Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: 

RelevânciaAutorTítuloAnoImprime registros no formato resumido
Registros recuperados: 5
Primeira ... 1 ... Última
Imagem não selecionada

Imprime registro no formato completo
Assessing the Spatial and Temporal Variation of Output-Input Elasticities of Agricultural Production in Turkey AgEcon
Yu, Tun-Hsiang (Edward); Cho, Seong-Hoon; Koc, A. Ali; Gulden, Boluk; Seung Gyu, Kim.
Preliminary Draft
Tipo: Conference Paper or Presentation Palavras-chave: Turkey; Agricultural Reform and Implementation Project; Geographically weighted regression; Agricultural and Food Policy; Research Methods/ Statistical Methods; Q18; C3.
Ano: 2010 URL: http://purl.umn.edu/56544
Imagem não selecionada

Imprime registro no formato completo
Applying Geographically Weighted Regression to Conjoint Analysis: Empirical Findings from Urban Park Amenities AgEcon
Tanaka, Katsuya; Yoshida, Kentaro; Kawase, Yasushi.
The objective of this study is to develop spatially-explicit choice model and investigate its validity and applicability in CA studies. This objective is achieved by applying locally-regressed geographically weighted regression (GWR) and GIS to survey data on hypothetical dogrun facilities (off-leash dog area) in urban recreational parks in Tokyo, Japan. Our results show that spatially-explicit conditional logit model developed in this study outperforms traditional model in terms of data fit and prediction accuracy. Our results also show that marginal willingness-to-pay for various attributes of dogrun facilities has significant spatial variation. Analytical procedure developed in this study can reveal spatially-varying individual preferences on attributes...
Tipo: Conference Paper or Presentation Palavras-chave: Choice experiments; Conjoint analysis; Dogrun; Geographically weighted regression; Spatial econometrics; Research Methods/ Statistical Methods; Resource /Energy Economics and Policy.
Ano: 2008 URL: http://purl.umn.edu/6233
Imagem não selecionada

Imprime registro no formato completo
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
Imagem não selecionada

Imprime registro no formato completo
An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis AgEcon
Lambert, Dayton M.; McNamara, Kevin T.; Garrett, Megan I..
The influence product markets, agglomeration, labor, infrastructure, and government fiscal attributes had on manufacturing investment flows in Indiana between 2000 and 2004 were estimated using Poisson regression, geographically weighted regression, and a spatial general linear model. Counties with access to urbanization economies, product markets, available labor, a high-quality workforce, and transport infrastructure were more likely to attract manufacturing investment. These effects were magnified to some extent when inter-county spatial effects were modeled. The distributional assumptions of the spatial models are different, but both methods are useful for understanding the spatial context of the factors influencing manufacturing investment flows.
Tipo: Journal Article Palavras-chave: Geographically weighted regression; Location determinants; Location theory; Manufacturing site selection; Poisson spatial generalized linear model; Agribusiness; Industrial Organization; Productivity Analysis; R1; R3.
Ano: 2006 URL: http://purl.umn.edu/43752
Imagem não selecionada

Imprime registro no formato completo
Persistent Pockets of Extreme American Poverty and Job Growth: Is There a Place-Based Policy Role? AgEcon
Partridge, Mark D.; Rickman, Dan S..
Over the past four decades almost 400 U.S. counties have persistently experienced poverty rates in excess of 20%. This raises the question of whether poverty-reducing policies should be directed more at helping people or helping the places where they reside. Using a variety of approaches, including geographically weighted regression analysis, we find that local job growth especially reduces poverty in persistent-poverty counties. Findings also show that these counties do not respond more sluggishly to exogenous shocks. Finally, this analysis identifies some key geographic differences among persistent-poverty clusters. Taken together, place-based economic development has a potential role for reducing poverty in these counties.
Tipo: Journal Article Palavras-chave: Economic development; Geographically weighted regression; Persistent poverty; Place-based policies; Poverty; Community/Rural/Urban Development; Labor and Human Capital.
Ano: 2007 URL: http://purl.umn.edu/8599
Registros recuperados: 5
Primeira ... 1 ... Última
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional