it was Ryff [15] who first presented a six-variable model for calculating psychological well-being, which she further refined in 1995, 1996, 1997, and 1999. In this paper, we will use Ryff's model to calculate psychological well-being.

Keyes in 1998 proposed a five-dimensional scale (social contribution, social integration, social coherence, social acceptance, and social actualization) and it was theoretically authenticated. Gallagher et al. [14] studied hedonic, eudaimonic and social well- being to explain sound mental health. There have been numerous socio-psychological studies previously discussed that take a multidisciplinary approach, resulting in overlapping concepts of social and psychological well-being.

In the contemporary, where need of well-being well realized and recognized, researchers are studying the several aspects of well-being starting from social well-being to financial well-being.

The empirical examination of the data provides compelling evidence against the set notions regarding money and its relationship to overall well-being. The particular data set reveals hidden patterns portraying well-being as a multi-dimensional phenomenon and policymaking cannot solely rely on financial growth and development.

It is interesting to note that the highest average scores in all three categories of well-being are observed in the upper middle-income group. The lowest financial well-being is surprisingly of the higher income group. The lowest social well-being is of the middle-income group. And the lowest psychological well-being is also of the middle-income group.

The total average psychological well-being is highest, followed by social and financial well-being. This result shows that although the economic models are based on financial prosperity the financial well-being scores the lowest among all three types of well-being. Even income-wise categorisation doesn’t change the result. The higher income group’s financial well-being is the lowest among all.

Table 2 describes the sample nature. The participants from 15-30 years of age participated more than other age categories. Furthermore, percentage of students was higher than other categories. Subjects whose income was below than 20000, their percentage was higher and post graduate subjects participated more than other mentioned categories.

Table 2. Sample description

3.1 The well-being equation and well-being score calculation for each income group

The well-being equation is comprised of:

W = f(S, P, F, I)         (a)

Wi=Well-being

f=function of

SWi=Social Well-being

PWi=Psychological Well-being

FWi=Financial Well-being

InWi=Income Well-being

Well-being=Income Well-being+Social well-being+Psychological well-being+Financial well-being

Or

Wi =  β0 + β1InWi + β2SWi + β3PWi + β4FWi + εi     (b)

(Annexure II)

Wi: This is the dependent variable, representing the outcome or response variable for the ith observation or unit in the dataset.

β0: This is the intercept term, the value of Wi when all the independent variables (InWi, SWi, PWi, FWi) are zero.

β1, β2, β3, β4: These are the coefficients associated with the respective independent variables (InWi, SWi, PWi, FWi). They represent the estimated impact or contribution of each independent variable to the dependent variable.

InWi, SWi, PWi, FWi: These are the independent variables or predictors. They are the factors that may influence or explain the variation in the dependent variable Wi.

εi: It includes all the unobserved factors or errors that affect the dependent variable but are not captured by the model.

In other words, the equation is a linear regression model, where the researchers are trying to predict Wi as a linear combination of the intercept and the weighted sum of the independent variables, each multiplied by its respective coefficient. The error term accounts for any unexplained variability in Wi that is not captured by the model.

First, we have to calculate the specific values for β0, β1, β2, β3, and β4, and then independent variables (InWi, SWi, PWi, FWi) that can be used to calculate an estimated value for Wi.

β2, β3 and β4 are the coefficients associated with the variables SWi (Social well-being), PWi (Psychological well-being) and FWi (Financial well-being). The estimated values of β2, β3 and β4 are assumed to be 1 initially to simplify the equations. This suggests that in a society a one-unit increase in each of the Social Well-being, Psychological well-being and financial well-being is associated with a one-unit increase in overall well-being (W). This shows a direct and linear positive relationship between Social Well-being/Psychological well-being/financial well-being and overall well-being.

If we substitute the income values in the equation, we can get the individual's total well-being. Depending upon the need we can set an income limit for comparison. Say for the present data maximum income could be ₹1,50,000/-per month for the higher income group, ₹1,20,000/-for the upper-middle income group, ₹90,000/-for the middle-income group and ₹60,000/-for lower income group and the total of social, psychological and financial wellbeing is 300 (100 for each variable).

