The Challenges of Sugar Market: An Assessment from the Price Volatility Perspective and its Implications for Romania

Available online at www.sciencedirect.com

ScienceDirect Procedia Economics and Finance 5 (2013) 605 – 614

International Conference on Applied Economics (ICOAE) 2013

The challenges of sugar market: an assessment from the price volatility perspective and its implications for Romania Larisa Nicoleta Popa*, Mihaela Rovinarub, Flavius Rovinaruc a,b,c

Faculty of Economics and Business Administration, Babes-Bolyai University Teodor Mihali Street, No. 58-60, 400591 Cluj-Napoca, Romania

Abstract Recently, the concerns regarding food and energy security, the threats brought by the global warming phenomenon, combined with the challenges that the commodity markets have faced since the beginning of the new millennium, have placed agricultural markets in the center of attention in both academic and policy spheres. In this revitalized awareness, a particular and fundamental role is played by sugar. The sugar market is far from being a peaceful and conventional one, bringing more challenges and unrest on its own. An unusual mixture of free and protected markets, special trade agreements and outstandingly volatile prices differentiate the trade of this product from other agricultural commodities. Historically, sugar has been one of the most volatile agricultural commodities, constituting a real challenge both for market participants and for policymakers to deal with its instability. In addition, with regard to domestic markets, sugar prices can differ substantially from country to country, generally registering higher levels than the world sugar prices. The Romanian economy manifests an increased responsiveness to external shocks, as a consequence of the processes it is traversing in the recent decades. The sugar market is consequently affected by the external instability while also facing other internal problems and challenges. The purpose of this paper is to analyze the particularities of the sugar market and their implications, by describing, modeling and analyzing the recent sugar price volatility on the Romanian market in comparison to the international one. After establishing the corresponding econometric models the paper compares the estimated conditional variance on the two markets, emphasizing the situation of the Romanian market and commenting on its implications. © Authors. Published by Elsevier B.V. B.V. ©2013 2013The The Authors. Published by Elsevier Selection peer-review underunder responsibility of the Organising CommitteeCommittee of ICOAE 2013 Selectionand/or and/or peer-review responsibility of the Organising of ICOAE 2013.

Keywords: price volatility; agricultural commodity markets; Romanian market; conditional variance; sugar market.

* Corresponding author. Tel.: +40.264 41 86 52; fax: +40.264 41 25 70. E-mail address: [email protected].

2212-5671 © 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the Organising Committee of ICOAE 2013 doi:10.1016/S2212-5671(13)00071-3

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1. Introduction Lately, the concerns regarding food and energy security at the global lever, combined with the threats brought by the global warming phenomenon through the alteration of the traditional weather patterns, have made agriculture once more a strategically significant sector worldwide and they placed it in the center of attention in both academic and policy spheres. Furthermore, the challenges that the commodity markets have faced since the beginning of the new millennium – the extensive and puzzling price boom from 2002 and until 2008, the further intensive and sudden collapse attributed to the installation of the global economic crisis, and the subsequent price swings in the context of the troubled global economic environment – augmented the concerns and opened new perspectives of analysis. In this revitalized awareness regarding the agricultural commodities, a particular and fundamental role is played by sugar. However, the sugar market is far from being a peaceful and conventional one, bringing more challenges and unrest on its own. An unusual mixture of free and protected markets, special trade agreements and outstandingly volatile prices differentiate the trade of this product from other agricultural commodities. Historically, sugar has been one of the most volatile agricultural commodities, constituting a real challenge both for market participants and for policymakers to deal with its instability. Price peaks similar to the ones registered in the recent years troubled the sugar market also in 1970s and 1980s. In addition, with regard to domestic markets, sugar prices can vary tremendously from country to country, generally registering higher levels than the world sugar prices. Due to its importance and unrest, the sugar sector is one that seems to require protection. Consequently, governmental interventions are a common practice. In the United States of America there have been established quotas and import tariffs on sugar imports, while in the European Union sugar market is under the Common Agricultural Policy (CAP) regulation. As the turbulences of the recent years have increased the world price instability, the European markets responded extensively to these shocks, as currently they are not as isolated from international price movements as they were in the past under more restrictive policy regimes. That is why European policymakers are paying an increased attention to price volatility. Due to its notorious instability, the moderation of price volatility on the sugar market, while preserving reasonable prices for both producers and consumers without creating supplementary pressures on the CAP budget, is not an objective easily to achieve. Like other Central and Eastern European countries, the Romanian economy manifests an increased responsiveness to external shocks, as a consequence of the processes it is traversing in the recent decades – the post-communist transformations, market externalizations, globalization and European Union integration. The sugar market is consequently affected by external instability while also facing other internal problems and challenges. The purpose of this paper is to analyze the particularities of the sugar market and its implications, by describing, modeling and analyzing the recent sugar price volatility on the Romanian market in comparison to the international one. The remainder of the paper is structured as follows. The second section presents an overview of the particularities of the sugar market and its recent developments. The third section offers a literature review of the main factors influencing sugar prices and the key determinants of their recent volatility. Further, the fourth section offers an empirical assessment of sugar price volatility both on the international and Romanian market, using the GARCH models to express the conditional variance. Consequently, this section offers a methodology description with an accent on the GARCH models and an empirical illustration in which the econometric models are applied for the analysis of the sugar price series on the Romanian market and at international level. Some conclusions and implications finalize the paper in the last section.

