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dc.contributor.advisorGolpe Moya, Antonio Aníbal 
dc.contributor.authorAlmeida Márquez, Alejandro 
dc.date.accessioned2022-05-17T10:18:28Z
dc.date.available2022-05-17T10:18:28Z
dc.date.issued2020-10-29
dc.identifier.isbn978-84-7993-598-6
dc.identifier.urihttp://hdl.handle.net/10334/6260
dc.description93 páginas.es
dc.description.abstractTesis doctoral (Lectura 29/10/2020). Director: Antonio Aníbal Golpe Moya. Tribunal: Raúl Ramos Lobo (presidente); María Concepción Román Díaz (secretaria); M. Begoña Cueto Iglesias (vocal). Spatial econometrics has studied and analyzed the horizontal interactions that take place between different geographic locations. The proximity between two locations makes them behave more similarly than those locations that are further away. The development of this literature has been possible, in part, due to the increase in disaggregated data at the geographical level. This disaggregation also allows us to have data at different geographic scales (i.e., provinces, regions, and countries), ending in nested data sets. This nested nature of the data allows and generates the need to take into account the possible vertical spillovers that occur when a higher scale can influence the lower scales, for example, countries that influence their regions. In recent years, some authors have proposed different models that allow the inclusion of both types of interactions, vertical and horizontal. However, the literature and the empirical applications are still scarce. For this reason, this thesis tries to empirically analyze these models and to develop new models that allow progress in the inclusion of vertical spillovers in the field of spatial econometrics. Through applications in the sensitivity of the regions to the economic cycle, self-employment, cigarette consumption and the productivity of the European countries and regions, different proposed models are analyzed, such the dynamic spatial econometrics model with common factors and hierarchical spatial econometrics models. Chapter 2 analyze which regions are more sensitive to aggregate fluctuations, finding a pattern for Spain where the most sensitive regions are on the Mediterranean coast. Chapter 3 analyzes the spatial dynamics of self-employment in the United States, finding a relationship between high self-employment clusters and sensitivity to the national cycle. In chapter 4 and 5, cigarette consumption in the Spanish provinces is analyzed and the price is modelled as a common national factor, finding heterogeneity in the behaviour of the provinces. Finally, Chapter 6 develops an HSD model of spatial econometrics in a hierarchical context and is applied to analyze the production of European regions and the influence of countries on them.es
dc.language.isoenges
dc.publisherUniversidad Internacional de Andalucíaes
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEconometría espaciales
dc.subjectSpilloverses
dc.titleVertical spillovers in spatial econometricses
dc.typedoctoralThesises
dc.identifier.doi10.56451/10334/3791es
dc.rights.accessRightsopenAccesses


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