From GDP to average household income: A look at the transmission channels

2016 ◽  
pp. 87-119
Author(s):  
Keyword(s):  
Household Income ◽  
Transmission Channels ◽  
Average Household Income

scholarly journals Association between parental socioeconomic status and offspring overweight/obesity from the China Family Panel Studies: a longitudinal survey

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e045433
Author(s):  
Suqin Ding ◽  
Jingqi Chen ◽  
Bin Dong ◽  
Jie Hu
Keyword(s):  
High School ◽  
Socioeconomic Status ◽  
Regression Model ◽  
Household Income ◽  
Parental Education ◽  
Education Level ◽  
Longitudinal Survey ◽  
Average Household Income ◽  
Education Levels ◽  
Parental Socioeconomic Status

ObjectiveTo examine the association between parental socioeconomic status (SES) and the risk of offspring overweight/obesity and the changes of the association that occur as children grow older.DesignWe used data from the nationally representative longitudinal survey of the China Family Panel Studies of 2010 and its three follow-up waves in 2012, 2014 and 2016.ParticipantsA total of 6724 children aged 0–15 years old were included.Primary and secondary outcome measuresAverage household income and paternal and maternal education levels were used as SES indicators. Logistic regression model for panel data was used to examine the associations between SES indicators and child overweight/obesity. A restricted cubic spline linear regression model was used to estimate body mass index (BMI) trajectories with child growth across parental SES levels.ResultsCompared with the lowest education level (primary school or less), the ORs for fathers who had completed junior high school, senior high school and junior college or higher were 0.85 (95% CI 0.75 to 0.97), 0.77 (95% CI 0.64 to 0.92) and 0.72 (95% CI 0.55 to 0.93), respectively. The corresponding ORs for mothers were 0.76 (95% CI 0.67 to 0.86), 0.59 (95% CI 0.47 to 0.72) and 0.45 (95% CI 0.34 to 0.60), respectively. A negative association between parental education and offspring overweight/obesity was observed in the first 10 years but not in children 11–15 years old. BMI differences across parental education levels emerged from birth and widened before 6–7 years old, but decreased before adolescence. High average household income was related to a low risk of offspring overweight/obesity but not when parental education level was adjusted for.ConclusionHigh parental education levels were associated with a low risk of offspring overweight/obesity, especially before adolescence. Effective approaches need to be adopted in early childhood to reduce socioeconomic differences in overweight/obesity.

scholarly journals ANALISIS PENDAPATAN DAN TINGKAT KESEJAHTERAAN RUMAH TANGGA MASYARAKAT SEKITAR TAMAN NASIONAL BUKIT BARISAN SELATAN KABUPATEN PESISIR BARAT

2021 ◽  
Vol 9 (3) ◽  
pp. 418
Author(s):  
M. Reza Fachrezy ◽  
Zainal Abidin ◽  
Adia Nugraha
Keyword(s):  
Household Income ◽  
National Park ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Farm Income ◽  
Labor Costs ◽  
The Third ◽  
Average Household Income ◽  
Average Education ◽  
On Farm

This study aims to determine the socio-economic characteristics of farmers, analyze the income structure, the factors that affect the income of farmers, and the level of household welfare of farmers who live around Bukit Barisan Selatan National Park, Pesisir Barat District. This research is a survey research involving 99 respondents who were randomly selected. Respondents were spread across four subdistricts, namely Bengkunat Belimbing, Ngambur, Pesisir Selatan, and Karya Penggawa Districts. The study was conducted from July to August 2018. The first objective was analyzed qualitatively, the second objective was analyzed using household income analysis, the third objective used multiple linear regression analysis, and the fourth objective was using Sajogyo's criteria (1997). The study suggested that the socio-economic characteristics of the farmers around TNBBS were spread from 15 to 64 years of age with an average age of 43.74 years. The average education level was elementary school, the number of majority of family sizes was from 4 to 6 people (67.68%), and the average land was 1.41 ha. The average household income of farmers is IDR 36,946,883.94 per year, which consists of on-farm income 63.68%, off-farm income 11.00%, and non-farm income 25.33%.. Factors that affect farmers' income are fertilizer costs and labor costs. The welfare of farmers around TNBBS is in quite prosperous category.Key words: characteristics, household income, welfare

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 INEQUALITY AND WELFARE OF THE DISPLACED HOUSEHOLDS DUE TO THE CONSTRUCTION OF KOTO PANJANG DAM

2019 ◽  
Vol 21 (1) ◽  
pp. 93
Author(s):  
Fery Andrianus ◽  
Syafruddin Karimi ◽  
Werry Darta Taifur ◽  
Endrizal Ridwan
Keyword(s):  
Income Inequality ◽  
Household Income ◽  
Gini Index ◽  
Economic Condition ◽  
Negative Relationship ◽  
Total Sample ◽  
Household Welfare ◽  
Average Household Income ◽  
The Relationship ◽  
Resettlement Programs

