Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. Economic Faculty. Universitas Muhammadiyah Ponorogo p-ISSN 1858-165X / e-ISSN 2528-7672 Regional Macro Policies for People's Happiness Ida Nuraini a,1,*. Candra Fajri Ananda b,2. Sri Muljaningsih c,3 Setyo Tri Wahyudid,4 a Universitas Muhammadiyah Malang. Bandung Street. Malang, 65113. Indonesia b,c,d Brawijaya University. Veteran Street. Ketawanggede. Malang, 65145. Indonesia 1 nurainiida@yahoo. 2 cfajri@ub. 3 muljaningsih@ub. id, 4 setyo. tw@ub. * corresponding author ARTICLE INFO Article history Received 15-1-2024 Revised 1-8-2024 Accepted 27-8-2024 Keywords Happiness Index Minimum Wage Income Inequality Gross Enrollment Rate ABSTRACT Currently, the most complete measure of community welfare is the happiness index because this measure is based on community This study aims to determine the effect of per capita income, minimum wage, income inequality and gross enrollment rates on the Happiness Index in Indonesia. The research objects are 34 provinces in Indonesia. The data used are secondary data for 2014, 2017 and 2021. The data source is the Indonesian Central Bureau of Statistics. Using the panel data regression, the results show that per capita income, income inequality, minimum wage and gross enrollment rates together have a significant effect on the happiness index. and partially the per capita income variable has no significant positive effect on the happiness index while income inequality has no significant negative effect on the happiness index, conversely the minimum wage variable and gross enrollment rate have a significant positive effect on the happiness index in Indonesia. In order to increase the happiness index, it is recommended that the provincial government periodically review the minimum wage policy, increase the gross enrollment rate and increase per capita income and reduce income inequality. This is an open access article under the CCAeBY-SA license. http://journal. id/index. php/ekuilibrium Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. Introduction 71,49 68,28 70,69 Currently macroeconomic indicators such as Gross Domestic Product per Capita have not been able to provide an adequate picture in describing the living conditions or welfare of individuals in a society. Meanwhile, in its development the indicator to see welfare no longer uses per capita Gross Domestic Product but uses the Human Development Index because the Human Development Index is considered to have the advantage of multidimensional human development which includes the dimensions of living standards, education and health (Paliova et al. , 2. However, in its development, welfare can no longer be measured from macro indicators such as health, education and standard of living. Welfare is seen more in terms of subjective welfare indicators in the form of happiness. The currently developing happiness indicator is the happiness index . ellbeing inde. The happiness index is the level of happiness or life satisfaction of the Indonesian population on a scale of 0-100 (Al, 2. The 2014 happiness index method is a composite index that measures the level of satisfaction with 10 important elements in life, namely . health, . education, . employment, . household income, . family harmony, . availability of free time, . social relations, . housing and asset conditions, . environmental conditions, and security conditions, . security conditions (Central Bureau of Statistics, 2. The level of community happiness is a benchmark in determining the achievement of Communities in countries with high levels of welfare tend to be happier because welfare indicates the fulfillment of people's desires, so that the possibility of people's hopes for happiness is greater (Kumalasari & Murjana, 2. Happiness includes living a happy life means having pleasant living conditions, being healthy and having a meaningful life (Badan Penelitian dan Pengembangan Kota Magelang, 2. Below is a graph of the Indonesian people's happiness index based on the survey results for 2014, 2017 and 2021. Figure 1. Happiness Index Graph in Indonesia Source: Central Bureau of Statistics, data processed The figure 1 shows the development of the happiness index which continues to increase 49 in 2014 to 70. 69 in 2017 and 71. 49 in 2021. Based on the list of the happiest countries in the world. Indonesia is ranked 86 out of 146 countries (Blanchflower & Bryson, 2. The greater the happiness index value indicates the higher the happiness level of the Conversely, when the index value is lower, the level of happiness of the population will also be lower (Harumi & Bachtiar, 2. Indonesia's happiness index in 2022 is ranked 21st out of 35 countries in Asia with 5. 28 points, while the average point for Asian countries is The first ranking is Israel with 7. 47 points and the last ranking is Afghanistan with 1. points (The World Happiness Indeks Report, 2. The World Happiness Index states that an individual's condition to reach a point of happiness or misery is influenced by two factors. Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. namely external or environmental factors such as income level and type of work and internal factors or individual conditions such as physical or mental health, family experience, level of education and gender (Helliwell et al. , 2. In economic development, gross domestic product (GDP), inflation rate, and economic growth cannot be used to describe the level of happiness of a society or individual, this is because the happiness index is influenced by material and non-material aspects. The material aspect is the fulfillment of basic needs, namely clothing, food, and shelter, while the nonmaterial aspect is education or social relations with various levels of society (Landiyanto et al. Many studies have been conducted to analyze the factors that influence welfare, one of which is per capita income. Azhar . in his research stated that Gross Regional Domestic Product (GRDP) Per Capita does not have a significant effect on the happiness index in Indonesia. Because GDP per capita has not been able to influence the level of happiness in Indonesia, it means that people who have high incomes are not necessarily accompanied by Gross Domestic Product as a measure of government economic performance can be generally recognized, but Gross Domestic Product as a single measure does not provide policy makers with sufficiently accurate information about how the economy is working for its It is therefore important for policy makers to identify areas that require priority (OECD, 2019. The results of the study on the relationship between the Gini ratio and happiness explain that the Gini ratio variable . has a negative and insignificant effect on the level of happiness in Indonesia, every 1% increase in the Gini ratio will have an impact on a decrease in the happiness index by 22% or in other words the higher the inequality or gap, the lower the level of happiness of individuals or society (Purwanti, 2. Inequality occurs due to government policies that are less supportive so that some groups of people cannot enjoy the benefits of development compared to other groups of people. The contemporary Gini coefficient has a significant negative impact on individual happiness (Latif. From the description above, it shows that regional macro conditions such as income inequality, regional economic growth, inflation and the quality of human resources can affect subjective well-being. In this case, it means that the government is required to prosper the people through the policies that are implemented. Helliwell . in his research findings said that the quality of government will have an effect on welfare. The size of social capital, especially trust, both general and specific, will affect welfare. Based on the background previously described, this study aims to measure the effect of regional macro variables on the level of people's happiness. The regional macro variables include GRDP per capita, the gini ratio, the provincial minimum wage and the education level of the population. If the influence of several regional macro variables on the happiness index is known, it can be useful for regional governments in deciding regional policies related to community happiness. Happiness is also positively influenced by the level of education. The higher the education the higher the acceptance or income. If income is still an important element in determining happiness, then the higher the education, the higher the income and happiness (Rahayu et al. , 2. Research on how education increases happiness in East Asia, namely Japan. South Korea. Taiwan and China, reveals that individuals who receive more education have wider social networks, these living conditions are positively related to happiness. increasing one's ability and tendency to connect with the wider social world and education will be able to improve one's subjective well-being (Chen, 2. Income has an important function in influencing welfare. Higher income will increase Happiness is influenced by several multidimensional factors such as the environment, regular work, income, and recreational activities (Januwarsono, 2. Welfare Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. is subjective/not related to income but positively related to satisfaction with basic needs (Fuentes & Rojas, 2. Helliwell . , in the results of his research said that the quality of government will affect welfare. The size of social capital, especially trust, both general and specific, will affect If in the research on happiness above, most of them use a subjective approach and use primary data, and some other researchers use secondary data but only use one or two variables, then in this study the approach used is spatial by using secondary data from several regions and more variables. Therefore, the purpose of this study is to measure the influence of regional macro variables on the level of community happiness. These regional macro variables include GRDP per capita. Gini ratio, provincial minimum wage, and population education If the influence of several regional macro variables on the happiness index is known, then the results of this study can be useful for local governments in deciding regional policies related to increasing community happiness. The results of this study can also contribute to the development of science related to the development of welfare theory and concepts of regional development performance. Literature Review The Basic Theory of Happiness Easterlin explains the existence of the Set Point theory in psychology. The existence of a set point or level of happiness will be influenced by various