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Quality of life in the regions: an exploratory spatial data analysis for West German labor markets

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  • Karsten Rusche

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Abstract

Which of Germany’s regions is the most attractive? Where is it best to live and work—on objective grounds? These questions are summed up in the concept “quality of life”. This paper uses recent research projects that determine this parameter to examine the spatial distribution of quality of life in Germany. For this purpose, an Exploratory Spatial Data Analysis is conducted which focuses on identifying statistically significant (dis-)similarities in space. An initial result of this research is that it is important to choose the aggregation level of administrative units carefully when considering a spatial analysis. The level plays a crucial role in the strength and impact of spatial effects. In concentrating on various labor market areas, this paper identifies a significant spatial autocorrelation in the quality of life, which seems to be contradictory to the hypothesis of a North-South divide. Instead, the German regions in the geographical mid show the highest clustering of low quality of life. In addition, the ESDA results are used to augment the regression specifications, which helps to avoid the occurrence of spatial dependencies in the residuals. The regression results indicate that soft location factors have half the impact on quality of life than hard economic factors. Copyright Springer-Verlag 2010

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  • Karsten Rusche, 2010. "Quality of life in the regions: an exploratory spatial data analysis for West German labor markets," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 30(1), pages 1-22, February.
  • Handle: RePEc:spr:jahrfr:v:30:y:2010:i:1:p:1-22
    DOI: 10.1007/s10037-009-0042-6
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    1. Thiess Büttner & Alexander Ebertz, 2007. "Lebensqualität in den Regionen: Erste Ergebnisse für Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 60(15), pages 13-19, August.
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    Cited by:

    1. Norbert Hiller & Oliver Lerbs, 2015. "The capitalization of non-market attributes into regional housing rents and wages: evidence on German functional labor market areas," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 35(1), pages 49-72, February.
    2. Karsten Rusche & Uwe Kies & Andreas Schulte, 2011. "Measuring spatial co-agglomeration patterns by extending ESDA techniques," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 31(1), pages 11-25, June.
    3. Hashem Dadashpoor & Nina Khalighi, 2016. "Investigating Spatial Distribution of Regional Quality of Life (RQoL) in Iran Between 1996 and 2011," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(3), pages 1217-1248, July.
    4. repec:rom:terumm:v:12:y:2017:i:1:p:21-37 is not listed on IDEAS

    More about this item

    Keywords

    Lebensqualität; Explorative räumliche Datenanalyse; Funktionalregionen; Räumliche Ökonometrie; LISA Dummies; Quality of life; Exploratory spatial data analysis; Functional economic areas; Spatial econometrics and statistics; LISA dummies; D63; R10; R12; R50;

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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