Empirical findings

We start this section by illustrating how the spillover index proposed in (6) is built. As mentioned before, we estimate spillover indices for 158 consecutive sub-periods of 60 months. We use ten-month ahead (H=10) forecast errors to decompose the variances in own and cross impacts. Since most of the international trade of agricultural commodities is done in US dollars, its variations (appreciation/depreciation) not only affect the amount but also the direction of the trade flows. To control for the effects of exchange rate, which could potentially preclude spillover dynamics, we consider the (US) Dollar Index volatility as an exogenous component in the VAR systems.

Table 4. Variance decomposition matrix, Ethanol Group

Source: Own elaboration.

Table 4 presents the variance decompositions for the Ethanol Group considering average values of the 158 windows. Columns show the contribution of individual commodities to the forecast error variances of the remaining ones. For instance, the first column describes how innovations in oil impact on sugar (0.32), corn (0.39) and wheat (0.27). Since our interest is in cross ‘spillover’ effects we don’t consider the diagonal elements of the matrix. In total, the contribution of oil volatility to ethanol feedstocks is 0.97. Rows, on the other hand, provide information on how much volatility a particular commodity receives from other markets. In the case of oil, sugar contributes with 0.13, corn with 0.35, and wheat with 0.10. The spillover index then corresponds to the total transmissions or receptions (without own effects) divided by the full matrix (3.7/40). In the case of the Ethanol Group, its average spillover index is, on average, 9.2%, whereas for the Biodiesel Group the index is 11.4%.

Figure 6 depicts the development of the volatility spillovers among oil and the corresponding ethanol and biodiesel feedstocks. The thinner lines represent index estimates without considering the dollar exchange rate volatility. One can observe for

Figure 6. Volatility spillover index evolution for the ethanol and biodiesel groups

Source: Own elaboration.

Note: Dotted arrows describe the trending behaviour of the index series.

instance, that for vegetable oils the spillover index was unaffected by exchange rate volatility until September 2008, when the financial crisis started. After this point, exchange rate effects might have induced more volatility spillovers among vegetable oils and between vegetable oils and oil. In the case of ethanol feedstocks, the exchange rate effects are present before and after the crisis outbreak. In the pre-crisis episode volatility spillovers were underestimated, while after the crisis, exchange rate volatility of US dollar-denominated trade might have provoked more volatility transmission among sugar, cereals and oil. In general, the indices (controlling for US exchange rate volatility) remain between 5% and 10% for the pre-crisis period. The biodiesel index started an upward trend at the beginning of 2005, which accelerates between 2011 and 2012. At the end of 2012 it reached a maximum spillover level of 24%. Since then, it falls back to pre-crisis levels close to 10%. The spillover index for ethanol feedstocks is in general lower, reflecting more stable cereal and sugar markets. It grew moderately during the first decade (1996-2006). However, between 2003 and 2008 the ethanol index became temporarily larger by around 3% (on

average). Until 2010 this index followed a downward trend, which reverted between 2011 and the first semester of 2013.

Table 5. Relative average contributions to the spillover index, Ethanol Group

Source: Own elaboration.

Note: Numbers in this table represent shares of the spillover index.

To reveal the contributions of the different commodities to the spillover index, as well as to other markets, Table 5 presents the variance-covariance matrix for the Ethanol Group. Its values are expressed as shares of the total spillover index. For instance, oil’s volatility transmission to other markets represents 26% of total group spillovers.

We can also observe that oil is a net volatility transmitter. Its contributions to agricultural markets (26%) are larger than its volatility receipts from them (16%).

Similar to oil, sugar and corn markets are net volatility transmitters. Wheat, on the other hand, remains the only volatility receptor of the group. One can also observe that ca. 58% of the spillovers originate in agricultural markets.

Figure 7. Relative contribution of oil to the spillover index, Ethanol Group

Source: Own elaboration.

To illustrate the development of oil’s contribution to the spillover index, Figure 7 shows a comparison of the volatility spillovers from oil to the three ethanol feedstocks

considered. One can observe in this graph that oil spillovers to corn, wheat and sugar markets reach similar important peak values in different periods. During the third quarter of 2003, for instance, spillovers to wheat represent 27% of the spillover index.

