IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/1399.html
   My bibliography  Save this paper

Forecasting the Levels of Vector Autoregressive Log-Transformed Time Series

Author

Listed:
  • Ariño, M.A.
  • Franses, Ph.H.B.F.

Abstract

In this paper we give explicit expressions for the forecasts of levels of a vector time series when such forecasts are generated from (possibly cointegrated) vector autoregressions for the corresponding log-transformed time series. We also show that simply taking exponentials of forecasts for logged data leads to substantially biased forecasts. We illustrate this using a bivariate cointegrated vector series containing US GNP and investments.

Suggested Citation

  • Ariño, M.A. & Franses, Ph.H.B.F., 1996. "Forecasting the Levels of Vector Autoregressive Log-Transformed Time Series," Econometric Institute Research Papers EI 9669-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1399
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/1399/eeb19960111120043.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dufour, Jean-Marie, 1985. "Unbiasedness of Predictions from Etimated Vector Autoregressions," Econometric Theory, Cambridge University Press, vol. 1(3), pages 387-402, December.
    2. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Mayr, Johannes & Ulbricht, Dirk, 2015. "Log versus level in VAR forecasting: 42 million empirical answers—Expect the unexpected," Economics Letters, Elsevier, vol. 126(C), pages 40-42.
    2. Helmut Lütkepohl & Fang Xu, 2012. "The role of the log transformation in forecasting economic variables," Empirical Economics, Springer, vol. 42(3), pages 619-638, June.
    3. Vijay Viswanathan & Linda D. Hollebeek & Edward C. Malthouse & Ewa Maslowska & Su Jung Kim & Wei Xie, 2017. "The Dynamics of Consumer Engagement with Mobile Technologies," Service Science, INFORMS, vol. 9(1), pages 36-49, March.
    4. Fok, Dennis & Franses, Philip Hans, 2001. "Forecasting market shares from models for sales," International Journal of Forecasting, Elsevier, vol. 17(1), pages 121-128.
    5. Franses, Philip Hans, 2006. "Forecasting in Marketing," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 18, pages 983-1012, Elsevier.
    6. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    7. Lo, Danny K. & Hall, Anthony D., 2015. "Resiliency of the limit order book," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 222-244.
    8. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
    9. Holtrop, Niels & Wieringa, Jakob & Gijsenberg, Maarten & Stern, P., 2016. "Competitive reactions to personal selling," Research Report 16004-MARK, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    10. Corradi, Valentina & Swanson, Norman R., 2006. "The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test," Journal of Econometrics, Elsevier, vol. 132(1), pages 195-229, May.
    11. E. A. Fedorova & D. D. Airapetyan & S. O. Musienko & D. O. Afanas’ev & F. Yu. Fedorov, 2018. "Influence of Import Substitution Policy on the Industrial Production Level in Russia: Sector-Specific Issues," Studies on Russian Economic Development, Springer, vol. 29(2), pages 167-173, March.
    12. Cheick Kader M’baye, 2023. "Fertility, employment, and the demographic dividend in sub-Saharan African countries with incipient demographic transition: evidence from Mali," Journal of Population Research, Springer, vol. 40(2), pages 1-15, June.
    13. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    14. Bårdsen, Gunnar & Lütkepohl, Helmut, 2011. "Forecasting levels of log variables in vector autoregressions," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1108-1115, October.
    15. Laing, Andrew R. & Nolan, James F., 2009. "Price Dynamics and Market Structure in Transportation: For-Hire Grain Trucking Along the Alberta- Saskatchewan Border," 50th Annual Transportation Research Forum, Portland, Oregon, March 16-18, 2009 207599, Transportation Research Forum.
    16. Salmanzadeh-Meydani, N. & Fatemi Ghomi, S.M.T., 2019. "The causal relationship among electricity consumption, economic growth and capital stock in Iran," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1230-1256.
    17. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 22, July-Dece.
    18. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    19. Helene Olsen & Harald Wieslander, 2020. "The Impact of Monetary Policy on Leading Variables for Financial Stability in Norway," Working Papers No 02/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    20. Wieringa, Jaap E. & Horvath, Csilla, 2005. "Computing level-impulse responses of log-specified VAR systems," International Journal of Forecasting, Elsevier, vol. 21(2), pages 279-289.
    21. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.

