1 © 2025 by the author; licensee Eastern Centre of Science and Education, USA Asian Business Research Journal Vol. 10, No. 5, 1-11, 2025 ISSN: 2576-6759 DOI: 10.55220/25766759.410 © 2025 by the author; licensee Eastern Centre of Science and Education, USA The Gini Index’s Dynamics as a Reflection of India’s Income Inequality Mohd Naved Khan College of Administrative and Financial Sciences, Saudi Electronic University, Riyadh, KSA. Email: m.naved@seu.edu.sa Abstract This paper aims to understand the income inequality trends in India using the Gini Index over time. The study makes a case for India’s economic expansion despite the existing social classes and efforts to clarify the role of the Gini Index in addressing this multifaceted phenomenon. It examines the historical context of income disparity in India. The research methodology entails the analysis of secondary data and pre-existing studies regarding income distribution and inequality in India. This encompasses official government publications, surveys, databases, scholarly journals, and studies. The research employs data from esteemed sources such as the World Bank, IMF, and Indian governmental statistical agencies, concentrating on household surveys and socioeconomic metrics. The India Human Development Survey is a principal data source, offering extensive information on household income, education, and socioeconomic attributes. The results demonstrate the variable nature of India’s Gini Index, highlighting the relationship among social programs, structural reforms, and economic growth. Post-independence policies initially maintained a stable Gini Index; however, economic liberalization increased income inequality, concentrating wealth among the wealthy. The study examines the effects of geographical disparities, the rural-urban split, and various socioeconomic determinants on income inequality, providing insights into the obstacles and potential remedies for attaining a more equitable income distribution in India. Keywords: Gini Index, Income inequality, India, Socioeconomic development, Structural reforms. 1. Introduction Considering India’s significant economic expansion and advancement in recent decades, income disparity in the country has been the focus of much research and discussion (Mishra et al., 2019). In India, the huge socio-economic problem is the diversity in its population, the growing economy, and the ever-enduring inequalities. We have had several changes in the Indian economy over the years, such as the change from communist policies during the early years of post-independence to policies of globalization today; all these changes have not affected income inequality. A very important way of measuring income inequality is using the Gini Index. This is how these inequities are examined. Many policymakers and scholars use this basic indicator, with 0 representing perfect equality and 1 perfect inequality, to analyze and combat socioeconomic problems. The fluctuations in India’s Gini Index demonstrate the intricate relationships between social policies, structural changes and economic development. The state’s focus on agrarian reforms and redistribution resulted in a relatively stable Gini Index in the decades following independence. However, when market-driven prosperity began to reveal income disparities, the deregulation of the 1990s indicated a transition. Recent evidence indicates that economic advancement has enabled millions to rise from poverty. However, it has also exacerbated income disparity by concentrating money among the affluent (WorldBank, 2020). Regional disparities among the rural-urban sectors, caste-based inequality, gender disparities, and the significance of the informal sector influence the dynamics of the Gini Index in India. Research indicates that urban elites have disproportionately reaped economic benefits from urbanization and industrialization, worsening the wealth gap between rural and urban inhabitants (Chancel & Piketty, 2019). Besides, social groups always tend to be at the most disadvantaged end of the scale in terms of education and employment opportunities. Due to these traditional social orders, such as the caste system, economic inequality is further aggravated (Drèze & Sen, 2013). Government interventions have also influenced the Gini Index. The Gini Index on inequality has been addressed locally by providing social services, for example, through MGNREGA and food and education subsidy schemes. Nonetheless, persistent structural issues such as tax evasion and inadequate redistributive policies have had a negligible impact on reducing the Gini Index (Economic Survey, 2023). Furthermore, globalization and the expansion of technology-driven economies have introduced novel forms of inequality, with access to technology and digital literacy becoming critical determinants of economic mobility (UNDP, 2020). This article provides an in-depth analysis of the changing Gini coefficient in India, how it has changed over time and what caused these changes. It also explores how these events shaped income inequality – for example, the mailto:m.naved@seu.edu.sa https://doi.org/10.55220/25766759.410 Asian Business Research Journal, 2025, 10(5): 1-11 2 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Green Revolution, the liberalization of the economy and the development of digital sectors. The discussion evaluates the efficacy of policy efforts to foster inclusive growth and reduce inequities. The Gini Index ultimately represents the socioeconomic composition of the nation rather than only providing a numerical representation of income inequality. Understanding its dynamics in the Indian context will help one better understand the larger problem of attaining sustainable and equitable development (Darku et al., 2020). Although India’s economy has been expanding quickly, Himanshu, (2022) claims it is still one of the nations with the most unequal income distribution. Over the last thirty years, there has been a tremendous increase in inequality. Through strategies such as inheritance and crony capitalism, the wealthiest individuals in the country have collected a significant portion of the nation’s wealth. As a result of ongoing underfunding, those who are in poverty continue to struggle to make the minimum wage and to gain access to high-quality healthcare and education. On the other hand, wealthy people are becoming wealthy far more quickly. Women and children are particularly impacted by the widening divides and inequality that are occurring. If the data is divided into urban and rural components, the rural population is the primary factor that leads to the drop at the bottom end of the income distribution. According to Sahasranaman & Kumar, (2019), the real average income experienced a decrease of 4.3% annually, leading to a fall of roughly 41% in the income segment of the lowest decile within the income distribution of rural India. On the other hand, the income shares at the lowest end of the urban distribution have increased throughout different historical periods. Furthermore, the movement of disparities in income in India has been significantly impacted by the drop in real earnings at the lowest tier, as indicated by these data, demonstrating that rural incomes form the predominant component of the lowest ventile in India’s aggregated income distribution. Second, metropolitan regions have had greater economic growth than rural areas because they have better access to medical care, educational opportunities, and employment opportunities. Despite employing a significant fraction of the workforce in India, the unregulated sector frequently fails to provide adequate social protection and fair wages (Guha et al., 2021). This further worsens the country’s income disparities. When attempting to ascertain income, many economists looked at the annual tax statistics published by the