Does Happiness Depend On Socioeconomic Conditions? Knowledge Gained From Indonesia

Text Box: Volume 4, Number 1, January 2023
e-ISSN: 2797-6068 and p-ISSN: 2777-0915

DOES HAPPINESS DEPEND ON SOCIOECONOMIC CONDITIONS? KNOWLEDGE GAINED FROM INDONESIA

Syaiful Anwar, Anita Yulia Sari, Nasri Bachtiar, Rahmi Fahmy

Universitas Andalas, Indonesia

E-mail: [email protected], [email protected], [email protected], [email protected]

KEYWORDS

Socioeconomics, Happiness, Indonesia.

ABSTRACT

The objective of this study is to identify and examine the socioeconomic variables that affect happiness in Indonesia. Secondary data from the Indonesia Family Life Survey (IFLS) batch 5 survey, which included 16,698 respondents, was the source of the information used in this study. The probit model is used in the data analysis technique using a multilevel category as the dependent variable. According to the study's findings, age, gender, social capital, including religious observance and a sense of security, variable consumer spending, and willingness to help variables have no bearing on the likelihood of happiness in Indonesia. Neither do income level, health, education, or age. Income, education, health, and social capital levels

INTRODUCTION

Gross Domestic Product (GDP) is the primary metric used to assess economic development in a nation (Arikunto & Praktek, 2001). Gross Domestic Products (GDP), which was first employed as a gauge of a nation's economic development in 1944 at the Bretton Woods conference, has also been used as a gauge of overall well-being since the 1960s.

According to (Nosek et al., 2009), the GDP has a number of flaws, including the failure to account for social costs like externality costs, the emphasis on absolute income levels and disregard for income distribution, the failure to measure activities outside of the market or unofficial transactions, and the failure to consider how economic activity affects the environment.

The effectiveness of this economic indicator in presenting the general public's perception of social considerations in building has increased (Bartolini & Bilancini, 2010). The economic indicators that have been more frequently seen in recent construction projects, such as economic growth and poverty is assessed, are not yet adequate indicators of the current level of sejahteraan activity. In recent years, it has become increasingly important to measure and analyze the penduduk kesejahteraan using other metrics than just the monetary unit of measure (GDP/PDB). The current indicator of sustainability does not only indicate a condition of material well-being or welfare, but also a condition of sustainability of the subject (subject well-being) or sustainability of the system (Happiness). The index of kesejahteraan that is currently giving kebijakan planners pause is the index of kebahagiaan (hapiness indeks). (Frey & Stutzer, 2013) asserts that the single most important issue facing human existence is kebahagiaan.

Pencapaian kebahagiaan is a crucial factor in human development. According to Aristoteles, however, kebahagiaan is actually the main goal of human existence. Every person possesses a set of wishes that they would like to be carried out in order to achieve fulfillment in their daily lives (Blanchflower & Oswald, 1994).

The current study explores the relationship between several socioeconomic, health, and educational indicators as well as gender, kelamin type, and religious (rela menolong, agama, and morality) social norms and Indonesian national behavior (Happiness, 2012).

Review Of The Literature And Hypothesis Formulation

Definition of Happiness Happiness can signify many different things. Some scholars attempt to use what happiness genuinely means rather than equating it with "good" or leading a nice life (Veenhoven, 2009). A person is said to have high happiness if they are content with their living circumstances, experience positive emotions frequently, and experience negative emotions infrequently (Cuï¿½ado & de Gracia, 2012). In addition, happiness can also result from an individual's success in achieving their goals and from their ability to develop their personal strengths and virtues. in daily lives and experience a pleasurable state (Eddington & Shuman, 2005).

According to an economic perspective, happiness is defined as a general sense of well-being, and happiness economics is the study of how happiness affects both income and non-income elements. A society's level of wellbeing rises with its level of happiness, and vice versa (Diener, 2009).

According to (Diener, 2009), happiness and subjective well-being share the same meaning and are comprised of two different things. The emotive component and the cognitive component are the two parts.

It was also clarified that happiness and life satisfaction are the same things. A more authentic form of happiness than attaining goals is life satisfaction (Easterlin, 1974). In reality, happiness is always linked to greater health, high levels of creativity, and a better work environment (Hancock, 2013).

In light of this, it may be said that happiness can be defined as the lack of depressive sentiments and the presence of sensations of joy, serenity, and well-being. These are all circumstances that lead to happiness in an individual (Mahadea, 2013).