Solving the equations:

Given:

(Annexure-II)

According to the set maximum income limits for different income groups following categories are drawn:

Higher-income group: ₹1,50,000/-per month

Upper-middle income group: ₹1,20,000/-per month

Middle-income group: ₹90,000/-per month

Lower income group: ₹60,000/-per month

β2 = β3 = β4 = 1   (c)

Lower income group (maximum income: ₹60,000/-per month):

$\left.\begin{array}{l}\mathrm{SWi}=60.52 \\ \mathrm{PWi}=65.6 \\ \mathrm{FWi}=48.9\end{array}\right\}$ (Average values from Table 2)

Substituting the given values:

$\begin{gathered}\mathrm{W}=\beta \mathrm{o}+\beta 1 \mathrm{InWi}+\beta 2 \mathrm{SWi}+\beta 3 \mathrm{PWi}+\beta 4 \mathrm{FWi}+\varepsilon \mathrm{i} \\ \mathrm{W}=\beta \mathrm{o}+\beta 1(60,000)+60.52(1)+65.6(1)+48.9(1) \\ \mathrm{W}=\beta \mathrm{o}+60,000 \beta 1+60.52+65.6+48.9 \\ W=\beta 0+60,000 \beta 1+175.02\end{gathered}$        (i)

Middle-income group (maximum income: ₹90,000/-per month):

$\left.\begin{array}{l}\mathrm{SWi}=59.92 \\ \mathrm{PWi}=64.32 \\ \mathrm{FWi}=49.7\end{array}\right\}$ (Average values fromTable 2)

$\begin{gathered}\mathrm{W}=\beta \mathrm{o}+\beta 1 \mathrm{InWi}+\beta 2 \mathrm{SWi}+\beta 3 \mathrm{PWi}+\beta 4 \mathrm{Fwi}+\varepsilon \mathrm{i} \\ \mathrm{W}=\beta \mathrm{o}+\beta 1(90,000)+59.92(1)+64.32(1)+49.7(1) \\ \mathrm{W}=\beta \mathrm{o}+90,000 \beta 1+59.92+64.32+49.7 \\ W=\beta 0+90,000 \beta 1+173.94\end{gathered}$       (ii)

Upper-middle income group (maximum income: ₹1,20,000/-per month):

$\left.\begin{array}{l}\mathrm{SWi}=62.07 \\ \mathrm{PWi}=66.15 \\ \mathrm{FWi}=50\end{array}\right\}$ (Average values from Table 2)

$\begin{gathered}\mathrm{W}=\beta \mathrm{o}+\beta 1 \mathrm{InWi}+\beta 2 \mathrm{SWi}+\beta 3 \mathrm{PWi}+\beta 4 \mathrm{Fwi}+\varepsilon \mathrm{i} \\ \mathrm{W}=\beta \mathrm{o}+\beta 1(1,20,000)+62.07(1)+66.15(1)+50(1) \\ \mathrm{W}=\beta \mathrm{o}+1,20,000 \beta 1+62.07+66.15+50 \\ W=\beta 0+1,20,000 \beta 1+178.22\end{gathered}$   (iii)

Higher income group (maximum income: ₹1,50,000/-per month):

$\left.\begin{array}{l}\mathrm{SWi}=60.6 \\ \mathrm{PWi}=65.34 \\ \mathrm{FWi}=45.58\end{array}\right\}$ (Average values from Table 2)

$\begin{gathered}\mathrm{W}=\beta \mathrm{o}+\beta 1 \mathrm{InW}+\beta 2 \mathrm{SWi}+\beta 3 \mathrm{PWi}+\beta 4 \mathrm{FWi}+\varepsilon \mathrm{i} \\ \mathrm{W}=\beta \mathrm{o}+\beta 1(1,50,000)+60.6(1)+65.34(1)+45.58(1) \\ \mathrm{W}=\beta \mathrm{o}+1,50,000 \beta 1+60.6+65.34+45.58 \\ W=\beta 0+1,50,000 \beta 1+170.92\end{gathered}$   (iv)

To solve for βo and β1 substitution method is used. First, we solved one equation for one variable and then substituted that expression into the other equations. Let's start by solving Eq. (i) for βo:

βo + 60,000β1 = 175.02    (v)

The left-hand side equation represents the total of zero social, psychological and financial well-being and maximum income for a particular income group. The right-hand side of the equation is the total average social, psychological and financial well-being according to the data collected. We are equating both sides because we are testing the notion that income equals total well-being.

