IDEAS home Printed from https://ideas.repec.org/r/pra/mprapa/9684.html
   My bibliography  Save this item

The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Ubilava, David & holt, Matt, 2013. "El Ni~no southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 1-25.
  2. David Colman, 2010. "Agriculture's terms of trade: issues and implications," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 1-15, November.
  3. Craig, Lee & Holt, Matthew T., 2012. "The Role of Mechanical Refrigeration in Spatial and Temporal Price Dynamics for Regional U.S. Egg Markets, 1880–1911," MPRA Paper 39554, University Library of Munich, Germany.
  4. Elkhan Richard Sadik-Zada, 2021. "Addressing the growth and employment effects of the extractive industries: white and black box illustrations from Kazakhstan," Post-Communist Economies, Taylor & Francis Journals, vol. 33(4), pages 402-434, May.
  5. Landajo, Manuel & Presno, Marıa Jose, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(02), January.
  6. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
  7. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffrey P., 2019. "Nonlinear exchange rate pass-through in timber products: The case of oriented strand board in Canada and the United States," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  8. Presno, María José & Landajo, Manuel & Fernández, Paula, 2012. "Non-renewable resource prices. A robust evaluation from the stationarity perspective," MPRA Paper 42523, University Library of Munich, Germany.
  9. Emediegwu, Lotanna Ernest, 2023. "Assessing the (a)symmetric effect of global climate anomalies on food prices: Evidence from local prices," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334555, Agricultural Economics Society - AES.
  10. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
  11. Kim, Hyeongwoo & Kim, Jintae, 2018. "London calling: Nonlinear mean reversion across national stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 265-277.
  12. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
  13. Ubilava, David, 2013. "El Niño Southern Oscillation and Primary Agricultural Commodity Prices: Causal Inferences from Smooth Transition Models," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152202, Australian Agricultural and Resource Economics Society.
  14. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
  15. Bekkerman, Anton & Goodwin, Barry K. & Piggott, Nicholas E., 2009. "Spatial Analysis of Market Linkages in North Carolina Using Threshold Autoregression Models with Variable Transaction Costs," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49282, Agricultural and Applied Economics Association.
  16. John Baffes & Xiaoli L. Etienne, 2016. "Analysing food price trends in the context of Engel’s Law and the Prebisch-Singer hypothesis," Oxford Economic Papers, Oxford University Press, vol. 68(3), pages 688-713.
  17. Atanu Ghoshray & Ashira Perera, 2016. "An Empirical Study of Commodity Prices after Sir Arthur Lewis," Manchester School, University of Manchester, vol. 84(4), pages 551-571, July.
  18. Jeffrey Frankel, 2013. "A Solution to Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Central Banking, Analysis, and Economic Policies Book Series, in: Luis Felipe Céspedes & Jordi Galí (ed.),Fiscal Policy and Macroeconomic Performance, edition 1, volume 17, chapter 9, pages 323-391, Central Bank of Chile.
  19. Ghoshray, Atanu, 2011. "A reexamination of trends in primary commodity prices," Journal of Development Economics, Elsevier, vol. 95(2), pages 242-251, July.
  20. Sanders, Daniel J. & Baker, Timothy G., 2012. "Hedgers’ Participation in Futures Markets Under Varying Price Regimes," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124872, Agricultural and Applied Economics Association.
  21. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
  22. A Ghoshray & Ashira Perera, 2011. "The Model of Commodity Prices after Sir Arthur Lewis Revisited," Department of Economics Working Papers 08/11, University of Bath, Department of Economics.
  23. Selin Güney & Andrés Riquelme & Barry Goodwin, 2023. "An Analysis of the Pass-Through of Exchange Rates in Forest Product Markets," Agriculture, MDPI, vol. 13(3), pages 1-16, February.
  24. Frankel, Jeffrey A., 2010. "The Natural Resource Curse: A Survey," Scholarly Articles 4454156, Harvard Kennedy School of Government.
  25. Jeffrey Frankel, 2012. "The Natural Resource Curse: A Survey of Diagnoses and Some Prescriptions," Growth Lab Working Papers 36, Harvard's Growth Lab.
  26. Konstantinos Chatzimichael & Dimitris Christopoulos & Spiro Stefanou & Vangelis Tzouvelekas, 2020. "Irrigation practices, water effectiveness and productivity measurement [Toward an understanding of technology adoption: risk, learning, and neighborhood effects]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 467-498.
  27. Yamada, Hiroshi & Yoon, Gawon, 2014. "When Grilli and Yang meet Prebisch and Singer: Piecewise linear trends in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 193-207.
  28. Byrne, Joseph P & Fazio, Giorgio & Fiess, Norbert, 2010. "Optimism and commitment: An elementary theory of bargaining and war," SIRE Discussion Papers 2010-102, Scottish Institute for Research in Economics (SIRE).
  29. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).
  30. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
  31. Kurmas Akdogan, 2018. "Mean-reversion and structural change in European food prices," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 163-173.
