scholarly journals Spatial Analysis of Fiscal Balance Fund on Income Inequality in West Kalimantan

2021 ◽  
Vol 17 (1) ◽  
pp. 1-19
Author(s):  
Amelia Amelia ◽  
Tri Diana
Keyword(s):  
Income Inequality ◽  
Spatial Dependence ◽  
Medical Personnel ◽  
Spatial Autoregression ◽  
West Kalimantan ◽  
Income Disparities ◽  
Spatial Aspect ◽  
Negative Effect ◽  
Fiscal Balance ◽  
Autoregression Model

Abstract: The research aims to analyze the effect of fiscal balance fund on income inequality in West Kalimantan by considering spatial inter-relationships between existing districts/cities. The study showed that the Spatial Durbin Model with fixed effect was empirically suitable. A variant of spatial autoregression model using Gini Ratio during the period of 2010 – 2018 in 14 districts/cities of West Kalimantan. The study concludes that income disparities between districts/cities were low and constant or the income was relatively distributed per capita. Spatial interactions between districts/cities and their neighbors are also relatively low. Spatial aspect, fiscal balance fund and regional minimum wage have a significant negative effect. On the contrary, the industrial workforce, educated workforce and medical personnel do not affect income inequality in West Kalimantan. This study provides academics with the understanding of the importance of spatial dependence in income inequality model because the economic activity is always related to the neighbor.Keywords: fiscal balance fund, income inequality, spatial aspect Analisis Spasial Dana Perimbangan Terhadap Disparitas Pendapatan Kalimantan BaratAbstrak: Penelitian ini bertujuan menganalisis pengaruh dana perimbangan terhadap disparitas pendapatan di Kalimantan Barat dengan mempertimbangkan keterkaitan spasial antar kabupaten/kota yang ada. Studi ini menghasilkan pemilihan model spasial durbin dengan efek tetap secara empiris sudah tepat. Variansi dari model autoregresif spasial menggunakan Indeks Gini kurun waktu 2010–2018 silang tempat dari 14 kabupaten/kota di Kalimantan Barat. Hasil penelitian menyimpulkan disparitas pendapatan antar kabupaten/kota rendah dan konstan atau relatif merata dalam pendapatan per kapita. Interaksi spasial antar kabupaten/kota dengan tetangganya juga relatif rendah. Aspek spasial, dana perimbangan dan UMR secara negatif signifikan mempengaruhi disparitas pendapatan. Sedangkan tenaga kerja industri, tenaga kerja terdidik dan tenaga medis tidak mempengaruhi disparitas pendapatan di Kalimantan Barat. Penelitian ini memberikan wawasan bagi kalangan akademisi tentang pentingnya memasukkan spatial dependence kedalam model ketimpangan pendapatan karena proses kegiatan ekonomi selalu berkaitan dengan wilayah tetangga.Kata kunci: dana perimbangan, disparitas pendapatan, aspek spatial

scholarly journals Inequality and Growth: A Heterogeneous Approach

2019 ◽  
pp. 18-49
Author(s):  
Francesco Grigoli ◽  
Evelio Paredes ◽  
Gabriel Di Bella
Keyword(s):  
Income Inequality ◽  
Capita Gross Domestic Product ◽  
Median Response ◽  
Negative Effect ◽  
Autoregression Model ◽  
Per Capita ◽  
Cross Country ◽  
Heterogeneous Panel ◽  
Positive Effect ◽  
Structural Vector

This article tests for cross-country convergence in income inequality and estimates its impact on growth with a heterogeneous Panel Structural Vector AutoRegression model, which addresses some empirical challenges plaguing the literature. We find that income inequality is converging across countries, and that its impact on growth is heterogeneous. While the median response of real per capita Gross Domestic Product (GDP) growth to income inequality shocks is negative and significant, at least one fourth of the sample presents a positive effect. Also, we find evidence that improved institutional frameworks can reduce the negative effect of income inequality on growth.

scholarly journals Spatial Externalities of Income Inequality on Security in Latin America

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 245
Author(s):  
Pablo Ponce ◽  
José Álvarez-García ◽  
Mary Cumbicus ◽  
María de la Cruz del Río-Rama
Keyword(s):  
Income Inequality ◽  
Latin American ◽  
Spatial Dependence ◽  
Generalized Least Squares ◽  
Homicide Rate ◽  
World Health ◽  
Control Variables ◽  
Spatial Error ◽  
Middle Income ◽  
Middle Income Countries