Rearranging the equation, we have:

βo=-175.02-60,000 β1

Now we can substitute this expression for βo in the other two equations.

Substituting in Eq. (ii):

βo+90,000 β1=-173.94

Simplifying, we get:

(-175.02-60,000 β1) +90,000 β1=-173.94

-175.02+30,000 β1=-173.94

30,000 β1=-173.94 + 175.02

β1≈0.00003

Now substitute this value of β1 into Eq. (i) or Eq. (ii) to find βo. Let's use Eq. (i):

βo+60,000 β1=-175.02

Simplifying, we have:

βo+60000 (0.00003) =-175.02

βo=-175.02-1.8

βo≈-176.82

Therefore, the solution for βo is approximately-176.82 (is the estimated value of total well-being when all other variables are zero), and the solution for β1 is approximately 0.00003 (indicates for every unit increase in income, total well-being is estimated to increase by 0.00003, which is negligible).

Now, substitute the values of βo and β1 in Eq. (b), we get the following:

Wi=βo+β1InWi+β2SWi+β3PWi+β4FWi+εi

W=(-176.82)+(0.00003) InWi+β2SWi+β3PWi+β4FWi+εi

Now, putting values of Wi, SWi, PWi and FWi for all income groups, we get the following four equations.

Lower Income Group:

$\begin{gathered}(-176.82)+(0.00003)(60000)=60.52 \beta 2+65.6 \beta 3+48.9 \beta 4 \\ 60.52 \beta 2+65.6 \beta 3+48.9 \beta 4=-175.02\end{gathered}$   (e)

Middle-income Group:

$\begin{gathered}(-176.82)+(0.00003)(90000)= 59.92 \beta 2+64.32 \beta 3+49.7 \beta 4 \\ 59.92 \beta 2+64.32 \beta 3+49.7 \beta 4=-174.12\end{gathered}$    (f)

Upper-Middle Income Group:

$\begin{gathered}(-176.82)+(0.00003)(1200000)= 62.07 \beta 2+66.15 \beta 3+50 \beta 4 \\ 62.07 \beta 2+66.15 \beta 3+50 \beta 4=-173.22\end{gathered}$    (g)

Higher Income Group:

$\begin{gathered}(-176.82)+(0.00003)(1500000)= 62.6 \beta 2+65.34 \beta 3+45.58 \beta 4 \\ 60.6 \beta 2+65.34 \beta 3+45.58 \beta 4=-172.32\end{gathered}$     (h)

Any three equations can be used to find the values of β2, β3 and β4, so we are using equations e, f and g.

Both Substitution and matric Methods are used and the following values are derived:

β1≈0.00003

β2≈5.22876,

β3≈-5.13238, and

β4≈-3.16524

This indicates for every unit increase in income, total well-being is estimated to increase by 0.00003, for every unit increase in social well-being the total income well-being is estimated to increase by 5.22876, for every unit increase in psychological well-being the total income well-being is estimated to decrease by 5.13238 and for every unit increase in total financial wellbeing the total income well-being is estimated to decrease by 3.16524.

We can derive total well-being for each group by substituting the above values in equations e, f, g and h:

W1=60.52β2+65.6β3+48.9 β4+175.02

W2=59.92β2+64.32β3+49.7 β4+174.12

W3=62.07β2+66.15β3+50 β4+173.22

W4=60.6 β2+65.34 β3+45.58β4+172.32

We get Total Well-being for each income group:

W1≈−0.785

W2≈−1.49

W3≈0.65

W4≈8.035

W1=Lower Income Group

W2=Middle Income Group

W3=Upper Middle-Income Group

W4=Higher Income Group

The result for this particular data set shows that lower- and middle-income groups have negative total well-being and the middle-income group is the lowest among them. Upper middle-and higher-income groups both have positive total well-being, in which higher higher-income group scores the highest.