life events such as marriage, job loss and accidents. In addition, with social comparison, a person will judge the quality of his life relatively and not absolutely by comparing it with other When a person gets a salary/income increase it doesn't necessarily increase his happiness because he will compare it to other people's income (Easterlin & OAoConnor, 2. Population welfare indicators can be seen from two types of indicators, namely subjective well-being indicators and objective well-being indicators, and Policy makers both in terms of development planning and evaluation in various countries basically agree to use welfare indicators with a larger portion than macroeconomic indicators because welfare indicators better reflect the real condition of people's welfare (OECD, 2019. Welfare measures should include various factors that significantly affect life and well-being (Stiglitz J. Some of the various theories quoted from Crisp, . The theory of hedonism from Jeremy Bentham, one of the famous hedonists, says that "Nature has placed mankind under the rule of two sovereign rulers, namely pain and According to this theory what we should do depends on pain and pleasure. The more pleasure one can put into one's life, the better it will be, and the more pain one encounters, the worse it will become. Desire theory. Economists see human well-being as consisting in the satisfaction of preferences or wants. This satisfaction will depend on the choices made by the individual so that it will allow preference ranking. Development of Auutility functionsAy for individuals and methods for assessing preference-satisfaction values, for example, using money as a The Gross Regional Domestic Product (GRDP) has no significant effect on the happiness index in Indonesia (Wiyanti et al. , 2. This shows that high-income people do not necessarily have a high level of happiness. And conversely, people with low incomes do not necessarily feel unhappy. Behera et al. , . in a study of people's happiness or life satisfaction in 166 countries using observation years from 2005 to 2020 showed that per capita income, social support and freedom to make life choices have a positive impact on The research findings also show that increasing per capita income in developing Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. countries tends to decrease happiness. This is in line with Easterlin's work which states that although income generally increases happiness, a saturation point still exists. Based on the results of a survey conducted by the Central Statistics Agency. Indonesia's happiness index in 2014 was 68. 28 on a scale of 0-100 which was carried out using a life satisfaction approach consisting of 10 indicators, namely health, education, work, household income, family harmony, availability of free time, social relationships, housing conditions and assets, environmental conditions and security conditions. This happiness index increased compared to 2013 which was 65. The measurement of the happiness index was carried out through the Happiness Index Measurement Survey with a sample coverage of 70,631 heads of families in all provinces. The composition of respondents was more in urban areas than in rural areas with a composition of 57. 84% of respondents in urban areas and 42. 6% of respondents in rural areas with a balanced gender of 50. 98% male and 49. 02% female. The three aspects of life that provided the highest contribution were household income . 64%), housing conditions and assets . 22%) and work . 12%). The productive age population . has a higher happiness index compared to the population over 65 years old, which is 24% (Central Bureau of statistics, 2. Indonesia's happiness index in 2017 increased to 70. The measurement of the happiness index in 2017 experienced a change in dimensions compared to 2014. The happiness index in 2014 only used the dimension of life satisfaction, so in 2017 the dimensions of feelings (Affec. and the dimension of the meaning of life . were added. The feeling dimension has 3 indicators, namely happy, not stressed and not worried, while the meaning of life dimension consists of 6 indicators, namely self-acceptance, life goals, environmental mastery, independence, positive relationships with others and selfdevelopment. Another change is that life satisfaction is divided into two sub-dimensions, namely the sub-dimension of personal life satisfaction and the sub-dimension of social life In the 2017 survey, the happiness index of men was greater than that of women and the older the age, the lower the happiness index. Meanwhile, the older a person is, the higher the dimension of feelings (Affec. until the age of 64 years and after that it will decrease. Likewise, the sub-dimension of social satisfaction will increase as a person ages up to 64 years. The happiness index for 2021 was 71. 