governments of India and Britain since 1922. The richest one per cent of India’s population controlled between 20% and 21% of the country’s GDP even during the most unequal period in India’s history, which lasted from the 1930s until the country gained its independence in 1947 (Ranvanshi, 2024). By 2022, there were 162 billionaires in India, while in 1991, there was just one billionaire. During this time, their total net worth as a percentage of India’s national income “soared from less than 1% in 1991 to a whopping 25% in 2022” (Ranvanshi, 2024). The economic liberalisation in India in the early 1990s marked a dramatic change toward a market-oriented economy (Ghosh, 2013). This liberalisation was responsible for India's enormous economic growth and development. On the other hand, not the entire Indian population profited evenly from this expansion. There was an increase in the general income levels, however, studies have shown that the richer segments of society reaped maximum benefits from the economy’s success. The increasing Gini index shows that this resulted in a widening gap between the rich and the poor. Further, there has been an increase in the difference between incomes due to the growth of technology and globalisation. Additionally, they have resulted in the relocation of jobs and wage polarisation, which has negatively impacted people with low levels of ability, even though they have created new markets and possibilities. These trends are shown through analysis of the Gini index, which demonstrates indisputably how structural changes and economic policies influence income distribution. To establish policies promoting inclusive growth, policymakers need to comprehensively understand the evolution of income disparity, as measured by the Gini coefficient. Truong & Barreto, (2020) said that to ensure everyone in society benefits equally from economic growth, we need to take targeted actions like making it easier for more people to get good healthcare, social protection, and education. 2. Literature Review Given the complexity and discrepancies in India’s socioeconomic structure, income disparity generated much discussion among economists and policymakers. The Gini Index, a statistical instrument measuring the degree of income distribution among the population, is a crucial metric to evaluate this disparity. The purpose of this literature review is to attempt to consolidate and integrate the corpus of information that is currently accessible in order to provide a comprehensive understanding of how the Gini Index portrays the intricate economic disparities that exist within India. The evaluation also identifies areas requiring further investigation and highlights deficiencies in the current comprehension. Considering the global Gini coefficient, according to Lakner & Milanović, (2015), global income inequality fell by 2 Gini points from 1988 to 2008 but stayed at about 70.5%. According to one key result, Chinese economic growth has lifted the country out of poverty and contributed to the emergence of a global “median” class. Accounting for potential underreporting of top incomes results in a less pronounced declining trend and a higher Gini of approximately 76%. However, Chauhan et al., (2015) indicate that income disparity increased in various regions of India from 1993 to 2012, even as poverty rates declined overall. Four regions experienced no change in poverty levels, whereas seven regions observed an increase. Significant poverty levels continued to exist in the southern areas of Chhattisgarh and Odisha. The increase in the poverty headcount ratio throughout the study indicates a widening disparity in regional poverty. As Batra & Reio, (2016) note, a wider issue in India revolves around gender inequality. The study discusses the existence of gender-based income differentials and emphasizes the need to examine sociocultural determinants of income and opportunity inequality. The report analyses the differences in income distribution and discrimination in India from 2014 to 2019, analyzing contemporary trends. The examination reveals that while overall income inequality has remained relatively stable, significant declines have occurred at the lower end of the income spectrum, particularly in rural regions. A comprehensive understanding of the Gini index’s dynamics on a global scale necessitates an examination of the broader international environment. The research highlights that the Asian Business Research Journal, 2025, 10(5): 1-11 3 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA perceived trend in global income inequality can be significantly altered by adjusting the Gini index to account for the underreporting of high incomes. Das, (2019) further investigates India’s educational disparity and how it affects affirmative action and income distribution. The study highlights how significant social and gender gaps in educational access, particularly in rural areas, intensify the wealth disparity. Das, (2019) also examines the relationship between earnings and educational disparity, showing that the distribution of educational opportunities strongly impacts income inequality and earnings distribution. Sahasranaman and Jensen (2019) analyze the dynamics of income inequality in India, highlighting the nation’s shift from a progressive to a regressive redistribution system. The authors contend that the persistent impoverishment of the poor directly propels the exponential income rise of the wealthy, resulting in a concerning trend of escalating inequality. Furthermore, it analyzes the alterations in income in India from 2014 to 2019, revealing that while overall disparity remained essentially constant, the lowest section of the income distribution saw substantial losses, especially in rural areas. Kulkarni and Gaiha (2020) examine the relationship between poverty and economic inequality in India, emphasizing the gap between the wealthiest 1% and the poorest 50% of the population. It argues that increasing economic inequality aggravates poverty, drawing on prior studies, notably the work of Chancel and Piketty (2019). The research uses data from the India Human Development Survey (2005–12) to identify significant negative elasticities between increasing income inequality and poverty across multiple poverty indicators. Specifically, there are serious consequences for the most destitute individuals in society: a 1% increase in income inequality is associated with a 1.24% rise in the squared poverty gap. The study underscores the imperative for policies targeting income disparities to foster equitable growth in India, highlighting that even minor escalations in income inequality can significantly impact poverty levels. Sahasranaman and Kumar (2020) saw large deficits among the lower parts of the income distributions, suggesting the overall inequality remained static between 2014 and 2019. This indicates a drop in income share for the lowest rural quintiles by ~38% and a negative revenue growth at an average -4.6% yearly. The lowest decile of rural income distribution suffered more significant losses, with an annual real average income growth rate of -4.3% and a 41% decrease in income share. Income share rose at the lower end of the urban income distribution relative to rural regions. Small and marginal farmers and agricultural laborers are closely linked to the lowest decile of rural income distribution, underscoring the growing economic instability of these professions. Analysis employing the RGBM model indicates that reallocation has diminished since 2015, becoming negative in 2018, consistent with the decline in real income. Indian respondents significantly overestimated the extent of economic inequality in India; over 90% of those surveyed believed that inequality was far greater than the Gini coefficient. According to Gulati & Ying (2021), the quality of government