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	Provedor de dados AgEcon (2) Autor Ma, Xingliang (1) Merlo, Antonio (1) Shi, Guanming (1) Palavra-chave Structural estimation (2) Agribusiness (1) Agricultural and Food Policy (1) Bayesian learning (1) C41 (1) C51 (1) C73 (1) C78 (1) Crop Production/Industries (1) D72 (1) Delay (1) Duration models. (1) Government formation (1) Industrial Organization (1) Noncooperative bargaining (1) Political Economy (1) Production Economics (1) Research Methods/ Statistical Methods (1) Research and Development/Tech Change/Emerging Technologies (1) Risk and Uncertainty (1) Mais... Tipo do documento Conference Paper or Presentation (1) Working or Discussion Paper (1) Ano 2011 (1) 1996 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Bargaining over governments in a stochastic environment AgEcon Merlo, Antonio. In this paper we structurally estimate a game-theoretic model of government formation in a multiparty parliamentary democracy. We focus on the timing and the terms of government agreements in the context of a multilateral stochastic model of sequential bargaining with complete information (Merlo and Wilson (1194, 1995)) where efficient delays may occur in the unique equilibrium. Besides showing that our model yields a good fit to the data on the duration of negotiations over government formation as well as government durations in postwar Italy, we use our estimates to quantify the advantage to proposing and to conduct policy experiments to evaluate the effects of changes in the bargaining procedure. We show that the gains from proposing tend to be quite... Tipo: Working or Discussion Paper Palavras-chave: Noncooperative bargaining; Delay; Government formation; Structural estimation; Duration models.; Political Economy; C41; C51; C73; C78; D72. Ano: 1996 URL: http://purl.umn.edu/7476 A Dynamic Adoption Model with Bayesian Learning: Application to the U.S. Soybean Market AgEcon Ma, Xingliang; Shi, Guanming. Agricultural technology adoption is often a sequential process. Farmers may adopt a new technology in part of their land first and then adjust in later years based on what they learn from the earlier partial adoption. This paper presents a dynamic adoption model with Bayesian learning, in which forward-looking farmers learn from their own experience and from their neighbors about the new technology. The model is compared to that of a myopic model, in which farmers only maximize their current benefits. We apply the analysis to a sample of U.S. soybean farmers from year 2000 to 2004 to examine their adoption pattern of a newly developed genetically modified (GM) seed technology. We show that the myopic model predicts lower adoption rates in early years than... Tipo: Conference Paper or Presentation Palavras-chave: Technology adoption; Bayesian learning; Structural estimation; Agribusiness; Agricultural and Food Policy; Crop Production/Industries; Industrial Organization; Production Economics; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; Risk and Uncertainty; Teaching/Communication/Extension/Profession. Ano: 2011 URL: http://purl.umn.edu/104577 Registros recuperados: 2 Primeira ... 1 ... Última

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