The Influence of Women's Development and Empowerment on Inclusive Economic Growth

: Inclusive Economic Growth in Indonesia is formed through aspects of economic growth, inequality, and access to opportunities. Equitable development and empowerment that is focused on women provide access to opportunities in realizing inclusive economic growth. This research was conducted with the aim of knowing the effect of women's development and empowerment on inclusive economic growth in provinces in Indonesia in 2012-2021. This research uses secondary data, uses a quantitative approach with the method of panel data regression analysis with a fixed effect model. The regression results found that women's development variables through the gender development index indicator showed that women's life expectancy had a significant negative effect, while the average length of schooling for women and women's per capita expenditure had a significant positive effect. The variable of women's empowerment through the gender empowerment index indicator found that women's involvement did not have a significant effect on inclusive economic growth and the variables of women as professionals and contribution of women's income had a significant positive effect on inclusive economic growth in 2012-2021. Four of the six variables showed significant positive results. This indicates that the development and empowerment of women can improve welfare which affects growth. There needs to be a policy formulation on women that must be carried


Abstract: Inclusive Economic Growth in Indonesia is formed through aspects of economic growth, inequality, and access to opportunities. Equitable development and empowerment that is focused on women provide access to opportunities in realizing inclusive economic growth. This research was conducted with the aim of knowing the effect of women's development and empowerment on inclusive economic growth in provinces in
. This research uses secondary data, uses a quantitative approach with the method of panel data regression analysis with a fixed effect model. The regression results found that women's development variables through the gender development index indicator showed that women's life expectancy had a significant negative effect, while the average length of schooling for women and women's per capita expenditure had a significant positive effect. The variable of women's empowerment through the gender empowerment index indicator found that women's involvement did not have a significant effect on inclusive economic growth and the variables of women as professionals and contribution of women's income had a significant positive effect on inclusive economic growth in [2012][2013][2014][2015][2016][2017][2018][2019][2020][2021]. Four of the six variables showed significant positive results. This indicates that the development and empowerment of women can improve welfare which affects growth. There needs to be a policy formulation on women that must be carried out by each region to help fulfill women's rights and reduce gender discrimination.

Introduction
The success of a country's development can be seen from economic development that can prosper its people. One of the characteristics of economic prosperity is that all people can enjoy the results of development without exception. This is the goal of inclusive economic growth. Inclusive Economic Growth in Indonesia is formed through aspects of economic growth, inequality, and poverty, as well as access and opportunity (Bappenas). So that women's development and women's empowerment related to gender equality have relevance to inclusive economic growth.
The phenomenon of women's development and women's empowerment has been attached to the issue of gender equality which has been widely discussed in many countries. Women are considered to have shown their existence in the fields of health, education, social and economic inequality. This was proven by previous research (Adika, 2021) which discussed gender inequality, showing that the results of the Life Expectancy of Women and the Average Years of Schooling for Girls showed a positive influence on Inclusive Development. In line, the research conducted (Nguyen, 2021) shows that gender equality in education has a positive impact on economic growth and good health will increase economic complexity. Research has re-proved the role of women (Matthew, 2020) that the involvement of women in social, economic and political roles will increase productivity which will have an impact on economic growth.
In Indonesia in realizing gender equality towards inclusive economic growth, there are still several problems. Among them, gender inequality still occurs in Indonesia, especially those related to basic human needs. According to the World Economic Forum, Indonesia is ranked 101st in the Global Gender Gap Index category. This ranking is lower when compared to several other ASEAN countries, namely the Philippines ranked 17th, Singapore ranked 54th, Timor Leste ranked 64th, Thailand ranked 79th and Vietnam ranked 87th.
Source: Global Gender Gap Report, 2022 Figure 1 health, education, and the economy taking into account equality between men and women (Rahmawati, 2021). In the last 10 years, male human development has shown a higher value than female human development. This is evidenced in the graph below, based on the category HDI for men has achieved HDI above 70 units, namely in the "high" category since 2012. Conditions are different for women's HDI achievements which are still included in the "medium" category, even up to 2020.
Source: BPS, 2022 Figure 2. Development of Total Human Development Index and Human Development Index by Gender in 2012-2021 Furthermore, the Gender Empowerment Index (IDG) indicates whether women can play an active role in economic, political, and decision-making life. The IDG indicator is seen from its three forming components, namely the involvement of women in parliament, women as professionals, and women's income contribution or income distribution. One way to evaluate the success rate of women's empowerment is by measuring IDG. The following contains the development of IPG and its components in Indonesia in 2017-2021.
Source: BPS, 2022 Figure 3. Gender Empowerment Index and Its Components in Indonesia 2017-2021 Based on the figure above, the development of the gender empowerment index and its components shows a slowly increasing trend over the last five years. indicators show that gender empowerment is caused by a significant increase in women's involvement in parliament in 2019, then an increase in the percentage of women as professionals in 2020 and 2021. From this, it can be interpreted that gender empowerment in Indonesia from 2017-2021 has progressed slowly. Seeing that the implementation of development and empowerment of women has not been maximized, can it increase quality economic growth. In this research, through the topic of women's development and empowerment it is interesting to develop. The extent to which the role of women in development can affect economic growth. This research has a research gap, namely that there are not many studies that raise gender issues related to inclusive economic growth. The interesting thing about this study is that it uses the IPG variable indicators, namely women's life expectancy, the average length of schooling for women, women's per capita expenditure and the IDG variable consisting of women's involvement in parliament, women as professionals, and women's income contribution to see inclusive economic growth of gender. This research is important to study because it focuses on measuring the effect of inclusive economic growth in terms of women's development and women's empowerment with provincial analysis units throughout Indonesia for 10 years and refers to each of the indicators forming the IPG and IDG.

