IDEAS home Printed from https://ideas.repec.org/a/jae/japmet/v22y2007i1p63-87.html
   My bibliography  Save this article

Nonlinear autoregressive leading indicator models of output in G-7 countries

Author

Listed:
  • George Athanasopoulos

    (Department of Econometrics and Business Statistics, Monash University, Clayton, Australia)

  • Heather M. Anderson

    (School of Economics, Australian National University, Canberra, Australia)

  • Farshid Vahid

    (School of Economics, Australian National University, Canberra, Australia)

Abstract

This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G-7 countries. Our models use the spread between short-term and long-term interest rates as leading indicators for GDP. We examine data admissibility by determining whether these models have the ability to produce time series with classical cycles that resemble the observed classical cycles in the data, and then we ask whether this data admissibility lends itself to better predictions of the probability of recession. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • George Athanasopoulos & Heather M. Anderson & Farshid Vahid, 2007. "Nonlinear autoregressive leading indicator models of output in G-7 countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 63-87.
    • Handle: RePEc:jae:japmet:v:22:y:2007:i:1:p:63-87
    DOI: 10.1002/jae.935
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/jae.935
    File Function: Link to full text; subscription required
    Download Restriction: no
    File URL: http://qed.econ.queensu.ca:80/jae/2007-v22.1/
    File Function: Supporting data files and programs
    Download Restriction: no
    File URL: https://libkey.io/10.1002/jae.935?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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 627-645, August.
    2. Kwark, Noh-Sun, 2002. "Default risks, interest rate spreads, and business cycles: Explaining the interest rate spread as a leading indicator," Journal of Economic Dynamics and Control, Elsevier, vol. 26(2), pages 271-302, February.
    3. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
    4. Gertler, Mark & Lown, Cara S, 1999. "The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 15(3), pages 132-150, Autumn.
    5. Don Harding & Adrian Pagan, 1999. "Dissecting the Cycle," Melbourne Institute Working Paper Series wp1999n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    6. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    7. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1.
    8. Davis, E Philip & Fagan, Gabriel, 1997. "Are Financial Spreads Useful Indicators of Future Inflation and Output Growth in EU Countries?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(6), pages 701-714, Nov.-Dec..
    9. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    10. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    11. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
    12. Hamilton, James Douglas & Kim, Dong Heon, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," University of California at San Diego, Economics Working Paper Series qt69v8p1m9, Department of Economics, UC San Diego.
    13. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    14. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    15. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    16. Benjamin M. Friedman & Kenneth N. Kuttner, 1998. "Indicator Properties Of The Paper-Bill Spread: Lessons From Recent Experience," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 34-44, February.
    17. Zellner, Arnold & Hong, Chansik, 1989. "Forecasting international growth rates using Bayesian shrinkage and other procedures," Journal of Econometrics, Elsevier, vol. 40(1), pages 183-202, January.
    18. Zellner, Arnold & Hong, Chansik & Min, Chung-ki, 1991. "Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 275-304.
    19. Anderson, Heather M. & Vahid, Farshid, 2001. "Predicting The Probability Of A Recession With Nonlinear Autoregressive Leading-Indicator Models," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 482-505, September.
    20. Weise, Charles L, 1999. "The Asymmetric Effects of Monetary Policy: A Nonlinear Vector Autoregression Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(1), pages 85-108, February.
    21. Michael P. Clements & Hans-Martin Krolzig, 2004. "Can regime-switching models reproduce the business cycle features of US aggregate consumption, investment and output?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 1-14.
    22. Galbraith, John W. & Tkacz, Greg, 2000. "Testing for asymmetry in the link between the yield spread and output in the G-7 countries," Journal of International Money and Finance, Elsevier, vol. 19(5), pages 657-672, October.
    23. Engle, Robert F. & Marcucci, Juri, 2006. "A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones," Journal of Econometrics, Elsevier, vol. 132(1), pages 7-42, May.
    24. Sensier, Marianne & Artis, Michael & Osborn, Denise R. & Birchenhall, Chris, 2004. "Domestic and international influences on business cycle regimes in Europe," International Journal of Forecasting, Elsevier, vol. 20(2), pages 343-357.
    25. repec:fth:harver:1418 is not listed on IDEAS
    26. Dennis W. Jansen & Wankeun Oh, 1999. "Modeling Nonlinearity of Business Cycles: Choosing Between the CDR and STAR Models," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 344-349, May.
    27. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886, August.
    28. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-360, May.
    29. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    30. Anderson, Heather M, 1997. "Transaction Costs and Non-linear Adjustment towards Equilibrium in the US Treasury Bill Market," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(4), pages 465-484, November.
    31. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 47-75.
    32. Ray C. Fair, 1993. "Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 157-178, National Bureau of Economic Research, Inc.
    33. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    34. Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December.
    35. Andrew Harvey & Esther Ruiz & Neil Shephard, 1994. "Multivariate Stochastic Variance Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(2), pages 247-264.
    36. J. Bradford De Long & Lawrence H. Summers, "undated". "How Does Macroeconomic Policy Matter?," J. Bradford De Long's Working Papers _130, University of California at Berkeley, Economics Department.
    37. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    38. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    39. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    40. James Peery Cover, 1992. "Asymmetric Effects of Positive and Negative Money-Supply Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(4), pages 1261-1282.
    41. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    42. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    43. J. Bradford DeLong & Lawrence H. Summers, 1988. "How Does Macroeconomic Policy Affect Output?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(2), pages 433-494.
    44. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    45. Sharon Kozicki, 1997. "Predicting real growth and inflation with the yield spread," Economic Review, Federal Reserve Bank of Kansas City, vol. 82(Q IV), pages 39-57.
    46. Kuttner, Kenneth N. & Friedman, Benjamin Morton, 1998. "Indicator Properties of the Paper—Bill Spread: Lessons from Recent Experience," Scholarly Articles 4554251, Harvard University Department of Economics.
    47. Choi, Woon Gyu, 1999. "Asymmetric Monetary Effects on Interest Rates across Monetary Policy Stances," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(3), pages 386-416, August.
    48. Karras, Georgios, 1996. "Are the Output Effects of Monetary Policy Asymmetric? Evidence from a Sample of European Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(2), pages 267-278, May.
    49. Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
    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. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. Ubilava, David, 2019. "On The Relationship Between Financial Instability And Economic Performance: Stressing The Business Of Nonlinear Modeling," Macroeconomic Dynamics, Cambridge University Press, vol. 23(1), pages 80-100, January.
    3. Ben Cheikh, Nidhaleddine & Ben Naceur, Sami & Kanaan, Oussama & Rault, Christophe, 2021. "Investigating the asymmetric impact of oil prices on GCC stock markets," Economic Modelling, Elsevier, vol. 102(C).
    4. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.
    5. John G Powell & Sirimon Treepongkaruna, 2012. "Recession fears as self-fulfilling prophecies? Influence on stock returns and output," Australian Journal of Management, Australian School of Business, vol. 37(2), pages 231-260, August.
    6. Igor L. Kheifets & Pentti J. Saikkonen, 2020. "Stationarity and ergodicity of vector STAR models," Econometric Reviews, Taylor & Francis Journals, vol. 39(4), pages 407-414, April.
    7. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    8. Ralf Becker & Denise R. Osborn, 2012. "Weighted Smooth Transition Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 795-811, August.
    9. Moid U. Ahmad, 2015. "Does CRR and Repo Change Affect Corporate Output?," Jindal Journal of Business Research, , vol. 4(1-2), pages 115-125, June.
    10. Nidhaleddine Ben Cheikh & Younes Ben Zaied & Pascal Nguyen, 2018. "Nonlinear Exchange Rate Transmission in the Euro Area: A Multivariate Smooth Transition Regression Approach," Economics Bulletin, AccessEcon, vol. 38(3), pages 1590-1602.
    11. NIDHALEDDINE BEN CHEIKH & SAMI BEN NACEUR & OUSSAMA KANAAN & Christophe RAULT, 2019. "Oil Prices and GCC Stock Markets: New Evidence from Vector Smooth Transition Models," LEO Working Papers / DR LEO 2697, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    12. Maksim Isakin & Phuong V. Ngo, 2020. "Variance Decomposition Analysis for Nonlinear Economic Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1362-1374, December.
    13. Kheifets, Igor L., 2018. "Multivariate specification tests based on a dynamic Rosenblatt transform," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 1-14.

