Income Inequality In Indonesia Research Articles

The Role of Digitalization of Financial Inclusion in Reducing Income Gaps: an Empirical Study at 33 Provinces in Indonesia

One of the problems faced by developing countries, including Indonesia, is income inequality. It is hoped that digitalization of financial inclusion can solve this problem. Increasing financial inclusion is expected to make financial services more accessible to everyone, especially for poor groups who previously did not have access to financial services. This research aims to analyze the role of digitalization of financial inclusion in reducing income gaps using empirical evidence from 33 provinces in Indonesia during the 2013-2022 period, using the fixed effects estimation method. The results of this study indicate that financial inclusion has a negative and significant impact on the Williamson index. This means that increasing financial inclusion can reduce income inequality. The decomposition results for each dimension show that the access dimension has a significant effect on reducing income inequality in Indonesia, while the usage dimension shows a positive influence on income inequality, but the presence of the SNKI policy in Indonesia in 2016-2022 has a negative influence on income inequality in Indonesia.

The Influence of Economic Openness on Income Inequality Among Provinces in Indonesia

Economic growth is a macro indicator to measure the success of development, so all countries strive to achieve high economic growth to create prosperity for the society, especially for developing countries. At the beginning of economic growth, income inequality will increase, but over time, income inequality will decrease. This research was conducted to analyze the influence of economic growth rate, non-oil export ratio, non-oil import ratio, and foreign direct investment ratio on income inequality among provinces in Indonesia. The data used in this study is panel data obtained from the Central Statistics Agency covering 34 provinces in Indonesia from 2018 to 2022. The results of this study indicate that the economic growth rate has a positive but not significant effect on income inequality in Indonesia, the non-oil import ratio has a positive and significant effect on income inequality in Indonesia, the foreign direct investment ratio has a negative but not significant effect on income inequality in Indonesia, while the non-oil export ratio does not have a significant effect on income inequality in Indonesia.

Disparity and Income Inequality in Indonesia

Objective: This study aims to determine the effect of the labor force variable, road infrastructure province, life expectancy, average length of schooling and economic growth on disparities of the development in Indonesia and find out which variable is the most dominant effect on development disparities in 33 provinces in Indonesia.   Methodology: This study uses quantitative research methods using panel data. This panel data regression model has three approaches that are often used in analyzing data.   Result and Conclusion: the gap between regions with WI values in 33 provinces in Indonesia in the period of time 2010 to 2021 illustrates that the average level of disparity between provinces in 2012-2021 still experienced quite large inequality. based on each province it is illustrated that inequality that occurs in the province tends to decrease every year.   Novelty: The novelty in this research The level of disparity between regions with the WI values at 33 Provinces in Indonesia in the period 2010 to 2021 illustrates that the level the average gap between provinces in 2010 to 2021 is still experiencing considerable inequality big. Based on the panel data regression results, there are three variables that affect the level of inequality between 33 provinces in Indonesia significantly.

The Paradox of Globalization: Unraveling the Short and Long-Term Impacts on Income Inequality in Indonesia

This study investigates the impact of globalization and financial growth on income inequality in Indonesia using empirical data from 1995 to 2020. The analysis reveals that globalization and financial development, while initially appearing advantageous, can exacerbate income inequality over time. In Model I, the overall measure of globalization contributes to income inequality in both the short and long run. Initially, globalization may reduce income inequality, but its long-term effects are detrimental. Financial development and inflation in Indonesia also have a significant and positive impact on income inequality in this model. Model II shows that economic, political, and social globalization have statistically significant impacts on income inequality in both the short and long term. Economic and political globalization can help mitigate income inequality over time, but in the short term, income inequality in Indonesia worsens. Social globalization, on the other hand, consistently has a positive influence on income disparity in both the short and long term. The study highlights the need for proactive government measures to maintain the stability of economic, political, and social globalization. Policymakers should implement progressive policies that address the adverse effects of globalization on income distribution to ensure a more equitable society.

