Rationale of the research The rationale driving this research is deeply entrenched in the burgeoning concern surrounding income inequality, which has emerged as a formidable impediment
Rationale of the research
This research is motivated by the growing concern over income inequality, which poses a significant challenge to sustainable development and social cohesion in Southeast Asia Despite rapid economic growth and the influence of globalization, the region has experienced a troubling widening of wealth gaps, leading to increased social disparities and threatening societal harmony and progress.
This study aims to thoroughly examine the complex relationship between GDP growth and income inequality in Southeast Asia By employing a comprehensive approach that combines rigorous statistical analysis, advanced economic modeling, and detailed policy evaluation, the research seeks to uncover the intricate dynamics between economic growth and the fair distribution of income among different social groups.
This inquiry aims to determine if GDP growth benefits all socioeconomic groups fairly or primarily enriches a privileged few, thereby worsening inequality By analyzing various statistical metrics such as average income levels, wage disparities, and the Population-Weighted Coefficient of Variation (PW-CV), the research seeks to reveal significant patterns and trends related to income inequality in the region over time.
Various economic theories have explored the link between income inequality and economic growth, with the inverted-U hypothesis by Kuznets in 1955 being one of the earliest Kuznets posited that during the initial phases of development, income inequality increases as many low-income agricultural workers transition to higher-paying jobs in the industrial sector, which is characterized by unequal wage distribution However, as urbanization progresses, the wages of the poor in both urban and rural areas begin to rise, accompanied by the implementation of policies aimed at reducing inequality.
2 within and across sectors, ultimately leading to an overall decline in income inequality in the economy
In the 1990s, Alesina, Rodrik, Persson, and Tabellini developed a political economy theory that links endogenous growth with political factors, particularly in democratic societies They argued that the median voter, typically of middle income, influences tax rates and public spending by advocating for greater redistribution that benefits them more than wealthier individuals Conversely, in societies with high inequality, the median voter often has an income below the average, leading to opposition against strong redistribution policies, which in turn hampers investment and economic growth.
Benabou's unified theory from 1996 posits that the relationship between redistribution and economic growth is non-linear It suggests that when public funds from redistribution are invested in education in credit-constrained economies, growth can be enhanced Conversely, if redistribution merely shifts income from the wealthy to the poor, it may hinder growth by diminishing investment incentives for the affluent Thus, both the redistribution-growth and inequality-redistribution relationships exhibit an inverted U-shape according to this theory.
This study aims to explore the key determinants of income inequality in Southeast Asia, examining various contributing factors such as economic policy design, educational disparities, and social stratification dynamics By analyzing these intricate relationships, the research seeks to enhance the understanding of the structural forces influencing income distribution and perpetuating systemic disparities in the region.
Gross Domestic Product (GDP) is a crucial indicator of a nation's economic performance, providing insights into overall economic health and guiding policymakers in fiscal and monetary decisions It reflects living standards by correlating with per capita income and household consumption Additionally, GDP serves as a benchmark for international comparisons, impacting investment and trade strategies.
Over the past 40 years, income inequality has surged across nations, particularly in developed countries and major emerging economies This growing disparity affects around two-thirds of the global population and accounts for 85 percent of the world's GDP.
Income inequality significantly influences both individual lives and overall economic growth Large disparities in income among households can create imbalances in spending, consumption, and investment, ultimately impacting living standards and economic development (Zia Qureshi, 2023).
Over the past three decades, many Asian countries have achieved significant growth and poverty reduction, with developing Asia experiencing an average annual GDP growth rate of 7.0% from 1990 to 2017, surpassing Latin America's 2.8% This remarkable growth has been largely propelled by the People's Republic of China and India, the two most populous nations, which saw annual GDP growth rates of 9.7% and 6.7%, respectively.
The rapid economic growth in Asia has significantly enhanced living standards and alleviated extreme poverty, with the average per capita GDP rising from $2,423 to $10,725 between 1990 and 2017 The percentage of people living on less than $1.90 a day plummeted from 53% in 1990 to approximately 9% in 2013, resulting in over 1 billion individuals being lifted out of poverty Notably, fifteen countries in the region achieved a reduction in poverty rates by more than 15 percentage points during this period.
Despite significant growth and progress in poverty reduction, many countries have experienced increasing income inequality Among 30 countries with comparative data from the 1990s to the early 2010s, nine countries, representing over 80% of developing Asia's population in 2016, showed a rise in inequality This trend indicates that as GDP and GDP per capita rise, income inequality often worsens (Juzhong Zhuang, 2018).
Our group's objective is to investigate and update data regarding the relationship between GDP and income inequality in Southeast Asia, aiming to enhance social knowledge and economic science This research will aid in the development of economic models and analytical tools to better understand the effects of income inequality.
This research aims to create a strong framework of evidence-based policy recommendations to address deep-rooted disparities and promote inclusive economic growth Proposed interventions include implementing progressive taxation, making targeted investments in education and skills development, and expanding social safety nets to protect against economic instability.
