Forecasting of Households Consumption Expenditure with Nonparametric Regression: The Case of Turkey

Abstract The relationship between household income and expenditure is important for understanding how the shape of the economic dynamics of the households. In this study, the relationship between household consumption expenditure and household disposable income were analyzed by Locally Weighted Scatterplot Smoothing Regression which is a nonparametric method using R programming. This study aimed to determine relationship between variables directly, unlike making any assumptions are commonly used as in the conventional parametric regression. According to the findings, effect on expenditure with increasing of income and household size together increased rapidly at first, and then speed of increase decreased. This increase can be explained by having greater compulsory consumption expenditure relatively in small households. Besides, expenditure is relatively higher in middle and high income levels according to low income level. However, the change in expenditure is limited in middle and is the most limited in high income levels when household size changes.

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The Size and Distribution of Hidden Household Income in China

Asian Economic Papers ◽

10.1162/asep_a_00064 ◽

2011 ◽

Vol 10 (1) ◽

pp. 1-26 ◽

Cited By ~ 35

Author(s):

Xiaolu Wang ◽

Wing Thye Woo

Keyword(s):

Low Income ◽

Household Income ◽

National Income ◽

Income Group ◽

High Income ◽

Institutional Reforms ◽

Middle Income ◽

Urban Household ◽

Household Disposable Income ◽

Official Data

Official Chinese data on urban household income are seriously flawed because of significant underreporting of income by respondents and non-participation by the high income groups in official household surveys. We collected urban household income and expenditure data in a way that increased their reliability and the coverage of the wealthy. We utilized the well-known relationship between Engel's coefficient and income level through two different approaches to deduce the true level of household income for each of the seven Chinese income categories (lowest income, low income, lower middle income, middle income, upper middle income, high income, and highest income). We found that the ratio of our estimated income to official income increased from 1.12 for the lowest income group to 3.19 for the highest income group. Total household disposable income in 2008 is RMB 14.0 trillion according to the official data but RMB 23.2 trillion according to our estimate; and 63 percent of the unreported income went to the wealthiest 10 percent of urban households. The income of the wealthiest 10 percent of Chinese households is really 65 times that of the poorest 10 percent instead of the 23 times reported in the official data. The Gini coefficient is clearly much higher than the usually reported figure of 0.47. In one of the estimations, we had to drop the 76 wealthiest households (1.8 percent of our sample) from the analysis because there were no super-rich in the official data for us to match characteristics with. We therefore still understate the income of the highest income households. As the amount of unreported income indicates the degree of corruption, it is troubling that it grew 91 percent in 2005–08 compared to the 71 percent growth in gross national income. Serious institutional reforms must be enacted if corruption is not to derail economic development and social harmony.

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The Conditional Effects of Health on Voter Turnout

Journal of Health Politics Policy and Law ◽

10.1215/03616878-8893529 ◽

2021 ◽

Author(s):

Gregory Lyon

Keyword(s):

Low Income ◽

Voter Turnout ◽

High Income ◽

Poor Health ◽

Conditional Effects ◽

2016 Election ◽

Excellent Health ◽

Reported Health ◽

Election Studies ◽

The Relationship

Abstract Context: Voting is the central instrument of democracy, yet there are a number of impediments that affect citizens' ability to turn out to vote. Health is one such impediment. Methods: This study draws on 2012 and 2016 election data from the Cooperative Congressional Election Study and the American National Election Studies and uses objective validated measures of voter turnout as well as postelection data on respondents' reasons for nonvoting to examine the relationship between self-reported health and voter turnout. Findings: The results indicate poor health depresses turnout among low-income voters but not high-income voters. A low-income citizen in poor health is 7 points less likely to turn out to vote than a low-income citizen in excellent health is. In contrast, a high-income citizen in poor health is just as likely to vote as a high-income citizen in excellent health is. Moreover, low-income citizens in poor health are 10 points more likely to cite sickness as an impediment to voting than are otherwise similar high-income citizens who are also in poor health. Conclusions: The findings have implications for health policy and unequal electoral engagement and suggest that health may narrow the scope of US democracy as poor health pushes low-income citizens out of the electoral sphere while high-income citizens continue to turn out to vote regardless of their underlying health conditions.

