High-income Individuals Research Articles

The influence of selective mortality on poverty rates in later life: evidence from a Swedish cohort born in 1926.

Mortality influences the composition of the surviving population. Higher mortality among low-income individuals than high-income individuals may result in lower poverty rates in the surviving population. The objective of this study was to describe poverty rates for both survivors and deceased individuals in a cohort born in 1926. We used Swedish total population data on the 1926 birth cohort (n = 83,382), calculating annual poverty rates from 1991 to 2016. We compared poverty rates for the entire cohort, those who died the next year, and those who survived for 5, 10, or 20+ years, measuring the impact of selective mortality as the differences in poverty rates between the cohort and these subgroups. Individuals who died the following year had higher poverty rates than the cohort at ages 65-90. Conversely, individuals who survived 5, 10, or 20+ years had lower poverty rates, with relatively small differences (1.1% to 6.9% lower) for survivors of 5 years or longer, and larger differences (26.4% to 32.8% lower) for those who survived 20+ years. Despite differences in mortality rates by income, selective mortality had only a modest impact on poverty rates. If life expectancy rises for all, and a more diverse population reaches old age, our findings indicate a potential slight increase in poverty rates due to reduced mortality as a selective factor. These findings emphasise the need to consider mortality selection when addressing future poverty rates in older adults.

Nudging consumers about the issue of microplastics: an experimental auction study on valuation for sustainable food packaging

Plastic, integral to food packaging since the 1950s, has become a global environmental concern due to its contribution to microplastic pollution. Microplastics harm ecosystems, impacting wildlife and human health. Amid increasing focus on sustainability, global initiatives target sustainable production and consumption, but consumers struggle to verify product claims, leading to potential greenwashing, particularly in the food industry. We conducted an experiment focusing on pasta products with varied packaging and labeling attributes. Findings suggest that consumers are willing to pay more for products with both biodegradable packaging and Product Environmental Footprint (PEF) labels, indicating heightened trust and perceived sustainability. Information about microplastics’ adverse environmental effects influenced consumer valuation, particularly among females, higher-income individuals, and those with stronger environmental concerns.

What resources are needed for engaging in community coproduction? Evidence from China

This study uses data from the 2012 Chinese General Social Survey to examines what resources in the form of human, social, and cultural capital are needed for engaging in community coproduction. We find that, in terms of human capital, middle-income individuals are more likely to participate in community coproduction than lower-income and higher-income individuals; also, those with more education are more likely to participate in community coproduction. Regarding social capital, individuals who are more involved in community social networks and have higher levels of trust in their neighbors are more likely to engage in community coproduction. Finally, in terms of cultural capital, individuals with more community-centered values are more likely to participate in community coproduction. Implications for public management theory and practice are discussed.

Characteristics of the participants in mass sporting events in Vietnam

This study aimed to examine the characteristics of athletes and spectators at mass sports competitions, focusing on aspects such as quantity, age, gender, educational level, occupation, and income to provide a comprehensive demographic overview. The study employed a sociological survey method, sampling 10 localities out of 63 provinces and cities across Vietnam. The survey included 520 spectators (Group 1) and 220 athletes (Group 2), resulting in a total sample size of 740 participants. The results are illustrated using graphical representations. The majority of spectators at mass sport events are aged 23 to under 60, whereas athletes show a more even age distribution, indicating lower student participation in spectating. Men significantly outnumber women. Most participants hold high school or university degrees, with the largest group being unskilled workers. Students, freelancers, and retirees are more evenly distributed. Professional field participants make up 35.5% of the total. Income-wise, most participants are middle to high-income earners, with nearly half earning between 5 and 10 million VND per month, and 42.3% earning over 10 million VND. Low-income and very high-income individuals are mostly spectators, while medium to high-income individuals are more likely to be athletes.

