dc.contributor.advisor | Johnson, Thomas G. | eng |
dc.contributor.author | Mishra, Bhawani Prasad (Researcher) | eng |
dc.contributor.other | University of Missouri-Columbia. Graduate School. Theses and Dissertations. Dissertations. 2013 Dissertations | eng |
dc.coverage.spatial | United States | eng |
dc.date.issued | 2013 | eng |
dc.date.submitted | 2013 Spring | eng |
dc.description.abstract | [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Firms tend to cluster in a relatively small geographical location. As a result, the distribution of the most of the economic activities is not even across space. There are advantages firms can get by being in a cluster. These advantages arise from the agglomeration economies either by localization economies or by urbanization economies. A cluster is an outcome of many firms' location decisions. The location of an industrial cluster is determined by nature and economic objective(s) of a firm. This study attempts to examine the clustering issue in the health care sector. Specifically, this study examines the distribution pattern of health care clusters and identifies the factors affecting health care clustering. It also examines the spatial interaction and spatial dependence between clusters. In order to examine these objectives, 930 CBSAs are selected from the 48 contiguous states of the US. The results show that the clustering process of health care sector has been continued over the years in the CBSA regions. The major health care clusters are located in the East and West coasts, and the Sunbelt regions of the country. A panel data model is used to identify the factors affecting health care sector cluster. Among the competitive panel models, the fixed effects panel model turns out to have the best fit. The result of the fixed effects model identifies factors like local competition, a number of small size establishments, localization economies index, neighboring cluster, neighboring employment in the health care sector, the neighboring population, and health GDP as significantly contributing to health care clustering. In addition, this study also examines the spatial interactions between clusters. The the result of the spatial interaction between the clusters shows that a relatively small health care cluster like Columbia, MO has more influencing power to its neighboring clusters than St. Louis, MO or Los Angeles, CA. The results also shows that the interregional interaction is significantly contributing to heal | eng |
dc.format.extent | 1 online resource (x, pages) : illustrations (some color), color maps | eng |
dc.identifier.oclc | 891140818 | eng |
dc.identifier.uri | https://doi.org/10.32469/10355/43326 | eng |
dc.identifier.uri | https://hdl.handle.net/10355/43326 | |
dc.language | English | eng |
dc.publisher | University of Missouri--Columbia | eng |
dc.relation.ispartofcommunity | University of Missouri--Columbia. Graduate School. Theses and Dissertations | eng |
dc.rights | Access is limited to the campus of the University of Missouri--Columbia. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | |
dc.source | Submitted by the University of Missouri--Columbia Graduate School. | eng |
dc.subject.lcsh | Industrial clusters. | eng |
dc.subject.lcsh | Health facilities. | eng |
dc.title | Health care sector clustering in U.S. regions | eng |
dc.type | Thesis | eng |
thesis.degree.discipline | Agricultural economics (MU) | eng |
thesis.degree.grantor | University of Missouri--Columbia | eng |
thesis.degree.level | Doctoral | eng |
thesis.degree.name | Ph. D. | eng |