TESTING INTERNATIONAL PRICE TRANSMISSION UNDER ...

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Empirical Tests for Spatial Price Analysis Unidirectional causality between two prices can be seen as informational inefficiency, since the second price is not incorporating the information coming from the first one, and its values could be predicted on the basis of those of the second one (see, for example, Gupta and Mueller 1982, p.303). Nonetheless, as Fackler and Goodwin point out (2001, p.998), the dynamics in the price adjustments, owing for example to delivery lags, could make this assumption questionable. GC analysis, together with IRFs (see paragraph 3.2.2.3) often accompanies dynamic model studies in empirical works. 3.2.2.2 Ravallion and Timmer market integration criteria Ravallion’s model, as presented in his original article (Ravallion 1986), builds up a radial structure with a central market and other satellites ones. Together with the Timmer model (which, as explained further in this paragraph, directly stems from Ravallion’s one), it can be interpreted as a VAR model with tests of restrictions on the reduced-form parameters of the model (Fackler and Goodwin 2001, p.1000). Ravallion’s model is described in equations (3.12) and (3.13). The price in market 1 is influenced by contemporary and lagged prices in all other markets and its own lags, while the price in any of the other i markets is influenced by the contemporary and lagged values of the price in market 1 and its own lagged values, only. Two equations describe the price transmission mechanisms, but, due to under-identification problems, only the second one is used in practice: n P 1 , t = ∑ a1, jP1 , t− j m n k + ∑ ∑ β i, jPk , t− j + X1, tc1 + e1, t j= 1 k= 2 j= 0 n n P i, t = ∑ ai, jPi , t− j + ∑ β i, jP1 , t− j + X i, tci + ei, t j= 1 j= 0 (3.12) (3.13) where Xi is a vector of other influences on local markets. Normally, it is equation (3.13) which is used; if βi,j = 0, we have market segmentation, since the market 1 doesn’t influence the market i. On the other side, if βi,0 = 1, immediate transmission is present. We have “strong” short run integration if βi,0 = 1 and αi,j = βi,j = 0 for any j > 0 (the lagged prices have no influence), while we can talk about a “weaker” short run market integration if 29
Empirical Tests for Spatial Price Analysis 30 n ∑ j= 1 a + β = 0 ij ij (3.14) i.e., the effects of the lagged central price and of the lagged price itself cancel, on average, each other out. To have long run integration, the equivalence n ∑ j= 1 n ai, j + ∑ β j= 0 i, j = 1 must hold; under long run integration, the second equation can be re-written as: ΔP + i, t n−1 = ( a i, 1 −1)( P ∑( βi, o −1+ ∑ j= 1 k = 1 j i, t−1 a i, k − P 1, t−1 ) + ∑ j= 2 + β ) ΔP i, k n a 1, t− j i, j ( P + X i, t− j i, t i − P c + e 1, t− j i, t ) + β ΔP i, 0 1, t + (3.15) (3.16) where changes in local prices are attributed both to past spatial price differentials and to changes in central prices; the latter variables allow for the possibility that the markets are not observed in an integrated equilibrium at a given point in time, and so there are feedbacks from prior disequilibria. Fackler and Goodwin (2001, p.1001) derive an interpretation of Ravallion’s model based on the structural VAR model they propose. The “strong” and the “weak” criterion are found not to refer to weaker equilibrium conditions but rather to weaker identification assumptions concerning the driving forces. They assert that the strong form of the short run integration implies transport rates to exhibit no persistence, which is a rather strong assumption, whereas in the weak form excess demand shocks are implicitly assumed not to have long run effects on the transport rate, which could be more reasonable. The so-called Timmer’s criterion is based on Ravallion’s model, but assumes that central market prices are predetermined relative to hinterland prices and that a first-order model is sufficient to capture price dynamics. After some algebraic manipulations the following expression is derived (Alderman 1992, p.9): P ( + cX + μ (3.17) where it = 1 + b1 ) Pit −1 + b2 ( P1 t − P1 t−1 ) + ( b3 − b1 ) P1 t−1 b α (3.18) 1 = i−1 t it
Page 1 and 2: TESTING INTERNATIONAL PRICE TRANSMI
Page 3 and 4: Associazione “Alessandro Bartola
Page 6 and 7: Index 1 INTRODUCTION ..............
Page 8 and 9: 1 INTRODUCTION The notion of “pri
Page 10 and 11: Introduction These recent phenomena
Page 12: Introduction Whereas the Common Agr
Page 15 and 16: Price Transmission and the Law of O
Page 24 and 25: 3 EMPIRICAL TESTS FOR SPATIAL PRICE
Page 26 and 27: Empirical Tests for Spatial Price A
Page 32 and 33: = β 2 i0 Empirical Tests for Spati
Page 48 and 49: ∆p + t ∑ ⎡β⎤ ' ⎡ p t =
Page 54 and 55: 4 INTERNATIONAL SOFT WHEAT MARKETS
Page 56 and 57: International Soft Wheat Markets Un
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Page 78 and 79: Empirical Analysis: Cointegration M
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Empirical Analysis: Cointegration M
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α LM test ARCH(13) Empirical Analy
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6 EMPIRICAL ANALYSIS: COINTEGRATION
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Concluding Remarks These models rep
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REFERENCES Alderman, H., 1992. Inte
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References agricultural policies: s
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References Isard, P., 1977. How far
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References Thompson, S. R., Sul, D.
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Annexes 124 Annex A - Empirical ana
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Annexes METHODOLOGY DATA USED MAJOR
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Annexes Variable swfr 138 Annex B -
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Annexes Variable swfr 140 Table B.3
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Annexes 142 Table B.7 - Unit root t
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Annexes 144 Table C.5 - Cointegrati
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Annexes 146 Table D.4 - Unit root t
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Annexes 148 Annex E - Unit root tes
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Annexes Table E.5 - Unit root tests
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The notion of “price transmission
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