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2. An overview of the particularities of the sugar market and its recent developments The recent decades have represented for the global sugar economy a period of profound and unparalleled transformations determined by the processes of globalization, privatization and market externalization, European Union enlargement, combined with significant political transformations and increased awareness regarding the environment, food and energy security. The key features that marked this period can be summarized as follows (Baron, 2008): the emergence of Brazil as the major power on the sugar and ethanol market; the radical reform of the EU sugar policy; the increasing attention to environmental issues; the significant development of the emerging Asian economies; the necessity of developing alternative energy sources and the emergence of sugar crops as an energy supplier in the context of increased oil prices and geopolitical unrest; the extension of the refining industry and increased cross-border investments. Sugar is an omnipresent product, being consumed, more or less, in any place on earth. Derived from two distinct raw materials, sugar is produced under a wide range of climatic conditions in around 120 countries or territories. Sugar beet is grown in temperate regions and sugar cane in tropical and subtropical ones, with the sugar cane accounting for approximately 70% of total production of raw sugar (UNCTAD, 2004). Nevertheless, sugar trade has a strong regional character. The EU is supplied by Brazil, Eastern Europe and Former Soviet Union are supplied by EU and Cuba, while the Asian markets are supplied by Australia and Thailand (OECD, 2005, p.13). From the overall sugar trade, 40% is traded at world market prices, while the rest is traded under preferential and regional agreements, frequently with subsidies, and long-term contracts. Presently, the world’s biggest exporter of sugar is Brazil (45%), followed by Thailand (13.5%), Australia (5.6%) and India (4%). Brazil is a leading exporter since the 1970s, and it has consolidated its position in the 1990s, when its exports have increased rapidly in line with production. The biggest importers, nowadays, are the EU, accounting for less than 10% of world total imports, followed by Indonesia (6.5%), USA (6%), China and Malaysia with under 5% each. The European Union is an intriguing actor on the world sugar market. At the end of the 1970s, EU became a net exporter of sugar, mainly due to increased production and stable consumption, and maintained this position for a few decades. However, as a result of some substantial reforms, in 2006, the EU turned from a net exporter into a net importer. For a better understanding of this shift, here are a few considerations and facts about sugar reforms in the European Union. The EU sugar policy is built on three main elements: quota management, a reference price and a minimum guaranteed price to growers, and measures regarding trade. The policy, implemented since 1968, experienced in 2005 its first most important reform meant to deal with the increasing imbalance in supply and demand. The reform targeted the following instruments: intervention price cut, voluntary production quota buyout, and restrictions on non-quota sugar exports (Elbehri et al., 2008). The whole sugar production is split between some of the member states. First aspect of sugar reform concerned production quotas, which decreased 24 percent from 17.5 million tons to 13.3 million tons. The minimum sugar beet price was set to 26.29 euro/tone, with 39.5% lower than the previous one (43.45 euro/tone). Also intervention buying was eliminated. Thus, the number of EU beet sugar producing countries fell from 23 to 18 member states, making production more geographically concentrated. France, Germany, Poland and the United Kingdom are the biggest sugar producers accounting for 70 percent of sugar production, while others traditional producers, such as Italy, Spain, and Belgium produced significantly less sugar (European Commission DGAGR, 2011). Aggregate sugar production in the 27 member states averaged 21.930 million tons, between 1990 and 2006. After the reform, this fell by 25 percent to 16.727 million tons in 2008-2012. 3. The price of sugar and the major determinants of its volatility Unquestionably, the fundamental drivers of commodity price volatility differ from a commodity to another, but in general, sudden price movements are correlated with low elasticities of demand and supply in the short term (UNCTAD, 2008, p. 39). Besides, price fluctuations tend to have determinants that go beyond

