Over time, economics has begun to integrate with other disciplines. The closest discipline to economics is psychology. Within the realm of psychology, economists can explore human behavior in economic activities, including aspects such as production, consumption, and distribution (Putra & Sudibia, 2018). One of the measurable outcomes of this integration is the level of societal well-being. Traditionally, economics has solely relied on Gross Domestic Product (GDP) as a measure of overall well-being. However, this measure is one-dimensional due to limitations. However, GDP only captures material living standards without capturing social welfare such as disregarding social costs and income distribution, and emphasizes absolute income growth (Kalimeris et al., 2020). Furthermore, factors such as inflation or other macro elements cannot fully capture an individual's happiness; there are non-material measures at play (Helliwell et al., 2023). Strengthened by previous research, GDP ignores non-market factors in household production in terms of leisure time and it only represents domestic products without including foreign production (Dynan & Sheiner, 2018).

Recognizing these limitations, policymakers have been compelled to seek alternative indicators. In general, it has been widely agreed in development planning and evaluation that happiness indicators should be broader and not solely macro-focused. Various alternative measures have been developed to assess the happiness of emerging societies including the GPI (Genuine Progress Indicator), GNH (Gross National Happiness), Better Life Index, Human Development Index, and Social Progress Index (Evroux et al., 2023). Other measures used include the Millennium Development Goals (MDGs) and Sustainable Development Indicators as in the Doughnut Concepts by downscaling local and social boundaries (Ferretto et al., 2022). Furthermore, in 2011, the happiness index based on the United Nations General Assembly's results, began to gain traction. In 2013, Statistics Indonesia began publishing data on the happiness index, obtained through a survey known as the Happiness Measurement Survey. This survey employs ten indicators to measure societal happiness, and a detailed breakdown of these indicators is provided in Table 1.

Table 1 shows that in the years 2013 and 2014, Indonesian society achieved a relatively high level of happiness. Investigating the reasons behind the high levels of happiness in Indonesian society during such period is important for identifying what contributes to well-being and for creating policies to maintain and improve quality of life. The results exhibit fluctuations in several indicators, showing that the components contributing to happiness are not solely derived from macroeconomic factors such as income levels, but also from other individual factors. The Happiness Index Component Indicators for 2013 and 2014 show a generally positive trend in well-being. Household income, housing and asset status, and employment status experienced improvements, indicating enhanced economic conditions. However, there is a slight decline in the education component, possibly signaling concerns in the educational system. Health quality saw a decrease, indicating a potential dip in perceived well-being. On a positive note, leisure time availability increased, suggesting a better work-life balance. Social relationships and family harmony exhibited slight improvements, indicating positive interpersonal dynamics. Security and environmental conditions also showed positive trends, reflecting an increased sense of safety and satisfaction with the surrounding environment.

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Economic and social factors are significantly related to the happiness of American citizens (Garrison & S, 2021). An increase in nominal income does not necessarily result in optimal happiness (Mentus & Vladisavljević, 2021). Hence, socioeconomic status can play a crucial role in influencing happiness levels, representing the socioeconomic dimension that positions individuals based on various aspects of their lives. Consequently, a comprehensive examination of the impact of factors beyond macroeconomic aspects on happiness levels in Indonesia is warranted. Research on socioeconomic determinants of happiness informs Sustainable Development Goals (SDGs) by identifying key factors impacting well-being. Understanding how income, education, and employment affect happiness helps policymakers align efforts with SDGs, fostering inclusive growth, reducing inequalities, and promoting societal well-being for sustainable development.

