Volatility of commodity prices has affected dramatically the coffee industry in recent years, particularly small holder farmers. Differentiation of coffee through certification, such as sustainahility and quality attr...Volatility of commodity prices has affected dramatically the coffee industry in recent years, particularly small holder farmers. Differentiation of coffee through certification, such as sustainahility and quality attributes, has been proposed as a strategy for protection of the farmers against volatility in the international prices. This research paper evaluated three different models to explore the effectiveness of the differentiation strategies in protecting the farmer against price volatility in recent years, focusing on the case of Costa Rica. Evidence showed important differences in the price dynamics over time when comparing three groups of coffee.展开更多
This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear determinist...This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types： the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S＆：P500 index, such as volatility clustering, fat tails （leptokurtosis）, autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.展开更多
文摘Volatility of commodity prices has affected dramatically the coffee industry in recent years, particularly small holder farmers. Differentiation of coffee through certification, such as sustainahility and quality attributes, has been proposed as a strategy for protection of the farmers against volatility in the international prices. This research paper evaluated three different models to explore the effectiveness of the differentiation strategies in protecting the farmer against price volatility in recent years, focusing on the case of Costa Rica. Evidence showed important differences in the price dynamics over time when comparing three groups of coffee.
基金This research is supported by MEXT Global COE Program （Kyoto University）, National Natural Science Foundation of China under Grant No.71001036 and No. 71171186, Main Direction Program of Chinese Academy of Sciences KACX1-YW-0906, and the Scientific Research Fund of Hunan Provincial Education Department under Grant No. 10A082.
文摘This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types： the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S＆：P500 index, such as volatility clustering, fat tails （leptokurtosis）, autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.