The Effect of Financial Literacy and Financial Inclusion on Income Inequality in Indonesia

Income inequality is an economic phenomenon that has an impact on economic instability and the welfare of society. Indonesia's income inequality has not significantly improved or changed much from previous years. This study aims to analyze the effect of financial literacy and financial inclusion on income inequality in Indonesia. The type of research used in this study is quantitative research. The data used is panel data of 34 provinces in Indonesia in 2016, 2019, and 2022. The analysis method used is Panel Data Regression using the Random Effect Model (REM) approach. The results show that (1) financial literacy does not affect income inequality in Indonesia; (2) financial inclusion does not affect income inequality in Indonesia; (3) poverty has a significant positive effect on income inequality in Indonesia; and (4) wages has a significant negative effect on income inequality in Indonesia. Suggestions in this study: Financial institutions should start expanding the target of introducing new and existing products to increase public understanding and confidence, especially among the lower middle class. In addition, government intervention must be carried out massively and aggressively so that a general understanding of finance increases.

Pengaruh Migrasi, Modal Manusia dan Investasi Asing Terhadap Ketimpangan Pendapatan di Indonesia

The results of this research explain that as long as there are influences betweenmigration, human capital, foreign investment on income inequality inIndonesia. This research is a combination of cross section and time series using33 provinces and from 2013 – 2019, using the panel regression method and thefixed effect model selection test. The results of the research prove that: (1)Migration has a significant positive effect on income inequality in Indonesia,(2) Human capital has a negative and significant effect on Income Inequality inIndonesia, (3) Foreign Investment has a not significant positive effect onIncome Inequality in Indonesia.

Unravelling Income Inequality in Indonesia

This study aims to analyze the effect of Information and Communication Technology (ICT) on income inequality in Indonesia. The analytical method used includes linear regression to evaluate the causal relationship between the dependent variable (Gini Ratio) and ICT indicators. Furthermore, the k-means clustering algorithm is used to group provinces based on ICT characteristics. The results of the regression analysis show that the ICT variables have a significant influence on the Gini Ratio, illustrating the close relationship between ICT and income inequality. In addition, clustering produces two regional groups: Cluster 1, with better access and use of ICT, and Cluster 2, with lower ICT characteristics but advantages in telecommunication infrastructure. This research shows the importance of inclusive and sustainable ICT development to reduce income inequality in Indonesia. Appropriate policies for increasing the accessibility and use of ICTs can have a positive impact on social and economic development throughout Indonesia.

Dual Monetary Policy and Income Inequality in Indonesia

Dual Monetary Policy and Income Inequality in Indonesia

The Effect of Economic Growth, Education Level, and Energy Subsidies on Income Inequality in Indonesia in 2005-2019

Income equality is the ideal of every country, to achieve it requires cooperation between the government and the community. This study aims to determine the effect of economic growth, education level, and energy subsidies on income inequality in Indonesia. This study used secondary data in the form of time series in 2005-2019 obtained from the world bank, the central statistics agency and the Ministry of Finance. The method used in this study is multiple regression analysis. The results obtained in this study show that the variable level of education and energy subsidies actually increases income inequality due to suboptimal policies, while the economic growth variable does not reduce income inequality due to economic activities focused on the upper class.

Pengaruh Penanaman Modal Asing, Indeks Persepsi Korupsi, Kemiskinan, Pengangguran dan Upah Minimum Terhadap Ketimpangan Pendapatan Di Indonesia

This study aims to analyze the influence directly or indirectly of Foreign Investment, Corruption Perception Index, Poverty, Unemployment and Minimum Wage on Income Inequality in Indonesia. The data used in this study is a secondary type of data sourced from the offices of the Central Statistics Agency, the World Bank Web and Transparency International. The data analysis method used is Multiple Linear Regression data (time series) in Indonesia for 25 years from 1997 to 2021. Based on the results of the analysis, it is known that Foreign Investment, Corruption Perception Index, Poverty, Unemployment, and Minimum Wage have a significant effect on Income Inequality in Indonesia.

Towards the quest to reduce income inequality in Indonesia: Is there a synergy between ICT and the informal sector?

Towards the quest to reduce income inequality in Indonesia: Is there a synergy between ICT and the informal sector?

Beyond economic growth: How Indonesia’s 2045 vision prioritized reducing income inequality?

