A Spatial Decomposition of Income Inequality in Chile

Paredes, Dusan; Iturra, Victor; Lufín, Marcelo

doi:10.1080/00343404.2014.933798

Cited by 34 publications

(19 citation statements)

References 23 publications

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“…This empirical evidence confirmed that the joint consideration of the spatial autocorrelation and income inequality produces important complementarities and offers insights that are not obtainable when these aspects are analysed alone. These results reveal that the proposed measure could be useful in assessing the actual extent of inequality, even in the presence of outstanding economic performances (Paredes et al 2016). Furthermore, our measure is flexible enough to be applied at different geographical scales.…”

Section: Resultsmentioning

confidence: 81%

Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure

Panzera

Postiglione

2019

Soc Indic Res

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Traditional inequality measures fail to capture the geographical distribution of income. The failure to consider such distribution implies that, holding income constant, different spatial patterns provide the same inequality measure. This property is referred to as anonymity and presents an interesting question about the relationship between inequality and space. Particularly, spatial dependence could play an important role in shaping the geographical distribution of income and could be usefully incorporated into inequality measures. Following this idea, this paper introduces a new measure that facilitates the assessment of the relative contribution of spatial patterns to overall inequality. The proposed index is based on the Gini correlation measure and accounts for both inequality and spatial autocorrelation. Unlike most of the spatially based income inequality measures proposed in the literature, our index introduces regional importance weighting in the analysis, thereby differentiating the regional contributions to overall inequality. Starting with the proposed measure, a spatial decomposition of the Gini index of inequality for weighted data is also derived. This decomposition permits the identification of the actual extent of regional disparities and the understanding of the interdependences among regional economies. The proposed measure is illustrated by an empirical analysis focused on Italian provinces.

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Section: Resultsmentioning

confidence: 81%

Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure

Panzera

Postiglione

2019

Soc Indic Res

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“…The Theil index is a special form of the generalized entropy index system, which was first proposed by Theil in 1967 and is now widely used to measure spatial inequality [51][52][53][54]. Unlike other indicators that measure spatial inequality, the Theil index can be decomposed and is an excellent tool for estimating the degree of inequality in countries with multiple levels of administrative divisions, such as China [54]. Since this paper considered three administrative division scales, the regional, provincial, and prefectural levels in China, it is more suitable to apply the two-stage nested Theil decomposition method proposed by Takahiro Akita in 2003 [52].…”

Section: Two-stage Nested Theil Decomposition Methodsmentioning

confidence: 99%

Spatial Differences in China’s Population Aging and Influencing Factors: The Perspectives of Spatial Dependence and Spatial Heterogeneity

Yuan-yuan

Song

2019

Sustainability

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Since China became an aging society in 2000, the regional inequality of population aging has been highlighted, and the phenomenon of "aging before getting rich" has gradually become a core issue in China's coordinated socioeconomic development. This paper aims to comprehensively assess the spatial differences and driving forces of China's population aging through two-stage nested Theil decomposition, ESDA, and spatial econometric models. Empirical results show that spatial differences in population aging were evident at different spatial scales, and the distribution gradually decreased from east to west, showing a positive spatial correlation of similar value aggregation. Moreover, China's population aging was determined by the demographic, socioeconomic, and natural environment, and there are different leading factors in different regions. The demographic aspects played a decisive role and had a direct influence, while the socioeconomic and natural environment indirectly affected population aging through demographic factors and became the root cause of regional differences in population aging. These findings provide an empirical basis for establishing a cooperative mechanism and formulating a targeted response to the problem of population aging in various regions in China.Sustainability 2019, 11, 5959 2 of 20 accumulation [4]. With regard to the social environment, population aging will have various effects on health care, the employment system, the pension insurance system, urban housing and transportation, and old-age service facilities [5]. Furthermore, the regional development imbalance associated with population development factors and socioeconomic characteristics has become a major feature of China's population aging. In view of this, studying the evolution of the spatial differences of China's population aging and its driving factors is conducive to identifying the geographical characteristics of China's population aging and provides a reference for narrowing regional differences, reducing unfavorable socioeconomic impacts and formulating reasonable population development strategies and policies.With the development of industrialization, modernization, and urbanization after the Second World War, developed countries took the lead in completing the modern transformation of population reproduction from high birth and high death rates to low birth and low death rates. The population age structure also changed from young to old. Some scholars have begun to explore the health problems of the elderly and the prevention and treatment of diseases caused by aging from the perspective of biology and medicine [6][7][8]. In the 1970s, geographers interested in aging broadened the understanding of the spatial issues of population aging due to advances in geography, and explored the spatial distribution of the elderly, the dynamic changes in the distribution over time [9][10][11], and the problems urban living spaces create for the elderly [12][13][14]. During this period, several scholars summarized the research on t...

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“…On the other hand, Chile has shown remarkable economic growth in the last decades and has been particularly successful in reducing poverty during the last decade, going from 29.1% in 2006 to 10.9% in 2017; see MINDES (2019). However, regional inequality persists over time and continues to be one of the highest in the world; see Contreras et al (2001); Paredes et al (2016).…”

Section: The Interest Of Regional Studies In the Latin American Contextmentioning

confidence: 99%

Development of Regional Economics Studies in Peru: Contributions and Criticisms

Palomino

2020

ECONOMIA

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This research presents an overview of the evolution of regional economic studies in Peru. After a brief introduction, the document presents a summary of the different conceptions of space in Regional Economics through time. In addition, the document shows the origins of Regional Economics, as well as the factors that explain the interest in the development of regional studies in the Latin American context. This document also explains the importance of the geographical space of Peru for regional research. Indeed, the country is the perfect setting because Peru has a wide geographic diversity (ecosystems, microclimates) throughout its territory, it has implemented a variety of public policies to propose economic growth measures, and it has many social issues to propose territorial policies (migration, crime, health, employment, among others). Despite these characteristics, regional research in Peru is relatively less than in other Latin American countries. Finally, the document offers the contributions and criticisms of the regional studies in the Peruvian context.

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A Spatial Decomposition of Income Inequality in Chile

Cited by 34 publications

References 23 publications

Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure

Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure

Spatial Differences in China’s Population Aging and Influencing Factors: The Perspectives of Spatial Dependence and Spatial Heterogeneity

Development of Regional Economics Studies in Peru: Contributions and Criticisms

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