scholarly journals The Effect of EITC Reform on Household Income Distribution

2019 ◽  
Vol 8 (1) ◽  
pp. 69-100
Author(s):  
Shin, Sangwha
Keyword(s):  
Income Distribution ◽  
Household Income

scholarly journals The impact of a minimum wage change on the distribution of wages and household income

2020 ◽  
Author(s):  
Paul Redmond ◽  
Karina Doorley ◽  
Seamus McGuinness
Keyword(s):  
Income Distribution ◽  
Minimum Wage ◽  
Wage Inequality ◽  
Household Income ◽  
Spillover Effects ◽  
Wage Distribution ◽  
Wage Increase ◽  
Minimum Wage Increase ◽  
Wage Change ◽  
The Impact

Abstract We use distribution regression analysis to study the impact of a 6% increase in the Irish minimum wage on the distribution of hourly wages and household income. Wage inequality, measured by the ratio of wages in the 90th and 10th percentiles and the 75th and 25th percentiles, decreased by approximately 8 and 4%, respectively. The results point towards wage spillover effects up to the 30th percentile of the wage distribution. We show that minimum wage workers are spread throughout the household income distribution and are often located in high-income households. Therefore, while we observe strong effects on the wage distribution, the impact of a minimum wage increase on the household income distribution is quite limited.

The effects of household income distribution on stroke prevalence and its risk factors of high blood pressure and smoking: a cross-sectional study in Saskatchewan, Canada

2016 ◽  
Vol 137 (2) ◽  
pp. 114-121 ◽  
Author(s):  
Yelena Bird ◽  
Mark Lemstra ◽  
Marla Rogers
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Risk Factor ◽  
Income Distribution ◽  
High Blood Pressure ◽  
Household Income ◽  
Lower Income ◽  
Cross Sectional ◽  
Statistical Adjustment ◽  
Stroke Prevalence

Background: Stroke is a major chronic disease and a common cause of adult disability and mortality. Although there are many known risk factors for stroke, lower income is not one that is often discussed. Aims: To determine the unadjusted and adjusted association of income distribution on the prevalence of stroke in Saskatchewan, Canada. Methods: Information was collected from the Canadian Community Health Survey conducted by Statistics Canada for 2000–2008. In total, 178 variables were analysed for their association with stroke. Results: Prior to statistical adjustment, stroke was seven times more common for lower income residents than higher income residents. After statistical adjustment, only four covariates were independently associated with stroke prevalence, including having high blood pressure (odds ratio (OR) = 2.62; 95% confidence interval (CI) = 2.12–3.24), having a household income below CAD$30,000 per year (OR = 2.49; 95% CI = 1.88–3.29), being a daily smoker (OR = 1.36; 95% CI = 1.16–1.58) and being physically inactive (OR = 1.27; 95% CI = 1.13–1.43). After statistical adjustment, there were five covariates independently associated with high blood pressure prevalence, including having a household income below CAD$30,000 per year (OR = 1.52; 95% CI = 1.41–1.63). After statistical adjustment, there were five covariates independently associated with daily smoking prevalence, including having a household income below CAD$30,000 per year (OR = 1.29; 95% CI = 1.25–1.33). Conclusions: Knowledge of disparities in the prevalence, severity, disability and mortality of stroke is critically important to medical and public health professionals. Our study found that income distribution was strongly associated with stroke, its main disease intermediary – high blood pressure – and its main risk factor – smoking. As such, income is an important variable worthy of public debate as a modifiable risk factor for stroke.

scholarly journals After the Financial Crisis: The Evolution of the Global Income Distribution Between 2008 and 2013

2020 ◽  
Author(s):  
Branko Milanovic
Keyword(s):  
Financial Crisis ◽  
Income Distribution ◽  
Household Income ◽  
Global Financial Crisis ◽  
Income Growth ◽  
Global Inequality ◽  
Working Paper ◽  
Income Data ◽  
The Global Financial Crisis ◽  
China’S Growth

Using the newly created, and in terms of coverage and detail, the most complete household income data from more than 130 countries, the paper analyzes the changes in the global income distribution between 2008 and 2013. This was the period of the global financial crisis and recovery. It is shown that global inequality continued to decline, largely due to China’s growth that explains one-half of global Gini decrease between 2008 and 2013. Income growth of the global top 1 percent slowed significantly. The slowdown is present even after survey data are corrected for the likely underestimation of highest incomes. The paper ends with a discussion of the effects of the financial crisis in the light of an even more serious looming crisis caused by the 2019-20 pandemic. (Stone Center on Socio-Economic Inequality Working Paper)

THE IMPACT OF THE ANTI-CORRUPTION CAMPAIGN ON INCOME DISTRIBUTION: EVIDENCE FROM CHINA

2021 ◽  
pp. 1-23
Author(s):  
YING GE ◽  
JINJUN XUE
Keyword(s):  
Income Distribution ◽  
Survey Data ◽  
Household Income ◽  
The Other ◽  
Public Officials ◽  
Government Officials ◽  
The Public ◽  
Earnings Gap ◽  
Micro Level ◽  
The Impact

