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	Provedor de dados AgEcon (2) Autor Bergstrom, John C. (1) Cai, Ruohong (1) Mullen, Jeffrey D. (1) Shurley, W. Donald (1) Syed, Arif (1) Wetzstein, Michael E. (1) Mais... Palavra-chave Climate change. (2) Crop Production/Industries (1) Crop yield response (1) Energy demand (1) Energy efficiency (1) Energy policy (1) Principal component regression (1) Resource /Energy Economics and Policy (1) Mais... Tipo do documento Conference Paper or Presentation (1) Working or Discussion Paper (1) Ano 2011 (2) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Energy use reduction and input productivity growth in Australian industries AgEcon Syed, Arif. A report by the Prime Minister’s Task Group on Energy Efficiency (July 2010) emphasised the need for improved energy efficiency as a response to climate change to ensure a reduction in greenhouse gas emissions from energy consumption in Australia. However, empirical evidence on energy efficiency and its effect on energy use in Australia is scarce. Given this, estimates of the magnitude of the autonomous energy efficiency improvement parameter and the bias in technological change in Australia’s agricultural and industrial sectors have been made, using statistical and econometric techniques. The strong interaction prevailing between capital use and energy productivity in many industries indicates that energy use efficiency may be augmented by optimising... Tipo: Conference Paper or Presentation Palavras-chave: Energy efficiency; Energy demand; Energy policy; Climate change.; Resource /Energy Economics and Policy. Ano: 2011 URL: http://purl.umn.edu/100715 Principal Component Analysis of Crop Yield Response to Climate Change AgEcon Cai, Ruohong; Bergstrom, John C.; Mullen, Jeffrey D.; Wetzstein, Michael E.; Shurley, W. Donald. The objective of this study is to compare the effects of climate change on crop yields across different regions. A Principal Component Regression (PCR) model is developed to estimate the historical relationships between weather and crop yields for corn, soybeans, cotton, and peanuts for several northern and southern U.S. states. Climate change projection data from three climate models are applied to the estimated PCR model to forecast crop yield response. Instead of directly using weather variables as predictor variables, the PCR model uses weather indices transformed from original weather variables by the Principal Component Analysis (PCA) approach. A climate change impact index (CCII) is developed to compare climate change effects across different... Tipo: Working or Discussion Paper Palavras-chave: Principal component regression; Crop yield response; Climate change.; Crop Production/Industries. Ano: 2011 URL: http://purl.umn.edu/103947 Registros recuperados: 2 Primeira ... 1 ... Última

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