Displacement due to the construction of the Koto Panjang dam has an impact on household welfare. The displaced households experienced a very poor economic condition at the beginning of the displacement period. This study seeks answers to two questions: how the current welfare of the households is and how the relationship between welfare and income inequality of those households is. The study was conducted on 12 villages which are the locations of involuntary resettlement programs with a total sample of 360 households. The study used Gini index to measure income inequality and Subjective Welfare Indicator to compare household welfare. The results showed that in general, the average household income in Koto Panjang was higher than the Provincial Minimum Wage, but it was not evenly distributed in all villages. The result also showed a negative relationship between welfare and income inequality, but it cannot be used for further analysis because the correlation value is very low.

scholarly journals SEVERAL FACTORS THAT AFFECT CATTLE ROWING PATTERNS AS WELL AS THEIR CONTRIBUTION TO HOUSEHOLD INCOME (CASE STUDY OF LIVESTOCK FARMERS IN TAEBENU SUBDISTRICT, KUPANG REGENCY, NTT)

2021 ◽  
Vol 21 (3) ◽  
pp. 175-184
Author(s):  
Salden E Nifu ◽  
Djoko Koestiono ◽  
Hery Toiba
Keyword(s):  
Household Income ◽  
Sampling Method ◽  
Logistics Regression ◽  
Group I ◽  
Average Household Income ◽  
Dependent Variables ◽  
Livestock Farmers ◽  
Privately Owned

This study aims to analyze several factors that affect cattle rowing patterns as well as their costs, receipts and contributions to the household income of livestock farmers in Taebenu Subdistrict, Kupang Regency, NTT. The research sample of 100 people was grouped into two groups: group I (50 row cattle farmers) and group II (50 non-row cattle farmers). Determination of the number of farmer samples follows slovin formula with random sampling method. Data on factors that influence the decisions of farmers' households are analyzed with binary logistics regression analysis. Meanwhile, the income of cattle farmers and non-rowdy cattle was analyzed by household income analysis. The results showed that the analysis of binary logistics regression using simultaneous tests showed that independent variables (X) namely X1, X2, X3, X4, X5, X6 significantly influenced dependent variables (Y). The average household income of cattle farmers rowdy pattern is Rp 13,327,080 with the contribution of income from the business of cattle rowing by 21.93%, while the average household income of non-rowdy cattle farmers (privately owned) Rp 12,820,488 with the contribution of income from non-row cattle businesses amounted to 22.93%. From the results of household income shows the household income of cattle farmers row pattern higher than the household income of non-row cattle farmers (privately owned).

scholarly journals Does Income Inequality Explain the Geography of Residential Burglaries? The Case of Belo Horizonte, Brazil

2019 ◽  
Vol 8 (10) ◽  
pp. 439 ◽  
Author(s):  
Ramos
Keyword(s):  
Income Inequality ◽  
Household Income ◽  
Criminological Theory ◽  
Independent Effect ◽  
Single Family ◽  
Average Household Income ◽  
Local Exposure ◽  
Residential Burglaries ◽  
Belo Horizonte ◽  
The Relationship

The relationship between crime and income inequality is a complex and controversial issue. While there is some consensus that a relationship exists, the nature of it is still the subject of much debate. In this paper, this relationship is investigated in the context of urban geography and whether income inequality can explain the geography of crime within cities. This question is examined for the specific case of residential burglaries in the city of Belo Horizonte, Brazil, where I tested how much burglary rates are affected by local average household income and by local exposure to poverty, while I controlled for other variables relevant to criminological theory, such as land-use type, density and accessibility. Different scales were considered for testing the effect of exposure to poverty. This study reveals that, in Belo Horizonte, the rate of burglaries per single family house is significantly and positively related to income level, but a higher exposure to poverty has no significant independent effect on these rates at any scale tested. The rate of burglaries per apartment, on the other hand, is not significantly affected by either average household income or exposure to poverty. These results seem consistent with a description where burglaries follow a geographical distribution based on opportunity, rather than being a product of localized income disparity and higher exposure between different economic groups.

scholarly journals Assessment of the income situation of households in the Czech Republic

2011 ◽  
Vol 57 (No. 7) ◽  
pp. 322-330
Author(s):  
J. Turčínková ◽  
J. Stávková
Keyword(s):  
Czech Republic ◽  
Gini Coefficient ◽  
Household Income ◽  
Lorenz Curve ◽  
Explanatory Power ◽  
Primary Source ◽  
The Czech Republic ◽  
Poverty Threshold ◽  
Average Household Income ◽  
The Lorenz Curve

The paper deals with the assessment of income situation of households in the Czech Republic. The primary source for the analysis were the data of the survey EU-SILC European Union – Statistics on Income and Living Conditions. The basic variable for the analysis is the level of the household income in 2005–2008. In addition to the decile classification, characteristics such as the average income per one household member, poverty threshold, poverty depth coefficient, Lorenz curve and Gini coefficient. were calculated in order to evaluate the income situation. The results show an increase of the average household income. The Lorenz curve followed by the Gini coefficient demonstrate the uniformity of distribution of income values. The results show a decreasing income differentiation. The poverty threshold was defined on the level of 60% of the median value and with this given threshold, the households were assessed, whether they belong to the ones at the risk of poverty. The results reveal a decreasing number of households at the risk of poverty. The poverty depth coefficient has a stronger explanatory power and shows how far below the poverty threshold the households are, or what is an income deficit of these households. Each category of households at the risk of poverty varies with the depth of poverty. The analysis also provides the results of how the households' income situation or poverty is perceived by the households themselves.

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