The aim of this research is to analyse the effect of income inequality on the homicide rate. The study is carried out in 18 Latin American countries for the period 2005–2018. The methodology used is the Generalized Least Squares (GLS) model and the data were obtained from World Development Indicators, the World Health Organization and the Inter-American Development Bank. Thus, the dependent variable is the homicide rate and the independent variable is income inequality. In addition, some control variables are included, such as: poverty, urban population rate, unemployment, schooling rate, spending on security and GDP per capita, which improve the consistency of the model. The results obtained through GLS model determine that inequality has a negative and significant effect on the homicide rate for high-income countries (HIC) and lower-middle-income countries (LMIC), whereas it is positive and significant for upper-middle-income countries (UMIC). On the other hand, the control variables show different results by group of countries. In the case of unemployment, it is not significant in any group of countries. Negative spatial dependence was found regarding spatial models such as: the spatial lag (SAR) and spatial error (SEM) method. In the spatial Durbin model (SDM), positive spatial dependence between the variables was corroborated. However, spatial auto-regressive moving average (SARMA) identified no spatial dependence. Under these results it is proposed: to improve productivity, education and improve the efficiency of security-oriented resources.

scholarly journals Who Becomes Unhappy when Income Inequality Increases?

2021 ◽  
Author(s):  
Bjorn Lous ◽  
Johan Graafland
Keyword(s):  
Life Satisfaction ◽  
Income Inequality ◽  
Harmful Effect ◽  
World Values Survey ◽  
Lower Income ◽  
Negative Effects ◽  
Average Life ◽  
Income Groups ◽  
The World ◽  
Negative Effect

AbstractLiterature has established that, on a macroeconomic level, income inequality has a negative effect on average life satisfaction. An unresolved question is, however, which income groups are harmed by income inequality. In this paper we investigate this relationship at the microeconomic level combining national indicators of income inequality with individual data of life satisfaction from the World Values Survey for 39 countries over a period of 25 years. Tests on moderation by income category show that the Gini coefficient is most negatively related to life satisfaction of the lowest income groups, but the negative effects also extends to other income groups. For the income share of the top 1% we find a similar result. These findings show that income inequality is especially a concern for the lower income groups, but that the harmful effect of income inequality also spillovers to the life satisfaction of other income groups.

scholarly journals Assortative Mating, Income Inequality, and Place

2021 ◽  
Author(s):  
◽  
Avril Macfarlane
Keyword(s):  
Income Inequality ◽  
Assortative Mating ◽  
Household Income ◽  
European Social Survey ◽  
Highly Educated ◽  
Wide Range ◽  
Negative Effect ◽  
Educational Assortative Mating ◽  
Highly Correlated ◽  
The Relationship

<p>There is a growing concern internationally about levels of income inequality, and the negative effect this has on the functioning of societies both in terms of productivity and social harmony. An unexpected contributor to inequality is assortative mating - the phenomenon of “like marrying like”. Educational attainment is highly correlated with income; when two highly educated people partner and form a household they are more likely to appear at the top of the household income distribution, while couples with only primary or incomplete secondary education appear at the bottom. Therefore the greater the propensity to mate assortatively the more unequal the distribution of household income becomes.   I ask two questions of the relationship between educational assortative mating and household income inequality. Firstly, how do countries (in Europe) differ in their degree of educational assortative mating? Secondly, what is the evidence that such differences are reflected in indicators of household income inequality?   My study differs from the prevailing approaches to this question by taking a geographical approach. Instead of comparing a single country over time and monitoring the correspondence between assortative mating and income inequality, I compare a wide range of countries, using a uniform instrument, at one point in time. In order to do so I draw on the unit records of 29 countries from the European Social Survey administered in 2012.   From these unit record data I have been able to identify two important patterns. Firstly, there is a clear presence of educational assortative mating in each country. However, the degree differs and it does so primarily as a reflection of the overall level of education in the country. Rising levels of education lower the returns for education, in turn making assortative mating comparatively less attractive. As a result, the level of assortative mating, compared to what would be expected under random conditions, is lower in highly educated nations. The lowered level of assortative mating in highly educated nations reduces the barriers to social mobility through marriage for those without university educations. Consequently, household income inequality is seen to be intrinsically related to assortative mating, although the outcomes can be mitigated by redistribution policies.</p>

scholarly journals Assortative Mating, Income Inequality, and Place

2021 ◽  
Author(s):  
◽  
Avril Macfarlane
Keyword(s):  
Income Inequality ◽  
Assortative Mating ◽  
Household Income ◽  
European Social Survey ◽  
Highly Educated ◽  
Wide Range ◽  
Negative Effect ◽  
Educational Assortative Mating ◽  
Highly Correlated ◽  
The Relationship