  32. David Harvey & Neil Kellard & Jakob Madsen & Mark Wohar, 2012. "Trends and Cycles in Real Commodity Prices: 1650-2010," CEH Discussion Papers 010, Centre for Economic History, Research School of Economics, Australian National University.
  33. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
  34. Winkelried, Diego, 2018. "Unit roots, flexible trends, and the Prebisch-Singer hypothesis," Journal of Development Economics, Elsevier, vol. 132(C), pages 1-17.
  35. Pierre JACQUET & Alexis ATLANI & Marwan LISSER, 2017. "Policy responses to terms of trade shocks," Working Papers P205, FERDI.
  36. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
  37. Kanieski da Silva, Bruno & Schons, Stella Z. & Cubbage, Frederick W. & Parajuli, Rajan, 2020. "Spatial and cross-product price linkages in the Brazilian pine timber markets," Forest Policy and Economics, Elsevier, vol. 117(C).
  38. David Ubilava, 2012. "Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 28(1), pages 29-41, January.
  39. Shu-Ling Chen & John D. Jackson & Hyeongwoo Kim & Pramesti Resiandini, 2014. "What Drives Commodity Prices?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(5), pages 1455-1468.
  40. Pierre JACQUET & Alexis ATLANI & Marwan LISSER, 2017. "Policy responses to terms of trade shocks," Working Papers P205, FERDI.
  41. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
  42. Murat ASLAN & Saban NAZLIOGLU, 2018. "Do International Relative Commodity Prices Support the Prebisch-Singer Hypothesis? A Nonlinear Panel Unit Root Testing," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 76-92, December.
  43. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
  44. Robert Czudaj & Joscha Beckmann, 2012. "Spot and futures commodity markets and the unbiasedness hypothesis - evidence from a novel panel unit root test," Economics Bulletin, AccessEcon, vol. 32(2), pages 1695-1707.
  45. MacDonald, Stephen & Meyer, Leslie, 2018. "Long Run Trends and Fluctuations In Cotton Prices," MPRA Paper 84484, University Library of Munich, Germany, revised 10 Feb 2018.
  46. Adrian Boos & Karin Holm‐Müller, 2012. "A theoretical overview of the relationship between the resource curse and genuine savings as an indicator for “weak” sustainability," Natural Resources Forum, Blackwell Publishing, vol. 36(3), pages 145-159, August.
  47. Lotanna E Emediegwu & Obianuju O Nnadozie, 2023. "On the effects of COVID-19 on food prices in India: a time-varying approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(2), pages 232-249.
  48. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein & Yadulla Hasanli, 2019. "Commodity Revenues, Agricultural Sector and the Magnitude of Deindustrialization: A Novel Multisector Perspective," Economies, MDPI, vol. 7(4), pages 1-15, November.
  49. Baffes, John & Haniotis, Tassos, 2010. "Placing the 2006/08 commodity price boom into perspective," Policy Research Working Paper Series 5371, The World Bank.
  50. Andaleeb Rahman, 2012. "Characterizing food prices in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-022, Indira Gandhi Institute of Development Research, Mumbai, India.
  51. Ranjan Aneja & Arjun, 2022. "Impact of Terms of Trade on GDP in the Context of Prebisch–Singer Theorem: Evidence from Egypt and Guinea," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(5), pages 2561-2575, October.
  52. Oglend, Atle & Selland Kleppe, Tore, 2016. "How regular are directional movements in commodity and asset prices? A Wald test," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 290-306.
  53. Lotanna E. Emediegwu, 2024. "Assessing the Asymmetric Effect of Global Climate Anomalies on Food Prices: Evidence from Local Prices," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(10), pages 2743-2772, October.
  54. Frankel, Jeffrey, 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Working Paper Series 11-012, Harvard University, John F. Kennedy School of Government.
  55. Meng Ming & Lee Junsoo & Payne James E., 2017. "RALS-LM unit root test with trend breaks and non-normal errors: application to the Prebisch-Singer hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 31-45, February.
  56. Hany Fahmy, 2021. "A Reappraisal of the Prebisch-Singer Hypothesis Using Wavelets Analysis," JRFM, MDPI, vol. 14(7), pages 1-17, July.
  57. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
  58. David Ubilava, 2014. "El Niño Southern Oscillation and the fishmeal–soya bean meal price ratio: regime-dependent dynamics revisited," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 583-604.
  59. Scandizzo, Pasquale Lucio & Savastano, Sara & Vezzani, Antonio, 2010. "The deterministic and speculative component of the terms of trade of primary commodities: An “Eclectic” Real Option value approach," 114th Seminar, April 15-16, 2010, Berlin, Germany 61086, European Association of Agricultural Economists.
  60. Presno, María José & Landajo, Manuel & Fernández, Paula, 2014. "Non-renewable resource prices: A robust evaluation from the stationarity perspective," Resource and Energy Economics, Elsevier, vol. 36(2), pages 394-416.
  61. David Ubilava, 2022. "A comparison of multistep commodity price forecasts using direct and iterated smooth transition autoregressive methods," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 687-701, September.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.