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market fundamentals, adding to supply and demand numerous macroeconomic and geopolitical factors, a list nearly impossible to conclude if all the correlations and inferences were to be considered. The variations registered in market fundamentals do not necessarily reflect the extent of the price swings that have occurred over the past two decades and particularly in the recent years. In the case of sugar, production, following periods of high prices, tends to increase faster than consumption and is not responsive to downward price movements. There are some basic features of the crop and processing that contribute to this tendency. First of all, sugar cane is a semi-perennial crop that allows consecutive harvests (5-6 years) from an individual planting, so it does not respond to changing market conditions on the short term. That is why a cyclical price pattern is around six years in duration. Second, the very limited alternative crops may also contribute to slow production responses to lower sugar prices. Thirdly, the sugar beet and cane processors conduct highly capital-intensive operations and tend to take a long-term view of the market. So, they will continue to produce sugar even when the price is low, and any adjustments in production capacity will be delayed. Also, supply is very sensitive to weather. Even revisions in production estimates often cause significant adjustments in international prices. As most of the sugar trade and production is protected, and it takes place at subsidized or protected prices that bear little relation to international market levels, the role played by government support policies is another important factor in explaining the low responsiveness of sugar supplies. Such government support policies are not only used by EU or USA, as also many other countries like Russia, China, Thailand and India protect and regulate their domestic sugar industries (OECD, 2005, p. 31-32). The reforms introduced by the European Commission in 2003 have resulted in an improved yield for sugar beets and an increased efficiency in refining. Following, the EU production quotas were set at 13.3 million tones of sugar. Since the EU consumption is about 16.5 million tones, means that it lacks around 3.2 million tones of sugar annually (Menato, 2012). Therefore, imports from traditional partners but also from developing countries became an important component of the trade balance. The European Union shift puts much more weight on Brazil’s position on global sugar market. Consequently, any change in Brazil’s production affects the world prices which are also strongly correlated with Brazilian production costs. Another factor that influences the sugar price instability is the volatility in production cycles in some Asian countries that are large sugar-consuming markets. A common feature of China, Pakistan and India, that together account for over 25 percent of global sugar consumption, is production variability. These countries also account for 20 to 30 percent of global sugar production, depending on the year, but they are subject to volatile production cycles. Steadily growing consumption combined with volatile production causes large swings in net trade for the region. There is another factor that has a high influence on sugar price volatility, and this is the price of oil. There is a strong relation between sugar price volatility and the extremely volatile oil prices, because petroleum prices affect the domestic ethanol production derived from sugar beets, and, from here it affects world sugar price levels and price volatility (Haley and Polet, 2011). A reduced production of sugar, in Brazil for example, which is also the second largest ethanol producer, means less exports, so a smaller world supply, that will conduct to higher world sugar prices. Moreover, if ethanol uses are not in line with expectations, the sugar market becomes the residual variable causing enhanced volatility (Van Bekrum et al., 2005). Due to the fact that the share of raw sugar in international trade is higher than the one of white sugar, prices for raw sugar are more exposed to volatility than prices for white sugar. This aspect emphasizes the fact that the situation for the raw sugar is even more complicated from the viewpoint of price risk. After the significant volatility experienced in the midst of the global crisis, the world sugar market continues to experience considerable price volatility, especially after 2009. In 2010 there was a succession of peaks and downward corrections, as world sugar prices soared to a 29-year high of 661.36 USD/tone at the beginning of the year, while in summer they fell to half that level, but still remaining at 50% higher than their average over the past 20 years. The explanation for this resides in supply shortfalls tied to changing economic incentives, weather disruptions, and policy factors, also reflecting a more permanent fundamental