is the most critical factor affecting public perception of economic inequality. Mitigating inequality necessitates improved governance. Dang and Peter (2021) emphasize the nation’s historical focus on poverty rather than overall inequality. They indicate that with the acceleration of economic growth and the reduction of absolute poverty, attention has shifted to the broader distributional impacts of the economy, raising concerns about social stability due to rising inequality. The variation concerning upward horizontal mobility is greatly affected by India’s caste system and the differences it creates. Their research focuses more on the patterns and trends caught on film in India over three decades until 2011-2012. In the early 1990s, economic liberalisation in India’s mixed market controls changed too much, fueling some growth and increasing income inequality. Chakraborty (2023) and similar studies suggest that the growth is disproportionately distributed, giving the better-off households a bigger advantage. The Gini index exhibited an upward trend during this period, signifying an expansion of income disparities. The division between rural and urban areas has profoundly influenced the patterns of economic inequality in India. Similar findings were reported by Azam and Shariff (2011), indicating that income disparity in rural India increased from 1993 to 2005. Salaries and farm income are two sources that contribute to inequality. Income from both agricultural and non-agricultural casual labour can also reduce inequality. In rural India, developing non-agricultural employment opportunities can also reduce wealth inequality. Sheoran (2024) analyses the intricate issue of wealth disparity in India, highlighting its sociological implications and historical underpinnings. India’s complex and varied social structure has resulted in income inequality, characterised by the disproportionate distribution of income among individuals or households, which poses a significant socioeconomic challenge. According to the findings, income disparity in India is not just a statistical issue but also a considerable element influencing social cohesiveness and economic stability. The authors Roy et al., (2024) provide a comprehensive analysis of the wealth gap in India. They discovered that there are significant geographical variances in the distribution of household wealth across the country. The data comes from the National Family Health Survey, which gathers information from 707 different areas. The findings indicate that India’s central, eastern, and northeastern regions experience elevated levels of inequality, while affluent households are predominantly situated in the northwestern and southern regions. Rurality, low female literacy rates, the educational level of household heads, and the prevalence of Scheduled Castes/Tribes are significant factors associated with wealth disparity. According to the research, more than 90% of the variance in characteristics of wealth distribution may be explained by geographical regression models, specifically GWR and MGWR. In order to guide efforts for equitable growth in different socioeconomic circumstances, the study highlights the significance of understanding the regional dynamics of wealth disparities. These studies’ discussions led to the formulation of the following research questions. 3. Research Objectives The primary objective of the research is to comprehensively examine the trends in the Gini Index, a widely used indicator of income inequality, with a particular focus on India. Asian Business Research Journal, 2025, 10(5): 1-11 4 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA • One of the specific objectives is to investigate the patterns and changes in the level of income inequality in India over time, with the Gini Index as the major indicator. • Determining the social, economic, and policy-related variables influencing income inequality in India. • Estimating the influence that income inequality has on the growth of the economy, the cohesiveness of society, and the general well-being of people. • It is important to provide stakeholders and lawmakers with viewpoints and proposals to combat income disparity and achieve fair socioeconomic results. 4. Research Methodology This study will investigate the trends of India’s Gini index from multiple angles, drawing on secondary data and existing literature. Income inequality in India is represented by the Gini Index, which is examined through a comprehensive data collection technique. Data for this study will primarily originate from official Indian government publications, surveys, and datasets that measure income disparity and distribution. Secondary data from academic journals, research papers, and studies dealing with India’s wealth disparities has also been collected. Primarily, the data has been collected from credible sources such as the World Bank, the International Monetary Fund, and statistical agencies of the Indian government. This data set provides a series of income distribution, household surveys, and other relevant socio-economic indicators that may be used to compute the Gini Index and comprehend the patterns of income inequality in India. The India Human Development Survey data offers extensive information on household income, education, and socioeconomic characteristics and allows for a thorough examination of income inequality across various demographic and geographic groupings. Upon data collection, suitable analytical methods will be used to analyze the trends in the Gini Index and, hence, the income inequality in India. The main analysis entails calculating and analysing the Gini Index, a common statistic for determining income inequality. A higher Gini coefficient reflects a higher inequality of income within a community. A descriptive statistical analysis summarises income distribution trends and changes over time. Thus, computation regarding mean income, median income, and quartiles is done in detail to analyze inequalities in income in the Indian context comprehensively. The analysis will encompass the subsequent steps: a. The Gini index data is sourced from World Bank statistics from 2014 to 2023. The data is subsequently validated by the SBI report (Gini Index, 2023). b. Analyze temporal trends in the Gini index, noting any substantial variations or patterns. c. Disaggregate the Gini index data to examine disparities across several states, rural and urban regions, and demographic categories (e.g., gender, caste, educational attainment). d. Utilizing the existing body of research, investigating the socioeconomic, policy, and structural factors that have the potential to influence the observed changes in income disparity. e. Investigate the impact of differences in education, employment, and regional circumstances on the documented income disparity patterns. f. Analyze the findings’ implications for policymakers and outline potential approaches to reducing the income gap in India. 