Research gap and research questions
This research examines the link between GDP growth and income inequality in Southeast Asian countries from 2013 to 2022, highlighting the need for a comprehensive temporal analysis to identify trends over time It explores regional variations in this relationship, clarifies the causal mechanisms involved, and assesses the nuanced effects of the COVID-19 pandemic on income distribution Additionally, the study evaluates the feasibility and effectiveness of proposed policy interventions, aiming to fill existing gaps and enhance the relevance of its findings for policymakers and stakeholders committed to sustainable development in the region.
The fundamental question we ask in our research is:
1 Whether growth in GDP has a positive or negative effect on income inequality in the community?
2 How can these findings inform policies aimed at reducing income inequality and maximizing the benefits of economic growth in the region?
In particular, this research will not only help to better understand the dynamics behind income fluctuations in the region but also suggest policies that can help reduce
This study analyzes income inequality in Southeast Asia by examining key factors such as education, population, and Foreign Direct Investment (FDI), while also assessing the impact of the COVID-19 pandemic The findings offer valuable insights for the international community, particularly for those focused on promoting sustainable economic and social development in the region.
Research scope
The research focuses on eleven Southeast Asian nations: Brunei Darussalam, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, Timor-Leste, and Vietnam This broad geographical area highlights the region's diversity and provides a comprehensive view for in-depth analysis of its complex socio-economic, political, and cultural dynamics.
This research examines diverse nations in Southeast Asia to identify both shared characteristics and differences Through a thorough comparative analysis, it aims to reveal significant trends and unique local details, enhancing our overall understanding of the region's intricate dynamics.
The extensive scope of this research guarantees that its findings accurately represent Southeast Asia as a unified region This methodological approach enhances understanding of the area's diverse realities, supporting informed decision-making and policy development in various fields, including economic growth and cultural preservation Ultimately, the research promotes regional cohesion and progress.
This research conducts a thorough examination of data collected from 2013 to 2022, providing a comprehensive overview of trends and significant developments relevant to the research objectives The ten-year timeframe allows for a detailed analysis of the evolutionary trajectory within the studied field.
By embracing this considerable time frame, the study endeavors to encapsulate not only
This comprehensive approach captures both short-term fluctuations and long-term trends, allowing for a deeper understanding of the dynamics at play.
The careful focus on data collection during this period highlights the research's commitment to methodological rigor and scholarly integrity This dedication guarantees the reliability, validity, and relevance of the findings, strengthening the foundation for strong conclusions and informed recommendations.
The extended timeframe of this research allows for the recognition of both temporal shifts and continuity in the phenomena studied This perspective enhances the depth and breadth of the findings, leading to a deeper understanding of the complexities involved in the subject matter.
In summation, the research's temporal breadth not only enhances the comprehensiveness of its findings but also underscores its commitment to scholarly excellence and methodological rigor
This research investigates the complex relationship between GDP and income inequality in Southeast Asia over the past decade It focuses on how changes in GDP impact income distribution among various socio-economic groups in the region By exploring this connection, the study aims to clarify the interplay between economic growth and equity in Southeast Asia.
This study employs a rigorous analytical approach, utilizing comprehensive data analysis and robust statistical methods to uncover patterns and trends in income distribution relative to GDP fluctuations By carefully examining these patterns, the research aims to provide valuable insights into how economic growth influences income distribution dynamics in Southeast Asia.
Moreover, by addressing this research object, the study aims to contribute substantially to the discourse surrounding policy interventions aimed at mitigating
Addressing income inequality and promoting inclusive economic development in Southeast Asia is essential This research offers data-driven insights aimed at guiding policymakers and stakeholders in understanding the effectiveness and potential impact of various strategies to reduce income disparities and foster equitable economic growth.
This research aims to enhance our understanding of the complex relationship between GDP and income inequality in Southeast Asia, while also providing actionable insights for evidence-based policy formulation Ultimately, it seeks to contribute to the pursuit of more equitable and sustainable development throughout the region.
THEORETICAL FRAMEWORK ON INCOME INEQUALITY AND
Economic Growth and its Components
1.1.1 Definition & Measures of economic growth
Throughout history, economists and political leaders have defined economic growth in various ways, reflecting its complexity and significance Adam Smith, in "The Wealth of Nations" (1776), characterized economic growth as the increase in production and labor supply, emphasizing productivity and economic freedom John Maynard Keynes (1930) viewed it as essential for reducing unemployment and enhancing living standards, advocating for government intervention through fiscal and monetary policies to stimulate growth The Solow-Swan Model (1956) introduced by Robert Solow and Trevor Swan framed economic growth as driven by technological progress and capital accumulation Recently, the focus has shifted to sustainable economic growth, which balances economic efficiency with environmental protection and social equity, addressing issues like natural resources, climate change, and social inequality.
Economic growth is commonly defined as the increase in the production of goods and services per capita over time Simon Kuznets, in his 1973 work "Modern Economic Growth: Findings and Reflections," describes it as a long-term rise in a country's ability to provide a diverse array of economic goods to its population, driven by advancements in technology and necessary institutional and ideological changes The sustained increase in the supply of goods is a key indicator of economic growth.