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Cross-State Comparison of Income and Vehicle-Ownership Effects on Household Mobility

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120947420 ◽

2020 ◽

Vol 2674 (11) ◽

pp. 813-826

Author(s):

Yi-Shih Chung ◽

Chi-Hung Wu

Keyword(s):

Household Income ◽

Random Effect ◽

Small Sample ◽

High Income ◽

Vehicle Ownership ◽

Income Levels ◽

Household Mobility ◽

Transit Services ◽

Trip Frequency ◽

Small Sample Sizes

The study investigated the effects of income and vehicle ownership on household mobility (measured as trip frequency, miles traveled, and transit use) across states on the basis of the 2017 National Household Travel Survey. Bayesian multilevel (or random-effect) regression models were developed to include state-policy variables and overcome the concern of small sample sizes in some household strata. The analysis results indicated that household income levels were positively associated with vehicle ownership and mobility; however, extremely high-income households were not necessarily more likely than high-income households to own more vehicles. Owning at least one vehicle was the norm for most households, except under two conditions: when the household income was extremely low or when the state transit level of service (LOS) was high. Moreover, states with a high transit LOS exhibited similar household mobility as long as households had similar income levels and vehicle ownership rates; by contrast, household mobility in states with a low transit LOS was relatively varied. Fully equipped (at least one vehicle per driver) and car-light households (having more drivers than vehicles) exhibited a similar trip frequency number; however, the vehicle miles traveled of car-light households were significantly shorter, especially in states with a high transit LOS. These results suggest that the mobility benefits of being fully equipped are more limited than we had anticipated. Transit services can affect household vehicle ownership and mobility only when being provided above a certain LOS.

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Impact of pneumococcal conjugate vaccine uptake on childhood pneumonia mortality across income levels in Brazil, Colombia, and Peru

Gates Open Research ◽

10.12688/gatesopenres.13187.1 ◽

2020 ◽

Vol 4 ◽

pp. 136

Author(s):

Kayoko Shioda ◽

Cristiana M. Toscano ◽

Maria Tereza Valenzuela ◽

William Valdez Huarcaya ◽

Joshua L. Warren ◽

...

Keyword(s):

Low Income ◽

Healthcare Access ◽

Population Level ◽

Income Level ◽

High Income ◽

Vaccine Uptake ◽

Mortality Data ◽

Income Levels ◽

The Difference ◽

Using Data

Background: Pneumococcal conjugate vaccines (PCVs) have prevented deaths due to pneumonia among children. The effect may differ between higher- and lower-income populations due to various factors, such as differences in the distribution of pneumococcal serotypes, healthcare access, and PCV uptake. This study aims to evaluate an association between increasing PCV coverage and population-level declines in death due to pneumonia and its variation by socioeconomic status of subnational regions. Methods: We analyzed municipality-level mortality data from 2005 and 2015 for children aged 2-23 months in Brazil, Colombia, and Peru. We fit Poisson regression models to estimate the relationship between changes in PCV uptake and deaths due to all-cause pneumonia among subnational regions with different income levels. We controlled for changes unrelated to PCV by using data on non-respiratory deaths over time. Results: Uptake of the third dose of PCV varied across subnational regions and was higher in high-income regions. Higher uptake of PCV was associated with larger declines in pneumonia mortality. This association did not differ by income level of the region in Brazil and Colombia. In Peru, low-income regions observed larger declines in pneumonia deaths, but there was large uncertainty in the difference between the low- and high-income regions. We estimated that, with 90% coverage, there would be 4-38% declines in all-cause pneumonia mortality across income levels and countries. Conclusions: Regions with higher PCV coverage experienced larger declines in pneumonia deaths, regardless of the income level. Having more reliable data on mortality records and vaccine uptake would improve the reliability of vaccine impact estimates.