Research Method
This study was designed using a quantitative approach. The discussion refers to the data obtained and then processed, which is then presented systematically. The scope of this research is in Indonesia which was conducted in provinces throughout Indonesia. The population and samples determined in this study are all provinces in Indonesia, totaling 34 provinces. This study uses secondary data so that researchers do not need to go directly to the field to conduct research. Furthermore, it is necessary to use several methods of data analysis to answer the problems that have been formulated. The analytical method used is panel data regression analysis. Panel data is a data set that contains individual sample data (households, companies, districts/cities, etc.) for a certain period (Ekananda, 2014). This study will examine and analyze the influence of inclusive economic growth which acts as the dependent variable. Women's development consists of the variables Women's Life Expectancy, Average Years of Schooling Women, and Women's Per Capita Expenditure while women's empowerment consists of the variables of Women's Involvement in Parliament, Women as Professionals, and Women's Income Contribution acts as the independent variable. To strengthen the model, research  says that many strong variables affect economic growth including investment, initial per capita income, and human resources. So that this research forms the basis of this study choosing robust variables as strong variables that affect economic growth. The following model will be used in the panel data regression estimation technique, among others.
= 0 + 1 1it + 2 2it + 3 3it + 4 4it + 5 5it + 6 6it + Penanaman Modal Dalam Negeri : 1,2,3,4,5 (data cross-section of provinces in Indonesia) : 1,2,3,4,5 (time series data for 2012-2021) : Error Understand the panel data estimation method which will then be carried out with regression to determine the best model. After finding the best model, classical assumption testing is carried out. The last stage is to make interpretations and conduct discussions. From the explanation of the panel data analysis method, it can be described in the following panel data regression framework.

Result and Discussion Result
The first stage in panel data analysis is to perform panel data regression testing with three model selection techniques. After carrying out these three tests, then data analysis can be carried out with the best approach. Following are the results of the three best approach tests: https://equatorscience.com/index.php/jabter  (2023) Based on Table 1, the probability value of the Chow test is 0.0000, which means that the best model between the Common Effect and the Fixed Effect chosen is the Fixed Effect because the probability value of the chi-square is less than 0.5%. The selected model from the Lagrange Multiplier test is the Random Effect with a probability value of 0.0000. The Hausman test results show a probability value of 0.0000, indicating that the best model is the Fixed Effect because the probability value of the chi-square is less than 0.5%.
When the Chow Test was carried out and the Fixed Effect was selected compared to the Common Effect, it meant that there was heterogeneity in each individual but the intercept was the same throughout the observation time (time-invariant). The second test is the Lagrange Multiplier test and the Random Effect model is selected, meaning that there is heterogeneity in each individual with a different impact. After the two models have been selected, it is continued with the Hausman test to determine which model is the best Fixed and Random. The test results show that the selected one is the Fixed effect model which shows different characteristics with the presence of individual effects during the observation time (Widarjono, 2013).