A Comparative Study of Loan Approval Prediction Using Machine Learning Methods

Loan prediction plays an important role in the process of evaluating loan applications by financial institutions. Machine learning models can automate this process and make the lending process faster and more efficient. In this context, the main objective of this research is to develop models for loan approval prediction using machine learning algorithms such as Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, and Random Forest and to compare their performances. In addition, determining the effect of K-Best and Recursive Feature Elimination feature selection methods on model performances is another important objective of the research. Furthermore, the evaluation of the effectiveness of techniques such as cross-validation (K-Fold) and Train, Test and Validation in measuring the performance of models is also among the objectives of the research. The findings revealed that married individuals are more likely to be approved for loans than single individuals, high income individuals more likely than low-income individuals, males more likely than females, and university graduates more likely than non-university graduates. According to the performance measures, Random Forest was the most successful algorithm with an accuracy rate of 97.71% in loan approval prediction. To achieve this accuracy rate, feature selection was performed with the Recursive Feature Elimination method and the measurement was made with the cross-validation method. It was found that the feature selection methods have a significant impact on the model performances and the Recursive Feature Elimination method was the most successful method. Moreover, the highest accuracy rate achieved by the Random Forest algorithm, which showed the highest performance in all cases, was measured by cross-validation.

Urban growth and stratification: The role of locational externalities

Urban areas that have undergone rapid and recent growth processes can shed light on the forces driving urban stratification and gentrification. This article analyzes how the process of urban growth itself, driven by migration, affects the stratification of the city. The availability of detailed data makes it possible to observe how high-income settlement patterns are driven by attraction (homophily) and repulsion (heterophobia). We consider neighborhood composition (i.e., the number of high-income residents in the vicinity of a given location) as a potential factor that can explain agents' higher willingness to pay in some locations. We propose a model of urban spatial equilibrium with locational externalities, related to preexisting neighborhood characteristics, that can help explain why new rich neighborhoods are located close to existing rich neighborhoods and far from poor neighborhoods. In this model a monopolistic owner will allocate available locations to those agents willing to pay the most, taking advantage of agents' willingness to pay more when locations are surrounded by high-income individuals. The location externality influences the dynamics of urban configuration through attraction-repulsion effects, as new rich neighborhoods are located near other rich neighborhoods and far from poor neighborhoods, thus reinforcing socio-spatial-stratification. This mechanism sheds light on why gentrification occurs only in some areas, while others with a priori better localization do not experiment changes.

The levels of women’s awareness, experience, acceptability and preference for Vaginal Human Papillomavirus (HPV) self-sampling in three provinces of China: a cross-sectional study

BackgroundThe primary screening technique for precancerous lesions and cervical cancer is human papillomavirus (HPV) testing, and HPV self-sampling has been shown to be consistent with clinician sampling in terms of the accuracy of the results and may improve cervical cancer screening rates. The aim of this study was to understand the level of awareness, experience, acceptability, and preference for vaginal HPV self-sampling among women in Jiangsu, Zhejiang, and Shanghai, China, and to analyze the possible influencing factors to determine the feasibility of implementing self-sampling.MethodsOverall, 1793 women were included in the data analysis. A self-administered questionnaire was utilized. In addition to descriptive analysis, univariate and multivariate analyses were used to explore the associations between sociodemographic features, history of cervical cancer screening, and the level of awareness, experience, acceptability, and preference for HPV self-samples.ResultsThe participants’ level of awareness of and experience with HPV self-sampling were moderate. A total of 88.8% of participants rated the acceptability as “high”, and self-sampling was preferred by 64.2% of them for cervical cancer screening. People aged 45 to 54 years showed a preference for both clinician sampling(OR = 1.762 (1.116–2.163)) and self-sampling (OR = 1.823 (1.233–2.697)). Those who had graduated from high school or above (OR = 2.305 (1.517–3.503), OR = 2.432 (1.570–3.768), OR = 3.258 (2.024–5.244)) preferred clinician-sampling, and those with a bachelor’s degree or above (OR = 1.664 (1.042–2.657)) preferred self-sampling. Middle- and high-income individuals showed no preference for either sampling method (OR < 1).ConclusionsHPV self-sampling is widely accepted, but awareness, experience and preferences need to be improved. These results may help to adjust public health strategies for the early inclusion of HPV self-sampling as a screening method in national initiatives to prevent cervical cancer.

E-scooters: how do latent and socioeconomic factors affect their usage in the global south? Implications for policy planning

ABSTRACT Electric scooters have been a rapidly growing mode of transport in recent years. This massive proliferation has brought issues frequently addressed without sufficient technical or scientific support, especially in cities of the Global South. This study seeks to identify latent and socioeconomic factors influencing e-scooter usage and their implications for policy planning. For this purpose, we applied a survey (n = 1073) to users and non-users in Bogota, Colombia. We estimated MIMIC model to assess the influence of individuals’ perceptions. The results show that perceptions of crash risk and fear of crime negatively influence usage, while environmental awareness and pro-technology attitudes have a positive influence. On the other hand, e-scooter use decreases with the age of individuals, while it is higher in men, car owners, high-income and college-educated individuals. Finally, using the modelling results, we study the implications for policy planning and propose measures to reduce concerns related to e-scooter usage.

