dc.contributor.author |
Balcilar, Mehmet
|
|
dc.contributor.author |
Chang, Shinhye
|
|
dc.contributor.author |
Gupta, Rangan
|
|
dc.contributor.author |
Kasongo, Vanessa
|
|
dc.contributor.author |
Kyei, Clement Kweku
|
|
dc.date.accessioned |
2017-06-08T06:56:04Z |
|
dc.date.available |
2017-06-08T06:56:04Z |
|
dc.date.issued |
2016 |
|
dc.description.abstract |
The increase in agricultural commodity prices in the recent past has renewed interest in ascertaining
the factors that drive agricultural commodity prices. Though a number of factors are possible, higher
oil prices are thought to be the major factor driving up agricultural commodity prices, especially as
the demand for biofuels production increases. However, empirical evidence of this relationship
remain ambiguous and largely depends on the method used. For this reason, there is a need to
examine the relationship in the context of different methodologies. Furthermore, information on how
South African commodity prices respond to world oil price shocks is less certain. A good
understanding of the factors that drive local commodity prices will assist in making sound
agricultural policies. In this paper, the Granger causality test is applied to the mean to investigate the
causality between oil prices and agricultural (soya beans, wheat, sunflower and corn) commodity
prices in South Africa. Daily data spanning from 19 April 2005 to 31 July 2014 is used for Brent
crude oil, corn, wheat, sunflower and soya beans prices. Agricultural commodity prices were
obtained from the Johannesburg Stock Exchange, and the series of Brent crude oil prices from the
U.S. Department of Energy. Results from the linear causality test indicate that oil prices do not
influence agricultural commodity prices. However, owing to structural breaks and nonlinear
dependence between the variables of study, these results are misleading. As an alternative, the
nonparametric test of Granger causality in quantiles, as proposed by Jeong, Härdle and Song (2012)
is used. Through this test, we not only look at causality beyond the mean estimates but also accounts
for the structural breaks and nonlinear dependence present in the data. Additionally, the method
becomes more instructive in the case where the distribution of variables has fat tails. The findings
show that the effect of changes in oil prices on agricultural commodity prices vary across the different
quantiles of the conditional distribution. The highest impact is not at the median, and the impact on
the tails is lower compared to the rest of the distribution. The analysis shows that the relationship
between oil prices and agricultural commodity prices depends on specific phases of the market, and
therefore contradicts the neutrality hypothesis that oil prices do not cause agricultural commodity
prices in South Africa. This implies that policies to stabilize domestic agricultural commodity prices
must consider developments in the world oil markets. |
en_ZA |
dc.description.department |
Economics |
en_ZA |
dc.description.librarian |
am2017 |
en_ZA |
dc.description.uri |
https://muse.jhu.edu/article/624657 |
en_ZA |
dc.identifier.citation |
Balcilar, M, Chang, S, Gupta, R, Kasongo, V & Kyei, C 2016, 'The relationship between oil and agricultural commodity prices in South Africa : a quantile causality approach', Journal of developing Areas, vol. 50, no. 3, pp. 93-107. |
en_ZA |
dc.identifier.issn |
0022-037X (print) |
|
dc.identifier.issn |
1548-2278 (online) |
|
dc.identifier.other |
10.1353/jda.2016.0117 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/60921 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Tennessee State University College of Business |
en_ZA |
dc.rights |
Tennessee State University College of Business |
en_ZA |
dc.subject |
Granger causality |
en_ZA |
dc.subject |
Nonparametric kernel |
en_ZA |
dc.subject |
Quantile causality |
en_ZA |
dc.subject |
Commodity prices |
en_ZA |
dc.subject |
South Africa (SA) |
en_ZA |
dc.title |
The relationship between oil and agricultural commodity prices in South Africa : a quantile causality approach |
en_ZA |
dc.type |
Article |
en_ZA |