5. Investigation and Discourse A typical Indian, beyond the elite, may benefit from globalization, provided the government increases public investments in health, education, and nutrition. Furthermore, a 2% “super tax” on the net wealth of the 167 wealthiest Indian households in 2022-23 would generate revenues amounting to 0.5% of national income and create significant fiscal space to enable such investments (Ranvanshi, 2024). A report by Oxfam (Himanshu, 2022) indicates that the wealthiest 10% of the Indian population owns 77% of the country’s total wealth. In 2017, 73% of wealth was concentrated in the hands of the wealthiest 1%, while 67 crore Indians, constituting the poorest half of the population, experienced a mere 1% increase. India hosts 119 billionaires. These numbers increased from only 9 in 2000 to 101 in 2017. Between 2018 and 2022, India is anticipated to produce 70 new millionaires daily. The net worth of billionaires increased almost tenfold during a decade. Their aggregate financial resources exceed India’s Union budget for the fiscal year 2018-19, amounting to Rs 24,422 billion. Menon (2024) analyzes taxpayer data, demonstrating a reduction in the Gini coefficient, a measure of income inequality, from 0.472 in 2014-15 to 0.402 in 2022-23. This reduction of roughly 15% signifies a noteworthy decline in income inequality over this period. To ascertain, data presented in Table 1 is sourced from the World Bank website. Table 1. Gini Coefficient Year Gini Coefficient 2014 0.47 2015 0.47 2016 0.47 2017 0.47 2018 0.46 2019 0.46 2020 0.46 2021 0.45 2022 0.41 2023 0.40 Source: World Bank, State Bank of India. Asian Business Research Journal, 2025, 10(5): 1-11 5 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Table 1 displays the Gini Coefficient for India from 2014 to 2023. From 2014 to 2023, the Gini Coefficient has constantly decreased, showing a drop in income inequality for this period. This could be due to different socio- economic policies, economic growth, access to more education, and other factors that might have helped distribute income more equitably. The data might indicate that initiatives for poverty reduction, economic inclusion, and reduction of disparities in development have been effective. The notable declines observed in specific years, such as 2021-2022 and 2022-2023, can be attributed to deliberate initiatives or economic conditions favouring a more equitable income distribution. It is relevant to analyze these years’ economic and social environment, including changes in tax laws, changes in minimum wage, and modifications in social assistance programs that may affect income distribution. The Gini Coefficient fell from 2014 to 2023, reflecting improvements in reducing income inequality in India. Scholarship corroborates this; for instance, Sahasranaman & Jensen, (2019) find that India has moved away from progressive and towards regressive redistribution with the continued deprivations among the poor, enabling significant income rises among the richest. Rural-urban separation is a vital issue, with intrastate income discrepancies accounting for a substantial share of interdistrict inequality in urban India, as noted by Azam & Bhatt, (2016). Although the Gini coefficient has decreased, income inequality in India persists at a significant level, as indicated by the substantial proportion of wealth possessed by the top 10% of the population (Lawson et al., 2018), (Vatta & Pavithra, 2016), (Roy et al., 2024). The findings indicate that although India has improved in diminishing overall income disparity, considerable obstacles persist in tackling the fundamental structural and socioeconomic factors contributing to inequality, especially in education, employment, and regional development. The study further analyses rural and urban Gini coefficients and their differences. Table 2. Gini Coefficient for Rural/Urban Areas with Difference. Year Rural Urban Difference 2014 0.396 0.426 0.030 2015 0.392 0.422 0.030 2016 0.387 0.417 0.030 2017 0.382 0.413 0.031 2018 0.377 0.409 0.032 2019 0.371 0.403 0.032 2020 0.368 0.400 0.032 2021 0.36 0.392 0.032 2022 0.352 0.384 0.032 2023 0.346 0.376 0.030 Source: State Bank of India and World Bank. It is pointedly underscored that this persistent rural-urban divide, coupled with gender and socioeconomically unequal barriers, influences income distribution in India. Table 2 presents information on metropolitan regions between 2014 and 2023, evidencing the decrease in income disparity between rural and urban parts of India. It indicates higher disparities within metropolitan regions than in rural areas. Overcoming such disparity requires a continued effort at legislation and intervention for inclusiveness in economic growth. This indicates that urban areas exhibited greater income inequality than rural areas in 2014, and this tendency persisted into 2015. In 2016, both rural and urban regions experienced a marginal reduction in inequality, a trend that continued, followed by a modest increase in the disparity in 2017. In 2018, both rural and urban areas had a decrease in inequality despite a marginal widening of the gap by 0.032. In 2019, the trend of diminishing inequality continued, with the disparity constant. In 2020, it is apparent that both rural and urban regions experienced a continued reduction in inequality. No alterations occurred in 2021, but a persistent decline in inequality in both rural and urban areas was observed in 2022. The reduced gap of 0.030 between rural and urban disadvantages is seen in 2023. The reduced income share of the underprivileged rural population significantly contributes to the overall rise in inequality. During the research period, real average income rose by merely 4.3% annually, although the poorest decile’s proportion of rural income dropped by 41.1% (Vatta & Pavithra, 2016). These patterns underscore the increasing disparity between rural and urban areas and the expanding divide between the wealthy and the underprivileged among the rural population. Figure 1. Gini Coefficient for Rural/Urban Area with Difference. Asian Business Research Journal, 2025, 10(5): 1-11 6 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Figure 1 illustrates the Gini Index for rural and urban regions of India from 2014 to 2023, highlighting the disparity between the two indices. The Gini indices for rural and urban areas have steadily decreased over the years, indicating a reduction in income inequality. The discrepancy between the rural and urban Gini coefficients is consistently minimal throughout the duration. Urban regions have continuously expressed a higher income inequality than rural regions over these years. This could be due to diverse economic perspectives and inequality within urban settings. The gap in Gini coefficients between rural and urban areas has remained quite stable over the years; scientists have remarked that only small deviations have occurred. The gap demonstrated only a slight decline in 2023 compared to previous years (Wang et al., 2020). Indeed, inequality has been reduced due to some influences: economic growth, the government's poverty reduction policy, and social welfare. Initiatives such as the MGNREGA (Mahatma Gandhi National Rural Employment Guarantee Act) and other urban development programs have marked these changes significantly (Farooquee, 2013). The pandemic caused significant changes in income distribution. The data indicates a persistent reduction in inequality; however, the economic disruptions from COVID-19 may have impacted various income groups disproportionately, with rural regions possibly gaining from agricultural resilience while urban areas encounter more severe economic difficulties (Mueller et al., 2020). Ongoing initiatives are required to tackle economic disparity, particularly in metropolitan regions. Policies targeting education, healthcare, and employment opportunities can reduce disparities and foster equal growth. Policymakers must implement a comprehensive strategy that addresses the structural and socioeconomic determinants of inequality, emphasizing enhanced educational access, creating inclusive employment opportunities, and promoting equitable regional development. Given that it has to strive for sustainability and equitability, a broad policy-action direction to address the roots of income inequalities is crucial for India to allow benefits from economic progress to reach all sections evenly (Sahasranaman & Jensen, 2019); (Azam & Bhatt, 2016) and (Batra & Reio, 2016). 