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shift in global market dynamics, as Brazil’s exchange rates and the role of ethanol in energy markets were putting upward pressures on global prices (McConnell, 2010). In February 2011, the world sugar prices reached a 30-year high level (USD 795.4/tone) due to large global sugar deficits in the previous two seasons and adverse weather that reduced the size of the expected rebound in production to higher prices, while world sugar stocks fell to their lowest level registered in the previous two decades, and supported higher and more volatile market prices (OECD-FAO, 2012). Also, the whole macroeconomic environment was weaker as the prices of energy and oil were rising (OECD-FAO, 2013). In 2011-2012, the global production of sugar shifted to surplus in response to recent higher prices, so sugar prices diminished in 2012 (Polet, 2012). With regard to domestic markets, sugar prices can differ extremely from a country to another, with the domestic prices generally registering much higher levels than world prices. According to recent estimates of the International Sugar Organization, domestic prices can reach values of about 2.5 times higher that the average world sugar price. In importing countries domestic prices can be even higher, with a further premium of 10% over average levels, while being about twice higher in beet producing countries than in sugarcane producers, possibly reflecting higher beet sugar production costs (Baron, 2008). Also their fluctuations can be more ample as they reflect both the instability absorbed from the world market and the internal tumult of the domestic market. 4. Empirical assessment of sugar price volatility – the international and Romanian market Due to Romania’s increased responsiveness to external shocks combined to its domestic instability and transformation, the sugar market is affected by imported volatility while also facing other internal challenges. In order to examine the Romanian sugar price instability, we chose to model the price volatility of sugar, both for the domestic and the international market, from January 2001 until December 2012. In order to reduce interferences in sugar market an empirically accurate measure of volatility is required, which accounts for the characteristics of this commodity and permits the forecast of future price developments. 4.1. Methodology The need for accurately assessing price volatility appears especially from the high level of risk and uncertainty it creates for producers, consumers and policymakers worldwide. The review of the econometric literature permitted the identification of several methods implemented for estimating price volatility, from rather simple ones (like unconditional standard deviation or the coefficient of variation) to more complex ones (such as the ARCH models). A series of limitations may be identified in the mentioned simple approaches, which cause an overstatement of uncertainty while calculating the volatility, by not distinguishing between predictable and unpredictable components of price series. Thus, the attention of the analysts has shifted towards more complex methods. The modeling of volatility in time series has been revolutionized by the introduction of the Autoregressive Conditional Heteroskedasticity (ARCH) models by Engle (1982) and their generalized form (GARCH) by Bollerslev (1986). In order to deal with all the modeling requirements of particular assets, several developments of the models have been formulated, as for example the multivariate GARCH models (MGARCH), meant to capture volatility spillovers across different markets, or the exponential ones (EGARCH), which also account for asymmetrical effects. Numerous authors, as for example Jordaan et al. (2007), Figiel and Hamulczuk (2010), Pop and Ban (2011), Apergis and Rezitis (2011), argue in favor of GARCH models on the grounds that they have the merit of accounting for both the predictable and unpredictable components in the price process, being also capable of capturing various dynamic structures of conditional variance and of allowing simultaneous estimation of several parameters under examination. The GARCH models and its extensions are commonly used in modeling stock market prices. With regard to commodity prices, Jordaan et al. (2007) measured and compared the conditional volatilities for the prices of some crops traded on the SAFEX; Figiel and