<p>There is a growing concern internationally about levels of income inequality, and the negative effect this has on the functioning of societies both in terms of productivity and social harmony. An unexpected contributor to inequality is assortative mating - the phenomenon of “like marrying like”. Educational attainment is highly correlated with income; when two highly educated people partner and form a household they are more likely to appear at the top of the household income distribution, while couples with only primary or incomplete secondary education appear at the bottom. Therefore the greater the propensity to mate assortatively the more unequal the distribution of household income becomes.   I ask two questions of the relationship between educational assortative mating and household income inequality. Firstly, how do countries (in Europe) differ in their degree of educational assortative mating? Secondly, what is the evidence that such differences are reflected in indicators of household income inequality?   My study differs from the prevailing approaches to this question by taking a geographical approach. Instead of comparing a single country over time and monitoring the correspondence between assortative mating and income inequality, I compare a wide range of countries, using a uniform instrument, at one point in time. In order to do so I draw on the unit records of 29 countries from the European Social Survey administered in 2012.   From these unit record data I have been able to identify two important patterns. Firstly, there is a clear presence of educational assortative mating in each country. However, the degree differs and it does so primarily as a reflection of the overall level of education in the country. Rising levels of education lower the returns for education, in turn making assortative mating comparatively less attractive. As a result, the level of assortative mating, compared to what would be expected under random conditions, is lower in highly educated nations. The lowered level of assortative mating in highly educated nations reduces the barriers to social mobility through marriage for those without university educations. Consequently, household income inequality is seen to be intrinsically related to assortative mating, although the outcomes can be mitigated by redistribution policies.</p>

The Economic Roots of External Efficacy: Assessing the Relationship between External Political Efficacy and Income Inequality

2015 ◽  
Vol 48 (4) ◽  
pp. 791-813 ◽  
Author(s):  
Mikel Norris
Keyword(s):  
Public Policy ◽  
Income Inequality ◽  
National Level ◽  
State Level ◽  
The United States ◽  
Political Efficacy ◽  
Multilevel Regression ◽  
Individual Level ◽  
Negative Effect ◽  
The 1960S

AbstractExternal political efficacy, the belief that government is responsive to the demands of its citizens, has been declining in the United States since the 1960s. However, scholars do not yet fully understand the reasons for its decline. Nor have they found suitable explanations for why it fluctuates within the electorate. Drawing on the growing literature on the effects of income inequality on public policy, I posit that increasing income inequality factors into the decline of external political efficacy. Using multilevel regression models accounting for individual and contextual factors, I find increasing state-level income inequality has a substantial negative effect on external political efficacy. It is greater than most state and national-level economic measures or individual-level variables on external political efficacy. These results have important implications both for research on income inequality and political participation and also for research on income inequality and distributional public policy.

The Monetary Policy Impact on the Dynamics of Russia’s Real Economy

2017 ◽  
Vol 2017 (3) ◽  
pp. 80-108
Author(s):  
Marina Tiunova
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Real Economy ◽  
Structural Vector Autoregression ◽  
Real Wages ◽  
Vector Autoregression Model ◽  
Real Gdp ◽  
Negative Effect ◽  
Autoregression Model ◽  
Exchange Rate Shocks

The article examines the influence of monetary policy of the Bank of Russia on the dynamics of real GDP and its components, real wages and employment from 2003 to 2016. Using the Bayesian structural vector autoregression model (BSVAR) with recent dataset, the paper provides the calculation of the extent of changes in the main Russia’s real sector indicators in response to monetary policy, money base and exchange rate shocks. The analysis allows to conclude that monetary policy leads to real variables changes in Russia. The expected contractionary monetary policy of the Central Bank of Russia with higher interest rates had a statistically valid weak negative effect on real indicators.

scholarly journals Growth and Income Inequality: A Comparative Analysis

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Ayla Ogus Binatli
Keyword(s):  
Comparative Analysis ◽  
Income Inequality ◽  
Time Period ◽  
Negative Effect ◽  
Time Periods ◽  
Growth Changes ◽  
Changes Over Time ◽  
The Relationship ◽  
Positive Effect ◽  
Over Time

This paper investigates whether the relationship between income inequality and growth changes over time. Two time periods, covering 1970–1985 and 1985–1999, are analyzed and compared. A statistically significant relationship between inequality and growth in either time period fails to emerge. However, there are indications that effect of inequality on growth may be different in the nineties when compared to the seventies. In the literature, a consistent negative effect of inequality on growth is documented although the significance of the effect is open to debate. This paper also finds a negative effect of income inequality on growth in the seventies but, although statistically insignificant, a consistently positive effect in the nineties.

A spatial autoregression model with time-varying coefficients

2020 ◽  
Vol 13 (2) ◽  
pp. 261-270
Author(s):  
Ke Xu ◽  
Luping Sun ◽  
Jin Liu ◽  
Xuening Zhu ◽  
Hansheng Wang
Keyword(s):  
Time Varying ◽  
Spatial Autoregression ◽  
Varying Coefficients ◽  
Autoregression Model ◽  
Time Varying Coefficients
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