The impact of regional inequality on economic growth: a spatial econometric approach

Panzera, Domenica; Postiglione, Paolo

doi:10.1080/00343404.2021.1910228

Cited by 51 publications

(34 citation statements)

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“…И иерархические, и пространственные модели по отдельности применяются в региональных исследованиях, однако последние значительно чаще. Так, посредством построения моделей пространственного лага (SAR) и пространственной ошибки (SEM) изучаются пространственные зависимости экономического роста в Китае Tian et al, 2010), США (Pede, 2013), Европе (Panzera, Postiglione, 2021). В России методы пространственной эконометрики также получили широкое применение.…”

Section: теоретический обзорunclassified

“…Как правило, в региональных исследованиях в качестве обобщающего показателя экономического развития территорий принимается валовой региональный продукт (ВРП). Пространственная автокорреляция ВРП неоднократно определялась как отечественными Буфетова, 2016;Горшкова, 2019), так и зарубежными учеными Tian et al, 2010;Panzera, Postiglione, 2021). При этом за рубежом все чаще проводятся такие исследования на более низком уровне агрегации данных.…”

Section: пэ № 4 2021unclassified

“…Фактически такие модели учитывают механизмы прямых и косвенных межрегиональных связей территорий, оценивают влияние импульсов роста, зародившихся и протекающих на соседних территориях (Коломак, 2010). При этом такая связь может быть как положительной, так и отрицательной, указывая на характер взаимосвязи территорий (Tian et al, 2010;Pede, 2013;Panzera, Postiglione, 2021). Факторы также могут быть пространственно зависимыми и иметь разнонаправленное влияние.…”

Section: Introductionunclassified

“…Факторы также могут быть пространственно зависимыми и иметь разнонаправленное влияние. Например, в работе (Panzera, Postiglione, 2021) показано, что развитие человеческого капитала на рассматриваемой территории может оказывать положительное влияние на экономический рост, в то время как развитие человеческого капитала в соседних территориях -отрицательное.…”

Section: Introductionunclassified

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Economic Activity of Territories: Comparative Analysis of the Spatial Effects Assessing Methods

Timiryanova¹,

Zimin²,

Yusupov³

2021

Spatial Economics

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The article discusses a hierarchical and spatial approach to assessing the spatial dependence of data. The advantages and disadvantages of each approach and the potential for their combination are determined on the basis of a literature review.The results of the OLS, SAR, SEM, HLM, HSAR models are compared. Despite an interesting set of data (2285 municipalities in the context of 85 constituent entities of the Russian Federation), the emphasis in the work is not on identifying the relationship between the dependent variable and factors, but on comparing spatial effects that can be identified within each of the models under consideration. The calculations showed a significant influence on the dependent variable of the following factors: the share of the average number of employees in the resident population, the volume of investments in fixed assets per capita and the share of the urban population. This result was shown by all the constructed models. In the context of models, the identified spatial effects have their own characteristics. The inclusion of spatial matrices is possible at the upper (for example, the subject of the Russian Federation), lower (for example, the municipal level), or both levels simultaneously. In hierarchical models, spatial relationships are additionally taken into account by grouping the objects of observation on a territorial basis. Calculations have shown that the spatial lag is not significant in all models. Spatial error is significant at the municipal level in the SEM model and at the regional level in the HLM and HSAR models. Additionally, hierarchical models showed a significant influence of the region on the municipalities variation. In general, the results of modeling and evaluating modelsquality are ambiguous. Despite this, the potential for expanding spatial econometrics on the basis of a combination of spatial and hierarchical (multilevel) modeling approaches is noted, and the need to select a model for each case is substantiated, taking into account the significance of spatial and hierarchical effects

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Section: теоретический обзорunclassified

Section: пэ № 4 2021unclassified

Section: Introductionunclassified

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Economic Activity of Territories: Comparative Analysis of the Spatial Effects Assessing Methods

Timiryanova¹,

Zimin²,

Yusupov³

2021

Spatial Economics

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“…Applying tools that analyse spatial proximity in geographical concentration of economic activities could help policy‐makers to assess these effects, and improve multi‐level governance in short and long‐run. Additionally, our spatial decomposition may also be used in spatial growth equations to measure what are the effects of spatial concentration on economic growth (e.g., Caragliu et al, 2016; Panzera & Postiglione, 2021).…”

Section: Introductionmentioning

confidence: 99%

New evidence on measuring the geographical concentration of economic activities

Panzera

Cartone

Postiglione

2022

Papers in Regional Science

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Spatial interactions among regional units may influence the geographical distribution of economic activities. Many traditional measures of geographical concentration fail in capturing this aspect, being insensitive to permutations of the spatial position of regions. This paper proposes an approach to the measurement of geographical concentration of economic activities that accounts for spatial interactions among regions. The locational Gini is split into spatial and nonspatial components, so that a new interpretation of the index is presented. The measure is applied to evaluate the geographical concentration of different economic sectors for 1,323 NUTS 3 regions in the European Union over the period 2001-2018.

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Impact factors and space‐time characteristics of income inequality in a global sample

Quito

Río‐Rama

Álvarez‐García

et al. 2022

Sustainable Development

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Inequality has been of growing interest in the political debate and in theoretical and empirical studies for some decades. Therefore, the study of regional inequality raises some relevant questions related to the spatial nature of the data. In fact, adopting a regional point of view implies the opportunity to consider spatial interactions, which traditional studies do not include in their analyses. Therefore, the study aims to analyze income inequality before (GINI1) and after (GINI2) income and transfers, using a data

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The impact of regional inequality on economic growth: a spatial econometric approach

Cited by 51 publications

References 55 publications

Economic Activity of Territories: Comparative Analysis of the Spatial Effects Assessing Methods

Economic Activity of Territories: Comparative Analysis of the Spatial Effects Assessing Methods

New evidence on measuring the geographical concentration of economic activities

Impact factors and space‐time characteristics of income inequality in a global sample

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