Threshold Effects in Price Transmission: The Case of Brazilian Wheat, Maize, and Soya Prices

Balcombe, Kelvin; Bailey, Alastair; Brooks, Jonathan

doi:10.1111/j.1467-8276.2007.01013.x

Cited by 113 publications

(85 citation statements)

References 21 publications

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“…While a few studies have econometrically assessed average price relationships within the Brazilian and North American ethanol industries (Balcombe andRapsomanikis 2008, Serra et al 2008), no previous published paper addresses the transmission of volatility within this industry. Volatility in oil prices, for example, may spill over ethanol markets which in turn may induce volatility into the feedstock market.…”

Section: Introductionmentioning

confidence: 99%

Price volatility in ethanol markets

Serra¹,

Zilberman²,

Gil³

2010

European Review of Agricultural Economics

150

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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

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Section: Introductionmentioning

confidence: 99%

Price volatility in ethanol markets

Serra¹,

Zilberman²,

Gil³

2010

European Review of Agricultural Economics

150

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“…Applications to agriculture building on this method find significant transaction costs on the European pig market (Meyer 2004) and the nineteenth century U.S. egg market (Serra and Goodwin 2004). Recently, Balcombe et al (2007) and Balcombe and Rapsomanikis (2008) use Bayesian methods to assess nonlinearities in spatial price behaviour, and Serra et al (2006) use local linear regression techniques to estimate a TVECM.…”

Section: Introductionmentioning

confidence: 99%

The Turkish wheat market: spatial price transmission and the impact of transaction costs

et al. 2010

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Agricultural production is spread all over Turkey and the considerably different climatic and topographical conditions among the provinces lead to highly diversified agricultural production. Therefore, is it reasonable to assume an integrated market all over Turkey? The authors analyze spatial price transmission among 28 Turkish provinces with regard to wheat markets. They apply a bivariate threshold vector error correction model with two symmetric thresholds to account for transaction costs. They find an inner cluster of highly integrated provinces and identify the market size as a driving force of market integration. Furthermore, this study is unique in determining the minimum level of transaction costs. The results suggest that the minimum transaction costs impede full market integration more often on smaller than on larger markets. [EconLit citations: L100; D230; Q110]. (C) 2010 Wiley Periodicals, Inc.

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“…A second and more sophisticated approach collects a set of alternative variants under the common label of regime-dependent or state-dependent Vector Error Correction Models (VECM). Among the possible specifications of this latter approach, recent empirical literature has mostly focused on the so-called threshold cointegration where the change in the price transmission relationship occurs when some price exceeds a given value, so the regime change is, in this respect, endogenous (Goodwin and Harper, 2000;Abdulai, 2002;Balcombe et al, 2007;Rezitis and Stavropoulos, 2011). It must be emphasised, however, that the common feature of the threshold cointegration approach is that it concentrates the non-linearity of price transmission (i.e.…”

Section: The Quantitative Approachmentioning

confidence: 99%

The effect of EU 2006 sugar regime reform on vertical price transmission

Aragrande

Bruni²,

Loi³

et al. 2017

Agric Econ

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CAP regulation of sugar sector has frequently been questioned because of its potential effect on competition. In 2006 the CAP reform of the sugar sector established a relevant break in policy trend with potential albeit untargeted effects on price transmission. In 2012 DG AGRI commissioned a study to assess the effects of the 2006 reform of the EU sugar regime on the price transmission within the sugar sector. This paper highlights the effects of the new CAP sugar regime on sugar retail price and on the degree of competition and concentration in the sugar industry. Vertical price transmission is tested through econometric models. The relationship between concentration and competition is analysed putting in relation the concentration index and a modified version of the Lerner index. Results of empirical investigation show that vertical price transmission asymmetries still exist after the reform, which in turn contributed to increase sugar sector concentration, partly confirming the validity of the Structure-Conduct-Performance assumptions. The sugar market is far from efficient and the reform only created more favourable conditions for its improvement.

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Threshold Effects in Price Transmission: The Case of Brazilian Wheat, Maize, and Soya Prices

Cited by 113 publications

References 21 publications

Price volatility in ethanol markets

Price volatility in ethanol markets

The Turkish wheat market: spatial price transmission and the impact of transaction costs

The effect of EU 2006 sugar regime reform on vertical price transmission

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