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South African Journal of Economic and Management Sciences

On-line version ISSN 2222-3436
Print version ISSN 1015-8812

S. Afr. j. econ. manag. sci. vol.13 n.2 Pretoria Jan. 2010

 

PRICING MODELS

 

Factors affecting forward pricing behaviour: Implications of alternative regression model specifications

 

 

H Jordaan; B Grové

Department of Agricultural Economics, University of the Free State

 

 


ABSTRACT

Price risk associated with maize production became a reason for concern in South Africa only after the deregulation of the agricultural commodities markets in the mid-1990s, when farmers became responsible for marketing their own crops. Although farmers can use, inter alia, the cash forward contracting and/or the derivatives market to manage price risk, few farmers actually participate in forward pricing. A similar reluctance to use forward pricing methods is also found internationally. A number of different model specifications have been used in previous research to model forward pricing behaviour which is based on the assumption that the same variables influence both the adoption and the quantity decision. This study compares the results from a model specification which models forward pricing behaviour in a single-decision framework with the results from modelling the quantity decision conditional to the adoption decision in a two-step approach. The results suggest that substantially more information is obtained by modelling forward pricing behaviour as two separate decisions rather than a single decision. Such information may be valuable in educational material compiled to educate farmers in the effective use of forward pricing methods in price risk management. Modelling forward pricing behaviour as two separate decisions is thus a more effective means of modelling forward pricing behaviour than modelling it as a single decision.

JEL: Q13


 

 

“Full text available only in PDF format”

 

 

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Accepted September 2009

 

 

End notes

1 Although Vaalharts has no SAFEX-certified silo, there is no reason why its absence should influence the adoption of hedging methods. At harvest, producers who hedged against price risk using a futures contract could sell their crops in the spot market, after which they could offset the futures position by buying back a similar futures contract prior to the delivery date.
2 The number of farmers initially drawn from the database was slightly higher than 78 to account for subject mortality (Strydom et al., 2003).
3 The fact that only 50 of the respondents actually did produce maize means that the number of respondents is lower than the suggested guidelines for sample size. By implication, the lower number of respondents may lead to possible bias in the results, which may have a negative influence on the ability to generalise the results obtained to the general population of irrigation farmers in Vaalharts. By implication, the results could also not be generalised to be representative of maize farmers in South Africa.
4 Initially the Tobit model specification was compared with a logit and OLS regression model specification. The observation by the editorial board that the Tobit model specification assumes an underlying Probit model led to the adoption of the Cragg model specification.
5 We are grateful to an anonymous reviewer for pointing out the importance of considering production finance requirements on the forward pricing behaviour of farmers.

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