5.1. Urban Income Disparity in India (2014-2023) Urban regions in India have persistently demonstrated more income disparity than rural regions, as seen by the Gini Index data from 2014 to 2023. This inequality can be ascribed to multiple variables, such as various economic prospects, differing access to education and healthcare, and the concentration of wealth in urban areas (Chakraborty, 2018). The rural-urban gap remains a chronic issue in India, where urban regions frequently reap disproportionate economic growth and development advantages. The gradual increase in the urban population and the diminishing proportion of agricultural land in India’s GDP have intensified this disparity, as the urban-focused economic model has failed to provide equitable opportunities for all (Azam, 2019). Policymakers must address the root structural and socio-economic causes of urban inequality: disparities in the returns to education, unequal distributions of economic resources, and spatial inequalities in metropolitan areas. Investment in the cities’ infrastructure, housing affordability, and skill development programs is a strategic thrust for developing an inclusive and equitable urban environment (Sahasranaman & Kumar, 2020; Chakraborty, 2018). 5.1.1. Economic Prospects and Inequities Urban environments have diverse economies, ranging from high-paying IT and financial jobs to low-paying informal labour. Significant wealth disparities are caused by this type (Mela & Toldo, 2019). High-income industries like IT, banking, and real estate are concentrated in cities like Bangalore, Delhi, and Mumbai, which attract skilled workers and business owners. Whichever the case, these cities also host numerous people in low- income jobs, such as hawkers, house helpers, and construction workers. Incorporating high and low-income earning groups contributes to the high Gini Index in metropolitan areas. 5.1.2. Access to Education and Healthcare One of the major causes of economic inequality in urban centers is access to quality health and education services. Urban areas often have better educational institutions and healthcare facilities than rural ones. However, unequal access to such services is common. Affluent households can afford private education and healthcare, improving economic opportunities and health outcomes. In contrast, lower-income families are forced to use public services, often inadequately funded and overutilized. The disparity in access perpetuates economic inequality since the better-educated and healthier a person is, the higher-paying jobs he or she is likely to get. Mutisya et al., (2021) confirm this fact. 5.1.3. Wealth Accumulation The concentration of wealth in cities considerably accelerates economic inequality. Investments and businesses naturally flock to urban centres. Hence, wealth tends to be concentrated within a limited population. A case in point is real estate. Property prices in metropolitan cities such as Mumbai and Delhi have stratospherically risen, thus yielding gains for property owners and investors and rendering housing well out of the reach of others (Nijman, 2006). Such concentration of wealth among property owners and high-salary professionals aggravates economic inequality. 5.1.4. Government Regulations and Social Initiatives Government policies and social activities have impacted urban income inequality; however, their consequences have been variable. Initiatives focused on poverty reduction, such as the Pradhan Mantri Awas Yojana (PMAY) for affordable housing and the National Urban Livelihoods Mission (NULM) for employment creation, have offered certain alleviation (ActionAid, 2024) & (Aarohi D. & Siddharth K.J., 2024). Yet, these programs do little in scope and implementation to tackle the more structural roots of such inequalities. Further, policies related to urban planning and development are also often biased toward rich individuals; such conditions could precipitate gentrification and dislocation of the poor. Asian Business Research Journal, 2025, 10(5): 1-11 7 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA 5.1.5. Impact of COVID-19 COVID-19 seriously impacted economic inequality within cities. The economic disruptions caused by lockdowns and restrictions significantly affected low-income workers in the informal sector, with many experiencing job loss or considerable wage reductions. In contrast, individuals in higher-income brackets, particularly those able to work remotely, faced reduced impact (Boza‐Kiss et al., 2021). The epidemic highlighted and sometimes intensified existing inequalities, underscoring the need for enhanced social safety nets and inclusive economic policies. The issues of urban income inequality in India can be addressed through improved access to quality education and healthcare, inclusive urban development policies, and inclusive economic growth for all segments of society. When these challenges are addressed, India can promote equitable and sustainable urban environments (Patil & Sharma, 2020). 5.2. Income Inequality in Rural India between 2014 and 2023 The Gini Index for rural areas in India declined continuously between 2014 and 2023. This trend suggests many socio-economic factors, including agricultural policies, rural development initiatives, and demographic shifts. 5.2.1. Agricultural Policies and Income Distribution Agriculture remains the cornerstone of rural India, employing a significant portion of the population. Government programs supporting agriculture, such as minimum support prices (MSP) for crops, fertilizer subsidies, and irrigation initiatives, have stabilised rural incomes. These methods promote fair pricing for agricultural products, thereby reducing income disparities (Venumuddala, 2020). Nevertheless, the majority of farmers continue to sell their produce to local merchants, which means that they do not directly benefit from MSP. The level of awareness regarding MSP was also found to be extremely low, with 70% of farmers being oblivious to it (Korekallu et al., 2023). 5.2.2. Schemes for Rural Development Several schemes for rural development have contributed significantly to reducing the gap in income inequality. MGNREGA (Mahatma Gandhi National Rural Employment Guarantee Act 2005) is one significant scheme that guarantees employment to rural households. It serves as a safety net that alleviates income instability and supports the livelihoods of the most impoverished segments of the rural population (Mir et al., 2018). Additionally, programs like the Pradhan Mantri Gramme Sadak Yojana (PMGSY) and the National Rural Livelihoods Mission (NRLM) aim to improve infrastructure and create sustainable employment opportunities, thereby promoting a more equitable income distribution (Patnaik & Prasad, 2014). 5.2.3. Access to Education and Healthcare The government of India has given considerable thrust to rural access to education and healthcare. There are programs such as SSA and NHM to improve the reach and quality of services. Improved access to these services can help rural people seek better-paying jobs and improve their economic status. Improved access to essential services can help rural residents seek better-paying jobs and improve their economic status (Gopalakrishnan & Immanuel, 2017). However, disparities exist in accessing these services, especially among far-flung and disadvantaged groups. 5.2.4. Migration and Remittances Rural-to-urban migration is a common feature in India, mainly influenced by the search for better employment opportunities. Remittances migrants send to family members in rural areas significantly affect income distribution. Remittances are like an added source of income that helps reduce poverty and inequality. However, the benefits from migration are distributed unevenly, with some families receiving substantial remittances while others gain little to no assistance. 