Inequality in dental flossing behavior among Korean adults based on household income levels.

The aim of this study was to estimate the association between household income and dental flossing. This cross-sectional study investigated the impact of household income on flossing among 9,391 adults aged 30+ with ≥20 natural teeth, utilizing data from the seventh Korea National Health and Nutrition Examination Survey (2016-2018). Outcome measures included flossing (yes/no), with income categorized into 4 levels: lowest, medium to low, medium to high, and highest. Logistic regression, adjusted for age, gender, brushing frequency, recent dental exams, periodontitis, smoking, and alcohol use, was employed to evaluate the influence of socioeconomic status on oral hygiene practices. In the highest income group, flossing was 62.6% more prevalent than in the lowest income group (adjusted odds ratio [aOR], 1.63; 95% CI, 1.27 to 2.08). The strongest association between income levels and flossing was observed in individuals aged ≥70 years (aOR, 3.64; 95% CI, 1.86 to 7.11), with a decreasing strength of association in the 60s (aOR, 1.72; 95% CI, 1.05 to 2.84) and 50s age groups (aOR, 1.69; 95% CI, 1.07 to 2.68). Higher-income women demonstrated a higher frequency of flossing than their lower-income counterparts (aOR, 1.67; 95% CI, 1.24 to 2.23). Higher-income individuals without periodontitis were more likely to floss (aOR, 1.64; 95% CI, 1.23 to 2.18), and among those with periodontitis, flossing was significantly associated only with the highest income category (aOR, 1.64; 95% CI, 1.10 to 2.44). The findings of this study indicate a significant correlation between higher household income levels and an increased prevalence of flossing.

Global Dynamics of a Social Hierarchy-Stratified Malaria Model: Insight from Fractional Calculus

In this study, a mathematical model for the transmission dynamics of malaria among different socioeconomic groups in the human population interacting with a susceptible-infectious vector population is presented and analysed using a fractional-order derivative of the Caputo type. The total human population is stratified into two distinguished classes of lower and higher income individuals, with each class further subdivided into susceptible, infectious, and recovered populations. The socio hierachy-structured fractional-order malaria model is analyzed through the application of different dynamical system tools. The theory of positivity and boundedness based on the generalized mean value theorem is employed to investigate the basic properties of solutions of the model, while the Banach fixed point theory approach is used to prove the existence and uniqueness of the solution. Furthermore, unlike the existing related studies, comprehensive global asymptotic dynamics of the fractional-order malaria model around both disease-free and endemic equilibria are explored by generalizing the usual classical methods for establishing global asymptotic stability of the steady states. The asymptotic behavior of the trajectories of the system are graphically illustrated at different values of the fractional (noninteger) order.

Prevalence of Work-Related Anxiety during the COVID-19 Pandemic

This cross-sectional study investigates the shifts in anxiety levels among Swedish employees throughout the Covid-19 pandemic, with data gathered in 2016, 2018, and 2020. Work-related anxiety was assessed through two metrics: General Work Anxiety (WA) and Work Performance Anxiety (WPA). Overall, there was a decline in both average WA and WPA over the five-year period. However, this trend did not apply uniformly across all social groups. Specifically, WA saw a significant decrease among older men, while it showed an increase among younger women. Additionally, the reduction in WPA was more pronounced among managers than employees during the pandemic. High-income individuals and those with advanced education levels also experienced a greater decrease in WPA. These findings underscore the role of employment conditions in shaping the impact that the pandemic might have had on workers’ mental health.