Previous research conducted in Indonesia, utilizing cross-sectional data from the 2014 IFLS Wave 5, focused solely on household heads as the sample. The findings suggested that happiness in Indonesia is influenced by various factors, including income levels, employment status, age, years of education, and the health of the household head (Putri & Prasetyani, 2021). All these determinants exhibited a significant positive impact on the happiness levels of household heads. In contrast to prior studies employing logit regression, this case study adopts ordered probit regression, utilizing data from IFLS-5 and a sample comprising respondents aged 16 to 64 years old. This research primarily focuses on socioeconomic status, encompassing wealth level, employment status, education, age, residence, and religious adherence, in their influence on Indonesian society's happiness level. The wealth level variable is gauged by home ownership as the interest variable. In this context, many believe that wealth, particularly material assets like homeownership, positively affects happiness. However, previous studies that found a positive association between homeownership and happiness did not account for the quality differences of the homes owned. Consequently, while asset ownership may enhance happiness, it does so up to a certain threshold and does not hold over the long term. Experiential acquisitions are deemed to carry greater significance than material purchases (Han et al., 2023). This is attributed to their ability to manifest authenticity and persuasive impact, positioning individuals as more competent in the eyes of society.

The primary objective of this research is to gain a comprehensive understanding of non-material variables that impact the happiness levels of the Indonesian population, beyond income. It is anticipated that the findings of this study will contribute to the existing literature on fundamental factors influencing happiness and serve as input for government policies aimed at enhancing the well-being of Indonesian society.

The data used in this research are secondary data from the Indonesian Family Life Survey, fifth edition (IFLS-5) in the year 2014. IFLS is a large-scale longitudinal survey dataset for Indonesia, publicly available, and the most comprehensive of its kind. The survey results have represented the national population, covering approximately 83% of the population residing in 13 provinces. IFLS 5 is the only edition that provides the most recent data on happiness levels.

The variables required for this study can be found in IFLS-5 within the household (HH) book. This is based on the components of variables that form the model and originate from household variables. The survey collects information about an individual's level of happiness as the dependent variable. The measurement of this variable is extracted from the following questionnaire: "Considering your current circumstances, do you feel very happy, happy, just happy, unhappy, or very unhappy?".

This study employs an independent variable, wealth, which refers to homeownership. Homeownership is the status of owning the home one occupies during the census, determined by the member who occupies it. A home is considered self-owned if it is owned by the head of the household or one of its members. Control variables are limited to the Indonesian population aged between 16 and 64, individuals who have received an education, reside in urban areas, and follow the Islamic religion. Based on these criteria, the number of respondents participating in this study is 29,018 individuals.

This research utilizes cross-sectional data processed using the ordered probit regression approach. The ordered probit approach is a generalization of probabilistic analysis used for cases with two or more ordinal dependent variables. In this case, the happiness level, as the dependent variable, is a categorical variable with five meaningful categories. The advantage of using ordered probit over binary probit is that it can handle ordinal dependent variables, which have a natural order but no numeric spacing between categories. The ordered probit regression equation in this study is as follows:

= ₀ + ₁ ℎ + ₂ + ₃ + ₄ + ₅ ² + ₆ + ₇muslim + (1)

Based on the regression function above, the happiness variable as the dependent variable is categorized into five levels: very unhappy (first level), unhappy (second level), just happy (third level), happy (fourth level), and very happy (fifth level). Happiness can be characterized as an ongoing assessment marked by a prevalence of positive emotional states over negative ones, ultimately leading to a fulfilling and advantageous life (Bieda et al., 2017) (Elliot et al., 2018). Thus, in this context, happiness levels can be viewed from both objective and subjective perspectives.

Independent variables in the study include the wealth variable, measured from respondent’s perception of homeownership. Ownership of a home is coded as 1 if they have their own home and 0 if they do not. The job status variable represents employment status, indicating an individual's position in the workplace and its influence on their happiness level (Kun & Gadanecz, 2022). This variable is binary, with a value of 1 for those who are employed and 0 for those who are not. "Educ" encompasses the years of education attained by respondents. In the professional arena, accomplishing challenging tasks necessitates a continuous pursuit of higher education and the acquisition of increasingly advanced skills (Alekseeva et al., 2021); (Hershbein & Kahn, 2017). "Age" refers to the respondent's age in years. The choice of the age group from 16 to 64 years is based on the productive age group classification by Statistics Indonesia. Within this age range, there is a productive age group with higher productivity compared to older age groups due to physical limitations and other factors (Aprilyanti, 2017). "Urban" is based on the geographic residence of respondents, with a value of 1 if they live in urban areas and 0 if they reside in rural areas. The "muslim" variable is a binary dummy variable, with a value of 1 for those who follow Islam and 0 for those who are non-Islamic

Prior to discussing the regression results, summary statistics are used to provide a concise overview of a dataset, including key metrics that describe the central tendency and dispersion. Table 2 presents a summary of the statistical results for each variable used in this study. The dependent variable, which represents happiness levels ranging from 1 to 5, has an average value of 3.322, indicating a state of happiness.