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Hamulczuk (2010) tested for conditional volatility analyzing monthly wheat prices in Poland; Apergis and Rezitis (2011) used GARCH and GARCH-X to examine food price volatility in Greece and the impact of macroeconomic factors, while Figiel et al. (2012) used weekly milling wheat price series for nine selected EU countries to evaluate volatility and to examine the sensitivity of the results to spatial aggregation of the data. Regarding the Romanian agricultural markets, Pop and Ban (2011) used EGARCH for modeling the price of wheat to estimate the price risk on Romanian and international market and Rovinaru et al. (2012) estimated and compared the price volatility on Romanian and international food market. To our knowledge, no previous analyses from the price volatility perspective have been made for the Romanian sugar market. In its general form, a GARCH (p,q) model includes two equations, one for conditional mean and one for conditional variance. The coefficients of ARCH-terms D i reveal the volatility of previous periods of time, measured with the aid of squared residuals from the equation of mean, and the coefficients of GARCH-terms E j show the persistence of passed shocks on volatility. For the price series we analyzed, the asymmetrical GARCH models performed better compared to the symmetrical ones, conclusion consistent also with the findings of Pop and Ban (2011). The extended asymmetrical model EGARCH also accounts for the leverage effect (different effect of positive and negative shocks) with the aid of the coefficient J i . For commodity markets, positive effects (good news) may be represented by favorable weather forecasts or supportive policies, while negative effects (bad news) may be devastating weather events or unexpected increases in oil prices. Consequently, the AR(k)-EGARCH(p,q) model that we used in our paper, elaborated by Nelson (1991), has the following structure, where the residuals from (1), H t , follow a GED distribution: k

(1)

S 0  ¦ S i ˜ X t i  H t

Xt

i 1

log V t2

§ H t i H t i  E¨ ¨V V t i © t i

p

Z  ¦D i ˜ i 1

(2)

q r · H t i ¸  ¦ E j ˜ log V t2 j ¸  ¦J l ˜ V l 1 j 1 t i ¹

4.2. Empirical results In our empirical assessment, we analyzed the evolution of price indices for Romanian sugar market, from the Romanian National Institute of Statistics (RNIS) and the corresponding ones at the international level, from the International Monetary Fund (IMF), Primary Commodity Prices database. We used monthly data between January 2001 and December 2012, in order to analyze as accurately as possible the recent developments, and we performed the analyses in Eviews 7.1. A series of steps required by the statistical analysis of the time series were initially implemented. We eliminated the seasonal component of the two series using the multiplicative moving average method. The graphs in Figure 1 show the sugar price evolution on the Romanian and international market, seasonally adjusted. 36

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Fig. 1. Sugar Price Indices Monthly Data from January 2001 – December 2012 (2005=100) (Source: Authors’ illustration in Eviews 7.1 based on data released by RNIS and IMF, 2013).

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Further, we operated with the logarithmic price ratios of the two series ( ln( Pt Pt 1 ) ), also called price returns (Figiel and Hamulczuk, 2010), due to their better statistical properties (Sironi and Marsella, 1997). The descriptive analysis of the sugar price return series, both on Romanian and international market, revealed that its volatility is not constant in time, indicating the presence of heteroscedasticity, aspect that makes the data appropriate for GARCH modeling. In order to detect the serial autocorrelation, we analyzed the ACF and PACF functions for a number of lags varying from 12, 24 to 36 and the calculated Q-statistics indicated the presence of this phenomenon. Based on descriptive statistics, we established that the log returns of sugar prices do not follow a Gaussian distribution. Further, we tested the non-stationarity of the time series, as they need to be stationary in order to not obtain spurious regressions. Table 1 presents the obtained results of ADF test, at the national and international level. For the logarithmic series, the calculated value of the t-Statistic shows that this series is not stationary. Consequently, we constructed the first order differences which proved to be stationary. Table 1. Testing the Non-Stationarity of Sugar Price Indices – Romanian and International Market Null Hypothesis: the series has a unit root t-Statistic LN_SUGAR_RO_SA -8.352105 LN_SUGAR_INT_SA -7.958763 *MacKinnon (1996) one-sided p-values.

Prob.* 0.8673 0.7235

t-Statistic -10.83131 -18.80986

DLN_SUGAR_RO_SA DLN_SUGAR_INT_SA

Prob.* 0.0000 0.0000

Source: Authors’ calculations in Eviews 7.1.

