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Threshold effects in price transmission: the case of Brazilian wheat, maize, and soya prices.


by Balcombe, Kelvin^Bailey, Alastair^Brooks, Jonathan

The support for the Band-TAR specification, with overshooting of the threshold limit from out-of-threshold episodes, over the Eq-TAR specification was unanimous in this study. However, this result was curious in that the posterior mass of the parameter [theta] was weighted toward unity even when adjustment was ostensibly symmetric in both equations in the case for the Brazil-U.S. wheat and Brazil-Argentina maize price pairs. While this finding is weakly indicative of a threshold model it does raise the awkward question of what this result means in these two cases? It is, of course, possible that there is some other form of nonlinearity or structural break that is responsible for the apparent existence of thresholds. This contention was supported by the timing of movements inside and outside of the threshold in the case of the Brazil-U.S. wheat price pair. In this case, the conclusion of Mercosur, institutionalizing a free trade agreement among member states, in 1995 may have reinforced the tendency for Brazil to obtain its wheat imports more or less exclusively from Argentina, and weakened price transmission from the United States. The ambiguous result for maize is less easy to explain but may be either a result of the relatively small volumes traded across Brazil's boarders or that the Mercosur agreement was effective at reducing transactions costs between South American countries at a time when Brazil switched from being a net importer to a net exporter of this commodity.

We are grateful for the suggestions and helpful comments of two anonymous referees and the constructive criticisms and encouragement of the editor, Wade Brorsen, during the preparation of this article. Any remaining errors are the authors'.

[Received April 2004; accepted May 2006.]

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(1) For the case of a trade flow from country B to country A, rearrange the superscripts.

(2) Balke and Fomby (1997) also consider a further model, the RD-TAR or returning drift threshold model, which has a unit root in each regime and uses the drift parameters to restore "equilibrium." From without, attraction is to the outer band rather than a central equilibrium point. However, we do not consider this model here.

(3) The author has developed algorithms along the lines of those suggested in Hansen and Seo (2002). However, Hansen and Seo's methods are highly model specific and we have not been able to generalize their methods to accommodate the more general TAR specification of Model III.

(4) Deterministic trends, seasonality, etc., may play a role, but we ignore these in the current exposition since they complicate but do not undermine the points being made.

(5) From here on, we use the terms "symmetry" and "asymmetry" to denote differential within and without threshold response, rather than differential upward and downward price adjustment, since our model is restricted to the symmetric case of the latter.

(6) Details of all of these tests can be found in Maddala and Kim (1998).

(7) These are nearly identical to a posterior mean from nonthreshold models.

Kelvin Balcombe is lecturer in the Department of Agricultural and Food Economics Department, in the School of Agriculture, Policy and Development at the University of Reading, U.K. Alastair Bailey is honorary senior lecturer and senior lecturer in Agricultural Economics at Imperial College, London, Wye Campus & University of Kent, U.K., respectively, and Jonathan Brooks is senior economist at the OECD, Paris, France. Table 1. Unit Root Tests for Monthly Wheat, Maize and Soya Prices, by Country, May 1988 to May 2001, August 1986 to May 2001, and May 1988 to April 2001, Respectively

With Time Trend Commodity/Country ADF PP KPSS LMc Wheat: Brazilian -2.78 -2.54 0.098 3.27 ** Argentine -2.55 -2.28 0.086 1.02 ** U.S. -1.89 2.04 0.097 1.73 ** Maize: Brazilian -2.33 -2.01 1.54 0.31 ** Argentine -2.96 -2.53 0.157 1.60 ** U.S. -2.25 -1.88 0.119 1.79 ** Soya: Brazilian -2.38 -2.19 0.08 9.07 ** U.S. -2.18 -1.73 0.08 1.56 ** Critical 5 % -3.41 0.463 Values 10% -3.12 0.347

Without Time Trend Commodity/Country ADF PP KPSS LMc Wheat: Brazilian -2.75 -2.52 0.108 0.68 ** Argentine -2.55 -2.3 0.078 1.05 ** U.S. -1.52 -1.41 0.224 ** 1.71 ** Maize: Brazilian -2.41 -2.12 0.145 * 0.25 ** Argentine -3.04 ** -2.12 * 0.134 * 1.15 ** U.S. -2.47 -2.02 0.144 * 1.79 ** Soya: Brazilian -2.38 -2.22 0.09 1.31 ** U.S. -2.07 -1.36 0.19 ** 8.78 ** Critical 5 % -2.86 0.119 Values 10% -2.57 0.146 Note: * and ** denote significance at the 5% and 10% levels, respectively. Also note that the ADF and PP and the KPSS and LMc share the same critical values, respectively. Table 2. Johansen ML Tests for Cointegration between Commodity Price Pairs

Number of Commodity/ Cointegrating Price Vectors Null Pair versus Actual Eigenvalue Wheat/Brazil 0 versus 1 21.58**

versus 1 versus 2 6.25


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COPYRIGHT 2007 American Agricultural Economics Association Reproduced with permission of the copyright holder. Further reproduction or distribution is prohibited without permission.
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NOTE: All illustrations and photos have been removed from this article.


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