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Cointegrated Vector Autoregression Methods: An Application to Non-Normally Behaving Data on Selected U.S. Sugar-Related Markets

Listed author(s):
  • Babula, Ronald A.
  • Newman, Douglas
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    The methods of the cointegrated vector autoregression/error correction (VAR/VEC) model are applied to monthly U.S. markets for sugar and for sugar-using markets for confectionary, soft drink, and bakery products. Primarily a methods paper, Johansen and Juselius' methods are applied, with a special focus on addressing well-known issues that preclude statistically normal behavior, and that confront the modelled sugar-based data. In so doing, we illustrate the effectiveness and the benefits of modelling this sugar-related set of markets as a cointegrated system. Perhaps for the first time, cointegrated VEC model results are used to estimate crucial policy-relevant market parameters that drive the markets, as well as to illuminate the dynamic nature of the relationships linking these sugar-based markets.

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    Paper provided by United States International Trade Commission, Office of Industries in its series Working Paper ID Series with number 15878.

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    Date of creation: 2005
    Handle: RePEc:ags:uitcoi:15878
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