The next step was to estimate the models, the conditional mean and conditional variance, for both variables using the maximum likelihood. Based on the information criterion minimization (especially Schwarz) and on the residual test, we chose the appropriate number of lags, and we selected ombined models ARIMA-EGARCH with a GED distribution. For the Romanian sugar prices, we considered the most appropriate model to be the following (the z-Statistics and the probabilities are given in parentheses): d ln sugarRo , t

0.999 ˜ d ln sugarRo , t 1  0.430 ˜ d ln sugarRo , t  2  0.257 ˜ d ln sugarRo , t 3  H t [4.835]

[50.993]

[3.303]

(0.000)



log V

2 t

(0.000) (0.005) H t 1 H t 1 5.472  0.451 ˜  0.06 ˜  0.331 ˜ log V t21 V t 1 V t 1

(3)



[ 1.517] [1.602]

[ 0.410]

(0.000)

(0.006)

(0.011)

(4)

[ 0.726] (0.004)

For the international market, the appropriate model is: d ln sugarInt., t



log V t2



1.00 ˜ d ln sugarInt , t 1  0.559 ˜ d ln sugarInt , t  2  0.202 ˜ d ln sugarInt , t  6  0.193 ˜ d ln sugarInt ,t 10  H t [35.57]

[9.554]

[3.246]

[2.853]

(0.000)

(0.000)

(0.000)

(0.004)

H t 1 H 5.524  0.294 ˜  0.382 ˜ t 1  0.147 ˜ log V t21 V t 1 V t 1 [ 1.946] [ 0.895] (0.000)

(0.003)

[1.940] (0.005)

[0.356] (0.007)

(5)

(6)

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Based on the estimated equations, we generated the series of conditional volatility, in order to compare for the period January, 2001 – December, 2012 which of the two markets was more volatile. The results are given in Figure 2, both for the conditional volatility at the national and international level. 4.70

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Forecast: DLNSUGARROF Actual: DLNSUGARROSA Forecast sample: 2001M01 2012M12 Adjusted sample: 2001M06 2012M12 Included observations: 139 Root Mean Squared Error 0.022592 Mean Absolute Error 0.018246 Mean Abs. Percent Error 0.396300 Theil Inequality Coefficient 0.002453 Bias Proportion 0.001445 Variance Proportion 0.109568 Covariance Proportion 0.888987

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4.75 Forecast: LNSUG ARINSF Actual: LNSUG ARINSA F orecast sample: 2001M01 2012M12 Adjusted sample: 2001M12 2012M12 Included observations: 133 Root Mean Squared Error 0.035497 Mean Absolute Error 0.025744 Mean Abs. Percent Error 0.559077 T heil Inequality Coefficient 0.003853 Bias Proportion 0.000229 Variance Proportion 0.053417 Covariance Proportion 0.946354

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Figure 2. Sugar Price Volatility Monthly Data from January 2001 – December 2012 (2005=100) (a) Romanian Market; (b) International Market; (c) Merged Graphs – Romanian and International Market (Source: Authors’ calculations and illustrations in Eviews 7.1 based on data released by RNIS and IMF, 2013).

As illustrated in Figure 2, the estimated values of conditional variances show that at the beginning of the years 2000s the volatility on the Romanian market was at a similar intensity to the one at international level. However, in the two years prior to EU accession, which took place in January 2007, Romania’s sugar market experienced periods of significant price volatility, much more acute than the ones registered on the world market. Also, in 2008 and especially in 2009, there has been an increase of volatility on the Romanian market. Even though at the end of 2009 and beginning of 2010 the volatility seemed attenuated, the spring and summer of 2010 brought new volatility peaks in correlation with the ones signalized on the world market. While 2011 and 2012 brought a more peaceful period, the end of 2012 appears to bring new instability on the Romanian sugar market. After 2007, the Romanian market appears to be more influenced by the situation on the international one, joining the peaks generated by different world events. The major reason for this higher synchronization is most probably the fact that, joining the EU in 2007 and opening its markets, Romania became more receptive to international shocks. In 2010, the volatility on the Romanian market was acute, as a sign of the fact that Romania is currently experiencing more severely the consequences of the global crisis, it is highly affected by the turbulences in the euro aria and the sovereign debt crisis, while also facing a period of internal turbulences that deepen the domestic volatility context. Several reasons can be found at the basis of these price fluctuations. Analyzing the equations resulted for the Romanian market we observed that the