47 or an increase compared to 2017. In 2021, a new method was used for measuring the index, where 2017 became the basic year for measuring happiness due to the development of the happiness index framework, which in 2014 only had one dimension, which changed to 3 dimensions in 2017. and in 2021, there will be an addition of the Feeling dimension and the Meaning of Life dimension to the Happiness Index measure. In 2021 it remains consistent with 2017 that urban residents have a higher happiness index than rural residents, and male residents have a higher happiness index than female residents (Central Bureau of statistics, 2. The Gini ratio variable which shows the level of income inequality has a negative and insignificant effect on the level of happiness in Indonesia and in general the income of individuals in big cities is relatively higher than the income of individuals in regions or small towns, but high income is followed by high living costs and competition. life that has an impact on the level of happiness. Therefore, income inequality . he gini rati. does not directly or significantly affect happiness in Indonesia (Purwanti, 2. The results of this study indicate that income does not affect individual or community happiness, but because the regression coefficient is negative, it means that the higher income inequality will reduce the level of individual or community happiness. Ugur, ( 2. in his research findings said that inequality in income distribution as measured by the Gini Ratio has a negative effect on subjective wellbeing. Meanwhile, perceptions of freedom and perceptions of social mobility mediate the Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. relationship between inequality and subjective well-being. Ryzer, . revealed his findings that there is a less strong positive relationship between income inequality and the subjective well-being of people in countries with high levels of social and institutional trust. A weak negative relationship between income inequality and people's subjective well-being occurs in countries that adhere to egalitarian norms. The positive relationship between happiness and income can also be influenced by This shows that income is still an important element in determining happiness, the higher the education, the higher the income and the higher happiness (Rahayu et al. Highly educated individuals have wider social networks, these living conditions are positively related to happiness. Income is positively related to other measures of subjective well-being, including happiness. Income plays an important role in influencing well-being, higher income will be able to increase happiness (Sacks et al. , 2. Research Method This study selected objects in 34 provinces in Indonesia using time series data from 2014, 2017 and 2021 obtained through documentation from the Central Bureau of Statistics of Indonesia. The reason for choosing 2014, 2017 and 2021 was based on the availability of complete survey data in all provinces and the survey was conducted in that year. The analysis tool used was panel data regression with a total of 102 observations. The panel data in this study is a combination of cross-section data and quantitative time series data. Cross-section data in the form of 34 provinces and time series data in the form of observation year data, namely 2014, 2017 and 2021. The regression equation model used is Y = a b1X1 b2X2 b3X3 b4X4 e, where the independent variables consist of X1, namely the gross regional domestic product in million rupiah. X2 is the regional minimum wage in rupiah. X3 is the gini ratio . X4 is the gross participation rate . n percen. and e is error. The dependent variable (Y) is the happiness index. The regression analysis model used is to choose the right model, whether the Common Effect Model. Fixed Effect Model and Random Effect Model. choose the right model, three stages of testing are carried out, namely the chow test, the hausman test and the lagrange multiplier test. Before the data is subjected to regression testing, the initial stage is to conduct a test to select the best model. The initial stage carried out is the chow test. If the cross-section probability (F) > 0. 05, then the common effect model is more appropriate to use, conversely, the cross-section probability (F) < 0. 05, then the fixed effect model is more appropriate. The next test is the Hausman test. If the cross-section probability (F) > 0. 05, then the random effect model is used, if the cross-section probability (F) < 0. 05, then the fixed effect model is more appropriate to use. The Lagrange Multiplier test is used to test the model between the common effect and random effect models. If the Breusch Pagan probability value < 0. 05, then using the Random Effect model is more appropriate. Conversely, if the probability > 0. 05, then the Common Effect Model is chosen. Results and Discussion The happiness index of Indonesian society continues to increase according to survey data from 2015, 2017 and 2021, although between provinces there are large differences in the happiness index figures, but not too far. In 2021, most have reached a value of 70 and above. The development of the happiness index between surveys can be seen in the following graph: Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. Figure 2. Happiness Index Graph by Provinces in Indonesia Source: Central Bureau of Statistics, data processed The figure 2 of the Indonesian people's happiness index above shows an increase in the happiness index in all provinces from 2015 to 2017 and 2021. In 2021 there are 10 provinces with the highest happiness index in a row as follows: North Maluku . Kalimantan North . Maluku . Jambi . North Sulawesi . Riau Islands . Gorontalo . West Papua . Central Sulawesi . and Southeast Sulawesi . Of the 10 