5.2.5. The Consequences of COVID-19 The COVID-19 epidemic had a two-pronged effect on rural income inequality. On the one hand, the lockdown and job loss in urban centres precipitated the arrival of migratory workers in rural areas, thus raising labour supply and, more than likely, depressing wages. On the other hand, the government relief programs were a vital source of sustenance for the rural populace through increased money allocations for MGNREGA and direct cash transfers. Since the farming sector received consistent agricultural returns from favourable monsoon seasons, it proved resilient during the epidemic. After collecting data from the World Inequality Database, further investigation was conducted using the percentile. Asian Business Research Journal, 2025, 10(5): 1-11 8 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Table 3. Gini Index with Percentile. Per-centile 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Bottom 50% Pre-tax national income p0 p50 0.1313 0.1297 0.1256 0.1239 0.1281 0.1307 0.1372 0.1364 0.1325 0.1325 Middle 40% Pre-tax national income p50 p90 0.2974 0.2926 0.2822 0.2774 0.2826 0.2824 0.2826 0.2817 0.2786 0.2786 Top 10% Pre-tax national income p90 p100 0.5713 0.5777 0.5923 0.5987 0.5893 0.587 0.5802 0.5819 0.5889 0.5889 Top 1% Pre-tax national income p99 p100 0.2173 0.221 0.2264 0.2265 0.2278 0.2203 0.2199 0.2213 0.2307 0.2307 GDP Constant (2023) pall 6658.16 7041.44 7465.79 7811.36 8152.88 8308.63 7681.22 8240.56 8708.71 9238.69 Asian Business Research Journal, 2025, 10(5): 1-11 9 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Table 3 represents the income distribution statistics. The dataset runs from 2014 to 2023 and reflects pre-tax national income share for the lowest 50%, middle 40%, top 10%, and top 1% in addition to GDP in constant 2011 USD. The data indicates a gradual decline in income inequality, with the pre-tax national income share of the poorest 50% having slightly increased over time, while the shares of the top 10% and top 1% have shrunk. It is possible to underline, by the Gini coefficient and income distribution, that despite overall economic growth, income inequality remains. According to Mishra, (2018), the promotion of equitable growth would need targeted measures since lower-income groups are relatively stable, the middle class has seen a slight decline while the rich have further concentrated their wealth. These issues must be considered if one wants a more equitable and long-term economic future where all share the benefits arising out of economic progress. Following 0.1313 in 2014, the pre-tax national income of the bottom 50%, p0p50, was 0.1325 in 2023, meaning the very stable share this demography possesses, with a slight fluctuation. The same trend has been followed over the past ten years regarding income distribution for the bottom half. The middle 40% Pre-tax National Income (p50p90) decreased from 0.2974 in 2014 to 0.2786 in 2023, indicating a marginal reduction in their share of pre-tax national income. This shows a slight deterioration in the economic status of the middle class over time. This group is essential for economic stability and growth, and its diminishing share may have wider repercussions for consumer expenditure and economic well-being (Eggimann & Kendzia, 2022). The top 10% of Pre-tax National Income (p90p100) fluctuates from 0.5713 in 2014 to 0.5889 in 2023, indicating that this demographic has consistently retained a substantial share of the national income, with a marginal increase over the years. This shows that there is still a significant income gap at the top. The increasing wealth disparity is evident since the pre-tax national income for the top 1%, p99p100, increased from 0.2173 in 2014 to 0.2307 in 2023. The level of income inequality has increased, and the top 10% have seen a high rise, especially the top 1%. This underlines the uneven distribution of economic resources and social uprisings, likely due to the increasing gap between the richest and the rest. According to a report by Oxfam, an international organization dedicated to poverty eradication, in 2017, the top 10% of earners in India held 80% of the nation’s wealth. The richest 1% holds 58% of Indian wealth, while the wealthiest 1% in the US has 37% of the total wealth (Basu, 2017). This pronounced inequality is not good for social cohesion, and it also binds future economic growth by limiting opportunities for the poor and middle class to participate in development and benefit from it. We choose 2023 as a reference year in national income and GDP discussions. The increase in GDP from 5754.60 in 2014 to 8014.53 in 2023 indicates a consistent rise in national revenue, signifying broad economic expansion. Nonetheless, this expansion has not been uniformly allocated across all income brackets. Even though the GDP) has seen a significant increase, the distribution of this growth has been unequal. There is a persistent and, in some cases, growing income discrepancy because the benefits of economic progress have not been dispersed uniformly. 6. Conclusion and Recommendations The Gini index between 2014 and 2023 indicates that income inequality decreased in some periods. However, according to consumption expenditure data (Vatta & Pavithra, 2016), many studies’ trends indicate alarming patterns. Inequality has remained elevated, as seen by the Gini coefficient rising from 33.4 in 2005 to 33.9 in 2012. Although the GDP has seen a significant increase, the distribution of this growth has been unequal. There has been a continued and, in some instances, an increasing income gap since the gains of economic growth have not been distributed evenly. From the trend observed in the figures above, policies are necessary to achieve a fairer income distribution. Such policies may include progressive taxation, higher social spending, and initiatives to support middle and low- income earners. Inclusive growth is pursued to achieve sustainable development and social stability. Continuous monitoring of the pattern of income distribution would provide a greater understanding of inequality patterns that have persisted over time. Income inequality has become more marked, with estimates of a Gini coefficient of around 0.48-0.51 in recent years (Naraparaju, 2016). It is indicated that the economic gains are inequitable, with the top 10% and the top 1% holding a huge share of national revenue. This suggests that the benefits of economic advancement are inequitably allocated and that the elite’s wealth is highly concentrated, thus marginalizing middle and lower-income populations. The Gini Index of India exhibits a dynamic trend, which increases with economic growth, social policies, and structural reforms. The initial decades following independence demonstrated a stable Gini Index; however, subsequent economic liberalization policies have been associated with rising income inequality. This suggests that while economic advancement has lifted millions out of poverty, it has primarily benefited the wealthier segments of society, leading to an increasing income inequality. The data reveals rather clear patterns, such as the increasing urban-rural income gap and persistent inequalities due to caste and gender. Regional disparities are likely an important factor, with some states showing more inequality than others. The results show a rising wealth concentration pattern in the highest income brackets, hence increased inequality. This finding highlights the need for policy interventions to address these trends. This suggests that while economic growth is essential, it must be accompanied by policies that promote equitable development and address structural disparities. These policies may include improving social safety nets, investing in education and healthcare, and ensuring equitable access to resources and opportunities. The study has pointed out that sound governance and correct implementation of policies hold the key to the percolation of economic growth in all strata of Indian society. Much research is needed on India’s complex mechanisms of income disparity, along with better