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Internal Migrations as a Driving Force of Regional Disintegration: An Empirical Analysis of NUTS-2 Regions in Turkey

10.12658/m0632 ◽

2021 ◽

Vol 11 (3) ◽

pp. 215-248

Author(s):

Ayfer Özyılmaz ◽

Yüksel Bayraktar

Keyword(s):

Internal Migration ◽

Low Income ◽

Household Income ◽

Economic Conditions ◽

Population Movements ◽

Income Levels ◽

Net Migration ◽

Migration Direction ◽

Internal Migrations ◽

Quantile Regression Method

Internal migrations, which involve population movements within the borders of a country for economic, political or social reasons, is seen as both a cause and a result of regional imbalances. In this framework, the effect increasing internal migrations have on developed and underdeveloped regions may differ through the effect of the different socio-cultural and economic conditions between regions. The aspect of imbalance is directly related to the extent to which migration affects parameters such as wage, production, consumption, human capital levels, entrepreneurial migration, unemployment, and household income in regions with different stages of development. This study analyzes the effect internal migration has on regional imbalances in Turkey’s NUTS-2 regions during 2008-2019 using the bootstrap quantile regression method. According to the analysis findings, internal migration increases growth in all NUTS-2 regions, but this effect is stronger at higher income levels. In this context, as a region’s income levels increase, the effect of net migration on growth also increases. When considering the migration direction to be from low-income regions to high-income regions, internal migration has been found to increase interregional disintegration in Turkey.

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“Association between Median Household Income, State Medicaid Expansion Status, and COVID-19 Outcomes Across US Counties”

10.1101/2021.02.03.21251075 ◽

2021 ◽

Author(s):

Tsikata Apenyo ◽

Antonio Vera-Urbina ◽

Khansa Ahmad ◽

Tracey H. Taveira ◽

Wen-Chih Wu

Keyword(s):

Mortality Risk ◽

Low Income ◽

Household Income ◽

Medicaid Expansion ◽

Median Household Income ◽

Incidence And Mortality ◽

Significant Difference ◽

Us Counties ◽

The Relationship ◽

Income Quartile

AbstractObjectiveThe relationship between socioeconomic status and its interaction with State’s Medicaid-expansion policies on COVID-19 outcomes across United States (US) counties are uncertain. To determine the association between median-household-income and its interaction with State Medicaid-expansion status on COVID-19 incidence and mortality in US countiesMethodsLongitudinal, retrospective analysis of 3142 US counties (including District of Columbia) to study the relationship between County-level median-household-income (defined by US Census Bureau’s Small-Area-Income-and-Poverty-Estimates) and COVID-19 incidence and mortality per 100000 of the population in US counties from January 20, 2020 through December 6, 2020. County median-household-income was log-transformed and stratified by quartiles. Medicaid-expansion status was defined by US State’s Medicaid-expansion adoption as of first reported US COVID-19 infection, January 20, 2020. Multilevel mixed-effects generalized-linear-model with negative binomial distribution and log link function compared quartiles of median-household-income and COVID-19 incidence and mortality, reported as incidence-risk-ratio (IRR) and mortality-risk-ratio (MRR), respectively. Models adjusted for county socio-demographic and comorbidity conditions, population density, and hospitals, with a random intercept for states. Multiplicative interaction tested for Medicaid-expansion*income quartiles on COVID-19 incidence and mortality.ResultsThere was no significant difference in COVID-19 incidence across counties by income quartiles or by Medicaid expansion status. Conversely, significant differences exist between COVID-19 mortality by income quartiles and by Medicaid expansion status. The association between income quartiles and COVID-19 mortality was significant only in counties from non-Medicaid-expansion states but not significant in counties from Medicaid-expansion states (P<0.01 for interaction). For non-Medicaid-expansion states, counties in the lowest income quartile had a 41% increase in COVID-19 mortality compared to counties in the highest income quartile (MRR 1.41, 95% CI: 1.25-1.59).Conclusions and RelevanceMedian-household-income was not related to COVID-19 incidence but negatively related to COVID-19 mortality in US counties of states without Medicaid-expansion. It was unrelated to COVID-19 mortality in counties of states that adopted Medicaid-expansion. These findings suggest that expanded healthcare coverage should be investigated further to attenuate the excessive COVID-19 mortality risk associated with low-income communities.Key FindingsQuestionIs there a relationship between COVID-19 outcomes (incidence and mortality) and household income and status of Medicaid expansion of US counties?FindingsIn this longitudinal, retrospective analysis of 3142 US counties, we found no significant difference in COVID-19 incidence across US counties by quartiles of household income. However, counties with lower median household income had a higher risk of COVID-19 mortality, but only in non-Medicaid expansion states. This relationship was not significant in Medicaid expansion states.MeaningExpanded healthcare coverage through Medicaid expansion should be investigated as an avenue to attenuate the excessive COVID-19 mortality risk associated with low-income communities.

