International prices of major crops rose dramatically from late 2006 through mid 2008. Price collapsed dramatically in the second half of 2008 with the onset of the financial crisis. This episode is often referred to as the “2008 agflation”. It seems that such a price swing appears again. Between early June 2010 and February 2011, the price of grain increased sharply, surpassing the 2008 peaks that had spread anxiety among policymakers and low income consumers around the world.
A number of studies have discussed the factors which lie behind the 2008 agflation. A large number of potential explanation is avaliable. Those given greatest prominence are i) rapid economic growth, particularly in China and other Asian economies, ii) decades of underdevelopment in agriculture, ⅲ) low inventory levels, iv) depreciation of the US dollar, v) speculative influences.
However, there is still in debates of whether grain prices have become more variable. When looked at in the long term, there is little or no evidence that volatility in international agricultural commodity prices, as measured using standard statistical measures is increasing and this finding applies to both nominal and real prices. Volatility has, however, been higher during the decade since 2000 than during the previous two decades and this is also the case of wheat and rice prices in the most recent years (2006~2010) compared to the nineteen seventies.
To answer a basic question has grain price volatility risen? this study sets up GARCH (Generalized Autoregressive Conditional Heteroscedasticity)-type models and measures exact volatilities for rice, wheat, corn, and soybeans, which are important for food security of net food importing countries. The GARCH model is now the standard procedure for modelling volatility in financial markets. GARCH specifies an ARMA (AutoRegressive Moving Average) process for the variance scedastic process followed by a time series to yield an estimate of the conditional variance of the process at each date in the sample. To summarize, this analysis has generated three conclusions;
a) International rice and wheat price volatility was generally higher over the past two decades than in the nineteen seventies and eighties, the major exception being soybean.
b) Although many grains exhibited high volatility over three year periods 2006-08, and this volatility persists to the present, these volatilities are generally in line within historical experience, except rice.
c) There is weak evidence that volatility levels may be increasing relative to historical levels across the grains. However, we will need to wait for a few more years to now whether this is indeed the case
There is also considerable empirical evidence that the volatility in agricultural prices has changed over the recent decade. It is not only the levels of prices which have had powerful effects, but also their volatilities. Increasing volatility is a concern for agricultural producers and for other agents along the food chain. Price volatility can have a long run impact on the incomes of many producers and the trading positions of countries, and can make planning production more difficult. Moreover, adequate mechanisms to reduce or manage risk to producers do not exist in many markets and/or countries. Therefore, an understanding the nature of volatility is required in order to mitigate its effects, particularly in developing countries.
In order to examine the nature and determinants of volatility in food crops, this study sets up both the dynamic panel model and the system equation models. The dynamic panel regression approach is useful for catching a number of key variables which can explain grain volatility as a whole, while the system equation approach has advantages of considering the interrelation among each crop. The results of the analysis can be summarized as following.
There is convincing evidence that many of the candidate variables have an impact on grain volatility. Inventory-use ratios have significant effects on grain volatility, being negatively affected. For some individual commodities, the relationship does appear to be stronger, with wheat the clearest example. Oil price volatility has a positive impact on grain price volatility. Thus, the recent coincidental high volatility in oil and grain prices is symptomatic of a connection between grain price volatility and oil price volatility. The link between oil prices and grain prices is likely to arise through the impact of energy prices on the costs of production, along with the alternative use of some crops for biofuel production. Therefore, we would expect the link between oil price volatility and grain prices to continue or strengthen as the biofuels sector grows. Likewise, exchange rate volatility was found to influence the volatility of agricultural prices. Thus, perhaps unsurprisingly, if the global economy is experiencing high levels of volatility these will also be reflected in agricultural prices.
Higher inflation volatility tends to increase grain price variation. The sensitivities vary quite widely across commodities, but in most cases the relationship is highly significant. Higher levels of the U.S. inflation, also have a consistent impact to most gains, being significantly and positively affected. Higher futures market volumes increase the volatility in grains. The effect is statistically significant, but economically small.
Policy options to reduce the grain price volatility

a) Emergency food reserves
Relatively smaller food security emergency reserves can be used effectively and at lower cost to assist the most vulnerable. Unlike buffer stocks that attempt to offset price movements and which act as universal subsidies benefiting both poor and non-poor consumers, emergency food reserves can make food available to vulnerable population groups in times of crisis. In addition, emergency reserves of relatively small quantities of staple foods will not disrupt normal private sector market development which is needed for long term food security.