and more effective policy solutions. The following recommendation is suggested for consideration by policymakers: a. Progressive taxation: A higher and stronger tax would help increase the financial burden on high-income earners so that they can afford to redistribute income and wealth or reallocate it. Asian Business Research Journal, 2025, 10(5): 1-11 10 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA b. Resource distribution to welfare policy: Increase spending on education, healthcare, and support structures for the poor and middle class to improve the poor’s living and economic opportunities. c. Encourage inclusive growth: Enact policies that provide employment, skill development, and entrepreneurial opportunities for marginalized groups, facilitating their active participation in the economic growth process. d. Enhance data collection and transparency: Improve the quality and accessibility of income and wealth statistics to better comprehend the dynamics of inequality and guide policymaking. e. Accelerate rural and urban development: Adopt a better-integrated approach towards regional development with an increasing urban-rural divide, ensuring that economic growth is equitably distributed between rural and urban areas. Implementing such policies would facilitate economic growth with social cohesion in India and eventually make the Indian economy more equitable and inclusive. Policymakers should contemplate strategies to resolve these issues, such as enhancing progressive taxation, investing in social welfare initiatives, fostering inclusive growth, augmenting data collection and transparency, and synchronizing rural and urban development (Vatta & Pavithra, 2016) (De & Devi, 2023) (Sahasranaman & Kumar, 2020). By implementing a holistic strategy, India may strive for a more equitable and sustainable economic framework that offers opportunity for all demographic segments. 7. Policy Recommendations The research might be limited to the feasibility of the proposed policy suggestions regarding their political acceptability or possible influence. Policies addressing income inequality can only be properly implemented with sufficient consideration of the political, economic, and social context. References Aarohi D. & Siddharth K.J. (2024). Road to Progress: An Analysis of India’s Urban Development Missions (2022). Youth for Unity and Voluntary Action (YUVA). https://yuvaindia.org/road-to-progress-an-analysis-of-indias-urban-development-missions- 2022/?utm_source=chatgpt.com ActionAid. (2024, August). Urban Housing for All: A Training Manual for Community Action. ActionAid Association India. https://www.actionaidindia.org/wp-content/uploads/2024/09/Urban-Housing-for-All-I-Manual-I- Final.pdf?utm_source=chatgpt.com Azam, M. (2019). Accounting for growing urban-rural welfare gaps in India. In World Development. Elsevier BV, 22, p. 410. https://doi.org/10.1016/j.worlddev.2019.06.004 Azam, M., & Bhatt, V. (2016). Spatial Income Inequality in India, 1993-2011: A District Level Decomposition. In SSRN Electronic Journal. RELX Group (Netherlands). https://doi.org/10.2139/ssrn.2761578 Azam, M., & Shariff, A. (2011). Income Inequality in Rural India: Decomposing the Gini by Income Sources (Vol. 31, Issue 1, p. 739). Springer Nature. Basu, M. (2017, January 1). Seeing the new India through the eyes of an invisible woman. https://edition.cnn.com/interactive/2017/10/world/i-on-india-income-gap/ Batra, R., & Reio, T. G. (2016). Gender Inequality Issues in India. In Advances in Developing Human Resources (Vol. 18, Issue 1, p. 88). SAGE Publishing. https://doi.org/10.1177/1523422316630651 Boza‐Kiss, B., Pachauri, S., & Zimm, C. (2021). Deprivations and Inequities in Cities Viewed Through a Pandemic Lens. In Frontiers in Sustainable Cities (Vol. 3). Frontiers Media. https://doi.org/10.3389/frsc.2021.645914 Chakraborty, S. (2018). Reflecting on Contemporary India’s Rising Inequality: Does Differential Rate of Return to Education Matter? In Advances in Economics and Business (Vol. 6, Issue 4, p. 232). https://doi.org/10.13189/aeb.2018.060404 Chancel, L., & Piketty, T. (2019). Indian Income Inequality, 1922‐2015: From British Raj to Billionaire Raj? In Review of Income and Wealth (Vol. 65). Wiley. https://doi.org/10.1111/roiw.12439 Chauhan, R. K., Mohanty, S. K., Subramanian, S. V., Parida, J. K., & Padhi, B. (2015). Regional Estimates of Poverty and Inequality in India, 1993–2012 (Vol. 127, Issue 3, p. 1249). Springer Science+Business Media. Dang, H.-A. H., & Peter , L. (2021). India: Inequality Trends and Dynamics: The Bird’s-Eye and the Granular Perspectives. In Oxford University Press eBooks (p. 157). Oxford University Press. https://doi.org/10.1093/oso/9780198863960.003.0007 Darku, F. B., Konietschke, F., & Chattopadhyay, B. (2020). Gini Index Estimation within Pre-Specified Error Bound: Application to Indian Household Survey Data. In Econometrics (Vol. 8, Issue 2, p. 26). Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/econometrics8020026 Das, P. (2019). Inequality of Opportunity in Educational Achievement in India: Implications of Earning Distribution and Affirmative Action. In Voprosy Obrazovaniya/ Educational Studies Moscow (Issue 4, p. 116). National Research University – Higher School of Economics. https://doi.org/10.17323/1814-9545-2019-4-116-132 De, U. K., & Devi, L. H. (2023). Inequality Dynamics in Urban Manipur, India: A Decomposition Analysis. In Social Indicators Research (Vol. 167, Issue 1, p. 67). Springer Science+Business Media. https://doi.org/10.1007/s11205-023-03096-8 Drèze, J., & Sen, A. (2013). An Uncertain Glory. https://doi.org/10.23943/9781400848775 Economic Survey. (2023). https://www.indiabudget.gov.in/economicsurvey/ Eggimann, A., & Kendzia, M. J. (2022). Rise of the Indian Middle Class and its Impact on the Labor Market. In SSRN Electronic Journal. RELX Group (Netherlands). https://doi.org/10.2139/ssrn.4154053 Farooquee, A. A. (2013). Policy Implementation and Impact Review: A Case of MGNREGA in India. In Mediterranean Journal of Social Sciences. Mediterranean Center of Social and Educational Research. https://doi.org/10.5901/mjss.2013.v4n13p367 Fleck, A. (2024, March 27). How the Income of India’s Richest 10% Surged. https://www.statista.com/chart/31991/per-adult-pre-tax-national-income-shares-india/ Ghosh, M. (2013). Liberalization, Growth and Regional Disparities in India. In Springer eBooks. Springer Nature. https://doi.org/10.1007/978-81-322-0981-2 Gini index. (2023). https://data.worldbank.org/indicator/SI.POV.GINI?locations=IN-NO-BR-ZA-US-MX Gopalakrishnan, S., & Immanuel, A. (2017). Progress of health care in rural India: a critical review of National Rural Health Mission [Review of Progress of health care in rural India: a critical review of National Rural Health Mission]. International Journal of Community Medicine and Public Health, 5(1), 4. Medip Academy. https://doi.org/10.18203/2394-6040.ijcmph20175758 Guha, S., Chandra, H., Yadav, R., & Pyne, S. (2021). Earning Disparities in Indo Gangetic Plain Region – Evidence from Periodic Labour Force Survey of India. In Research Square (Research Square). Research Square (United States). https://doi.org/10.21203/rs.3.rs-819425/v1 Gulati, A., & Ying, K. (2021). Meeting the Real “Gini” of India: An Analysis of Indian Respondents’ Perceptions of Income Inequality in India. https://yuvaindia.org/road-to-progress-an-analysis-of-indias-urban-development-missions-2022/?utm_source=chatgpt.com https://yuvaindia.org/road-to-progress-an-analysis-of-indias-urban-development-missions-2022/?utm_source=chatgpt.com https://www.actionaidindia.org/wp-content/uploads/2024/09/Urban-Housing-for-All-I-Manual-I-Final.pdf?utm_source=chatgpt.com https://www.actionaidindia.org/wp-content/uploads/2024/09/Urban-Housing-for-All-I-Manual-I-Final.pdf?utm_source=chatgpt.com https://doi.org/10.1016/j.worlddev.2019.06.004 