Fixed Effect Estimation Results
The statistical test results show that the selected model is the Fixed Effect, along with the regression results shown in the table below: Based on the table above the results of the Fixed Effect regression model, it is concluded that the Life Expectancy variable has a significant influence on the probability level below 10% on IPEI. Variable Average Years of Schooling for Women, Expenditure Per Capita of Women, and Women as Professionals have a significant influence on the probability level below 1% on IPEI. Meanwhile, the variable Women's Involvement in Parliament has no significant effect on IPEI. Furthermore, hypothesis testing is carried out, namely the coefficient of determination test. This test is carried out to provide an overview of the ability of the independent variable to explain the dependent variable. The results of the Fixed Effect model regression show an R-square value of 0.559 meaning that only about 55% can be explained by women's AHH, women's RLS, women's per capita expenditure, women's involvement in parliament, women as professionals, and women's income contribution, the remaining 45% is explained by other variables outside the regression model or there are other factors.

Multicollinearity Test
The multicollinearity test aims to test the existence of a correlation between independent variables. The basis for making this test decision is to use a correlation value. If the correlation value between variables exceeds 0.8, multicollinearity is suspected. The following results of the multicollinearity test show that the correlation value between the independent variables has a correlation number of less than 0.8. Based on the results of the heteroscedasticity test, it shows that the prob>chi2 value is less than 0.05, so there is heteroscedasticity in this model. The problem of heteroscedasticity has been overcome by cluster testing when performing regression equations using Stata.

Autocorrelation Test
The autocorrelation test is carried out to find out whether there is a correlation between members of the observation with one another at different times. In testing autocorrelation, the following hypothesis is used: H0: There is no autocorrelation H1: There is autocorrelation If prob> 0.05 then H0 is accepted and there is no autocorrelation. If prob <0.05 then H0 is rejected, H1 is accepted and autocorrelation occurs. Following are the results of the autocorrelation test: Based on the autocorrelation test results, it shows that the Prob>chi2 value is less than 0.05, so there is an autocorrelation problem in this model. Autocorrelation problems have been overcome by cluster testing when doing regression using Stata.