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Spatial distribution of roadway environment features related to child pedestrian safety by census tract income in Toronto, Canada

Injury Prevention ◽

10.1136/injuryprev-2018-043125 ◽

2019 ◽

Vol 26 (3) ◽

pp. 229-233 ◽

Cited By ~ 3

Author(s):

Linda Rothman ◽

Marie-Soleil Cloutier ◽

Kevin Manaugh ◽

Andrew William Howard ◽

Alison K Macpherson ◽

...

Keyword(s):

Low Income ◽

Census Tract ◽

Motor Vehicle ◽

Pedestrian Safety ◽

High Income ◽

Geographical Information ◽

Income Status ◽

Local Roads ◽

The Relationship ◽

Speed Humps

BackgroundInvestments in traffic calming infrastructure and other street design features can enhance pedestrian safety as well as contribute to the ‘walkability’ of neighbourhoods. Pedestrian–motor vehicle collisions (PMVCs) in urban areas, however, remain common and occur more frequently in lower income neighbourhoods. While risk and protective features of roadways related to PMVC have been identified, little research exists examining the distribution of roadway environment features. This study examined the relationship between roadway environment features related to child pedestrian safety and census tract income status in Toronto.MethodsSpatial cluster detection based on 2006 census tract data identified low-income and high-income census tract clusters in Toronto. Police-reported PMVC data involving children between the ages of 5 and 14 years were mapped using geographical information system. Also mapped were roadway environment features (densities of speed humps, crossing guards, local roads, one-way streets and missing sidewalks). Multivariate logistic regression was used to examine the relationship between roadway environment features (independent variables) and cluster income status (dependent variable), controlling for child census tract population.ResultsThere were significantly fewer speed humps and local roads in low-income versus high-income clusters. Child PMVC rates were 5.4 times higher in low-income versus high-income clusters.ConclusionSocioeconomic inequities in the distribution of roadway environment features related to child pedestrian safety have policy and process implications related to the safety of child pedestrians in urban neighbourhoods.

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Neighbourhood characteristics and health outcomes: evaluating the association between socioeconomic status, tobacco store density and health outcomes in Baltimore City

Tobacco Control ◽

10.1136/tobaccocontrol-2017-053945 ◽

2017 ◽

Vol 27 (e1) ◽

pp. e19-e24 ◽

Cited By ~ 6

Author(s):

Panagis Galiatsatos ◽

Cynthia Kineza ◽

Seungyoun Hwang ◽

Juliana Pietri ◽

Emily Brigham ◽

...

Keyword(s):

Socioeconomic Status ◽

Life Expectancy ◽

Health Outcomes ◽

Low Income ◽

Household Income ◽

Spatial Regression ◽

Median Household Income ◽

Baltimore City ◽

Education Status ◽

The Relationship

IntroductionSeveral studies suggest that the health of an individual is influenced by the socioeconomic status (SES) of the community in which he or she lives. This analysis seeks to understand the relationship between SES, tobacco store density and health outcomes at the neighbourhood level in a large urban community.MethodsData from the 55 neighbourhoods of Baltimore City were reviewed and parametric tests compared demographics and health outcomes for low-income and high-income neighbourhoods, defined by the 50th percentile in median household income. Summary statistics are expressed as median. Tobacco store density was evaluated as both an outcome and a predictor. Association between tobacco store densities and health outcomes was determined using Moran’s I and spatial regression analyses to account for autocorrelation.ResultsCompared with higher-income neighbourhoods, lower-income neighbourhoods had higher tobacco store densities (30.5 vs 16.5 stores per 10 000 persons, P=0.01), lower life expectancy (68.5 vs 74.9 years, P<0.001) and higher age-adjusted mortality (130.8 vs 102.1 deaths per 10 000 persons, P<0.001), even when controlling for other store densities, median household income, race, education status and age of residents.ConclusionIn Baltimore City, median household income is inversely associated with tobacco store density, indicating poorer neighbourhoods in Baltimore City have greater accessibility to tobacco. Additionally, tobacco store density was linked to lower life expectancy, which underscores the necessity for interventions to reduce tobacco store densities.

