Measuring the Price Volatility of Certain Field Crops in South Africa using the ARCH/GARCH Approach

Jordaan, Henry; Grové, Bennie; Jooste, André; Alemu, A.G.

doi:10.1080/03031853.2007.9523774

Cited by 45 publications

(41 citation statements)

References 7 publications

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“…The Augmented Dickey Fuller (ADF) test is used for testing the stationarity of the price series of wheat and rice. Jordaan et al (2007), Karali & Power (2013), May (2010), Moledina et al (2004), Swaray (2007) and Yang et al (2001) estimated price volatility employing generalised auto regressive heteroscedasticity (GARCH/ARCH) technique. It is argued that by distinguishing predictable and unpredictable components of prices, these techniques provide accurate estimates of volatility.…”

Section: Price Volatilitymentioning

confidence: 99%

Price volatility trends and price transmission for major staples in India

Mittal¹,

Hariharan²,

Sasidharan³

2018

Agri. Econ. Rese. Revi.

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India is one of the largest producers as well as exporters of some major food commodities, and is often criticized for its protectionist measures to curb transmission of price shocks from international markets. This paper examines if such policies are necessary to protect domestic consumers from price fluctuations and what are their implications on international prices. To understand this, in this paper we have examined the patterns, trends and volatility in domestic and international prices of rice and wheat, and found that although both the international and domestic prices are volatile, the degree of volatility is higher in the international prices. The volatility in domestic prices is mainly due to internal production shocks and is not influenced much by the international prices. This disconnect is attributed to domestic policy measures, such as market support to farmers and public stockholding of food grains for public distribution and price stabilization.

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Section: Price Volatilitymentioning

confidence: 99%

Price volatility trends and price transmission for major staples in India

Mittal¹,

Hariharan²,

Sasidharan³

2018

Agri. Econ. Rese. Revi.

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“…Groenewald et al (2003) argue that the variability of input and product prices have increased since the deregulation of the agricultural commodities market in the mid 1990s. Jordaan et al (2007) compared price volatility of field crops that are traded on SAFEX (yellow maize, white maize, wheat, sunflower seed and soybeans). They found the volatility associated with the price of white and yellow maize to be substantially higher than that of other crops that are traded on SAFEX.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Maize Producers Adoption of Forward Pricing in Price Risk Management: The Case of Vaalharts

Jordaan¹,

Grové²

2007

Agrekon

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“…The estimates of equation (2) and (3) were used to test the persistence of volatility in the selected food crop in the study period. The GARCH approach has been used to study volatility in variables by many researchers (Moledina et al, 2003;Ghebrechristos, 2004& Jordaan et al, 2007. The model relied on the assumption of homoscedasticity -instead of considering heteroscedasticity as a problem to be solved.…”

Section: Measuring Food Crop Output Volatilitymentioning

confidence: 99%

“…Also, the mean food crop outputs showed a progressive growth rate across the policy programme periods since 1961, and were best during Post Structural Adjustment period (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). Jordaan et al, (2007) in South Africa, used standard error of the ARIMA process as the measure of volatility of prices of wheat and soybeans and found that volatility in the two crops was constant over time.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Dynamic Relationship between Food Crop Output Volatility and Its Determinants in Nigeria

Akpan¹,

Udoh²,

Umoren³

2012

JAS

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The study modeled the short run and long run food crop output volatility equations in Nigeria. Time series data derived from the FAO data base for Nigeria and publications of the CBN covering the period 1961 to 2010 was used in the study. Unit root test conducted on the specified time series shows that all series were integrated of order one at 1% probability level. The GARCH (1, 1) model was used to generate the food crop output volatility for the selected food crops (i.e. rice, maize, sorghum, cassava and yam). The short-run and long-run elastic cities of food crop output volatility with respect to specify explanatory variables were determined using the techniques of co-integration and error correction model estimation based on the OLS estimation. The empirical results revealed that inflation rate, per capita real GDP, loan guaranteed by ACGSF in the food crop sub sector, harvested area of land for food crop and liberalization policy era had mixed influence on food crop output volatility both in the short and long run periods in Nigeria. The result also showed that harvested area of land for the selected food crop was the most important factor that affects food crop volatility in the country. In addition, food crop volatility show an average declines pattern in the liberalization policy period. The study however advocated for appropriate short and long term policy packages that should addressed appropriately the identified significant macroeconomic shifters of food crop output volatility in the country. Also attention should be directed towards improving the quality of land allocated to food crop sub sector. Furthermore, agricultural policies in the liberalization policy package should be design in the short term basis and use as a means for altering food crop output in Nigeria.

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Measuring the Price Volatility of Certain Field Crops in South Africa using the ARCH/GARCH Approach

Abstract: The conditional volatility in the daily spot prices of the crops traded on the South

Cited by 45 publications

References 7 publications

Price volatility trends and price transmission for major staples in India

Price volatility trends and price transmission for major staples in India

Factors Affecting Maize Producers Adoption of Forward Pricing in Price Risk Management: The Case of Vaalharts

Modeling the Dynamic Relationship between Food Crop Output Volatility and Its Determinants in Nigeria

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