Anthony PARIS

This paper investigates the determinants of solar photovoltaic (PV) deployment in the electricity mix for a panelof OECD and BRICS countries from 1997 to 2016 by paying particular attention to the impact of oil market con-ditions. Relying on a nonlinear, regime-switching specification, we show that rising oil prices stimulate PV de-ployment only if their growth rate exceeds 6.7% per annum. Although wefind that various other determinantsmatter—with the influence of some of them depending on the situation on the oil market—public policies playa crucial role.

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Many developed countries promote the use of biofuels for environmental concerns, leading to a rise in the price of agricultural commodities utilized in their production. Such environmental policies have major effects on the economy of emerging and developing countries whose activity is highly dependent on agricultural commodities involved in biofuel production. This paper tackles this issue by examining the price impact of biofuels on the current account for a panel of 16 developing and emerging countries, and the potential nonlinear effect exerted by the price of oil on this relationship. Relying on the estimation of panel smooth-transition regression models, we show that positive shocks in the price of biofuels lead to a current-account improvement for agricultural commodity exporters (resp. producers) only when the price of oil is below 45 (resp. 56) US dollars per barrel. When the price of oil exceeds these thresholds, the effect of fluctuations in the price of biofuels on the current account tends to weaken and become non significant. Under these conditions, our findings indicate that, for agricultural commodity exporters which are also oil importers, the current account is pulled by two opposite forces, making its overall reaction modest or even nil. JEL Classification: Q16; Q43; F32; C23.. We would like to thank Cécile Couharde, Anne-Laure Delatte and Sébastien Jean for helpful comments and suggestions.

The aim of this paper is to investigate the long-term effect of the price of oil on agricultural commodity prices by accounting for the influence of biofuel production. Relying on the estimation of nonlinear, cointegrating regime-switching processes, we show that biofuel development has led to an increase in the oil-price effect on agricultural commodity prices: the growing production of biofuels is contributing to the price rise of agricultural commodities. This result underlines the importance of considering alternative biofuels which are not produced from agricultural commodities, and of analyzing the potential effects of the second-generation biofuels derived from agricultural plant residuals or non-food plants.

This working paper overviews theoretical foundations and estimators derived from econometric models used to analyze stated choices proposed in Discrete Choice Experiment (DCE)surveys. Discrete Choice Modelling is adapted to the case where the variable to be explained is a qualitative variable which cannot be ranked in relation to each other. A situation which occurs in many cases in everyday life as people often have to choose only one alternative among a proposed set of different ones in many fields (early in the morning, just think about how you pick clothes for instance). DCE is a Stated Preference method in which preferences are elicited through repeated fictional choices, proposed to a sample of respondents. Compared to Revealed Preference methods, DCEs allow for an ex ante evaluation of public policies that do not yet exists.

This paper investigates the determinants of solar photovoltaic (PV) deployment in the electricity mix for a panel of OECD and BRICS countries from 1997 to 2016 by paying particular attention to the impact of oil market conditions. Relying on a nonlinear, regime-switching specification, we show that rising oil prices stimulate PV deployment only if their growth rate is important, above 6.7%. Although we find that various other determinants matter—with the influence of some of them depending on the situation on the oil market—public policies play a crucial role. In particular, our findings show that feed-in-tariffs should be encouraged to ensure a continuous fight against climate change, whatever the dynamics followed by oil prices.

The aim of this paper is to study the ethanol price dynamics in the US market and find the optimal hedging strategy. To this end, we first attempt to identify the long-term relationship between ethanol spot prices and the prices of futures contracts on the Chicago Board of Trade (CBOT). Then, we model the short-term dynamics between these two prices using a Markov-switching vector error correction model (Ms-VECM). Finally, accounting for the variance dynamics using a Gjr-MGarch error structure, we compute a time-varying hedge ratio and determine the optimal hedging strategy in the US ethanol market.

Many developed countries promote the use of biofuels for environmental concerns, leading to a rise in the price of agricultural commodities utilized in their production. Such environmental policies have major effects on the economy of emerging and developing countries whose activity is highly dependent on agricultural commodities involved in biofuel production. This paper tackles this issue by examining the price impact of biofuels on the current account for a panel of 16 developing and emerging countries, and the potential nonlinear effect exerted by the price of oil on this relationship. Relying on the estimation of panel smooth-transition regression models, we show that positive shocks in the price of biofuels lead to a current-account improvement for agricultural commodity exporters and producers only when the price of oil is below a certain threshold. When the price of oil exceeds this threshold, uctuations in the price of biofuels no longer affect the current account. These findings illustrate that a rise in the price of oil exerts a negative effect on the trade balance of commodity exporters which are also oil importers, dampening the biofuel price impact on the current-account position.

Given the few studies highlighting the existence of an oil-price effect on agricultural commodity prices in the last decade, we sought to demonstrate the role of first-generation biofuel production in such a relationship. Relying on a smooth transition cointegration approach, we show that biofuel development has led to an increase in the long-term price effect of oil on agricultural commodity prices. Thus, the increasing production of biofuels contributes to the price rise of agricultural commodities. This result underlines the importance of accelerating second-generation biofuel production to replace first-generation biofuels.

Given the few studies highlighting the existence of an oil-price effect on agricultural commodity prices in the last decade, we sought to demonstrate the role of first-generation biofuel production in such a relationship. Relying on a smooth transition cointegration approach, we show that biofuel development has led to an increase in the long-term price effect of oil on agricultural commodity prices. Thus, the increasing production of biofuels contributes to the price rise of agricultural commodities. This result underlines the importance of accelerating second-generation biofuel production to replace first-generation biofuels

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The aim of this paper is to study the ethanol price dynamics in the US market and find the optimal hedging strategy. To this end, we first attempt to identify the long-term relationship between ethanol spot prices and the prices of futures contracts on the Chicago Board of Trade (CBOT). Then, we model the short-term dynamics between these two prices using a Markov-switching vector error correction model (Ms-VECM). Finally, accounting for the variance dynamics using a Gjr-MGarch error structure, we compute a time-varying hedge ratio and determine the optimal hedging strategy in the US ethanol market.

The aim of this paper is to study the ethanol price dynamics in the US market and find the optimal hedging strategy. To this end, we first attempt to identify the long-term relationship between ethanol spot prices and the prices of futures contracts on the Chicago Board of Trade (CBOT). Then, we model the short-term dynamics between these two prices using a Markov-switching vector error correction model (Ms-VECM). Finally, accounting for the variance dynamics using a Gjr-MGarch error structure, we compute a time-varying hedge ratio and determine the optimal hedging strategy in the US ethanol market.

The aim of this paper is to investigate the long-term effect of the price of oil on agricultural commodity prices by accounting for the influence of biofuel production. Relying on the estimation of nonlinear, cointegrating regime-switching processes, we show that biofuel development has led to an increase in the oil-price effect on agricultural commodity prices: the growing production of biofuels is contributing to the price rise of agricultural commodities. This result underlines the importance of considering alternative biofuels which are not produced from agricultural commodities, and of analyzing the potential effects of the second-generation biofuels derived from agricultural plant residuals or non-food plants.