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	Provedor de dados AgEcon (2) Autor Karantininis, Kostas (1) Oude Lansink, Alfons G.J.M. (1) Rasmussen, Svend (1) Serra, Teresa (1) Stefanou, Spiro E. (1) Palavra-chave State-contingent (2) Agricultural and Food Policy (1) C13 (1) C15 (1) D21 (1) D80 (1) Dynamic model (1) Farm Management (1) Investment decisions (1) Land Economics/Use (1) Maximum entropy (1) Monte Carlo simulation (1) Production (1) Production Economics (1) Risk (1) Uncertainty (1) Mais... Tipo do documento Conference Paper or Presentation (2) Ano 2010 (1) 2005 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última A dynamic dual model under state-contingent production uncertainty AgEcon Serra, Teresa; Stefanou, Spiro E.; Oude Lansink, Alfons G.J.M.. In this paper we assess how production costs and capital accumulation patterns in agriculture have evolved over time, by paying special attention to the influence of risk. A dynamic state-contingent cost minimization approach is applied to assess production decisions in US agriculture over the last century. Results suggest the relevance of allowing for the stochastic nature of the production function which permits to capture both the differences in the costs of producing under different states of nature, the differences in the evolution of these costs over time, as well as the differential impacts of different states of nature on investment decisions. Tipo: Conference Paper or Presentation Palavras-chave: Risk; State-contingent; Dynamic model; Investment decisions; Agricultural and Food Policy; Farm Management; Land Economics/Use; D21. Ano: 2010 URL: http://purl.umn.edu/61353 Estimating State-Contingent Production Functions AgEcon Rasmussen, Svend; Karantininis, Kostas. The paper reviews the empirical problem of estimating state-contingent production functions. The major problem is that states of nature may not be registered and/or that the number of observation per state is low. Monte Carlo simulation is used to generate an artificial, uncertain production environment based on Cobb Douglas production functions with state-contingent parameters. The parameters are subsequently estimated based on different sizes of samples using Generalized Least Squares and Generalized Maximum Entropy and the results are compared. It is concluded that Maximum Entropy may be useful, but that further analysis is needed to evaluate the efficiency of this estimation method compared to traditional methods. Tipo: Conference Paper or Presentation Palavras-chave: Maximum entropy; State-contingent; Uncertainty; Production; Monte Carlo simulation; Production Economics; C13; C15; D80. Ano: 2005 URL: http://purl.umn.edu/24529 Registros recuperados: 2 Primeira ... 1 ... Última

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