This study aims to identify critical success factors for reducing income inequality in Indonesia by analysing the country's 2045 vision. This study employs a qualitative research design that utilises secondary data sources. Strength, Weakness, Opportunities and Threats (SWOT) analysis is used as the primary analytical tool to examine the critical success factors that influence Indonesia's economic growth in achieving its 2045 vision. The study reveals that Indonesia faces numerous challenges in reducing income inequality. However, by leveraging its strengths, Indonesia can reduce income inequality and become one of the world's top economies. Furthermore, the study identifies potential opportunities that could contribute to Indonesia's economic growth. The study concludes that Indonesia needs to focus on strength-opportunities (SO) strategies to achieve its 2045 vision and reduce income inequality by taking advantage of its strengths and potential opportunities. The study's findings have practical implications for policymakers and business leaders in Indonesia. The government needs to prioritise country strength to promote economic growth and reduce income inequality. Additionally, the private sector could explore the potential opportunities in the digital and manufacturing transformations to contribute to Indonesia's economic growth.

Balancing Funds, Investment, Length of Schooling, Unemployment Rate and Income Inequality in Indonesia

The goal of a country's economic development is an equal distribution of income. This study aimed to analyze the direct and indirect effects of balancing funds, domestic investment (PMDN), foreign investment (PMLN), the average length of schooling (RLS), and the open unemployment rate (TPT) on income inequality in Indonesia in 2015-2021. GRDP per capita is an intervening variable, while income inequality is the dependent variable with the Gini Ratio as an indicator. This study uses secondary data in the form of panel data. The method used is Random Effect Model (REM) and Fixed Effect Model (FEM). The results of the panel data regression show that the variable balance funds and RLS have a negative and significant effect, and PMDN has a positive and significant impact on income inequality. Indirectly, the variable balancing funds, PMLN, and RLS negatively and significantly affect income inequality through GRDP per capita. Meanwhile, the TPT variable does not affect income inequality.

Balancing Funds, Investment, Length of Schooling, Unemployment Rate and Income Inequality in Indonesia

Balancing Funds, Investment, Length of Schooling, Unemployment Rate and Income Inequality in Indonesia

The Effect of the Defense Budget on Income Inequality in Indonesia

The Effect of the Defense Budget on Income Inequality in Indonesia

Digital Technology Development and Income Inequality in Indonesia: Using System GMM Model

This study aimed to analyze the importance of information and communication technology (ICT) for economic development. ICT development has been widely studied and well understood, but its impact on income inequality is less well documented. Therefore, this study used a panel data set in 34 provinces in Indonesia during 2013-2020 to examine the impact of ICT development on income inequality. The econometric Generalized Method of Moments (GMM) with the estimation model of the System GMM showed that higher ICT development (Information and Communication Technology Development Index) reduces income inequality (Gini Ratio). This implies that ICT development does not contribute to exacerbating income inequality. However, it could play a role in mitigating and reducing income inequality in Indonesia. Socio-economic and political factors are also important in reducing income inequality. Therefore, redistribution policies and government spending are crucial to reducing income inequality due to ICT development. These policies must be adapted to the needs of each region for ICT development. Keywords: ICT Development, Income Inequality, Socio-Economic and Political Factors, GMM Model.

Do Government Policies and Socioeconomic Conditions Affect Income Inequality?

The problem that is often faced by developing countries is high-income inequality among the population. On the other hand, the development of digital technology occurs very quickly and encourages the community to play a more active role in economic activities. This condition needs to be further explored, especially considering its relation to income inequality in Indonesia. This study aims to determine the effect of government policies and socioeconomic conditions on income inequality in Indonesia in the 2019-2021 period by analyzing secondary data in 34 provinces in Indonesia. The analytical method uses panel data regression with the selected model of the fixed effect model. The data was taken from the Central Bureau of Statistics, each provincial government's Directorate General of Finance, and the Ministry of Manpower of the Republic of Indonesia. The results showed that the number of poor people significantly positively affected income inequality and regional minimum wages, and the information and communication technology development index negatively affected income inequality. In contrast, the human development index and social assistance spending had no impact on income inequality. The government must improve poverty alleviation programs to reduce the income inequality gap while expanding the accessibility of Information and Communication Technology (ICT) to provide a better quality of life for the people. This study enriches previous research on the effect of socioeconomic conditions on income inequality by adding the newly developed ICT development index variable

The effect of inflation on income inequality: Evidence from a non-linear dynamic panel data analysis in indonesia