provinces, none of the provinces on the island of Java are included in the top 10 of the highest happiness index. If it is related to per capita income in figure 2, such as DKI Jakarta with the highest per capita income, the people's happiness index will only be 68 in 2021 and Maluku. North Maluku and Gorontalo which have low per capita income but their people's happiness index is higher than other provinces. This indicates that the happiness index has nothing to do with income. However, this is only limited to a sample of several provinces, for statistical proof a test must be carried out as will be explained below. To test several variables that affect the happiness index as in the graph above, whether the variables of per capita income, minimum wage, income inequality and education level are used regression. While to determine the right regression model whether the fixed effect model, common effect model or random effect model is carried out through testing stages, namely the Chow test, the Hausman test and the Lagrange multiplier test. The test results can be seen in the following table: Table 1. Chow Test Effects Test Cross-section F Cross-section Chi-square Statistic . Prob. Source: Secondary data, processed The results of the chow test in table 1 show that the probability F = 0. This value is smaller than 0. 05, which means that the fixed effect model is more appropriate than the common effect model. Table 2. Hausman Test Test Summary Cross-section random Chi-Sq. Statistic Source: Secondary data, processed Chi-Sq. Prob. Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. The results of the Hausman test in table 2 show that the probability F = 0. This value is greater than 0. 05, which means that the Random effect model. Because the results of the Chow test show that the fixed effect model is more suitable, while the Hausman test shows that the random effect model is more suitable, a Lagrange multiplier test is needed to choose between the fixed effect model or the random effect model. The following are the results of the Lagrange multiplier test. Table 3. Lagrange Multiplier Test Breusch-Pagan Honda King-Wu Standardized Honda Standardized King-Wu Gourieroux, et al. Cross-section . Test Hypothesis Time . Both . Source: Secondary data, processed The results of the Lagrange multiplier test show that the Breusch-Pagan probability is 0000, which means that the random effect model is more suitable. The following is a random effect model: Table 4. Regression results of the random effect model Variable GRDP Per capita (X. Minimum Wage (X. _ Gini Ratio (X. _ Gross enrollment rate (X. _ Root MSE Mean dependent var dependent var Sum squared residu Durbin-Watson stat Source: Secondary data, processed Coefficient Std. Error t-Statistic Weighted Statistics R-squared Adjusted R-squared of regression F-statistic Prob(F-statisti. Prob. Based on the results of the best model selection test, it was found that the random effect model was the best model based on table 4. So a hypothesis test was carried out with the random effect model. So the model equation is obtained as follows: Happiness index = 57. 34X1 1. 38X2 - 7. 73X3 0. 15 X4 1,19. The model equation explains that a constant value of 57. 65 means that if all other variables are assumed to be zero, then the happiness index in Indonesia is 57. The per capita GRDP variable (X. has a positive and insignificant coefficient, meaning that every 1% increase in per capita GRDP will increase the happiness index by 4. 34, but this effect is not significant. The regression coefficient of the minimum wage variable (X. is also positive, meaning that every 1% increase in the minimum wage will significantly increase the happiness index by 1. 38 and each increase in the Gini ratio index 1 (X. will decrease the Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. happiness index by 7. 73 but this effect is not significant. A significant increase in the gross enrollment rate (X. of 1 will increase the happiness index by 0. GRDP per capita has no effect on the happiness index because the probability is greater These results are in accordance with Malia & Hamzah, . which proves that GRDP per capita has a positive but not significant effect on the happiness index. This means that during the periods of 2014, 2017 and 2021, the GRDP per capita has not been able to increase the happiness index. Based on the provinces in Indonesia, the high per capita income of the Indonesian people can be seen in the following graph: Figure 3. Gross Regional Domestic Product Per Capita by Province 2015, 2017, 2021. Source: Central Bureau of Statistics, data processed Indonesia's Gross Domestic Product Per Capita in 2015 was IDR 35,161,890, - in 2017 it was IDR 37,851,370, - and in 2021 it was IDR 40,780,310, -. Based on the GRDP Per Capita graph, in 2021 there were only a few provinces in Indonesia whose GRDP was above Indonesia's GDP Per Capita, such as Bali Province. Riau Islands. DKI Jakarta. East Kalimantan. North Kalimantan. Central Sulawesi, and West Papua. DKI Jakarta is the province with the highest per capita income, in 2021 it had a GRDP per capita of IDR 174,941,720. - The province with the lowest GRDP is East Nusa Tenggara, which is IDR 13,092,810. - The amount of this gross regional domestic product does not have an impact on the happiness