Discussion
The regression coefficient for the female AHH variable is -0.0450. This has a significant negative effect on inclusive economic growth. When the Life Expectancy of Women increases by one unit, the Inclusive Economic Development Index will decrease by 0.0450 units. The negative results of this study are in line with research conducted (Deris, 2022) that the average life expectancy of women compared to men does not affect economic growth in Indonesia. When women have a higher life expectancy than men, but with a woman's life expectancy continuing to increase but not accompanied by women's optimal contribution to development, the availability of jobs for women, and women's expertise in work will hinder development. Stunted development will reduce the productivity of goods or services that drive the economy so that economic growth in a region will be hampered The regression coefficient for the average length of schooling for girls is -0.139. The results obtained show a significant negative effect on inclusive economic growth. This shows that when the average school year increases by one unit, the Inclusive Economic Development Index will increase by 0.139. In Indonesia, the average length of schooling is used as an indicator in measuring the length of learning achieved starting from elementary school. When educational attainment increases, especially for women, it will be seen that equality in education contributes to women's development, women's development indirectly affects inclusive economic growth in Indonesia. According to research by Herdiansyah and Kurniati (2020) in (Zaluku, 2021), it states that education is the driver of the human development index. Women's high education and ability will not guarantee them access to the highest positions in the world of work. More and more women have higher education and can occupy high positions, making them greater opportunities to rise to higher positions. Different results were carried out research (Nabiel, 2021) that there is an imbalance between the average length of schooling for boys and girls. The average length of schooling for girls is lower than the average schooling for boys. This shows that equity has not been achieved in the education sector. Gender inequality that occurs in the education sector results in low productivity of human resources which has an impact on economic growth. Low productivity can result in a low standard of living and reduce economic growth.
There should be an increase in women's RLS in Indonesia because it will not only affect IPEI but also as an effort to achieve equality in education. In research (Adika, 2021) it is stated that increasing women's RLS has a positive impact on economic growth. Several reasons https://equatorscience.com/index.php/jabter support women's RLS for economic growth, firstly in developing countries, the feedback from women's education is higher than that of men. The second is that an increase in education will increase labor participation, reduce early marriage, as well as the impact on health, for example, more rendering fertility and improved nutrition in children. The third is that having educated mothers and nutritious children will have a multiplier effect on the quality of future generations. And the fourth is that educated women can have an important impact in the long run in breaking the cycle of poverty that is still happening in Indonesia and that education is still inadequate. This is also the same as the explanation from Todaro and Smith that narrowing the gender gap in education can be economically beneficial, namely it can increase female labor participation which can delay marriage and educate children in a higher quality.
The regression coefficient for the female per capita expenditure variable is 0.000261. The results obtained show a significant positive effect on inclusive economic growth. This shows that when women's per capita expenditure increases by one unit, the Inclusive Economic Development Index will increase by 0.000261. If a person's expenditure increases, the consumption of goods and services issued will increase. Increased consumption of goods and services indicates an increase in people's purchasing power, thus affecting the production of goods and services. Increased production levels will affect economic growth so women's per capita spending can affect economic growth. Based on research (Oyvat, 2022) per capita expenditure is an indicator of a decent standard of living for women. The average income generated by women is lower than that of men, resulting in lower expenditures. This difference is caused by the classification of types of work based on gender. In Indonesia, based on BPS data, women's income is also lower than that of men, this indicates that there is still an imbalance in per capita spending between women and men.One of the reasons is that spending between men and women is caused by inequality in terms of workers' wages, the average wage/salary for women in 2021 is 2.8 million rupiahs, which is smaller than the average wage/salary for men 3.1 million rupiahs for men. From this explanation, increasing IPEI through women's per capita spending can be done by increasing the average wage/labor/employee salary, and this has also become a government policy through the existence of a Minimum Wage so that it can reduce wage inequality for women against men. From the explanation of the variable life expectancy for women, the average length of schooling for women and spending per capita all influence inclusive economic growth. These three variables are indicators that form the Gender Development Index as well as indicators of the Human Development Index which are calculated based on the sex ratio. Then these three variables can be associated with longevity, healthy life, knowledge, and a decent standard of living.
Based on statistical tests conducted, the variable Women's Involvement in Parliament does not affect the Inclusive Economic Growth Index. The absence of a significant effect illustrates that when there is an increase in women's involvement in parliament, it does not affect an increase in the inclusive economic development index. In Indonesia, women's involvement in parliament is an important part of implementing a democratic party. Women are a benchmark for participating and expressing opinions about women's rights, especially in the political field. Equal participation of women in decision-making in the political field is not only a conditional requirement but also a representation of women's interests. Political representation supported by women will strengthen the economy. When women are economically strong, they can influence politics better. Therefore, women's economic empowerment also has several non-economic benefits (Bayeh, 2016). Research conducted (Garboni, 2015) succeeded in realizing that more than 30 percent of female members were in delegations and active in terms of substantive representation of women compared to male counterparts in Romania.