https://doi.org/10.2139/ssrn.2761578 https://edition.cnn.com/interactive/2017/10/world/i-on-india-income-gap/ https://doi.org/10.1177/1523422316630651 https://doi.org/10.3389/frsc.2021.645914 https://doi.org/10.1111/roiw.12439 https://doi.org/10.1093/oso/9780198863960.003.0007 https://doi.org/10.3390/econometrics8020026 https://doi.org/10.17323/1814-9545-2019-4-116-132 https://doi.org/10.1007/s11205-023-03096-8 https://doi.org/10.23943/9781400848775 https://www.indiabudget.gov.in/economicsurvey/ https://doi.org/10.2139/ssrn.4154053 https://doi.org/10.5901/mjss.2013.v4n13p367 https://www.statista.com/chart/31991/per-adult-pre-tax-national-income-shares-india/ https://doi.org/10.1007/978-81-322-0981-2 https://data.worldbank.org/indicator/SI.POV.GINI?locations=IN-NO-BR-ZA-US-MX https://doi.org/10.18203/2394-6040.ijcmph20175758 https://doi.org/10.21203/rs.3.rs-819425/v1 Asian Business Research Journal, 2025, 10(5): 1-11 11 © 2025 by the authors; licensee Eastern Centre of Science and Education, USA Himanshu. (2022, September 6). India: Extreme Inequality in Numbers. https://www.oxfam.org/en/india- extreme-inequality-numbers Korekallu S.A., Praveen, K.V., Surendran P.S., Nithyashree M.L. and Jha, G.K. (2023). Does a farmer's knowledge of minimum support price (MSP) affect the farm-gate price? Evidence from India. Journal of Economics and Development, Vol. 25 No. 4, pp. 302-316. https://doi.org/10.1108/JED-04-2023-0079 Kulkarni, V. S., & Gaiha, R. (2020). Beyond Piketty: A new perspective on poverty and inequality in India. In Journal of Policy Modeling (Vol. 43, Issue 2, p. 317). Elsevier BV. https://doi.org/10.1016/j.jpolmod.2020.10.003 Lakner, C., & Milanović, B. (2015). Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession (Vol. 30, Issue 2, p. 203). Oxford University Press. Lawson, M., Chan, M.-K., Rhodes, F., Butt, A. P., Marriott, A., Ehmke, E., Jacobs, D., Seghers, J., Sieres, J., & Gowland, R. (2018). Public Good or Private Wealth? https://doi.org/10.21201/2019.3651 Mela, A., & Toldo, A. (2019). Socio-Spatial Inequalities in Contemporary Cities. In Springer briefs in geography. Springer Nature (Netherlands). https://doi.org/10.1007/978-3-030-17256-5 Menon, R. (2024, January 24). Analysing the rising gap in incomes. https://www.thehindu.com/news/national/analysing-the-rising-gap-in-incomes/article67770234.ece Mir, M. A., Doorwar, V., & Azad, S. (2018). Impact of Mahatma Gandhi National Rural Employment Guarantee Act MGNREGA on Unemployment and Village Economy. In International Journal of Trend in Scientific Research and Development (p. 137). Rekha Patel. https://doi.org/10.31142/ijtsrd12857 Mishra, A. K. (2018). Household Income Inequality and Income Mobility: Implications Towards Equalizing Longer-Term Incomes in India. In International Economic Journal (Vol. 32, Issue 2, p. 271). Taylor & Francis. https://doi.org/10.1080/10168737.2018.1480640 Mishra, A. K., Kumar, A., & Sinha, A. K. (2019). The shape of income distribution and decomposition of the changes in income inequality in India. In Journal of Economic Studies (Vol. 46, Issue 3, p. 760). Emerald Publishing Limited. https://doi.org/10.1108/jes-09-2017-0253 Mueller, J. T., McConnell, K., Burow, P. B., Pofahl, K., Merdjanoff, A., & Farrell, J. (2020). Impacts of the COVID- 19 pandemic on rural America. In Proceedings of the National Academy of Sciences (Vol. 118, Issue 1). National Academy of Sciences. https://doi.org/10.1073/pnas.2019378118 Mutisya, M., Muchira, J. M., & Abuya, B. (2021). Understanding Wealth Inequalities in Education Access in Urbanizing Sub-Saharan Africa. In Frontiers in Education (Vol. 6). Frontiers Media. https://doi.org/10.3389/feduc.2021.649730 Naraparaju, K. (2016). Income generation and inequality in India’s agricultural sector: The consequences of land fragmentation (p. 4). Nijman, J. (2006). Mumbai’s Mysterious Middle Class. In International Journal of Urban and Regional Research (Vol. 30, Issue 4, p. 758). Wiley. https://doi.org/10.1111/j.1468-2427.2006.00694.x Patil, G. R., & Sharma, G. (2020). Urban Quality of Life: An assessment and ranking for Indian cities. In Transport Policy (Vol. 124, p. 183). Elsevier BV. https://doi.org/10.1016/j.tranpol.2020.11.009 Patnaik, S., & Prasad, C. S. (2014). Revisiting Sustainable Livelihoods: Insights from Implementation Studies in India. In Vision the Journal of Business Perspective (Vol. 18, Issue 4, p. 353). SAGE Publishing. https://doi.org/10.1177/0972262914553258 Ranvanshi, A. (2024, April 27). India’s Income Inequality Is Now Worse Than Under British Rule, New Report Says. https://time.com/6961171/india-british-rule-income-inequality/ Roy, S., Majumder, S., Bose, A., & Chowdhury, I. (2024). The rich-poor divide: Unravelling the spatial complexities and determinants of wealth inequality in India. In Applied Geography (Vol. 166, p. 103267). Elsevier BV. https://doi.org/10.1016/j.apgeog.2024.103267 Sahasranaman, A., & Jensen, H. J. (2019). Dynamics of income inequality under disequilibrium: The case of India. In arXiv (Cornell University). Cornell University. https://arxiv.org/pdf/1909.04452 Sahasranaman, A., & Kumar, N. (2020). Income Distribution and Inequality in India: 2014–19. In SSRN Electronic Journal. RELX Group (Netherlands). https://doi.org/10.2139/ssrn.3707153 Sheoran, A. (2024). Exploring the causes and consequences of income inequality in India. In Innovative Research Thoughts (Vol. 10, Issue 2, p. 92). https://doi.org/10.36676/irt.v10.i2.1412 Truong, S., & Barreto, H. (2020). Visualizing Income Distribution in the United States. In RePEc: Research Papers in Economics. Federal Reserve Bank of St. Louis. https://EconPapers.repec.org/RePEc:dew:wpaper:2020- 03 UNDP. (2020). Human Development Report 2020. In Human Development Report. United Nations. https://doi.org/10.18356/9789210055161 Vatta, K., & Pavithra, S. (2016). Household Income Inequality and Asset Distribution: The Case of Rural Punjab. In India, studies in business and economics (p. 215). Springer Nature. https://doi.org/10.1007/978-981-10- 0197-0_10 Venumuddala, V. R. (2020). Farmers’ situation in agriculture markets and role of public interventions in India. In arXiv (Cornell University). Cornell University. https://doi.org/10.48550/arXiv.2005. Wang, M., Kang, W., Zhang, R., & Xia, J. (2020). The Gap between Urban and Rural Development Levels Narrowed. In Complexity (Vol. 2020, p. 1). Hindawi Publishing Corporation. https://doi.org/10.1155/2020/4615760 WorldBank. (2020, January 1). World Bank - World Development Indicators. https://databank.worldbank.org/source/world-development-indicators. https://www.oxfam.org/en/india-extreme-inequality-numbers https://www.oxfam.org/en/india-extreme-inequality-numbers https://doi.org/10.1108/JED-04-2023-0079 https://doi.org/10.1016/j.jpolmod.2020.10.003 https://doi.org/10.21201/2019.3651 https://doi.org/10.1007/978-3-030-17256-5 https://www.thehindu.com/news/national/analysing-the-rising-gap-in-incomes/article67770234.ece https://doi.org/10.31142/ijtsrd12857 https://doi.org/10.1080/10168737.2018.1480640 https://doi.org/10.1108/jes-09-2017-0253 https://doi.org/10.1073/pnas.2019378118 https://doi.org/10.3389/feduc.2021.649730 https://doi.org/10.1111/j.1468-2427.2006.00694.x https://doi.org/10.1016/j.tranpol.2020.11.009 https://doi.org/10.1177/0972262914553258 https://time.com/6961171/india-british-rule-income-inequality/ https://doi.org/10.1016/j.apgeog.2024.103267 https://arxiv.org/pdf/1909.04452 https://doi.org/10.2139/ssrn.3707153 https://doi.org/10.36676/irt.v10.i2.1412 https://econpapers.repec.org/RePEc:dew:wpaper:2020-03 https://econpapers.repec.org/RePEc:dew:wpaper:2020-03 https://doi.org/10.18356/9789210055161 https://doi.org/10.1007/978-981-10-0197-0_10 https://doi.org/10.1007/978-981-10-0197-0_10 https://doi.org/10.48550/arXiv.2005 https://doi.org/10.1155/2020/4615760 https://databank.worldbank.org/source/world-development-indicators