Between 2007 and 2008 oil’s volatility spillovers to corn and sugar attain similar levels. After 2011, however, oil spillovers to agricultural markets decline, while the spillover index rise. This suggests more volatility dynamics across agricultural markets than between these markets and oil.

Table 6. Relative average contributions to the spillover index, Biodiesel Group

Source: Own elaboration.

Note: Numbers in this table represent shares of the spillover index.

Table 6 displays the individual volatility contributions among the commodities which make up the Biodiesel Group. In this case, oil’s volatility transmissions to agricultural markets are smaller (21%). Accordingly, much of the volatility spillovers derive from vegetable oil markets (74%). Although oil remains a net volatility transmitter, the volatility spillovers received from agricultural markets (6%) are almost three times smaller than for the case of cereals and sugar (16%). This is partially explained by the low integration of rapeseed oil to international markets. Besides oil, soybean oil, and rapeseed oil are also net volatility transmitters. Palm oil, on the other hand, is the only net volatility receiving market. Based on empirics, we established the following causality order for this group: oil, soybean oil, rapeseed oil and palm oil.

Consequently, it is not surprising that palm oil is the major volatility receptor as is the case of wheat in the ethanol group.

Figure 8 depicts the evolution of the spillovers from oil to vegetable oils. Oil’s spillover contributions to vegetable oils range, on average, between 6% and 8%. In August 2002, however, there was a large volatility spillover episode to the soybean oil market representing 36% of the spillover index alone. Between 2007 and 2008 the remaining vegetable oils were particularly volatile, reaching values between 20% and 35%. However, their influence in the spillover index declined rapidly and remained

Figure 8. Relative contribution of oil to the spillover index, Biodiesel Group

Source: Own elaboration.

mostly close to or below 10% after 2008. Since the beginning of 2009 volatilities originating and spilling over to agricultural markets are responsible for the largest share of the spillover index, suggesting a minor role of oil during this period.

3.6 Conclusions

Biofuel production is mainly driven by political decisions in developed (and to an increasing extent, in developing) countries, which assign large budgets to promote the ethanol and biodiesel industries as a way to reduce greenhouse gases and manage their grain surpluses.

While ethanol production is concentrated around two countries (the US and Brazil) and two major feedstocks (corn and sugar cane), biodiesel is more evenly distributed (Germany, France, US, Argentina and Brazil). Although biodiesel feedstocks are more diverse, they have low productivities, with the exception of palm oil.

Comparatively, ethanol feedstocks are more productive. Owing to the generous support given to biofuels, between 1991 and 2011 ethanol and biodiesel production grew at an average annual rate of 9% and 67%, respectively. However, due to the low energy density of agricultural commodities as compared to fossil fuels, the degree of substitution of oil-based liquid fuels by biofuels has been negligible and at the expense of large amounts of foodstuffs. This in turn has destabilised agricultural markets.

Until September 2008, the levels of volatility spillovers in the Biodiesel Group remained unaffected when controlling for the effect of the US dollar exchange rate

volatility. Conversely, during this period, volatility spillovers in the Ethanol Group appeared to be overestimated. During the post-crisis period, however, exchange rate volatility might have induced more volatility in both groups amplifying the connection among markets.

The Ethanol Group shows a cyclical pattern with alternating periods of high and low volatility transmission among markets before, during and after the financial crisis.

The Biodiesel Group displayed a more persistent development. It started an upward trending behaviour at the beginning of 2005, which accelerated between 2011 and 2012, and declined abruptly subsequently. Although the average spillover index for the Ethanol Group is lower (9.2%) if compared to the Biodiesel Group (11.4%), oil’s contribution to ethanol feedstocks is comparatively larger (26%) than for biodiesel feedstocks (21%). This situation denotes a closer relation between oil and cereals/sugar. However, since 2009 oil’s contribution to both indices decline, suggesting larger risk transmissions among agricultural markets and a secondary role of oil.