index. When a person gets an increase in income it will not necessarily increase his happiness because he will compare it with other people's income (Easterlin & OAoConnor. However, the graph above actually shows the high inequality of per capita income in Indonesia. Gross regional domestic product per capita can generally be used as an indicator of welfare, but it is not the only indicator. Therefore, the statistical results show insignificant results, but the direction of the coefficient is positive, which means that an increase in gross regional domestic product will have an impact on increasing the happiness index. Income per capita on the one hand has weaknesses in determining happiness, but the government must continue to spur an increase in this gross regional domestic product per capita evenly, so that GRDP per capita can be strongly correlated with people's happiness. Bannister & Mourmouras, . in their research in 151 countries said that there is a close relationship between income per capita and Gross Domestic Product. Therefore, in taking development policies, especially in the context of improving people's welfare, the government cannot only focus on increasing gross domestic product or economic growth, but must consider nonmaterial aspects such as improving the quality of health, education, security, peace, and Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. quality of public services. Data from two large-scale studies show a weak correlation between income and happiness, but there are differences in average happiness between rich and poor groups (Lucas and Schimmack, 2. The regression coefficient of minimum wage is 1. 38 with a probability of 0. 00, which means that minimum wage has a significant positive effect on the happiness index. The higher the minimum wage, the higher the happiness index. This is in line with the basic needs theory which states that individual welfare depends on the fulfillment of basic needs such as food, shelter and health. In this case, wages play an important role in meeting needs. Individuals whose wages are below a certain level cannot meet basic needs and are not able to achieve welfare (Doyal & Gough, 1. Likewise, in the theory of social comparison, it is stated that a person's well-being does not only depend on absolute wages but also on the comparison of wages with others around them. If someone feels that their wages are lower than others, it will reduce their well-being (Festinger, 1. When a person gets an increase in income it will not necessarily increase his happiness because he will compare it with other people's income (Easterlin & Connor, 2. Wages that can absolutely meet the basic needs of employees will increase work productivity, thereby having an impact on increasing production and this will have a macro impact on increasing economic growth. Based on table 4, it can be seen that the probability value of the gini ratio variable is 13 or > 0. 05, so it can be said that the gini ratio variable has no effect on the happiness index. Wahyudi & Tiara . in their research stated that income inequality using the gini ratio index measurement tool has a significant negative effect on the level of happiness of the If an area's income distribution becomes more unequal, it means that there are large differences in income in society and differences in participation so that the level of happiness becomes lower. He et al . in his research using aggregate data from all rounds of the European and World Values Survey between 1981 and 2004 concluded that inequality accumulates negatively with life satisfaction, meaning that the higher income inequality, the lower life satisfaction. The probability value of the gross enrollment rate is 0. 00 or <0. 05, which means that the gross enrollment rate variable has a significant positive effect on the happiness index with a coefficient of 0. 15, which means that a 1 percent increase in the gross enrollment rate will increase the happiness index by 0. The gross enrollment rate reflects the percentage of the population attending school at a certain level of education . egardless of ag. to the number of school-age population that corresponds to that level of education. Education is the main thing that is very important for the sustainability of a country (Yasir et al. , 2. Each individual also has factors that bring happiness to him, these factors include money, marital status, social life, age, health, negative emotions, education, climate, race, gender and religion or a person's level of religiosity (Zhahira & Utami, 2. The higher the education, the higher the welfare, because education can increase access to non-alienated economic resources and paid work can increase a sense of control over life, as well as the stability of social relationships, especially marriage, which increases social support (Ross & Willigen, 1. The adjusted R-squared value shows a result of 0. 64 with a probability (F statistic of 00<0,. ) which means that together the variables of gross regional domestic product, regional minimum wage. Gini ratio and gross participation rate are significantly able to influence the happiness index by 64% while the remaining 36% of the happiness index is influenced by other variables outside this research model. The results of this study are in line with the statement of the Central Bureau of Statistics . using the 2014 happiness index method, which is a composite index that measures the level of satisfaction with 10 important elements in life, namely . health, . education, . Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. employment, . household income , . family harmony, . availability of free time, . social relations, . housing and asset conditions, . environmental conditions, and security . security conditions. The results of this research are similar to Livingston et al. Individual well-being is influenced by income, mental health, physical health, education, social relationships, employment, discrimination, government policies and environmental conditions. Conclusion The happiness index is one of the newest indicators used to measure people's welfare. This happiness index approach is more subjective. The happiness index is formed from 3 main dimensions, namely the dimension of life satisfaction, the dimension of feelings and the dimension of the meaning of life. The research results show that several variables that influence the happiness index are regional gross domestic product per capita, regional minimum wage, income inequality and Regional minimum wages and education are variables that need to be given top priority in formulating policies to increase the happiness index. The policy of increasing gross regional domestic product per capita will increase people's purchasing power and thereby improve their welfare. Meanwhile, a minimum wage policy that can accommodate workers' basic needs will help improve their welfare. Per capita income has a direct relationship with the happiness index. Another policy is to reduce relative income inequality between residents in one region. For this reason, residents in the low-income group must be prioritized for improvement so that inequality is reduced. The results of the study show that several variables that affect the happiness index are regional per capita gross domestic product, regional minimum wage, income inequality and The four variables together have a significant effect on the happiness index, but partially only two variables have a significant effect, namely the regional minimum wage and Per capita income and income inequality have no effect on the happiness index, but per capita income has a direct relationship with the happiness index and income inequality has an inverse relationship with the happiness index. Regional macro policy models in increasing the happiness index that need attention are wage policies or policies on setting minimum wages and increasing public education. Meanwhile, an increase in economic growth is needed because it has a positive relationship with people's happiness. Likewise, income inequality which has a negative relationship with happiness means that income distribution policies need to get a priority portion besides growth policies. From the results of the research that has been done, it is suggested especially to the provincial regional government that increasing the index of people's happiness can be done through a wage policy. The minimum wage setting policy must be carried out carefully and the minimum wage setting should always adjust to the increase in the inflation rate for each Don't let the minimum wage policy burden one party, whether it's just the workers or the employers. Wage policies that favor one of the interested parties will cause the market to not work efficiently, can create tension between workers and employers so that it can have an impact on termination of employment or have an impact on waves of protests that disrupt economic and political stability. For this reason, the policy for determining minimum wages must be carried out with studies of the minimum basic needs of workers in each region. Another suggestion to local governments is a policy to improve the quality of public education and create inclusive education by increasing the gross enrollment rate or increasing the percentage of the population attending school and providing educational opportunities for Ekuilibrium: Jurnal Ilmiah Bidang Ilmu Ekonomi Vol. No. : September, pp. all children regardless of physical or social limitations. This can be done by increasing educational subsidies, improving educational facilities and infrastructure, facilitating access to education, educational assistance for underprivileged families and access to education for children with special needs so that education at all levels can be reached by all levels of society. To increase the gross regional domestic product, it is necessary to increase sectoral For this reason, both sectoral labor productivity and sectoral investment productivity need to be increased. Another policy is to reduce income inequality among residents in one region. The priority of the regional government is to increase the income of low-income groups so that income disparities can be reduced. Policies can be implemented through access to cheap credit to create new businesses, access to employment, a progressive tax system and increasing distributive government spending. Acknowledgment The researcher would like to thank the Doctoral Program in Economics. University of Brawijaya Malang and the Faculty of Economics. University of Muhammadiyah Malang as well as those who helped complete this research. References