SUMMARYOur paper seeks to assess the decision to adopt organic farming practices. More specifically, we use Duration Analysis (DA) to determine why farmers adopt organic farming and the timing of adoption. We extend previous studies by including farmers' objectives, risk preferences and agricultural policies as covariates in the DA model. The Analytical Hierarchy Process (AHP) is used as a multi-criteria decision-making methodology to measure farmers' objectives. The empirical analysis uses farm-level data collected through a questionnaire to a sample of vineyard farms in the Spanish region of Catalonia. Farmers' objectives are found to influence the conversion decision. Moreover, farmers who are not risk averse are more prone to adopt organic farming.Results also identify the policy changes that have been more relevant in motivating adoption of organic practices.

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We use a smooth transition vector error correction model to assess price relationships within the U.S. ethanol industry. Monthly ethanol, corn, oil, and gasoline prices from 1990 to 2008 are used in the analysis. Results indicate the existence of long-run relationships among the prices analyzed. Strong links between energy and food prices are identified. JEL classification: L1

Our paper looks at how price volatility in the Brazilian ethanol industry changes over time and across markets. Demand and supply forces in the energy and food markets are likely to ensure that crude oil, ethanol and feedstock prices co-move in the long-run. Hence, when assessing price volatility changes and spillovers in the ethanol industry, one should also pay attention to the notion of cointegration. Until recently, the methods proposed to estimate cointegration relationships, have not explicitly considered time varying volatility in the data. Seo (2007) suggests an estimator of the cointegration vector that explicitly models conditional heteroskedasticity. More specifically, he proposes a maximum likelihood estimator that estimates the error correction model and the multivariate GARCH process jointly. We follow this proposal.World ethanol production is dominated by the US and Brazil. In 2006 worldwide production totaled 13,489 million gallons, with the US and Brazil producing, respectively, a 36 and a 33% of this quantity. Although both countries produce a conspicuous part of worldwide ethanol, their industries are not equally developed: while the Brazilian market is starting to

Previous literature on volatility links between food and energy prices is scarce and mainly based on parametric approaches. We assess this issue by using a semiparametric GARCH model recently proposed by Long et al. (2009), which is essentially a nonparametric correction of the parametric conditional covariance function. We focus on price links between crude oil, ethanol and sugar prices in Brazil. Results suggest strong volatility links between the prices studied. They also suggest that parametric approximations of the conditional covariance matrix may lead to misleading results and can be improved using nonparametric techniques.