Approximately 73.9% of the respondents own their own homes, with an average education level of 9 years, equivalent to the third year of junior high school. The average age of the participating sample is approximately 35 years, within the age range of 16 to 64 years. Of all respondents, nearly 61% are employed, and 59.4% reside in urban areas. Most of the sample adheres to the Islamic faith, with 90% of the total participants, considering that Indonesia is one of the countries with the largest Muslim population.

This study aims to seek out the role of socioeconomic status on happiness level of adult population in Indonesia. Table 3 displays the regression results using the ordered probit method. The information obtained indicates that all factors of socioeconomic status, including wealth level, education, age, employment status, place of residence, and Islamic religion, significantly affect the variable of happiness levels at a 5% significance level. However, the variables of age and employment status have a negative impact on happiness. This implies that an increase of one year in age will decrease happiness by 1.96%, and individuals who are employed have a 3.95% lower level of happiness. Based on Table 3, each level of happiness has a marginal effect that can indicate the probability change when independent variables increase by one unit for the dependent variable. Marginal effects with a positive sign can be interpreted as the independent variable influencing higher levels of happiness. In contrast, negative-sign marginal effects affect an individual's placement in lower levels of happiness.

Based on the estimation results for the wealth variable, it can be observed that individuals who own homes tend to experience greater happiness. This is evidenced by higher probabilities and a significant positive correlation of 1.45% to 5% for feeling happy and very happy. However, homeownership is significantly negatively correlated with the potential to feel very unhappy (0.62%), unhappy (2.96%), and just happy (2.87%). Feeling miserable encourages a person to become materialistic with the aim of improving their lives from material possessions (Mason et al., 2019) (Shrum et al., 2022). This principle is likely to affect an individual's social and economic aspects. Individuals who own homes are perceived as having high socioeconomic status, while those who do not own homes fall into the lower socioeconomic status category. In a developing country like Indonesia where not everyone can meet their basic needs, homeownership can significantly affect an individual's happiness. This aligns with the research which suggests that owning physical assets, like a house, contributes to an individual's sense of stability (Stewart et al., 2023). Having continuous access to such assets is key, and the loss or destruction of these possessions can lead to decreased happiness. A financially stable person is more likely to own their own house and experience greater happiness.

Happiness levels are also influenced by the duration of education pursued. Each additional year of education increases the probability of an individual feeling happy by 0.67% and very happy by 0.19%. Education serves as a gateway to a more promising future (Putri & Prasetyani, 2021). The higher the level of education attained, the greater the chances of developing connections and gaining better job opportunities. Therefore, education forms the foundation for an individual's future success. While education itself may not directly boost happiness, it enhances cognitive and spiritual abilities, leading to higher educational attainment. This, in turn, raises income levels, improves family social standing, and enhances access to health information, collectively contributing to overall well-being (FitzRoy & Nolan, 2017); (Huang & Grol-Prokopczyk, 2022); (Yang et al., 2022).

Furthermore, an increase in age decreases the probability of feeling very happy by 0.6% and completely happy by 0.17%. Each additional year of age increases the likelihood of individuals feeling happy by 0.34%, unhappy by 0.35%, and very unhappy by 0.07%. As people age, they tend to experience better financial situations, marital status, higher education, and psychological maturity (An et al., 2020). The happiness-age relationship is described as a trumpet shape, indicating that as people age, happiness decreases due to the increasing standard error at certain minimum points (Tomo & Pierewan, 2018). Afterward, happiness can increase again. Moreover, by utilizing data from seven datasets encompassing 51 countries and involving 1.3 million individuals aged 20 to 90, happiness follows a "U" shape (Blanchflower & Oswald, 2017). The results indicated that the lowest level of happiness tends to occur in one's 40s. This supports the study's findings, as increasing age can sometimes lead to changes in happiness and unhappiness. It cannot be denied that as people age, their expectations and burdens increase due to various factors.

