Spatial econometrics can bring a useful approach to macroeconomic analysis of regional data. This thesis delineates suitable cross-section data models regarding their geographical location. Neighbourhood relation is used for the analysis. The relation of neighbourhood among the regions is expressed using spatial weight matrix. We focus on spatial autocorrelation tests and introduce processes of finding a suitable spatial model. Further, we describe regression coefficients estimates and estimates of spatial dependence coefficients, especially method of maximum likelihood estimates. Besides illustrative examples we apply chosen basic spatial models on real macroeconomic data. We examine how they describe relation between household incomes, GDP and unemployment rate in western Europe. Results are compared with a linear regression model.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:359198 |
| Date | January 2017 |
| Creators | Macková, Simona |
| Contributors | Formánek, Tomáš, Tomanová, Petra |
| Publisher | Vysoká škola ekonomická v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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