Economic growth is defined as an increase in the production of goods and services over a specific period, with measurements adjusted for inflation (The Balance Money, 2022).
Economic growth refers to the increase in the production of goods and services within a specific timeframe compared to a previous period It encompasses both the quantity and quality of economic output, leading to an expansion of national income Different nations experience varying rates of economic growth due to factors such as population growth, levels of investment, and advancements in technology According to the Oxford and Cambridge Dictionaries, economic growth signifies the enhancement of a country's economy, particularly in terms of the value generated by goods and services produced.
Economic growth refers to the increase in a nation's production of goods and services over a specific period, signifying an overall rise in national income and economic output In academic terms, it represents the transformative process of progressive expansion in quantitative factors within an economy, while maintaining its structural integrity and quality.
Measuring economic growth involves various indicators to assess an economy's performance, with key metrics including Gross Domestic Product (GDP), which reflects the total value of goods and services produced within a country over a specific timeframe Gross National Product (GNP) considers income earned by residents both domestically and internationally, while Gross National Income (GNI) accounts for total income from all sources Real GDP provides a more precise measure by adjusting for inflation, and GDP Per Capita evaluates average income per person to determine living standards Additionally, the growth rate, representing the percentage change in GDP or other indicators over time, is essential for evaluating economic performance This analysis focuses on GDP and GDP Per Capita.
Gross Domestic Product (GDP) represents the total monetary value of all goods and services produced within a country's borders over a specific period, typically a year or a quarter, serving as a key indicator of economic performance While an increase in GDP indicates economic growth and higher production levels, it does not provide a complete picture of prosperity as it does not account for population size or distribution This is where GDP per capita becomes important; by dividing a nation's GDP by its population, it offers an average measure of economic output per person, helping to assess living standards and quality of life A rise in GDP per capita suggests improvements in income and living conditions for individuals By analyzing both GDP and GDP per capita, policymakers and economists can gain valuable insights into a nation's economic health and well-being, enabling them to make informed decisions and develop policies that promote sustainable and inclusive growth.
Economic growth is influenced by various key factors, including investment and capital formation, technological advancements, economic policies, demographic trends, social policies, education, and the labor market Each of these elements plays a significant role in driving the economic expansion of a country or region, contributing uniquely to overall growth.
Investment and capital formation are crucial for economic growth, as they involve expenditures on infrastructure, research and development (R&D), and industrial capacity Enhancing infrastructure, including transportation systems and communication networks, lowers production costs and boosts operational efficiency Additionally, R&D spending drives technological innovation, resulting in new products and improved production processes Upgrading industrial facilities further enhances the economy's competitiveness.
Technological advancements play a vital role in driving economic growth by enhancing efficiency, reducing waste, and increasing output The integration of new technologies fosters the emergence of new markets and business opportunities, contributing to a diversified economy and sustainable development Additionally, these improvements boost labor productivity and elevate the quality of products and services, effectively meeting the rising demands of consumers.
Economic policies, encompassing monetary and fiscal measures alongside labor market and trade regulation reforms, significantly influence the pace and sustainability of economic growth Governments are essential in fostering a conducive business environment through appropriate policies For example, effective monetary policies that manage inflation, interest rates, and money supply directly impact investment and consumption levels Additionally, sound fiscal policies, characterized by efficient public spending and equitable taxation, can stimulate investment and entrepreneurship, driving economic expansion Furthermore, reforms that enhance labor market flexibility, promote competition, and facilitate trade are crucial for unlocking growth potential and improving overall economic performance.
Demographic factors significantly influence economic growth, as population size and structure impact labor supply, consumer demand, and resource utilization A growing, youthful population can enhance consumption and investment, driving economic expansion, while an aging population may lead to labor shortages and increased healthcare costs Policymakers can better plan for future growth by understanding demographic trends and addressing associated challenges A dynamic, young population fosters a strong labor force and high consumption demand, boosting production and services In contrast, an aging population necessitates targeted measures to sustain labor force levels and manage healthcare expenses, ensuring long-term economic sustainability.
Additionally, investments in social policies and education are also critical factors contributing to human capital development, creating a skilled workforce and
Strengthening long-term economic growth requires effective education and training programs that equip individuals with essential skills for the labor market, thereby enhancing productivity Additionally, social policies focused on reducing inequality and promoting inclusivity, along with robust social safety nets, play a crucial role in improving overall welfare These initiatives not only elevate the quality of life for citizens but also establish a strong foundation for sustainable economic development.
A flexible and efficient labor market fosters employment opportunities, entrepreneurship, and productivity, all of which are essential for economic growth Implementing policies that enhance labor market flexibility, such as adaptable work arrangements and active labor market programs, can lead to job creation and lower unemployment rates Furthermore, investing in education and training, along with initiatives to improve workforce skills, boosts labor productivity and competitiveness, driving overall economic advancement By cultivating a supportive work environment, we can not only reduce unemployment but also stimulate innovation and creativity, vital components of sustained economic growth.