This research investigates the impact of inflation on income inequality in Indonesia. This study is part of a comprehensive examination investigating which monetary policy can be utilized to lessen inequality. As a central bank objective, inflation can influence the distribution of income, wealth, and endogenous consumption, hence defining inequality. This study employed dynamic panel data analysis for linear autoregressive data using the generalized method of moments (GMM) for both first differences GMM (FD-GMM or AB-GMM) and system GMM (Sys-GMM or BB-GMM) with regional data from 58 cities in 2010-2020. The Arellano-Bond estimator reveals a positive and statistically significant association between inflation and inequality. When inflation rises, the purchasing power of the poor will decline, while the wealthiest will benefit as their non-cash assets proliferate. This study finds, indirectly, that Indonesia’s monetary policy can play a crucial role in lowering income distribution gaps. As one of the nations with an inflation-targeting framework, the Indonesian Central Bank can target the inflation rate by considering inequality. The ITF becomes the most effective monetary policy for stabilizing prices and promoting economic stability. The ITF reduces income inequality by reducing inflation rates. The study also finds that, similar to other emerging nations, economic growth in Indonesia exacerbates inequality. Poverty can be reduced by increased economic growth, but the positive impact of development on the wealthy is significantly more significant than on the poor. Therefore, economic expansion increases inequality.

Zakat and Income Inequality in Indonesia: Panel Data Analysis in 34 Provinces

ABSTRAK Tujuan utama dari makalah ini untuk menguji secara empiris pengaruh zakat, Produk Domestik Regional Bruto (PDRB) perkapita, Upah Minimum Regional/Provinsi (UMP), dan inflasi terhadap tingkat gini rasio di 34 provinsi di Indonesia selama tahun 2018-2020.  Temuan penelitian ini menunjukkan bahwa distribusi zakat yang diproksikan dengan Indeks Kesejahteraan BAZNAS serta tingkat inflasi secara statistik tidak berpengaruh signifikan terhadap tingkat ketimpangan pendapatan di Indonesia. Sementara itu, tingkat PDRB perkapita dan UMP memiliki arah hubungan negatif dan berpengaruh signifikan secara statistik terhadap tingkat ketimpangan pendapatan di Indonesia. Penelitian ini memberikan rekomendasi kepada pengelola zakat untuk menciptakan dan mengembangkan program zakat yang mampu memberdayakan perekonomian mustahik sehingga mampu mengurangi tingkat kesenjangan pendapatan dalam masyarakat. Selain itu, seluruh pemangku kepentingan (stakeholders) harus bersinergi dalam upaya meningkatkan realisasi pengumpulan dana zakat di lembaga dengan melalui peningkatan literasi dan kesadaran masyarakat guna mengoptimalisasikan peran zakat dalam peningkatan kesejahteraan masyarakat. Kata kunci: Indeks Kesejahteraan BAZNAS, Ketimpangan Pendapatan, Makroekonomi, Zakat.   ABSTRACT The main objective of this paper was to empirically examine the effect of zakat, Gross Regional Domestic Product (GRDP) percapita, Regional/Provincial Minimum Wage, and inflation on the gini ratio in 34 provinces in Indonesia during 2018-2020. The findings of this study indicate that the distribution of zakat, which is proxied by the BAZNAS Welfare Index, and the inflation rate has no statistically significant effect on the level of income inequality in Indonesia. 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Analisis Kausalitas Indeks Pembangunan Manusia Pengangguran Pertumbuhan Ekonomi dan Ketimpangan Pendapatan di Indonesia

This study aims to analyze: (1) The causality relationship between unemployment and the human development index, (2) The causal relationship between economic growth and the human development index, (3) The causal relationship between income inequality and the human development index, (4) The causal relationship between economic growth and unemployment, (5) Causality relationship between income inequality and unemployment, (6) Causality relationship between income inequality and economic growth, (7) Long-term and short-term relationship between human development index, unemployment, economic growth and income inequality in Indonesia. The data used is panel data from 34 provinces in Indonesia during the 2011-2020 period. The analytical method used is Panel Vector Error Correction Model (PVECM) and Panel Granger Causality Test. The results of this study indicate that there is a relationship: (1) Two-way causality between unemployment and the human development index, (2) Economic growth to the human development index, (3) Income inequality to the human development index, (4) Economic growth to unemployment, ( 5) Income inequality to unemployment, (6) Income inequality to economic growth, (7) There is a long-term relationship between unemployment and the human development index which has a positive effect, economic growth has a negative effect on the human development index and income inequality on the human development index has a positive effect negative.