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current volatility depends both on passed shocks in the system and on the passed volatility. Thus, the current volatility context has its origins on the shocks and transformations Romanian market in general, and the sugar sector in particular, experienced in the recent period. Six years after joining the EU, the Romanian sugar sector is confronted with many difficulties whose effects are reflected on its performance and competitiveness. Compared to other Member States, Romania has a significant agricultural potential. However, the excessive fragmentation of parcels, which reduces productivity and discourages investments, cumulated with inadequate funding, are obstructing the achievement of an adequate level of performance that is necessary to cope with the increasingly competitive pressures (RCC, 2010, p. 31). Over the past two decades, this sector has experienced fluctuations in its development, owed to structural changes like privatization, restitution of land after the communist period, and other external influences and transformations due to the processes of market liberalization and the need of alignment to the requirements of the European Community. The Romanian producers have been highly affected by the production quotas imposed by the EU under the sugar reform regulations. Over the analyzed decade, 85% of Romania’s sugar requirements have been imported, particularly from EU, at a lower price than the domestic one. The domestic industry cannot cover demand due to low tariffs and tax-free imports, being unable to compete in price terms because of the relatively small size of its industry compared to major EU players. Regarding the agricultural potential, according to European Union statistics, in Romania, there are about 20.000 ha fields with sugar beet (European Commission DG-AGR, 2011), while the Romanian potential for sugar beet crops is about 150.000 ha. So Romania would have a great potential from this perspective, if the quota system would not be in place. Moreover, the total demand for sugar is around 500,000 tones, which Romanian producers would have the potential to satisfy with domestic resources. Despite that, Romania was the only country in Europe which needed to increase production to reach its quota set by the Commission in Brussels for 2007. The lack of investment capacity in the years prior to EU accession brought Romania in the impossibility to compete with the international players and the inability to meet the set production quota. As just a few companies had the financial capacity to modernize production, the market remains dominated by imports. If in the early 1990s, on the Romanian market were functioning 33 sugar beet processing factories, today only nine are active, as only the ones that have been purchased by foreign investors who had the capacity to invest in equipment and refurbishment have resisted on the market (Hagiu, 2012). Consequently, sugar market in Romania depends on international markets fluctuations and the prices set by the leading international exchanges, and also on European Union regulations. Because Romania imports more than two-thirds of raw sugar, it is extremely vulnerable to changes in price on foreign markets. More, as a full member of the EU, Romania has become part of CAP being requested to follow the principles and regulations the EU sets for its members. The share of white sugar from sugar beets, allocated to Romania is 104,688 tons and it is divided between the remaining plants in operation. Current quota system should have been valid until 2015, but the Committee on Agriculture of the European Parliament voted in late January 2013, five-year extension in sugar quota until 2020. 5. Conclusions The current volatility context has its origins on the shocks and transformations Romanian market in general, and the sugar sector in particular, experienced in the recent period, transformations that had a major effect on the efficiency of the sector and its international competitiveness. Despite Romania’s significant agricultural potential, the low productivity levels and inadequate funding are obstructing the achievement of an adequate level of performance that is necessary to cope with the increasingly competitive pressures. The increased imports and the need of alignment with the European Union requirements are the main reasons why the world and European market evolutions in the sector are directly felt on the Romanian market. Consequently, Romania’s current volatility context is a mixture between imported volatility, internal instability and lack of maturity of its market structures. As price volatility represents a very complex

