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Spatial Analysis of Market Linkages in North Carolina Using Threshold Autoregression Models with Variable Transaction Costs

  • Bekkerman, Anton
  • Goodwin, Barry K.
  • Piggott, Nicholas E.

In North Carolina, where soybeans and corn are the two primary crops, the recent increase in the demand for U.S. corn has triggered a shift of farm acreage from soybeans to corn, leading to a rapid rise in prices of both commodities. However, the rate of the price changes, as well as the price level, is significantly different in markets that are located in different parts of the state. This study extends the literature that examines linkages between spatially separated markets by using a threshold autoregressive model with a less restrictive assumption for estimating the transaction cost neutral band -- the band within which trade is not profitable. This generalization allows the neutral band of transactions costs to change according to various external factors, including fuel costs and seasonality. The estimation results indicate that for longer time series data, variable thresholds models statistically outperform the constant thresholds specification, and may provide a better representation of corn and soybean price data. Additionally, impulse response functions that use the asymmetric variable threshold model parameters indicate that the magnitude of the shock as well as the time-to-price-parity-equilibrium in the linked markets may be underestimated if a constant thresholds specification is implemented.

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File URL: http://purl.umn.edu/49282
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Paper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49282.

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Date of creation: 2009
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Handle: RePEc:ags:aaea09:49282
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  1. Li, Jau-Rong & Barrett, Christopher B., 1999. "Distinguishing Between Equilibrium And Integration In Markets Analysis," Working Papers 14607, International Agricultural Trade Research Consortium.
  2. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  3. Haesun Park & James Mjelde & David Bessler, 2007. "Time-varying threshold cointegration and the law of one price," Applied Economics, Taylor & Francis Journals, vol. 39(9), pages 1091-1105.
  4. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffery P., 2008. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," MPRA Paper 9684, University Library of Munich, Germany.
  5. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers 693, UCLA Department of Economics.
  6. Nathan S. Balke & Thomas B. Fomby, 1992. "Threshold cointegration," Research Paper 9209, Federal Reserve Bank of Dallas.
    • Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-45, August.
  7. Goodwin, Barry K. & Piggott, Nicholas E., 1999. "Spatial Market Integration In The Presence Of Threshold Effects," 1999 Annual meeting, August 8-11, Nashville, TN 21489, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  8. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  9. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July.
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