Economic growth is influenced by a variety of complex factors, including investment, capital formation, technological advancements, economic and social policies, demographic trends, education, and the labor market Each of these elements plays a crucial role in the development and expansion of a region's economy By comprehensively understanding and managing these factors, policymakers and stakeholders can foster an environment that supports sustainable economic growth and development.
Income Inequality Its Components
1.2.1 Definition & Measures of income inequality
Throughout history, income inequality has been defined and interpreted in various ways by economists, sociologists, and political theorists Karl Marx and Lenin attributed the income gap to the capitalist system, where the bourgeoisie monopolizes resources and labor, resulting in social injustice Conversely, Adam Smith, the pioneer of modern economics, acknowledged the importance of market freedom while also recognizing the existence of income inequality.
6 proposing measures like progressive income taxes to alleviate it John Maynard Keynes
In the 1930s, the importance of government intervention in addressing income inequality through monetary and fiscal policies was emphasized, advocating for the establishment of a social safety net and improved consumer purchasing power John Rawls, in 1971, contributed to this discourse with his theory of social justice, asserting that a fair society requires collective agreement on income and resource distribution, irrespective of individual positions Both perspectives highlight the complex nature of income inequality and underscore the necessity of reducing disparities for a more equitable society.
Income inequality refers to the disparity in income distribution among various societal groups, highlighting the gap between individuals, families, and different social classes According to the OECD (2023), it is defined as household disposable income, which includes earnings, self-employment, capital income, and public cash transfers, adjusted for household size The Balance Money (2022) emphasizes that income inequality is crucial for understanding socioeconomic statuses, including class distinctions Investopedia (2023) notes that income inequality indicates how unevenly income is distributed, often correlating with wealth inequality The Oxford Dictionary highlights that income differences arise from varying earning abilities and property ownership, while the Cambridge Dictionary points to the social injustices stemming from unequal wealth and opportunities.
Income inequality refers to the unequal distribution of income among individuals and households, leading to significant disparities in wealth and opportunities This issue affects social mobility, access to education and healthcare, and overall economic stability Various factors contribute to income inequality, including historical racial segregation, government policies, stagnant minimum wages, outsourcing, globalization, technological shifts, and the declining power of labor unions.
Understanding income inequality necessitates the use of various metrics that shed light on wealth distribution in societies The Gini index is a key measure, providing a numerical representation of income disparity among populations, with values ranging from 0 to 1.
The Gini index provides a clear measurement of income inequality, ranging from 0, which represents perfect equality where everyone has the same income, to 1, indicating perfect inequality with one individual receiving all income This quantification of income disparity is essential for policymakers and researchers aiming to comprehend and tackle issues related to wealth distribution.
The Gini index, 20:20 ratio, and Palma ratio are essential tools for analyzing income distribution, with the 20:20 ratio comparing the average incomes of the top and bottom 20% of earners to highlight disparity The Palma ratio adds depth by contrasting the income shares of the top 10% with the bottom 40%, focusing on the extremes of wealth distribution Additionally, the Hoover index, or Robin Hood index, quantifies the income percentage needing redistribution for perfect equality, providing insights into the effects of redistributive policies Furthermore, the Galt score assesses income concentration among top earners, enhancing our understanding of economic equity.
Wealth distribution within societies can be effectively analyzed using metrics like the coefficient of variation and the variance of the natural logarithm of income The coefficient of variation evaluates the relative variability of income by comparing the standard deviation to the mean income, providing insights into income dispersion across different societal segments This measure is crucial for policymakers and researchers as it highlights the degree of income inequality, pinpointing areas with significant disparities and guiding the development of targeted interventions to mitigate these inequalities.
The coefficient of variation serves as a standardized measure of income variability, essential for developing effective policies that promote economic equity and social justice Additionally, the wage share metric provides valuable insights into income distribution between labor and capital, highlighting labor market dynamics The Sen poverty measure adopts a multidimensional approach to evaluate poverty by considering factors like education, healthcare, and basic amenities, thus offering a comprehensive view of economic well-being The Theil index enables detailed analysis of inequality decomposition by groups, revealing sources of disparity, while its comparison with the Hoover index offers a broader perspective on overall inequality and the need for redistribution Furthermore, the Atkinson index incorporates societal aversion to inequality, illustrating the trade-offs between income equality and welfare By utilizing these diverse metrics, policymakers and researchers can gain a thorough understanding of income inequality, allowing for targeted interventions that promote equitable wealth distribution and inclusive economic growth.
The PW-CV provides a thorough method for evaluating income inequality by considering both the degree of income differences among individuals or regions and the population sizes of each unit This approach is based on the coefficient of variation (CV).
The PW-CV measures the ratio of standard deviation to mean income while adjusting for population size, offering a deeper insight into income distribution dynamics By incorporating demographic factors, it provides a more accurate evaluation of income inequality, as a higher PW-CV indicates significant disparities relative to population size, whereas a lower PW-CV suggests greater equality This makes the PW-CV an essential tool for policymakers and researchers to comprehensively assess income inequality and make informed decisions to effectively address disparities.