    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. Justin Doran & Bernard Fingleton, 2014. "Economic shocks and growth: Spatio-temporal perspectives on Europe's economies in a time of crisis," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 137-165, November.
    2. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    3. Lisbeth Funding la Cour, 1995. "A Component® based Analysis of the danish Long-run Money Demand Relation," Discussion Papers 95-18, University of Copenhagen. Department of Economics.
    4. Levent, Korap, 2007. "Modeling purchasing power parity using co-integration: evidence from Turkey," MPRA Paper 19584, University Library of Munich, Germany.
    5. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    6. Darrian Collins & Clem Tisdell, 2004. "Outbound Business Travel Depends on Business Returns: Australian Evidence," Australian Economic Papers, Wiley Blackwell, vol. 43(2), pages 192-207, June.
    7. Christian Schoder, 2012. "Effective demand, exogenous normal utilization and endogenous capacity in the long run. Evidence from a CVAR analysis for the US," IMK Working Paper 103-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    8. Muhammad Shahbaz & Vassilios G. Papavassiliou & Amine Lahiani & David Roubaud, 2023. "Are we moving towards decarbonisation of the global economy? Lessons from the distant past to the present," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2620-2634, July.
    9. Karaman Örsal, Deniz Dilan & Droge, Bernd, 2014. "Panel cointegration testing in the presence of a time trend," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 377-390.
    10. Jakšić Saša, 2022. "Modelling Determinants of Inflation in CESEE Countries: Global Vector Autoregressive Approach," Review of Economic Perspectives, Sciendo, vol. 22(2), pages 137-169, June.
    11. António Duarte, 2009. "The Portuguese Disinflation Process: Analysis of Some Costs and Benefits," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 16(1), pages 157-173, May.
    12. Njangang Henri & Nembot Ndeffo Luc & Nawo Larissa, 2019. "The Long‐run and Short‐run Effects of Foreign Direct Investment on Financial Development in African Countries," African Development Review, African Development Bank, vol. 31(2), pages 216-229, June.
    13. Lego, Brian & Gebremedhin, Tesfa & Cushing, Brian, 2000. "A Multi-Sector Export Base Model of Long-Run Regional Employment Growth," Agricultural and Resource Economics Review, Cambridge University Press, vol. 29(2), pages 192-197, October.
    14. Ali MNA & Moheddine YOUNSI, 2018. "A monetary conditions index and its application on Tunisian economic forecasting," Journal of Economics and Political Economy, KSP Journals, vol. 5(1), pages 38-56, March.
    15. Franses, Ph.H.B.F. & Paap, R., 1999. "Forecasting with periodic autoregressive time series models," Econometric Institute Research Papers EI 9927-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Hauser, Shmuel & Kedar-Levy, Haim & Milo, Orit, 2022. "Price discovery during parallel stocks and options preopening: Information distortion and hints of manipulation," Journal of Financial Markets, Elsevier, vol. 59(PA).
    17. Jaromir Benes & David Vavra, 2004. "Eigenvalue Decomposition of Time Series with Application to the Czech Business Cycle," Working Papers 2004/08, Czech National Bank.
    18. Çakır, Mustafa Yavuz & Kabundi, Alain, 2013. "Trade shocks from BRIC to South Africa: A global VAR analysis," Economic Modelling, Elsevier, vol. 32(C), pages 190-202.
    19. Stanislav Yugay & Linde Götz & Miranda Svanidze, 2024. "Impact of the Ruble exchange rate regime and Russia's war in Ukraine on wheat prices in Russia," Agricultural Economics, International Association of Agricultural Economists, vol. 55(2), pages 384-411, March.
    20. Apergis, Nicholas & Payne, James E., 2010. "Coal consumption and economic growth: Evidence from a panel of OECD countries," Energy Policy, Elsevier, vol. 38(3), pages 1353-1359, March.

    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:ems:eureir:1399. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.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.