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	Provedor de dados AgEcon (2) Autor Brorsen, B. Wade (1) Kenkel, Philip L. (1) Lee, Byoung-Hoon (1) Polyakov, Maksym (1) Zhang, Daowei (1) Palavra-chave Agribusiness (2) Spatial lag (2) Conditional logit (1) Environmental Economics and Policy (1) Farm Management (1) Labor and Human Capital (1) Land Economics/Use (1) Land use change (1) Population gravity index (1) Prediction (1) Production Economics (1) Productivity Analysis (1) Protein (1) Q15 (1) Q23 (1) R14 (1) Risk and Uncertainty (1) Test weight (1) Weather (1) Wheat yield (1) Mais... Tipo do documento Conference Paper or Presentation (1) Journal Article (1) Ano 2011 (1) 2008 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Population Growth and Land Use Dynamics along Urban–Rural Gradient AgEcon Polyakov, Maksym; Zhang, Daowei. In this study we apply a spatial conditional logit model to determine factors influencing land cover change in three contiguous counties in West Georgia between 1992 and 2001 using point (pixel) based observations of land characteristics. We found that accessibility to population and population growth affect not only development of rural lands and transition between agricultural and forestry uses, but also influence changes between forest types. The model could be used to project land use–land cover change at watershed or subwatershed level and thus serve as a valuable tool for county and city planners. Tipo: Journal Article Palavras-chave: Conditional logit; Land use change; Population gravity index; Spatial lag; Agribusiness; Labor and Human Capital; Land Economics/Use; Q15; Q23; R14. Ano: 2008 URL: http://purl.umn.edu/47205 Pre-harvest Forecasting of County Wheat Yield and Wheat Quality Conditional on Weather Information AgEcon Lee, Byoung-Hoon; Kenkel, Philip L.; Brorsen, B. Wade. Wheat regression models that account for the effect of weather are developed to forecast wheat yield and quality. Spatial lag effects are included. Wheat yield, protein, and test weight level are strongly influenced by weather variables. The forecasting power of the yield and protein models was enhanced by adding the spatial lag effect. Out of sample forecasting tests confirm the models’ usefulness in accounting for the variations in average wheat yield and qualities. Tipo: Conference Paper or Presentation Palavras-chave: Prediction; Protein; Spatial lag; Test weight; Weather; Wheat yield; Agribusiness; Environmental Economics and Policy; Farm Management; Production Economics; Productivity Analysis; Risk and Uncertainty. Ano: 2011 URL: http://purl.umn.edu/98829 Registros recuperados: 2 Primeira ... 1 ... Última

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