A framework for investigating new firm entry: The (limited) overlap between informal-formal and necessity-opportunity entrepreneurship

We analyse entrepreneurial entry along the dimensions of informal-formal and necessity-opportunity entrepreneurship, distinguishing between them yet considering them jointly. While the dominant view in the literature conflates necessity with informal entry, and opportunity with formal entry, we hypothesise that informal entrepreneurship may be attractive to higher-income individuals as a testing ground for entrepreneurial ideas. We also explain why higher-income individuals may undertake necessity entrepreneurship. We utilise individual Global Entrepreneurship Monitor (GEM) data from Chile (2019–2021), which identifies informal-formal and necessity-opportunity entrepreneurial entry modes, to test hypotheses on the role of individuals´ income in the four types of entrepreneurial entry. We also consider changes in entrepreneurial entry during a crisis and a non-crisis periods. Our results confirm that the patterns in the data are consistent with hypotheses derived from our proposed theoretical framework. Executive summaryEmerging markets economies have very large informal sectors, and their entrepreneurial entry is often motivated by economic necessity rather than by business opportunity. But neither informal nor necessity entrepreneurship are usually expected to generate the positive benefits for growth and development predicted for formal and opportunity entrepreneurship. We argue that the dominant stream in the literature actually conflates informal and necessity entrepreneurship, both of which have been associated with low human and financial capital and productivity. We propose that the appropriate typology is more complex than this because there are examples of successful and dynamic informal firms. This leads us to identify four categories of entrepreneurial entry: informal-necessity (Type 1), formal-opportunity (Type 2), informal-opportunity (Type 3), and formal-necessity (Type 4). While necessity entrepreneurship has typically been associated with low-income individuals, we propose that formal-necessity entrepreneurship may be an entry path for both low- and high-income individuals, though for different reasons. Informal opportunity entry may likewise be an option for people with low-income as well as high-income.We therefore seek to disentangle the analysis of opportunity-necessity and of formal-informal entry and to demonstrate that the two less explored entry modes - informal-opportunity, and formal-necessity - are of considerable theoretical and practical significance in emerging economies. We test our framework in the emerging market economy setting of Chile, one of the more prosperous and open economies in Latin America. We use Global Entrepreneurship Monitor (GEM) data which uniquely for Chile allow us to distinguish between individuals along both the formal-informal and the necessity-opportunity dimensions. On this basis, we distinguish empirically between these four categories of entrepreneurial entry and explain how higher-income individuals may use informal-opportunity entrepreneurial entry as a “seed bed” to test their new business ideas. At the same time, we show that necessity entrepreneurship may be attractive to both lower- and higher-income individuals.We also show that the interplay between individuals´ income groups and four entrepreneurial entry modes is stable over “normal times” versus “crisis periods”. We observe that in response to a crisis, individuals with lower-incomes are likely to engage more in informal-necessity entrepreneurship while opportunity-informal entry by higher-income individuals will decline. These changes represent a more complex adjustment pattern than has been identified for developed economies, where entrepreneurial activity has been found to be countercyclical. Thus, in emerging markets, informal-necessity entrepreneurship plays a stabilizing role for those individuals with a more marginal position in the labor market during the crisis. In contrast, for those individuals who have access to higher household income, all forms of entrepreneurship become a less attractive option. We interpret this as indicating that these individuals have the option to wait for higher return opportunities to re-emerge. This is one of the first papers to explore the impact of the COVID-19 pandemic on entrepreneurship in an emerging market economy.

Association of per- and polyfluoroalkyl substances with constipation: The National Health and Nutrition Examination Survey (2005-2010).

The impact of per- and polyfluoroalkyl substances (PFAS) on constipation, as mediated through gastrointestinal absorption and perturbations to the intestinal microecology, remains poorly understood. This study seeks to explain the relationship between PFAS and constipation. A total of 2945 adults from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 were included in this study. Constipation was defined using the Bristol Stool Form Scale (BSFS) based on stool consistency. The relationship between PFAS and constipation was evaluated using weighted logistic regression and restricted cubic spline (RCS) analysis, while adjusting for confounding variables. The weighted median concentration of total PFAS (ΣPFAS) was significantly lower in individuals with constipation (19.01 μg/L) compared to those without constipation (23.30 μg/L) (p < 0.0001). Subgroup analysis revealed that the cumulative effect of PFAS was more pronounced in the elderly, men, individuals with obesity, high school education or equivalent, and high-income individuals (p < 0.05). After adjusting for confounding factors, multivariable analysis demonstrated an inverse association between PFOA [OR (95% CI), 0.666(0.486,0.914)] and PFHxS [OR (95% CI), 0.699(0.482,1.015)], and constipation. None of the personal and lifestyle factors showed a significant correlation with this negative association, as confirmed by subgroup analysis and interaction testing (p for interaction > 0.05). The RCS analysis demonstrated a linear inverse relationship between PFAS levels and constipation. The findings of this study provide evidence of a significant inverse correlation between serum concentrations of PFAS, particularly PFOA and PFHxS, and constipation.

Creating inequality in access to public transit? Densification, gentrification, and displacement

Densification is a key concept in contemporary urban planning. Yet, there are widespread concerns about densification causing displacement and gentrification. This paper examines densification around train stations—a prevalent form of transit-oriented development (TOD) in cities with established public transit systems—in the Canton of Zurich, Switzerland. We assess the effects of densification around train stations on the socioeconomic population composition in these areas and investigate three different potential displacement effects. Leveraging 1.8 million linked person-housing unit observations for all individuals within our study perimeter, we provide a more nuanced understanding of densification’s effects on the population composition and displacement than prior research. Our findings reveal that even though densification increases the absolute number of low-income residents, it primarily benefits middle- and high-income households. Specifically, there is a decline in the share of low-income residents, attributed to the influx of younger high-income individuals. Moreover, incumbent low-income residents experience an increased risk of direct displacement due to housing demolitions. These outcomes highlight the limitations of TOD strategies in mitigating persistent socioeconomic disparities in public transit access, emphasizing the need for more comprehensive measures to address the challenges of equitable housing and public transit accessibility.

Impact of COVID-19 on healthcare utilization among chronic disease patients in South Korea

BackgroundFrom 2020 to 2022, South Korea has experienced significant direct and indirect damage because of the coronavirus pandemic. Preventive measures aimed at controlling the spread of the virus have inadvertently limited healthcare accessibility for patients without COVID-19, leading to detrimental consequences, particularly for patients with chronic diseases. Hence, there is a growing need to comprehensively examine the changes in healthcare utilization among patients with chronic diseases owing to the COVID-19 pandemic, along with the associated factors and health outcomes. MethodsTo examine changes in healthcare utilization among patients with chronic diseases and their impact on health outcomes, we used the NHIS database. Logistic regression analysis was used to investigate changes in healthcare utilization, and a two-part model was applied to explore the effects of reduced healthcare utilization on hospitalization status and length of hospital stay. ResultsSince the onset of the pandemic, the likelihood of hospitalization has been 1.10 times higher than that during pre-pandemic times in the population groups with a 20 % decrease in outpatient healthcare utilization. Notably, individuals belonging to the low-income group exhibited a 1.77-fold higher likelihood of hospitalization than those in the high-income group. Furthermore, in cases where hospitalization could have been avoided, low-income individuals had an extended hospital stay of 16.7 days compared with high-income individuals. ConclusionThere is a need for a more proactive approach for classifying patients with chronic diseases based on various vulnerability factors to effectively respond to future novel infectious diseases and reduce the long-term burden on the nation.

The Relationship between International Migration, Agricultural Employment, and Household Labor Force in Türkiye

There isn't much academic research on the impacts of immigration on the labor market and job structure at the national level, although Türkiye is one of the nation’s hosting the greatest populations of refugees. Because of the scarcity of information, a research gap exists. As a result, the study was carried out to determine the impact of international migration on agricultural employment and the changes in agricultural employment in Türkiye. Johansen Co-integration and Granger Causality analyses were performed on data from 1988 to 2018 to evaluate the change in the agricultural workforce in Türkiye and to demonstrate the temporal influence of immigration. According to the findings of the cointegration study, a rise in emigration has a negative impact on the agricultural areas and agricultural employment while having a good impact on agricultural GDP. Migration has long-term detrimental consequences. According to the causality study, there is a one-way link between migration and agricultural GDP. A panel data analysis was performed to establish the short-term detrimental impact of migration on agricultural employment, as well as how the structure of employment altered and developed during this process. The statistics provide temporal data from 2004 to 2020, and the individual's agricultural employment status, education, income, continuous employment, and extra work status are cross-sectional data. According to the Panel Logistic Regression Analysis results, while more educated and higher income individuals leave away from the agricultural sector, the desire to have a side job leads the individual to the agricultural sector. International migration has a detrimental impact on agricultural employment and its structure in this scenario. As a result, the sustainability of the working arrangements established by immigration regulations should be assured, and limits and constraints should be implemented, particularly in the agricultural sector. When agricultural employees transition to other industries, agricultural areas are being used in ways that were not planned. As a result, in the long run, the decline in output may have a negative impact on agricultural GDP. This condition has been the topic of several research and may serve as the foundation for new ones.