Income inequality is driven by various factors, including education disparities, technological advancements, economic policies, labor market structures, globalization, demographic changes, and social policies Each of these elements uniquely influences the level of income inequality, making it a complex issue This article explores how factors such as population dynamics, education, foreign direct investment (FDI), and external events like the COVID-19 pandemic affect income disparities By analyzing these diverse influences, it offers a comprehensive understanding of how they contribute to either widening or narrowing income inequality.
Income inequality is significantly influenced by the disparities in education and skills among individuals Those with higher education levels and specialized skills, particularly in high-demand fields like technology, medicine, or finance, tend to secure better-paying jobs and greater economic opportunities In contrast, individuals with lower educational attainment and fewer skills are often relegated to lower-paying positions, thereby exacerbating the income gap Additionally, access to quality education is frequently uneven, with wealthier families having the means to afford superior educational resources.
10 educational opportunities for their children, thus perpetuating the cycle of inequality across generations
Technological advancements drive economic growth but can also worsen income inequality by increasing demand for high-skilled workers while diminishing the need for low-skilled labor This shift leads to higher wages for those skilled in advanced technologies, such as artificial intelligence and machine learning, while routine jobs in manufacturing and services face automation, resulting in job losses and wage stagnation Additionally, the digital divide exacerbates this issue, leaving individuals without access to technology and digital literacy at a disadvantage in the evolving job market.
Economic policies, particularly taxation and government spending, play a crucial role in influencing income inequality Implementing progressive tax policies and robust social welfare programs can effectively reduce income disparities by redistributing wealth For instance, imposing higher taxes on affluent individuals and increasing public investment in education, healthcare, and social services can create more equitable economic opportunities In contrast, regressive tax systems and reductions in social spending often exacerbate income inequality by favoring higher-income earners and limiting assistance for lower-income populations Furthermore, policies that promote deregulation and privatization tend to concentrate wealth among the rich while undermining protections and support for economically vulnerable groups.
Impacts of Reducing Inequality on Economic Growth
Decreasing inequality has a significant positive impact on economic growth by fostering a more inclusive economy When wealth and income are distributed more equitably, it creates a larger consumer base with greater purchasing power Lower-income individuals tend to spend a higher percentage of their earnings on goods and services, which boosts demand and drives production This phenomenon, known as the "multiplier effect," initiates a cycle of growth, leading to increased employment, higher incomes, and more investment opportunities Additionally, reducing inequality promotes advancements in human capital, which is essential for sustainable economic development.
Promoting equitable access to education, healthcare, and essential services is crucial for reducing inequality and enhancing workforce skills and productivity A healthier and better-educated population is more capable of driving economic growth through increased productivity, entrepreneurial ventures, and technological advancements Furthermore, reducing inequality fosters social cohesion and stability, which are essential for sustainable economic development Societies with lower inequality often experience lower crime rates, higher trust and cooperation levels, and improved social mobility, creating a favorable environment for investment, entrepreneurship, and overall economic prosperity.
Efforts to reduce inequality can pose challenges and trade-offs for economic growth Policies like progressive taxation and social welfare programs may discourage investment and innovation among higher-income individuals, as excessive taxation can deter business and investor incentives Additionally, significant public investments and interventions needed to address inequality might strain government budgets and incur short-term economic costs Higher taxes or increased spending could suppress private investment, slowing economic growth To effectively reduce inequality, policymakers must implement targeted measures that address its root causes while avoiding unintended consequences, ensuring that these efforts remain sustainable and do not disrupt market mechanisms or economic incentives.
Reducing inequality can significantly boost economic growth by stimulating demand, improving human capital, and promoting social stability However, policymakers need to consider the potential benefits alongside the challenges and trade-offs involved to achieve sustainable and inclusive growth over the long term.
The COVID-19 pandemic has highlighted the vital connection between reducing inequality and promoting economic growth, making it essential for countries to address income disparities as they navigate the economic challenges brought on by the crisis By tackling inequality, nations can significantly influence their economic growth trajectories in the wake of the pandemic.
Reducing inequality strengthens economic resilience and stability during crises, such as the COVID-19 pandemic Countries with lower inequality often possess stronger social safety nets and healthcare systems, crucial for protecting vulnerable populations By guaranteeing access to essential services for all societal segments during challenging times, the reduction of inequality plays a vital role in fostering greater economic stability and resilience.
Reducing inequality can boost economic growth by enhancing productivity and innovation When resources are distributed more equitably, individuals from diverse backgrounds gain access to education, skills training, and entrepreneurial opportunities This creates a dynamic and inclusive economy where talent and creativity thrive, ultimately resulting in increased productivity and innovation.
Reducing inequality can enhance consumer demand and stimulate economic activity Implementing measures like progressive taxation and targeted social spending redistributes income and wealth to lower-income households, which typically have a higher propensity to consume This boost in consumer spending drives demand for goods and services, ultimately fostering economic growth and job creation.
Reducing inequality is crucial for enhancing social cohesion and political stability, both of which are vital for fostering an environment conducive to economic growth High levels of inequality can lead to social tensions and hinder trust in institutions, making cooperation and collective action difficult By promoting equity and social inclusion, governments can create a more stable setting that supports economic development.