This paper provides the first systematic micro-level evidences on the effectiveness of anti-corruption campaign in disciplining public officials and its impact on income distribution. Based on China Household Income Project (CHIP) survey data 2007 and 2013, we found that party and government officials had significant hidden income and the public–private earnings gap was as high as 8% before the campaign. However, the hidden income become not significant and the earnings gap declined to −18% in this post-campaign period. The regions inspected by central anti-corruption inspection groups experience larger public earnings penalties compared to the other regions. Overall, our findings suggest that the privilege of public officials declined sharply during this anti-corruption campaign.

scholarly journals Addressing Household Income Distribution in Air Travel Demand Models: Case Study of the Baltimore–Washington Region

2019 ◽  
Vol 2673 (1) ◽  
pp. 491-502 ◽  
Author(s):  
Geoffrey D. Gosling ◽  
David Ballard
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Travel Demand ◽  
Metropolitan Region ◽  
Annual Data ◽  
Demand Model ◽  
Passenger Demand ◽  
Average Household Income ◽  
Demand Models ◽  
The Future

The paper describes the development of an air passenger demand model for the Baltimore–Washington metropolitan region that was undertaken as part of a recently concluded ACRP project that explored the use of disaggregated socioeconomic data in air passenger demand studies. The model incorporated a variable reflecting the change in household income distribution, together with more traditional aggregate causal variables: population, employment, average household income, and airfares as measured by the average U.S. airline yield, as well as several year-specific dummy variables. The model was estimated on annual data for the period 1990 to 2010 and obtained statistically significant estimated coefficients for all variables, including both the average household income and the household income distribution variable. Including household income distribution in the model resulted in a significant change to the estimated coefficient for average household income, giving a much higher estimated elasticity of demand with respect to average household income compared with a model that does not consider changes in household income distribution. This has important implications for the use of such demand models for forecasting, as household income distribution and average household income may change in the future in quite different ways, which would affect the future levels of air passenger travel projected by the models.

scholarly journals ANALISIS STRUKTUR DAN DISTRIBUSI PENDAPATAN RUMAH TANGGA SERTA TINGKAT KESEJAHTERAAN ANGGOTA KOPERASI SERBA USAHA PETERNAK MOTIVASI DOA IKHTIAR TAWAKKAL (KSUP MDIT) DI KECAMATAN GISTING KABUPATEN TANGGAMUS

2018 ◽  
Vol 6 (1) ◽  
pp. 95
Author(s):  
Fikri Syahputra ◽  
Dyah Aring Hepiana Lestari ◽  
Fembriarti Erry Prasmatiwi
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Secondary Data ◽  
Primary Data ◽  
Farm Income ◽  
Household Welfare ◽  
Distribution Analysis ◽  
On Farm ◽  
Positive Effect

This study aims to analyze the household income’s structure and distribution, and the household welfare level among cooperatives members, in addition to analyze factors that affected the household welfare of cooperative members. This research employed case study method.  The data was collected from September to October 2016.  The research respondents were 55 people who were all members of KSUP MDIT.  The data was consisted of primary and secondary data. Primary data was obtained by observation and interview; while secondary data was obtained  from the agencies and literatures associated with the study.  The data was analyzed by income analysis, income distribution analysis, welfare analysis and binnary logistic regression analysis. The result showed that the biggest member of cooperative member's household income structure in the latest year was non livestock earnings of On Farm followed by non farm income, goat business income and off farm income.  Distribution of household member income of cooperatives were in low inequality. Based on Socio Metrix indicator, 70.91% cooperative members’ households were included in prosperous category and the remaining 29.09% were not prosperous and old variables of education, length of membership, and household income have a positive effect on welfare level.Key words: distribution income, prosperity of members, income

scholarly journals A Bayesian Analysis of Income Distribution Image

2017 ◽  
Author(s):  
Atsushi Ishida
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Reference Group ◽  
Social Position ◽  
Analytical Models ◽  
Distribution Characteristics ◽  
Average Income ◽  
Bayesian Hierarchical ◽  
Age Cohort ◽  
The Mean

The purpose of this study is to investigate people’s image of income distribution and its difference by social position from data collected during a 2015 Japanese survey (SSP 2015) by applying Bayesian statistical analytical models. From the observed variable of average income image, the latent income distribution images from which the observed average income image is supposed to be derived were estimated and differences in income distribution image by social position were analyzed using Bayesian hierarchical models.In the analysis, differences in income distribution image by age cohort and household income class were examined in terms of the mean and the Gini inequality coefficient of the distribution image. Consequently, it was found that although the distribution image tends to underestimate the average income level and overestimate inequality, the income distribution image could be an incomplete reflection of the income distribution characteristics of the reference group.

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