Employment status significantly influences happiness levels negatively. Individuals who are employed tend to experience a decrease in their happiness. The generated probabilities increase feelings of being very happy by 0.07%, unhappiness by 0.71%, and just happiness by 0.69%. Employees often feel unhappy when they encounter improper work schedules, limited chances for career growth, conflicts with colleagues, concerns about the company's reputation, and being located far from home (Rahmi, 2019). An individual working in a poor environment experiences significant fatigue. Residential location in urban areas has a significantly positive impact on an individual's happiness. Individuals living in urban areas increase their happiness levels by 2.33% for being very happy and 0.67% for being happy. This is due to the modernization occurring in urban areas. Modernization brings about changes in governance, geographical conditions, education, stratification systems, human values, and personalities. Consequently, it encourages individuals to progress and feel assured. This aligns with the case study of Sub-Saharan Africa where people in urban areas are happier than people in rural areas across all socio-demographic categories (Burger et al., 2020).

The muslim variable has a significant and positive impact on an individual's happiness. Individuals practicing Islam have a probability of feeling very happy by 3.95% and happy by 1.14%. Due to Indonesia's predominantly Muslim population, people find it more convenient to access prayer facilities and infrastructure. This aligns with a previous study that Indonesian teenagers can easily engage in social media studies led by religious figures or attend sessions at nearby mosques (Hatta, 2019). It is important to note, however, that the sense of being accompanied by one's faith is universal among all devoted believers, but the mentioned conditions are specific to Indonesia's larger Muslim demographic.

The findings suggest that increasing homeownership in developing countries like Indonesia can boost happiness by providing stability and higher socioeconomic status. Extending education can also enhance happiness by improving job prospects and mobility. Tailored support for different life stages, especially middle age, can address dips in happiness. Improving work conditions and work-life balance can increase employee happiness. Urban modernization policies can further boost happiness for city residents. Recognizing the positive impact of religious practice on happiness, especially in predominantly Muslim areas, can guide planning to support religious activities and overall well-being.

This research provides empirical evidence that happiness levels are influenced not only by income but also by socioeconomic factors. Homeownership can enhance an individual's happiness. Other factors that significantly contribute to increased happiness include the years of education, residential location, and religious affiliation. Higher levels of education correspond to an increased likelihood of experiencing happiness. Individuals residing in urban areas tend to be happier compared to those in rural areas. Higher levels of happiness are also reported among individuals practicing Islam. However, age and employment status variables show a significant negative correlation. As one's age increases, the probability of feeling happy decreases. Employed individuals also tend to experience lower levels of happiness compared to those who are not employed. Nevertheless, both variables can still result in happiness at certain points.

Based on the marginal effects obtained, it is evident that the happiness of Indonesian society needs to be enhanced through socioeconomic policies. The existence of the Housing Liquidity Facility by the Ministry of Public Works and People's Housing is a positive step towards increasing homeownership across all segments of the population. However, this needs to be complemented by stronger synergy among the central government, local governments, and the community, so that everyone can have decent housing. Furthermore, there is a need for an improvement in the quantity and quality of both formal and non-formal education on a nationwide scale, policies to create a healthier working environment such as the establishment of minimum wages and universal compensation, and policies for the establishment of places of worship for all religious communities to ensure that non-Muslims can experience happiness equal to that of Muslims. Local governments should also engage in sustainable village development by determining appropriate village models. In addition to curbing urbanization, such policies can improve various aspects of rural life. The implication is that rural communities can experience happiness on par with urban communities. People should also be aware that they need to improve their standard of living in various aspects in preparation for their old age, including physical and psychological health. This research is limited by the data used from the Indonesian Family Life Survey fifth edition in 2014. Therefore, future research is expected to draw the latest micro dataset from other sources such as the National Socioeconomic Survey (SUSENAS) and Village Potential (PODES) data, enriching the literature on the fundamental factors of happiness in Indonesia.