In conclusion, the relationship between reducing inequality and fostering economic growth is intricate yet vital, especially in the context of challenges like the
The COVID-19 pandemic has highlighted the importance of addressing income inequality, which can significantly enhance economic resilience, productivity, and social cohesion While policymakers face challenges in balancing redistribution with investment incentives and managing government budgets, prioritizing measures to reduce inequality is crucial By stimulating demand and fostering human capital, countries can achieve a more inclusive and sustainable economic recovery in the aftermath of the pandemic.
LITERATURE REVIEW
The Kuznets Curve, developed by economist Simon Kuznets in 1950, serves as a fundamental framework in economic analysis, shedding light on the relationship between economic development and income inequality This U-shaped model provides valuable insights into how economies evolve over time, particularly during periods of growth and transformation following economic upheaval Kuznets' work remains influential in understanding the complex dynamics that drive changes in income distribution as economies progress.
Kuznets' methodological approach focuses on the systematic analysis of income data from specific nations or regions, categorized into various income brackets This analysis led to the development of the "Kuznets Ratio," a key metric that indicates income inequality by highlighting the disparity between the wealthiest and the economically marginalized segments of society This ratio serves as a powerful tool for Kuznets to track the progression of income inequality over time.
Kuznets' analytical framework is represented by an inverted U-shaped curve, illustrating that income inequality initially rises during early economic development, peaks, and then declines This phenomenon arises from rapid industrialization and urbanization, which cause certain sectors to grow disproportionately, increasing income disparities However, as economies mature, income distribution tends to become more equitable, leading to a reduction in inequality This critical point, known as the "Kuznets Turning Point," signifies a transition from high inequality to a more balanced distribution of income.
Keynesian economics, developed by John Maynard Keynes, provides valuable insights into addressing economic inequality through government intervention It emphasizes aggregate demand as the key driver of economic growth, advocating for policies like fiscal stimulus and monetary easing to support demand during downturns These measures stimulate economic activity, create jobs, and reduce unemployment, ultimately leading to a more equitable distribution of income.
Our research centers on the Kuznets Curve to analyze the link between economic growth and income inequality, while also acknowledging the importance of other influencing factors such as government policies, institutional frameworks, and social norms By incorporating these elements, we strive for a thorough understanding of the intricate dynamics of income inequality and economic development Through detailed empirical analysis and theoretical exploration, we aim to enrich the conversation on income inequality and guide policy discussions that foster inclusive and sustainable economic growth.
Numerous studies have examined the connection between GDP and income inequality in various regions, particularly highlighting Vietnam One notable research effort by Phan Thang An in 2015 investigated how economic growth affects income inequality in Vietnam's central key economic regions over a defined period This study utilized a combination of qualitative and quantitative methods, analyzing data from annual statistical reports of the provinces in the central economic zone.
In 2019, the Financial Magazine of Vietnam conducted an extensive analysis to explore the factors contributing to income inequality across the country, utilizing data collected from all 63 provinces and cities over multiple years.
19 inquiry marshaled data sourced from the General Statistics Office of Vietnam and provincial Statistics Offices
Nguyen Tan Van's 2016 study focused on the relationship between income inequality and economic growth in a specific province over a set period Using diverse statistical methods, Van analyzed data obtained from local authorities to illuminate the dynamics of income distribution in the region.
Research by Zeyao Luan and Ziyi Zhou in 2017 explored the connection between GDP growth and income inequality across various countries, utilizing data from the World Bank and government sources to analyze global income inequality trends.
In 2021, Gashaw Getaye conducted a study in Ethiopia examining the connection between economic growth and income inequality over several decades Through descriptive analysis techniques, Getaye provided a detailed evaluation of the factors affecting income distribution in Ethiopia.
N P Ravindra Deyshappriya conducted extensive research across multiple Asian countries over several years, utilizing an experimental research model By analyzing data from reputable sources like WB Data, he explored the complex relationship between GDP and income inequality in various economic contexts.
Research on the relationship between GDP and income inequality reveals a significant discrepancy, with some studies indicating a positive correlation—suggesting that rising GDP leads to increased income inequality—while others propose a negative correlation Most research employs linear regression models, although some studies also utilize experimental research methods.
Income inequality is often analyzed as the independent variable, while GDP serves as the dependent variable in the reviewed scholarly works This approach enables researchers to explore the causal mechanisms that connect economic growth with income disparity.
20 income inequality, thus providing valuable insights for policymakers and practitioners alike
DATA AND RESEARCH METHODOLOGY
Research Methodology
This article examines the complex relationship between GDP and income inequality in Southeast Asian countries from 2013 to 2022, highlighting the need for a detailed quantitative research methodology This investigation is essential for informing policy decisions, promoting social equity, and supporting sustainable development initiatives A careful and comprehensive approach, utilizing various methodological tools and analytical techniques, is crucial to effectively address the economic dynamics and social disparities in the region.