b) International safety nets
In times of crisis, contingent and compensatory financing facilities are important mechanisms assisting countries to avoid major fiscal deficits, and lower the cost of imported food, while maintaining key social assistance programmes. The World Bank is currently helping countries deal with the food crisis through instruments to help manage short-term impacts, including grant funding for rapid response in the poorest and most vulnerable countries and expedited use of International Development Assistance (IDA) and International Bank for Reconstruction and Development (IBRD) funds under programs such as the Global Food Crisis Response Program (GFRP), as well as increased Regular IDA and IBRD lending, policy advice and technical assistance.

c) Risk management for governments
For price risks, the principal instruments that could be used to manage the price volatility of food import bills are futures and options contracts (financial instruments) or over the-counter (OTC) contracts (physical instrument). The main difference between them is that financial instruments can provide a country with a cash payout to enable them to offset higher food prices for physical imports, whereas physical instruments seek to manage price and supply risk and provide for the physical import of the food. Both types of instruments are offered by financial institutions and traders.
By buying futures contracts, a government which wishes to protect itself against a possible grains price surge “locks” in a price agreed at the time the contract was concluded. With futures contracts the country will obtain greater certainty over the price, but not flexibility. Call option contracts “lock” in a maximum price, but with no obligation to buy at that price if market conditions are favourable for the government (i.e. if prices have moved lower). The country will still be able to benefit from lower prices after the agreement, as they do not have to purchase at the agreed price. This approach provides certainty about a maximum price and flexibility.
Significant investment is needed to overcome the lack of technical expertise on the use of these instruments in developing countries. Experience has shown that engaging developing and emerging countries on risk management takes a sustained effort to build capacity to the point where decision-makers are comfortable with the use of risk management tools. Globally there is a need to learn lessons from countries such as Mexico that have become sophisticated in developing a framework for analyzing risks and taking innovative steps to manage those risks.
Finally, it is important to recognize that there is no single risk management tool that will meet the diverse needs of countries exposed to price volatility, particularly given the complexity of local market and policy environments. Solutions need to be highly customized, drawing on a mix of different tools and responses. A successful approach to strengthening risk management frameworks in low income countries will need to build on existing capacities, create platforms which allow private sector market participants to be part of the solution, and find ways to overcome the major constraints to greater use of risk management tools: weak legal/regulatory frameworks, poor credit standing, and a lack of knowledge, understanding, and confidence about how to use these tools.

서언

국문요약

제1장 서 론
1. 연구의 배경과 목적
2. 연구 방법
3. 연구 내용과 구성

제2장 국제곡물시장의 특징과 가격의 동태적 변화
1. 국제 곡물시장의 특징
가. 대표적인 엷은 시장(thin market)
나. 국제곡물시장 구조의 취약성: 공급자 과점시장
2. 국제곡물가격의 동태적 변화
3. 가격변동성 증가 가능성

제3장 국제곡물가격의 변동성 계측
1. 가격 변동성의 개념과 계측방법
2. 가격 변동성 계측을 위한 모형 설정
가. 변동성 측정을 위한 시계열 모형 검토
나. 자료 및 기초 통계량
다. 모형의 선별
3. 가격변동성 계측 결과

제4장 국제곡물가격의 변동성 요인분석
1. 변동성에 영향을 주는 요인 검토
가. 농업 내부 요인: 곡물의 수급 요인
나. 농업 외부 요인
2. 변동성 요인분석을 위한 모형 설정과 추정
가. 동태패널 및 연립방정식 모형 설정
나. 추정
3. 추정 결과 및 정책 시사점
가. 추정 결과
나. 정책 시사점

제5장 국제곡물가격의 변동성 파급영향 분석
1. 국내 수입곡물가격과 국제곡물가격 간의 관계
2. 국내 수입곡물가격의 변동성 계측과 분석자료의 안정성 검증
가. 수입곡물가격의 변동성 계측
나. 계측된 변동성 자료의 안정성 분석
3. 벡터자귀회귀모형(VAR)의 설정과 추정
가. VAR 모형의 설정
나. 모형의 추정과 예측오차 분산분해

제6장 가격변동성 완화를 위한 국제협력과 국내 대응
1. 변동성 완화를 위한 국제협력방안과 한국의 역할
가. 기존에 제시된 국제협력방안의 검토
나. 한국의 역할
2. 국내의 정책적 대응
가. 조기 경보시스템 구축
나. 선물과 옵션의 활용
다. 직접구매방식

제7장 요약 및 정책제언
1. 요약
제2장 국제곡물시장의 특징과 가격의 동태적 변화
제3장 국제곡물가격의 변동성 계측
제4장 국제곡물가격의 변동성 요인분석
제5장 국제곡물가격의 변동성 파급영향 분석
2. 정책 제언
가. 국제협력방안
나. 국내 대응

참고문헌

부록

Executive Summary