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	Provedor de dados AgEcon (2) Autor Cho, Seong-Hoon (2) Jung, Suhyun (2) Kim, Seung Gyu (1) Lambert, Dayton M. (1) Roberts, Roland K. (1) Palavra-chave Community/Rural/Urban Development (1) Extreme coefficient (1) Fixed and adaptive calibrations (1) GWR (1) Geographically weighted regression (1) Government expenditure (1) Mapping (1) Poverty (1) Research Methods/ Statistical Methods (1) Southern United States (1) Mais... Tipo do documento Conference Paper or Presentation (2) Ano 2009 (2) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Public Expenditure and Poverty Reduction in the Southern United States AgEcon Jung, Suhyun; Cho, Seong-Hoon; Roberts, Roland K.. The objective of this research was to analyze the effects of education, health and hospital, parks and recreation, and public welfare expenditures on poverty, focusing particularly on how these relationships change over space and time. Government expenditure on parks and recreation has been the single most effective government expenditure category over time, although the marginal effects of the government expenditure on poverty alleviation have weakened over time. Clusters of the highest marginal effects of government expenditures on poverty reduction were identified for each time period using geographically weighted regression (GWR) and analysis of local indicators of spatial association (LISA) Tipo: Conference Paper or Presentation Palavras-chave: Government expenditure; GWR; Poverty; Southern United States; Community/Rural/Urban Development. Ano: 2009 URL: http://purl.umn.edu/47145 Extreme coefficients in Geographically Weighted Regression and their effects on mapping AgEcon Cho, Seong-Hoon; Lambert, Dayton M.; Kim, Seung Gyu; Jung, Suhyun. This study deals with the issue of extreme coefficients in geographically weighted regression (GWR) and their effects on mapping coefficients using three datasets with different spatial resolutions. We found that although GWR yields extreme coefficients regardless of the resolution of the dataset or types of kernel function, 1) the GWR tends to generate extreme coefficients for less spatially dense datasets, 2) coefficient maps based on polygon data representing aggregated areal units are more sensitive to extreme coefficients, and 3) coefficient maps using bandwidths generated by a fixed calibration procedure are more vulnerable to the extreme coefficients than adaptive calibration. Tipo: Conference Paper or Presentation Palavras-chave: Extreme coefficient; Fixed and adaptive calibrations; Geographically weighted regression; Mapping; Research Methods/ Statistical Methods. Ano: 2009 URL: http://purl.umn.edu/49117 Registros recuperados: 2 Primeira ... 1 ... Última

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