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phenomenon that can be moderated only up to some extent by adjusting market structures and specifying regulatory and fiscal policies, and considering that for the sugar market these policies are not in Romania’s hand anymore as they depend on the EU and CAP regulations, Romania should concentrate on strengthening its internal potential of production in order to reduce the level of imported volatility, to reach at least the quotas established, while also dealing with the problem through price risk management strategies and consolidating internal futures markets. References Apergis, N., Rezitis, A., 2011. Food Price Volatility and Macroeconomic Factors: Evidence from GARCH and GARCH-X Estimates, Journal of Agricultural and Applied Economics, 43(1), p. 95-110. Baron, P., 2008. “Sugar – is the situation hopeless?” 4th Dubai Sugar Conference ‘Thinking Outside the Barrel’, 3-5 February, Dubai, United Arab Emirates. Bollerslev, T. 1986. Generalised autoregressive conditional heteroskedasticity. Journal of Econometrics, 51, p. 307–327. Elbehri, A., Umstaetter, J., Kelch, D., 2008. The EU Sugar Policy Regime and Implications of Reform, USDA Economic Research Report, 59, July. Engle, R. 1982. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflatio, Econometrica 50, p. 987-1006. European Commission, Agriculture and Rural Development DG, 2011. Statistics: Area under sugar beet, yield and production of sugar, available at: http://ec.europa.eu/agriculture/statistics/agricultural/2011/pdf/d03-1-43_en.pdf Figiel S., Hamulczuk M., Klimkowski C., 2012. Price volatility and accuracy of price risk measurement depending on methods and data aggregation: The case of wheat prices in the EU countries, 123rd EAAE Seminar, February 23-24, Dublin, Ireland. Figiel, S., Hamulczuk, M. 2010. Measuring price risk in commodity markets, Olsztyn Economic Journal, 5(2), p. 380-394. Hagiu, A., 2012. Costs management – essential factor for increasing the competitiveness of the Romanian sugar industry, Facultatea de management agricol- Lucrări ştiinţifice, XIV (1), p. 231-236. Haley, S., Polet Y., 2011. Post-Reform European Union Sugar - Prospects for the Future, USDA Foreign Agricultural Service, GAIN Report E60078, December 21. International Monetary Fund (IMF). 2012. Primary Commodity Prices Database. Jordaan, H., Grové, B., Jooste, A., Alemu, Z.G. (2007). Measuring the price volatility of certain field crops in South Africa using the ARCH/GARCH approach, Agrekon, 46(3), p. 306-322 McConnell, M., Dohlman, E., Haley, S., 2010. World Sugar Price Volatility Intensified by Market and Policy Factors, Amber Waves, 8(3), September. Menato, G., 2012. US/Turkey/EU: Understanding differences and crafting a way forward. The sugar case: EU, 31 st Annual Conference on US – Turkish Relations, 11 June, Washington, USA. Nelson, D.B., 1991. Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica, 59(2), p. 347-370. OECD, 2005. “An analysis of sugar policy reform and trade liberalization”, 54rd Session of the Joint Working Party on Agriculture and Trade, 6-8 April, COM/AGR/TD/WP(2004)54/REV, p.13. OECD-FAO, 2012. Sugar - Agricultural Outlook 2011-2020, Paris, available at: http://www.oecd.org/site/oecdfaoagriculturaloutlook/48184295.pdf OECD-FAO, 2013. Sugar - Agricultural Outlook 2012-2021, Paris, available at: http://www.oecd.org/site/oecdfaoagriculturaloutlook/sugar-oecd-faoagriculturaloutlook2012-2021.htm Polet, Y., 2012. EU-27, Sugar Annual Report, USDA Foreign Agricultural Service, GAIN Report E70018, April 27. Pop, L.N., Ban, I.M., 2011. Comparative Approach of Measuring Price Risk on Romanian and International Wheat Market, World Academy of Science, Engineering and Technology, Special Journal Issue 77, May, p. 512-517. Romanian Competition Council (RCC), 2010, The Challenges of the Single Market and the Competition in Sensitive Sectors, available at: http://www.consiliulconcurentei.ro/uploads/docs/items/id6479/the_challenges_of_the_single_market_and.pdf Romanian National Institute of Statistics (RNIS), 2012, Tempo On-line Database. Rovinaru, F., Rovinaru, M., Pop, L.N., 2012. Commodity Price Volatility in the Midst and Beyond the Economic Crisis – Implications for Romania, ICES 2012 Proceedings, Eldin Mehic (ed.), pp.264-276, 12-13 October, Sarajevo, Bosnia and Herzegovina. Sironi, A., Marsella, M., 1997. La misurazione e la gestione dei rischi di mercato: Modelli, strumenti e politiche, Il Mulino, Bologna. UNCTAD, 2004. “Commodity atlas – Sugar”, available at: http://unctad.org/en/docs/ditccom20041ch19_en.pdf UNCTAD, 2008. Trade and Development Report, Chapter II, Commodity Price Hikes and Instability, New York and Geneva. Van Berkum, S., Roza, P., Van Tongeren, F., 2005. Impacts of the EU sugar policy reforms on developing countries, Report 6.05.09, Agricultural Economics Research Institute (LEI), The Hague.