Research conducted (Samson, 2019) concluded that women in Kenya are still underrepresented in political leadership positions. It was further argued that some communities were less cooperative in ensuring that women took senior leadership positions in both the public and private spheres. Likewise in Indonesia, according to BPS data for 2021, the average representation of women in parliament only reaches 21.89 percent. Even though in law no. 7 of 2017 it has been stipulated that 30% of women's representation in political affairs at the central level and legislative candidacy at each level. When the number of women elected is less than specified it can diminish their ability to influence the group's overall decision-making process.
The regression coefficient for the female variable as a professional is 0.0595. The results obtained show a significant positive effect on inclusive economic growth. The regression coefficient explains that the variable of women as professionals increase by one unit, so the inclusive economic development index increases by 0.0595 units. Many women have decided to become professionals. According to research conducted (Nguyen, 2021) The participation of female workers in the industrial or service sectors can increase economic complexity. In line with Nguyen's research, when women get managerial positions, they can increase company profits or profits. Women's participation as professionals is a tool to increase women working in companies, but the impact is not to ensure that women can be represented and occupy the highest positions in the company, but they can create land or space for women to participate and increase access slowly to positions leadership (Gizelis, 2018). When women have space, women are independent and empowered, then women can be more autonomous and able to improve their relationship with their surroundings in a more equal manner in making decisions. Women's active participation in the economic sector and decision-making can strengthen economic conditions, increase national development achievements and improve the quality of life not only for women but also for men, families, and communities. Therefore, it is important to take into account the participation of women in the formal and informal sectors as well as professionals.
The regression coefficient for the female income contribution variable is 0.115. The results obtained show a significant positive effect on inclusive economic growth. This shows that when the contribution of women's income increases by one unit, the Inclusive Economic Development Index will increase by 0.115. In addition to the involvement of women in parliament and women as professionals, the contribution of women's income can affect economic growth. Women's income contribution shows how women play a role and https://equatorscience.com/index.php/jabter contribute financially and indicates the existence of women's economic independence which has an impact on more equal relations and autonomous control abilities (Kementerian Pemberdayaan Perempuan dan Perlindungan Anak Republik Indonesia, 2020). The contribution of women's income also reflects the position of women in the labor market and how women have been or have not been taken into account in the world of work. When women participate in the financial system, gaps or inequalities will be reduced so that it is possible to create high economic growth as well as increase physical and social welfare (Cabeza-Gracia L. E.-V., 2018). From the explanation, the variables involving women's involvement do not have a significant effect on inclusive economic growth, while the variables on women as professionals and women's income contribution have a significant positive effect on inclusive economic growth. These three variables are the three components that make up the Gender Empowerment Index. An increase in the average Gender Empowerment Index obtained from the arithmetic average will show an increase in the indicators that form it.
The regression coefficient for the GRDP per capita variable is 0.351 each. This has a significant positive effect on inclusive economic growth. When the GDP per capita increases, it will increase inclusive economic growth. If a person's income increases, it will affect the consumption of goods and services. Consumption of goods and services increases, indicating that people's purchasing power also increases, so that when the consumption of goods and services increases, the level of production of goods and services also increases. Increased production levels will affect the increase in GRDP per capita. GRDP per capita can affect economic growth in the region. Based on statistical tests conducted, the PMDN variable has no effect on the Inclusive Economic Growth Index. The absence of a significant effect illustrates that there are other factors such as investment that are not accompanied by labor productivity. To optimize economic growth through the variables which are GRDP per capita and PMDN, it is necessary to do planning. Planning is used to view macroeconomic experiences and provide guidance in policy making for stakeholders. Forecasting can be a significant consideration in development planning . So that in the next few years you can consider which variables will strongly influence economic growth, especially macroeconomic indicators.

Conclusion
Women's Development and Women's Empowerment are directly proportional to the increase in the inclusive economic development index. Women's development through the gender development index indicator with the variable life expectancy of women that reflects the longevity and healthy life has not yet reflected its contribution to achieving inclusive economic growth. Meanwhile, the variable average length of schooling that reflects the knowledge and per capita spending shows a decent standard of living has an important impact on economic activity and reduces inequality. Women's empowerment through the gender empowerment index indicator with the variable involvement of women in parliament has not been able to increase inclusive economic growth. Women as professionals and the contribution of women's income show the results that women can have the power to improve welfare and influence economic growth. More and more empowered women also increase the level of labor force participation, an increase in labor force participation coupled with an expansion of employment opportunities will increase economic growth.