The importance of spatial autocorrelation for regional employment growth in Germany

Zierahn, Ulrich

doi:10.1007/s10037-011-0062-x

Cited by 11 publications

(4 citation statements)

References 24 publications

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“…The results of the Moran's test computed on the residuals of the presented models suggesting spatial autocorrelation, confirm the importance of spatial relationships among the regions under consideration. This is not new in the literature, since previous studies (i.e., Niebuhr, ; Zierahn, ) have found that labour market dynamics in neighbour regions are interrelated. If not adequately modelled, the presence of spatial dependence and heterogeneity in cross‐section estimates, can affect the reliability of results (Anselin, ; Arbia, ; Piras & Arbia, ).…”

Section: Resultsmentioning

confidence: 85%

The role of regional competitiveness in shaping the heterogeneous impact of the Great Recession

Pizzuto

2020

Regional Science Policy & Practice

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This paper assesses the employment resilience of 202European regions to the Great Recession by investigating the role of regional competitiveness. By using the regional shift component derived from a multiple bases shift-share analysis of employment change as a measure of regional endogenous employment growth, we show that pre-crisis regional competitiveness determinants are associated with positive performances during the crisis period. However, the variables considered explain well the different vulnerability of the economies, but less convincingly the ability to recover. Taking into account the spatial interactions among regions, results are confirmed and allow us to identify spillover effects.

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Section: Resultsmentioning

confidence: 85%

The role of regional competitiveness in shaping the heterogeneous impact of the Great Recession

Pizzuto

2020

Regional Science Policy & Practice

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“…where n is the sample size, h and i are the locations, W hi is the matrix's size, and W is the sum of values. The distance function is w hi ; y h equals one and the particular distance groups are y i where y h y i and 0 in all other cases; y h , y i are the values of the variables (Coetzee and Kleynhans 2018a;Zierahn 2012).…”

Section: Applying Moran's I-statisticmentioning

confidence: 99%

The Effect of Spatial Unemployment on the Neighbouring Regions’ Economies: A Regional Case Study of KwaZulu-Natal in South Africa

Coetzee

Kleynhans

Dyason

2022

MGT

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This article investigates the degree of spatial dependence of unemployment on neighbouring economies with possible implications for cross-border community development initiatives. The local municipalities within the KwaZulu-Natal province in South Africa are used as a case study. Spatial econometric techniques are employed that incorporate dependence between regions in close geographical proximity. Disaggregated data and knowledge about the dynamics at a sub-regional level are usually unavailable for designing employment policies, especially for regional economies in under-developed countries. The results suggest an absence of spatial unemployment clustering and autocorrelation between neighbouring economies. The absence of externalities implies that little mutual dependence exists between adjacent economies, and therefore municipal unemployment patterns can be viewed as spatially random. The economy of a region is therefore fundamentally heterogeneous in that its unemployment rates are determined and influenced by its unique and diverse factors rather than neighbouring unemployment trends or patterns.

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“…According to Zierahn (). the growth rate of unemployment in one region is interrelated with the employment growth in another region because of a productivity effect.…”

Section: Spillovers In Local Performancementioning

confidence: 99%

Territorial determinants and NUTS 3 regional performance: A spatial analysis for Italy across the crisis

Cascio

Mazzola

Epifanio

2019

Papers in Regional Science

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This paper analyses the differential impact of several territorial determinants of the economic performance of Italian provinces (NUTS 3 level). as measured by per capita GDP, export and employment growth from 1999 to 2014. It covers both the pre‐crisis and the crisis period and stresses the role of geographical proximity in shaping local performance over a wide set of explanatory variables. In order to do so, we employ, firstly, a spatial Durbin model which enables us to discriminate between direct and indirect effects and to highlight the possible contagion or crowding‐out spatial effects for each territorial dimension affecting growth. Then, we extend the analysis by allowing for the possibility of two regimes (pre‐crisis and post‐crisis). The performance of the provinces before and during the crisis relates to specific territorial components and geographic proximity appears to influence differently the results and their interpretation.

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The importance of spatial autocorrelation for regional employment growth in Germany

Cited by 11 publications

References 24 publications

The role of regional competitiveness in shaping the heterogeneous impact of the Great Recession

The role of regional competitiveness in shaping the heterogeneous impact of the Great Recession

The Effect of Spatial Unemployment on the Neighbouring Regions’ Economies: A Regional Case Study of KwaZulu-Natal in South Africa

Territorial determinants and NUTS 3 regional performance: A spatial analysis for Italy across the crisis

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