RESEARCH METHODS

The Indonesia Family Life Survey (IFLS) batch 5 of 2014 was the survey institute that provided the secondary data used in this study. The household survey and the community and facility survey are the two primary parts of the IFLS survey. The IFLS was originally conducted in 1993, representing 83% of Indonesians residing in 13 out of 27 provinces, while the most recent survey was conducted in 2014ï¿½2015, representing 90% of households in 24 out of 33 provinces. All participants in this study were Indonesia Family Life Survey respondents from the fifth wave (IFLS). 50,580 people, representing 15,900 homes, participated in this survey.

The Indonesia Family Life Survey's fifth wave, which covered the years 2014ï¿½2015, collected data on the dependent variable in this study, which is Level of Happiness. It can be found in book 3a of the household survey's SW (Welfare) subsection. This variable represents a category, with 1 denoting happiness and 0 denoting unhappiness.

Money Level, the income produced by respondents or persons in the Indonesian Family Life Survey (IFLS) household survey's fifth wave in 2014ï¿½2015, makes up the dependent variable. Section A1 of Book 1 has it. Health Status, The level of health used in this study is the level of individual health in the Indoniosia Family Life Survey household survey's fifth wave from 2014ï¿½2015.

Section kk1 of Book 3b contains it (health). The information is presented as categorical data from the suggested questionnaire, with the following formula: 1 = if 1 = Healthy, 0 = if 2 = Unhealthy. The level of education acquired by persons or respondents in the 5th batch of the Indonesian Family Life Survey household survey in 2014-2015 is known as Education Level. Located in Book 3a, Section DL (Education). The information is broken down into the following categories: 0 for others, 4 for college or equivalent, 3 for SMA or equivalent, 2 for SMP or equivalent, and 1 for SD or equivalent. Age, Age is the age of the person or respondent in the Indonesia Family Life Survey household survey's fifth wave for the years 2014ï¿½2015. Section Cov4 of Book 3a contains that (Age). The gender of the person or respondent in the Indonesian Family Life Survey household survey's fifth wave, which was conducted in 2014ï¿½2015, is gender. The data in Book 3a section Cov 5 (sex) is presented as a dummy model category with the following values: 1 = if 1=male, 0 = if 3=female. In this study, social capital was measured using social capital that was willing to lend a hand, religious observance, and a sense of security from the Indonesian Family Life Survey household survey's fifth batch for the years 2014ï¿½2015. (Trust). Data for the category: willing to assist 0 if 3 disagrees, 1 if 1 agrees, Religion: 1 if you follow it, 0 if you don't, Feeling secure: If 1 = Secure,

That information is included in Book 3a, Section Cov4 (Age). The Indonesian Family Life Survey household survey's fifth wave, which was conducted in 2014ï¿½2015, asked respondents about their gender. The data in Book 3a section Cov 5 (sex) is presented as a dummy model category, with the values 1 if the value is male and 0 if the value is female. The 5th batch of the Indonesian Family Life Survey household survey for 2014ï¿½2015, included in Book 3a section TR, was used in this study to measure social capital. Social capital used in this study included social capital eager to assist, religious observance, and a sense of security (Trust). combined with information on the category: ready to assist 0 = if 3 = Disagree, 1 = if 1 = Agree Religion: 1 if you obey 1; 0 if you disobey 3; Feeling Safe: If 1=Safe, then 0 = if 3 = Unsafe.

Method of Data Analysis

Utility theory is used in this study's use of the probit model. The equivalent deviate, abbreviated as ned, or the normal model are other names for this model that are frequently used. Utility theory, often known as McFadden's theory of rational selection, served as the foundation for the probit model's development.

The purpose of this investigation is known as:

Pi = (0+iXi) (Yi=1|Xi)

Where the probit model function is ) and Y= 1 is the probability. Meanwhile, the expression for (Z), which is based on the normal distribution of Z, is as follows:

Pi equals f(Zi)=dz.

In that case, the regression equation would look like this:

Pi (yi = 1 | xi) = 𝜙 (𝜷0+𝜷𝟏𝑿𝟏𝒊+⁡𝜷𝟐𝑿𝟐𝒊+⁡𝜷𝟑𝑿𝟑𝒊+⁡𝜷𝟒𝑿𝟒𝒊+⁡𝜷𝟓d𝑿𝟓𝒊+⁡𝜷𝟔𝑿𝟔𝒊+⁡𝜷𝟖𝑿𝟖𝒊+𝜷𝑿+𝜷𝑿9𝒊+𝒆)

Information:

Y = Happiness Level

Y=1 Probability

𝜙 (Z)= Probit model function

𝜷= unknown intercept parameter

𝜷i=(𝜷 1𝜷 2𝜷 3... 𝜷p) coefficient parameter

X1 = Income Level

X2 = Health Level

X3 = Education Level

RESULTS AND DISCUSSION

The results of the probit estimation can be observed as follows based on the outcomes of data processing using the STATA program:

