TESTING INTERNATIONAL PRICE TRANSMISSION UNDER ...

Empirical Tests for Spatial Price Analysis
the price response to disequilibria may take several periods to be complete
(Goodwin et al. 1999, p.177), as delivery lags and other impediments to arbitrage
and trade exist.
IRFs have been interpreted as both dynamic disequilibrium adjustments (which
is justified only if shocks are serially uncorrelated) and equilibrium adjustments to
ongoing changes in the economic fundamentals. If price data alone are available,
due to identification problems it is difficult to decide which interpretation is
correct (Fackler and Goodwin 2001, p.1004). In either case, shocks must be given
an economic interpretation: a standard practice is to assume that the shocks are
uncorrelated and that, in equation (3.7), A0 is triangular, implying that prices form
a causally recursive system; this means that shocks on some prices have no effect
on the others. Unfortunately, not only is this assumption untestable and rather
strong, but it is like imposing a priori inefficiency on the market, while wanting to
study it. Finally, for agricultural commodities, it must be noticed that seasonal
differences (like those originating form different harvesting times in the two
hemispheres of the world) may lie behind different pattern of responses
(Margarido et al., 2004).
3.2.2.4 Cointegration analysis
Starting from the seminal work of Ardeni (1989), cointegration techniques
soon had an intuitive appeal for the study of price transmission mechanisms.
Indeed, commodity price time series are often I(1) (integrated of order 1), which
need to be differentiated before becoming stationary. Cointegration models
presuppose that variables exhibiting nonstationary behaviour will nonetheless be
linked by a long run relation, whose residuals are stationary. In this case, the latter
is nothing but the LOP, which is expected to hold in the long-run despite short-run
price variations.
As it is this methodology which will be adopted for the empirical estimates of
this work, cointegration techniques will be extensively dealt with in paragraph
3.3.
3.2.3 Switching regime models
Switching regime models provide estimates of being in one of different trade
regimes, determined on the basis of information on prices and transport costs.
Indeed, conventional tests that rely on price data alone normally fail to recognize
the role played by transport costs (see paragraph 3.4). Sexton et al. (1991), by
using information on trade flows, study a market which is linked by unidirectional
trade and develop a switching regime model in which arbitrage conditions may be
violated; transport costs are estimated endogenously. The three regimes are
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