IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpit/0512016.html
   My bibliography  Save this paper

Trade balance and terms of trade in U.S.: a time-scale decomposition analysis

Author

Listed:
  • Luca De Benedictis

    (University of Macerata, Italy)

  • Marco Gallegati

    (DEA, Università Politecnica delle Marche, Italy)

Abstract

The aim of this paper is to provide evidence on the nature of the relationship between the terms of trade and the trade balance for US on a scale-by-scale basis using wavelet analysis. Thus, after decomposing the two variables into their time-scale components using to the maximum overlap discrete wavelet transform (MODWT) we analyze the time scale relationships between the terms of trade and the trade balance through the wavelet correlation analysis, and nonparametric regression models(GAMs). Wavelet correlation analysis indicates that, if the association between the trade balance and the terms of trade depends mainly on the elasticity of substitution between foreign and domestic goods, the Armington elasticities may be di¤erent across scales, and in particular, tend to get larger as the time horizon of the agents increases. Moreover, the long-run relationship between the trade balance and the terms of trade from the nonparametric …tted functions seems to provide support to the existence of the Harberger-Laursen-Metzler e¤ect .

Suggested Citation

  • Luca De Benedictis & Marco Gallegati, 2005. "Trade balance and terms of trade in U.S.: a time-scale decomposition analysis," International Trade 0512016, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpit:0512016
    Note: Type of Document - pdf; pages: 15
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/it/papers/0512/0512016.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Backus, David K & Kehoe, Patrick J & Kydland, Finn E, 1994. "Dynamics of the Trade Balance and the Terms of Trade: The J-Curve?," American Economic Review, American Economic Association, vol. 84(1), pages 84-103, March.
    2. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    3. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    4. Elliott, Graham & Fatas, Antonio, 1996. "International business cycles and the dynamics of the current account," European Economic Review, Elsevier, vol. 40(2), pages 361-387, February.
    5. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
    6. David K. Backus & Patrick J. Kehoe & Finn E. Kydland, 1992. "Dynamics of the trade balance and the terms of trade: the J-curve revisited," Discussion Paper / Institute for Empirical Macroeconomics 65, Federal Reserve Bank of Minneapolis.
    7. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ibrahim Ahamada & Philippe Jolivaldt, 2010. "Classical vs wavelet-based filters Comparative study and application to business cycle," Post-Print halshs-00476022, HAL.
    2. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, August.
    3. Ibrahim Ahamada & Philippe Jolivaldt, 2010. "Classical vs wavelet-based filters Comparative study and application to business cycle," Documents de travail du Centre d'Economie de la Sorbonne 10027, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Stan Plessis & Gideon Rand & Kevin Kotzé, 2015. "Measuring Core Inflation in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 527-548, December.
    5. Jean Imbs, 2010. "The First Global Recession in Decades," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 58(2), pages 327-354, December.
    6. Rabanal, Pau & Rubio-Ramírez, Juan F., 2015. "Can international macroeconomic models explain low-frequency movements of real exchange rates?," Journal of International Economics, Elsevier, vol. 96(1), pages 199-211.
    7. Stéphane Pallage & Michel A. Robe, 2001. "Foreign Aid and the Business Cycle," Review of International Economics, Wiley Blackwell, vol. 9(4), pages 641-672, November.
    8. Xu, T.T., 2012. "The role of credit in international business cycles," Cambridge Working Papers in Economics 1202, Faculty of Economics, University of Cambridge.
    9. Mario J. Crucini & Mototsugu Shintani, 2010. "Measuring business cycles by saving for a rainy day," Globalization Institute Working Papers 50, Federal Reserve Bank of Dallas.
    10. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    11. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    12. Naknoi, Kanda, 2008. "Real exchange rate fluctuations, endogenous tradability and exchange rate regimes," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 645-663, April.
    13. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    14. Imbs, Jean, 2006. "The real effects of financial integration," Journal of International Economics, Elsevier, vol. 68(2), pages 296-324, March.
    15. Hassan Farazmand & Amin Mansouri & Morteza Afghah, 2014. "Choosing the best type of wavelet: Case study-business cycle in Iran," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 4(5), pages 293-314, May.
    16. Aguiar-Conraria, Luis & Brinca, Pedro & Gudjonsson, Haukur & Soares, Joana, 2015. "Optimal currency area and business cycle synchronization across U.S. states," MPRA Paper 62125, University Library of Munich, Germany.
    17. Krüger, Jens J., 2024. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149438, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Patrick M. Crowley, 2005. "An intuitive guide to wavelets for economists," GE, Growth, Math methods 0508009, University Library of Munich, Germany.
    19. Oscar Avila-Montealegre & Carter Mix, 2020. "Common Trade Exposure and Business Cycle Comovement," Borradores de Economia 1149, Banco de la Republica de Colombia.
    20. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.

    More about this item

    Keywords

    trade variables; wavelet correlation analysis; generalized additive models;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • F10 - International Economics - - Trade - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpit:0512016. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.