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Group Incomes and Preferences for Redistribution

Group Interests, Individual Attitudes ◽

10.1093/oso/9780192896209.003.0005 ◽

2021 ◽

pp. 113-132

Author(s):

Michael J. Donnelly

Keyword(s):

Ethnic Groups ◽

Low Income ◽

High Income ◽

British Household Panel Survey ◽

Panel Survey ◽

Preferences For Redistribution ◽

The World ◽

The Relationship ◽

Global Data

In this chapter, I examine the relationship between group incomes and individual attitudes toward redistribution. One major implication of heuristic theory is that individuals who are members of relatively high income ethnic groups or live in high income regions should oppose redistribution more than those in relatively low income ethnic groups or regions. To test this, I present global data from the World Values Survey, UK data from the British Household Panel Survey, and Czech and Slovak data from the Central and Eastern Eurobarometer. I show that the predicted pattern holds in all three settings across a range of approaches, and close by discussing the methodological lessons from these analyses.

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Abstract P130: Association Between Ready-to-eat Cereal Consumption And Nutrient Intakes Among Children 2 To 18 Years, Stratified By Household Income: Results From The National Health And Nutrition Examination Survey 2015-2018

Circulation ◽

10.1161/circ.143.suppl_1.p130 ◽

2021 ◽

Vol 143 (Suppl_1) ◽

Author(s):

Jessica Smith ◽

Neha Jain ◽

James Normington ◽

Norton Holschuh ◽

Yong Zhu

Keyword(s):

Vitamin D ◽

National Health ◽

Low Income ◽

Household Income ◽

Income Group ◽

High Income ◽

Nutrition Examination Survey ◽

Nutrient Intakes ◽

Vitamin D Intake ◽

Health And Nutrition

Ready-to-eat (RTE) cereal has been associated with higher diet quality and dairy intake (it is often consumed with milk) in children and is an affordable source of under-consumed nutrients and whole grains. Because of its affordability and accessibility, the contribution of RTE cereal to nutrient and whole grain intake could potentially differ by household income level. We hypothesized that children living in low income households, which may be more susceptible to poor dietary intakes due to food insecurity, may differentially benefit, in terms of nutrient intake, from RTE cereal consumption compared to children in higher income households. The objective of this study was to quantify the nutrient intakes of U.S. children who reported consuming RTE cereal eater versus those that did not according to household income. We used data from the 2015-2016 and 2017-2018 National Health and Nutrition Examination Survey, a nationally representative, cross-sectional survey. Children 2 to 18 years (n=5,028) were stratified into six groups according to RTE cereal consumption (cereal eaters vs non-eaters) and poverty-to-income ratio (PIR; low-, mid-, and high-income). We calculated the difference in intakes of 28 nutrients between cereal eaters and non-eaters stratified by PIR. Overall, it appeared that there was a greater difference in intake of nutrients between RTE cereal eaters and non-eaters for the low-income compared to the high-income children. For example, in the low-income group, RTE cereal eaters had 23% higher calcium, 70% higher iron, and 90% higher vitamin D intake compared to non-RTE cereal eaters (p<0.0001 for all). In the high-income group, these differences were attenuated with cereal eaters having 12% higher calcium (p=0.03), 58% higher iron (p<0.0001), and 62% higher vitamin D intake (p<0.0001) compared to non-RTE cereal eaters. These data suggest that although cereal eaters had higher intake of under-consumed nutrients across all incomes, children in the low-income group particularly benefited.

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