Table 1

ï¿½Results of Probit Estimation

Happiness	Coefisien	Std.Eror
Health	0.506***	(0.0156)
Income	0.152***	(0.0060)
Sex	-0.0953**	(0.0155)
Age	-0.0103***	(0.0006)
Education	0.1735***	(0.0076)
Willingness to help	0.0603	(0.0775)
Religion	0.2272***	(0.0167)
Feeling Save	0.3178***	(0.0276)
Consumption	0.0377**	(0.0046)
_cons	-2.2935***	(0.13137)
N	16698

The equation is then expressed as follows:

Pi (Yi=1|Xi) = (-2.2935 + 0.152X1+ 0.506X2+ 0.173X3-0.0103 X4 - 0.095 X5 + +0.0603X6+0.227 X7+0.317 X8+0.0377X9)

The coefficient value may be seen in the estimation results above, however unlike the LPM model, the probit regression model's coefficient value cannot be easily read because it is based on the probability value of the normal distribution. Only a direct interpretation of the coefficients' sign will do. From the equation above, we can deduce that the income variable is positive, so income has a positive impact on Indonesians' level of happiness; the health variable is positive, so Indonesians' level of health has a positive impact on Indonesians' level of happiness; and the education variable is positive, so Indonesians' level of education has a positive impact on Indonesians' level of happiness.

In contrast to the consumer spending variable, which is positive and has a positive influence on happiness in Indonesia, the social capital variable wanting to help is positive but not significant, meaning that it has no impact on the country's level of happiness.

Discussion

The Marginal Effect, also known as changes in the probability value, is the most effective technique to observe the outcomes of probit estimation. A marginal effect table is noise:

Table 2

ï¿½Results of Probit Regression's Marginal Effects

Happiness	dy/dx	Std.Eror	Z	p>z
Health	0.0639***	0,0019	32.06	0.000
Income	0.0193***	0,0007	24.93	0.000
Age	-0.0013***	0.0001	-17.19	0.000
Sex	-0,0118**	0.0019	-6.23	0.000
Education	0,0219***	0.0009	22.38	0.000
Willingness to help	0.0076	0.0098	0.78	0.437
Religion	0,0287***	0.0021	13.53	0.000
Feeling Save	0.0401 ***	0.0034	11.48	0.000
Cunsumption	0.0048	0.0005	8.24	0.000
Pseudo R2	0.1099
Prob>Chi	0.0000
Correctly Classified	91.81%

Proceed data from IFLS *=10%, **=5%, ***=1%

According to the marginal effect, the income level variable had a positive and significant impact on Indonesia's level of happiness. These findings suggest that the Indonesian economy is not affected by the Easterlin paradox. This suggests that, in the absence of the Easterlin paradox, happiness in Indonesia would not drop as income levels rise over time. Instead, it will expand along with opportunities for happiness. This indicates that it contradicts the Easterlin Paradox idea, according to which a rise in money cannot lead to an improvement in wellbeing or happiness.

Both in the regression calculations and when a number of additional variables were included in the multiple regression, it was demonstrated that there is a statistically significant correlation between income and happiness. This implies that happiness is influenced by income. People who are happier will have greater incomes, and happier people will have higher incomes.

Higher-income earners have greater opportunity to accomplish their goals, may purchase the things and services they desire, and can enjoy a higher social standing.

The degree of health was found to have a positive and significant impact on the level of happiness in Indonesia based on the marginal effect. The findings revealed a significant link between wellbeing and health. It is believed that happiness and health are inversely correlated, so that when a person is happy, he will also be in good health. As happiness promotes physical health, it has been found that happy people tend to live longer.

According to this study, Indonesia's level of health plays a major role in boosting the likelihood of happiness. Whereas when a person's health declines, it reduces output, necessitates the purchase of more equipment to sustain his health, and affects those around him adapt to the sick person's state, which will make you unhappy because your health is deteriorating and you feel uncomfortable around other people.

According to the marginal effect, the level of education in Indonesia has a positive and considerable impact on people's levels of happiness. According to this study, there is a link between Indonesian happiness levels and educational attainment. Since higher education can lead to more career options and higher income levels, it is more likely that having a high degree of education will make someone happier. In addition, highly educated individuals are viewed as having high status in society. indirect.