Why Do We Dislike Inflation?

ABSTRACT: This paper provides new evidence on a long-standing question asked by Shiller (1997): why do we dislike inflation? I conducted two surveys on representative samples of the US population to elicit people's perceptions about the impacts of inflation and their reactions to it. The predominant reason for people's aversion to inflation is the widespread belief that it diminishes their buying power, as neither personal nor general wage increases seem to match the pace of rising prices. As a result, respondents report having to make costly adjustments in their budgets and behaviors, especially among lower income groups. Inflation also provokes stress, emotional responses, and a sense of inequity, as the wages of high-income individuals are perceived to grow more rapidly amid inflation. Many respondents believe that firms have considerable discretion in setting wages, opting not to raise them in order to boost profits, rather than being compelled by market dynamics. The potential positive associations of inflation, such as with reduced unemployment or enhanced economic activity, are typically not recognized by respondents. Inflation ranks high in priority among various economic and social issues, with respondents blaming the government and businesses for it. I also highlight a substantial polarization in attitudes toward inflation along partisan lines, as well as across income groups.

Analyzing the Influence of Demographic Factors on Consumer Preferences in the Tourism Industry in Bali

This research investigates the influence of demographic factors on consumer preferences within the tourism industry in Bali. 250 tourists examined their accommodation choices, activity preferences, and overall satisfaction. The study employs Structural Equation Modeling with Partial Least Squares (SEM-PLS) to analyze the data. Results reveal nuanced patterns: younger tourists favor budget accommodations, older tourists opt for luxury, and higher-income individuals prefer upscale options. Gender and education impact preferences, emphasizing the need for tailored strategies. The measurement model assessment confirms the reliability and validity of the constructs. Findings contribute to understanding Bali's tourism dynamics, guiding businesses and policymakers in optimizing offerings for diverse demographic segments.

How temporary disruption of metro service influence metro commuters’ mode shifts during the COVID-19 pandemic? Evidence from Tianjin, China

Since the outbreak of the COVID-19 epidemic, the commuting behavior of urban residents has been profoundly influenced. However, little research has focused on commuting travel changes in the aftermath of metro disruption caused by the COVID-19 pandemic. A face-to-face intercept survey was conducted at the metro stations that have been closed to reveal the mode preferences of metro commuters. The latent class analysis and multinominal logit model were used to assess the heterogeneity in metro commuters’ travel behavior and examine the determinants that influence commuters’ mode shifts response to the temporary metro disruption, respectively. Results show that metro commuters who have chosen other transportation modes during metro system disruption can be classified into three groups, “conservative commuters”, “neutral commuters” and “dauntless commuters”. Metro commuters are most likely to choose cars (including private cars, taxis, and ride-hailing), followed by active modes and other unclosed public transport. In the “conservative commuters” group, the more family members the respondents have, the less likely they are to use other unclosed public transport. In the “neutral commuters” group, compared to high-income individuals, low-income commuters are more inclined to use active modes and work-from-home. In the “dauntless commuters” group, the higher the level of education of respondents, the more they are inclined to use active mode and car. Research findings can help the government develop comprehensive policies to deal with disruptions in the metro system, arising not only from epidemics similar to COVID-19 but also from a range of other circumstances.

Income inequality effect of government investment behavior: Comparisons based on different investment areas, different regions and different groups in China

The research focuses on and analyses the effect of government investment on income distribution by evaluating the effects of public spending on income variation in various fields, in various regions, and at different income levels in the Chinese economy. The study found that government investment in different fields substantially decreases income inequality. Increasing housing security, medical, agriculture, forestry and other expenditures has a significant impact on improving the income inequality between rural and urban inhabitants; the impact of government investment in the western, central, and eastern regions on the reduction of income variation is decreasing successively, with emphasis on government investment in the western and central regions. The effects of government investment on the decline of the income distribution are twofold: first, it influences the amount of low- and middle-income groups; second, it has an impact on the reduction of high-income organizations; however, the impact on the income equality of high-income and low-income organizations is not considerable. In investment, the study demonstrates that income inequality can be reduced without negatively affecting the financial status of higher-income individuals. It is significant to value providing adequate housing security for low-income populations as a critical policy implication. This study, utilizing novel indicators, contributes to the current body of research on the impact of fiscal policy in addressing income inequality in China.