This investigative journey is grounded in an extensive literature review that explores the theoretical foundations and empirical insights related to GDP growth and income inequality By integrating perspectives from economics, sociology, political science, and public policy, this comprehensive review acts as a guiding framework, offering a wealth of theoretical models, conceptual paradigms, and empirical evidence to shape the forthcoming analysis.
Following the initial research phase, the focus shifts to the careful curation of data, similar to piecing together a complex jigsaw puzzle from various sources This involves the challenging task of gathering GDP data, income inequality indicators, and numerous control variables from reputable repositories, including the World Bank, Asian Development Bank, and national statistical offices However, acquiring the data is just the beginning; the next steps involve a strong commitment to data validation and cleansing, using various statistical techniques and quality assurance measures to ensure the reliability and quality of the data.
With the data landscape meticulously mapped and the analytical canvas primed, the research voyage progresses into the realm of econometric inquiry, where
Sophisticated statistical methodologies and computational algorithms are essential for navigating the complexities of economic research Key tools such as panel data analysis, fixed-effects, and random-effects regression models are specifically designed for longitudinal studies that span multiple countries and years The application of these analytical techniques goes beyond basic statistics; it represents a dedicated effort to uncover insights into the relationship between GDP growth and income inequality, while also accounting for various confounding factors that could obscure these connections.
This article emphasizes the importance of transparency and reproducibility in scientific research, which are essential for maintaining scholarly integrity Every aspect of the research process, including data collection, validation, and analysis, is carefully documented, akin to a map for future researchers This dedication enhances the credibility of the findings and encourages collaborative inquiry, inviting feedback and validation from peers within the academic community.
This study adopts a rigorous quantitative research methodology to explore the complex relationship between GDP growth and income inequality in Southeast Asia By integrating theoretical insights and methodological precision, the research aims to reveal empirical trends while providing actionable insights and policy recommendations The ultimate goal is to promote inclusive growth, reduce socio-economic disparities, and support sustainable development in the region and beyond.
Before running models, the study would calculate the PW-CV index Following Kyriacou & Roca-Sagales (2012), PW-CV can be estimated by the following formular:
In Southeast Asia, the average GDP per capita, denoted as gdpse, is calculated based on the total population, referred to as totalpop, of the region Each country's GDP per capita, represented as gdp, along with its population, indicated as pop, contributes to this overall economic metric.
This study utilizes a model inspired by Kuznets (1955) and previous research to analyze the relationship between economic growth and income inequality in Southeast Asia The proposed analytical framework aims to assess how economic growth influences income inequality in the region.
PW–CV ij = β 0 + β1gdp ij + β2pop ij + β3edu ij + β4fdi ij + β5covid ij + ε ij
Table 1: Explanation of Variables in the Model
The PW-CV index quantifies income inequality in a country (i) for a specific year (j), utilizing correlation coefficients β0, β1, ,β5 to analyze various factors Key variables include gdpij, representing the Gross Domestic Product of the country in year j, and popij, which denotes the total population Additionally, eduij reflects the secondary education completion rate, while fdiij measures foreign direct investment levels A dummy variable, covidij, is also incorporated to assess the impact of the COVID-19 pandemic on these metrics.
If (j) >= 2020, covid ij =1; If (j) < 2020, covid ij =0 ε ij Random variable
Source: Compiled by group of authors
To study the impact of GDP on income inequality, the research paper chooses to use two regression models: Random Effects Model (REM) and Fixed Effects Model (FEM)
The study conducts the F-Test to select the regression model between the Pooled OLS and FE:
The null hypothesis (H0) posits that Pooled Ordinary Least Squares (OLS) is suitable, indicating that individual-specific or time-specific effects are not significant This suggests that there are no meaningful differences across entities or over time, making the Pooled OLS model adequate for analysis.
The Fixed Effects Model (FEM) is suitable when individual-specific or time-specific effects are significant, indicating notable differences across entities or over time This model effectively captures these variations, making it the preferred choice for analysis in such scenarios.
If the p-value of the F-test is less than 0.05, indicating that the fixed effects model is more appropriate
The Breusch-Pagan Lagrange Multiplier (BP-LM) test is essential for determining whether to use a random effects model or a pooled OLS model in statistical analysis This test evaluates the presence of significant random variation among entities, which supports the appropriateness of a random effects model.
The hypothesis H0 suggests that using Pooled Ordinary Least Squares (OLS) is suitable, indicating that there is no significant variance across different entities or time periods This means that the random effects are negligible, and a Pooled OLS model can adequately capture the data without the need for more complex modeling.
The Random Effects Model (REM) is suitable when the variance among entities or time periods is greater than zero, indicating the presence of significant random effects Consequently, the random effects model is deemed more appropriate for analysis in such scenarios.
If the p-value of the BP-LM test is less than 0.05, indicating that the REM is more appropriate
The study conducts the Hausman test to select the regression model between the FEM and the REM with the hypothesis that:
● H 0 : Between the explanatory variables and the random component, there is no correlation (REM model is suitable)
● H 1 : Between the explanatory variables and the random component, there is correlation (FEM model is suitable)
If the Hausman test yields a P-value < 0.05, indicating a correlation between the explanatory variables and the random component, we use the FEM; otherwise, we use the REM
If the FEM is accepted, the independent variable is likely to be endogenous On the contrary, if REM is accepted, the possibility of endogeneity is low
The study evaluates the regression model by testing for heteroscedasticity and autocorrelation If these issues are identified, the model will be adjusted using Generalized Least Squares (GLS) to ensure accuracy.