Age has a negative and considerable impact on Indonesia's level of happiness, as can be observed from the marginal effect. The relationship between age and happiness is shaped like the letter U; as a person gets older, his or her likelihood of being happy decreases until it reaches a certain minimum level, at which point it rises again. According to this study, happiness peaked at the age of 60. This is consistent with (Schnittker & McLeod, 2005) assertion that self-reported health declines with age, especially after age 50. For instance, emotions of exclusion, feeling unneeded, and a refusal to accept new truths, such as those brought on by a chronic illness or the death of a spouse. People could feel unhappy as they get older as a result of this. On the other hand, aging might also be accompanied by an increase in happiness.

Gender has a negative and considerable impact on happiness in Indonesia, as evidenced by the marginal effect. In this study, women are more likely than men to experience an increase in their degree of happiness. This study supports prior research, particularly that of (Sukarniati, 2021), who found that gender has an impact on happiness and that women are generally happier than men

CONCLUSION

According to the study's findings, Indonesia has a very high percentage of happiness (91.77%), which is exceptionally high. Additionally, there is no Easterlin paradox in the Indonesian economy, which means that when income levels improve, so does happiness there and vice versa.

According to the findings of a regression study on socioeconomic factors affecting happiness in Indonesia, variables such as income level, health status, education level, age, gender, social capital, including religious observance and security, consumption expenditure, and willingness to help, have no bearing on the likelihood of happiness in Indonesia.

Income level, education level, health level, social capital including religious adherence, security, and consumption expenditure variables all have a positive and substantial impact on raising the likelihood of happiness in Indonesia, according to the results of the regression conducted. The likelihood of happiness in Indonesia is significantly and negatively impacted by age and gender factors.

REFERENCES

Arikunto, Suharsimi, & Praktek, Prosedur Penelitisn Suatu Pedekatan. (2001). Rineka Cipta. Jakarta.

Bartolini, Stefano, & Bilancini, Ennio. (2010). If Not Only Gdp, What Else? Using Relational Goods To Predict The Trends Of Subjective Well-Being. International Review Of Economics, 57(2), 199ï¿½213.

Blanchflower, David G., & Oswald, Andrew J. (1994). Estimating A Wage Curve For Britain 1973-90. The Economic Journal, 104(426), 1025ï¿½1043.

Cuï¿½ado, Juncal, & De Gracia, Fernando Pï¿½rez. (2012). Does Education Affect Happiness? Evidence For Spain. Social Indicators Research, 108(1), 185ï¿½196.

Diener, Edward. (2009). The Science Of Well-Being: The Collected Works Of Ed Diener (Vol 37). Springer.

Easterlin, Richard A. (1974). Does Economic Growth Improve The Human Lot? Some Empirical Evidence. In Nations And Households In Economic Growth (Bll 89ï¿½125). Elsevier.

Eddington, Neil, & Shuman, Ricard. (2005). Subjective Well Being (Happiness). Continuing Psychology Education: 6 Continuing Education Hours. Go To Reference In Article.

Frey, Bruno, & Stutzer, Alois. (2013). Recent Developments In The Economics Of Happiness. Edward Elgar Publishing.

Hancock, Elizabeth K. (2013). Assessing Happiness: How Economic Factors Measure Up.

Happiness, How Education Enhances. (2012). Wan-Chi Chen. Soc Indic Res, 106, 117ï¿½131.

Mahadea, Darma. (2013). On The Economics Of Happiness: The Influence Of Income And Non-Income Factors On Happiness. South African Journal Of Economic And Management Sciences, 16(1), 39ï¿½51.

Nosek, Brian A., Smyth, Frederick L., Sriram, Natarajan, Lindner, Nicole M., Devos, Thierry, Ayala, Alfonso, Bar-Anan, Yoav, Bergh, Robin, Cai, Huajian, & Gonsalkorale, Karen. (2009). National Differences In Genderï¿½Science Stereotypes Predict National Sex Differences In Science And Math Achievement. Proceedings Of The National Academy Of Sciences, 106(26), 10593ï¿½10597.

Schnittker, Jason, & Mcleod, Jane D. (2005). The Social Psychology Of Health Disparities. Annual Review Of Sociology, 75ï¿½103.

Sukarniati, Lestari. (2021). Determinants Of Local Original Income The Era Of Special Autonomy For The Government. Universitas, 11(1), 93ï¿½107.

Veenhoven, Ruut. (2009). How Do We Assess How Happy We Are? Tenets, Implications And Tenability Of Three Theories. In Happiness, Economics And Politics. Edward Elgar Publishing.

Copyright holders:

Syaiful Anwar, Anita Yulia Sari, Nasri Bachtiar, Rahmi Fahmy (2023)

First publication right:

Devotion - Journal of Research and Community Service

This article is licensed under a Creative Commons Attribution-ShareAlike 4.0 International