IDEAS home Printed from https://ideas.repec.org/a/ibn/ijefaa/v16y2024i8p1.html
   My bibliography  Save this article

Identifying the Temporal Dynamics and Macroeconomic Interactions of the US Economy

Author

Listed:
  • Omar Barroso Khodr
  • Mathias Schneid Tessmann
  • Humberto Nunes Alencar
  • Alex Cerqueira Pinto

Abstract

This paper employs the VAR model to analyze interrelations among key macroeconomic variables, emphasizing unemployment, inflation, and the Fed Funds rate. The model reveals asymmetry in the unemployment-Fed Funds rate relationship, emphasizing the unique influence of unemployment. Lagged values contribute to understanding temporal dependencies, highlighting positive associations between lagged and current inflation. Impulse response analysis and the covariance matrix validate the IS-LM model and Stock and Watson’s (2001) findings. Forecasts anticipate increased unemployment and a slight Fed Funds rate decrease, though accuracy tests reveal reliability issues, especially for the Fed Funds rate. ADF tests support stationarity for inflation and unemployment showing a weak indication against the unit root hypothesis for the Fed Funds rate. Lastly, SARIMA, ARIMA, and DM tests suggest performance differences, pointing to avenues for future research to enhance precision, address reliability issues, and explore variations between SARIMA and VAR models, potentially in a cross-country comparative context.

Suggested Citation

  • Omar Barroso Khodr & Mathias Schneid Tessmann & Humberto Nunes Alencar & Alex Cerqueira Pinto, 2024. "Identifying the Temporal Dynamics and Macroeconomic Interactions of the US Economy," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 16(8), pages 1-1, August.
    • Handle: RePEc:ibn:ijefaa:v:16:y:2024:i:8:p:1
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ijef/article/download/0/0/50388/54567
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/ijef/article/view/0/50388
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christopher A. Sims, 1982. "Policy Analysis with Econometric Models," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 13(1), pages 107-164.
    2. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
    3. John C. Robertson & Ellis W. Tallman, 1999. "Prior parameter uncertainty: Some implications for forecasting and policy analysis with VAR models," FRB Atlanta Working Paper 99-13, Federal Reserve Bank of Atlanta.
    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. Dal Bianco, Marcos & Camacho, Maximo & Perez Quiros, Gabriel, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 377-396.
    2. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    3. Ellwanger, Reinhard & Snudden, Stephen, 2025. "Putting VAR forecasts of the real price of crude oil to the test," Finance Research Letters, Elsevier, vol. 77(C).
    4. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
    5. Summers, Peter M., 2001. "Forecasting Australia's economic performance during the Asian crisis," International Journal of Forecasting, Elsevier, vol. 17(3), pages 499-515.
    6. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    7. Ana-Maria Fuertes & Elena Kalotychou, 2004. "Forecasting sovereign default using panel models: A comparative analysis," Computing in Economics and Finance 2004 228, Society for Computational Economics.
    8. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the oil–gasoline price relationship: Do asymmetries help?," Energy Economics, Elsevier, vol. 46(S1), pages 44-56.
    9. Bharat Trehan, 1986. "Oil prices, exchange rates and the U.S. economy: an empirical investigation," Economic Review, Federal Reserve Bank of San Francisco, issue Fall, pages 25-43.
    10. repec:ers:journl:v:volumexxi:y:2018:i:issue4:p:622-636 is not listed on IDEAS
    11. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters, in: Monetary Policy Rules, pages 203-262, National Bureau of Economic Research, Inc.
    12. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
    13. Pär Österholm, 2009. "Incorporating Judgement in Fan Charts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 387-415, June.
    14. Gideon O. Fadiran & Adebisi Edun, 2013. "An Overview of the Repo Rate in an Inflation Targeting Economy," African Development Review, African Development Bank, vol. 25(4), pages 621-635.
    15. Kocherlakota, Narayana R., 2019. "Practical policy evaluation," Journal of Monetary Economics, Elsevier, vol. 102(C), pages 29-45.
    16. Carlo Altavilla & Domenico Giannone, 2017. "The Effectiveness of Non‐Standard Monetary Policy Measures: Evidence from Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 952-964, August.
    17. repec:hal:spmain:info:hdl:2441/7l23tbn4rd9539sljmp8of2hcb is not listed on IDEAS
    18. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    19. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
    20. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    21. Clarida, Richard H & Friedman, Benjamin M, 1984. "The Behavior of U.S. Short-Term Interest Rates since October 1979," Journal of Finance, American Finance Association, vol. 39(3), pages 671-682, July.
    22. Bryan Kelly & Semyon Malamud & Kangying Zhou, 2024. "The Virtue of Complexity in Return Prediction," Journal of Finance, American Finance Association, vol. 79(1), pages 459-503, February.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:ijefaa:v:16:y:2024:i:8:p:1. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.