The test for heteroscedasticity has two hypotheses:
● H0: There is no heteroscedasticity in the model
● H1: There is heteroscedasticity in the model
If the test yields a P-value < 0.05, indicating the presence of heteroscedasticity in the model Otherwise, the model has no heteroscedasticity
In terms of autocorrelation, the hypotheses are:
● H0: There is no autocorrelation in the model
● H1: There is autocorrelation in the model
If the autocorrelation test yields a P-value < 0.05, then autocorrelation is present; otherwise, it is not
Data collection
The investigation of the intricate relationship between income inequality and GDP in Southeast Asia requires an in-depth analysis of complex socio-economic dynamics This research aims to uncover the connections between income distribution disparities and economic fluctuations, employing a rigorous methodology to clarify these phenomena and provide insights into the mechanisms that drive them.
The analysis focuses on identifying key variables, primarily income inequality as the dependent variable, which reflects the differences in income distribution within a population GDP is the independent variable used to measure economic prosperity and development, offering insight into the macroeconomic conditions of the nations studied Acknowledging the complexity of these relationships, the research incorporates various control variables to enhance the core analysis.
Demographic factors, particularly population size, play a crucial role in influencing income distribution dynamics By analyzing population data, this study aims to contextualize income inequality within the demographic framework of each nation, highlighting potential demographic drivers behind income disparities Additionally, education, exemplified by secondary education completion rates, is identified as a significant factor affecting income inequality, emphasizing the importance of human capital development in determining economic outcomes.
Foreign Direct Investment (FDI) plays a crucial role in driving economic growth and development This research aims to measure the impact of FDI inflows on income distribution dynamics in the examined countries Additionally, the COVID-19 pandemic has emerged as a significant variable, creating unprecedented challenges that have affected economies globally.
Integrating COVID-19 into the analytical framework acknowledges the pandemic's unique challenges and its significant impact on income distribution and economic growth By using a binary dummy variable to define the pandemic period, this research seeks to clarify the specific effects of COVID-19 on income inequality and GDP trends, providing crucial insights into the resilience of socio-economic systems during unprecedented disruptions.
The research design is refined iteratively to enhance robustness and reliability while addressing the complexities of data availability and methodological choices Although the GINI coefficient was initially intended as the main measure of income inequality, practical constraints require a shift in methodology.
In response, the research adopts the PW-CV as a more feasible alternative, demonstrating a commitment to adaptability and methodological rigor
The PW-CV index measures income inequality in a country (i) for a specific year (j) and is calculated using STATA with data from the World Bank The correlation coefficients, represented by β 0 , β 1 , ,β 5, provide insights into the relationship between various economic factors Additionally, gdp ij denotes the GDP of the country (i) in year (j), while pop ij indicates the total population for the same country and year, sourced from the Asian Development Bank (ADB) Furthermore, edu ij reflects the completion rate of secondary education in the country (i) during the year (j), also obtained from ADB.
28 fdi ij The index measures the FDI of the country
(i) in the year (j) ADB covid ij
If (j) >= 2020, covidij=1; If (j) < 2020, covidij=0 ε ij Random variable
Source: Compiled by group of authors
Utilizing extensive data from reputable sources like the World Bank and the Asian Development Bank, this study provides a thorough analysis up to 2023 The research team's commitment to data accuracy ensures that the findings are both academically sound and relevant to real-world situations By analyzing these carefully selected datasets, the study aims to deliver in-depth insights into the complexities of income inequality and GDP in Southeast Asia, enhancing our understanding of the region's socio-economic landscape.
The research paper assesses the GDP growth and inequality in Southeast Asia from 2013 to 2022, highlighting significant economic progress, particularly in countries like Vietnam, the Philippines, and Indonesia Despite this growth, economic inequality persists, with notable disparities in income and access to opportunities among various demographic groups and regions within countries Many nations still depend on natural resources and cheap labor, leading to uneven development and a pressing need to shift towards a knowledge-based and technologically advanced economy Furthermore, challenges such as climate change and the COVID-19 pandemic have exacerbated risks for both economic and social development in the region.
This chapter offers a detailed overview of the research methodology used to explore the relationship between GDP and income inequality in Southeast Asia from 2013 to 2022 It includes a thorough literature review and careful data collection from credible sources like the World Bank and the Asian Development Bank The study employs various econometric models, such as panel data analysis, Pooled OLS, fixed-effects, and random-effects regression models, to assess the impact of GDP and other independent variables on income inequality, measured by the Population Weighted Coefficient of Variation (PW-CV) The chapter emphasizes transparency and reproducibility, outlining steps to ensure data validation and reliability, while also highlighting the necessity of correcting for heteroscedasticity and autocorrelation in regression models, utilizing the GLS model when required.