    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. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.
    2. Issler, Joao Victor & Vahid, Farshid, 2006. "The missing link: using the NBER recession indicator to construct coincident and leading indices of economic activity," Journal of Econometrics, Elsevier, vol. 132(1), pages 281-303, May.
    3. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    4. Marianne Sensier & Denise R. Osborn & Nadir Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 315-339, September.
    5. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    6. Maximo Camacho, 2004. "Vector smooth transition regression models for US GDP and the composite index of leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 173-196.
    7. Chris Birchenhall & Denise Osborn & Marianne Sensier, 2001. "Predicting UK Business Cycle Regimes," Scottish Journal of Political Economy, Scottish Economic Society, vol. 48(2), pages 179-195, May.
    8. Sensier, Marianne & Artis, Michael & Osborn, Denise R. & Birchenhall, Chris, 2004. "Domestic and international influences on business cycle regimes in Europe," International Journal of Forecasting, Elsevier, vol. 20(2), pages 343-357.
    9. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    10. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    11. Medhioub, Imed, 2007. "Asymétrie des cycles économiques et changement de régimes : cas de la Tunisie," L'Actualité Economique, Société Canadienne de Science Economique, vol. 83(4), pages 529-553, décembre.
    12. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    13. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    14. Yongsung Chang & Sunoong Hwang, 2015. "Asymmetric Phase Shifts in U.S. Industrial Production Cycles," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 116-133, March.
    15. L.A. Gil-Alana, 2005. "Fractional Cyclical Structures & Business Cycles in the Specification of the US Real Output," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 99-126.
    16. Vincent, BODART & Konstantin, KHOLODILIN & Fati, SHADMAN-MEHTA, 2005. "Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models," Discussion Papers (ECON - Département des Sciences Economiques) 2005006, Université catholique de Louvain, Département des Sciences Economiques.
    17. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    18. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    19. Gilchrist, Simon & Yankov, Vladimir & Zakrajsek, Egon, 2009. "Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 471-493, May.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:jae:japmet:v:22:y:2007:i:1:p:63-87. 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: Wiley-Blackwell Digital Licensing or Christopher F. Baum (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0883-7252/ .

    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.