IDEAS home Printed from https://ideas.repec.org/p/fip/fedhwp/wp-99-22.html
   My bibliography  Save this paper

Is there evidence of the new economy in the data?

Author

Listed:
  • Michael A. Kouparitsas

Abstract

The popular new economy theory argues that the U.S. economy can now grow at rates much greater than in the past without igniting higher levels of price inflation. At the core of the new economy paradigm is the belief that the U.S. Economy experienced an innovation in the 1990s that raised its so-called constant-inflation trend growth rate. According to its advocates, evidence of the new economy comes from the fact that the U.S. economy experienced relatively strong output growth and low levels of price inflation over the 1990s. This paper evaluates the new economy theory by formally testing whether the growth rate of the constant-inflation trend changed significantly over the 1990s. I find that there is no evidence of the new economy when the constant-inflation trend is estimated using recent GDP and CPI data. My results suggest that the robust economy expansion of the 1990s was not due to a increase in the trend growth rate but rather a cyclical expansion and a level increase in the trend.

Suggested Citation

  • Michael A. Kouparitsas, 1999. "Is there evidence of the new economy in the data?," Working Paper Series WP-99-22, Federal Reserve Bank of Chicago.
  • Handle: RePEc:fip:fedhwp:wp-99-22
    as

    Download full text from publisher

    File URL: http://www.chicagofed.org/digital_assets/publications/working_papers/1999/wp99_22.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nelson, Charles R & Kang, Heejoon, 1981. "Spurious Periodicity in Inappropriately Detrended Time Series," Econometrica, Econometric Society, vol. 49(3), pages 741-751, May.
    2. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    3. 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.
    4. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    5. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, Oxford University Press, vol. 102(4), pages 797-814.
    6. Kenneth N. Kuttner, 1993. "An unobserved-components model of constant-inflation potential output," Working Paper Series, Macroeconomic Issues 93-2, Federal Reserve Bank of Chicago.
    7. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    8. Lam, Pok-sang, 1990. "The Hamilton model with a general autoregressive component: estimation and comparison with other models of economic time series : Estimation and comparison with other models of economic time series," Journal of Monetary Economics, Elsevier, vol. 26(3), pages 409-432, December.
    9. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.
    10. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Response," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 313-315, October.
    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. Jack L. Hervey & Loula S. Merkel, 2000. "A record current account deficit: causes and implications," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 25(Q IV), pages 2-13.

    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. Nelson, Charles R., 1988. "Spurious trend and cycle in the state space decomposition of a time series with a unit root," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 475-488.
    2. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.
    3. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    4. Robert J. Hodrick, 2020. "An Exploration of Trend-Cycle Decomposition Methodologies in Simulated Data," NBER Working Papers 26750, National Bureau of Economic Research, Inc.
    5. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    6. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    7. Paolo Guarda, 2002. "Potential output and the output gap in Luxembourg: some alternative methods," BCL working papers 4, Central Bank of Luxembourg.
    8. Yýlmaz Akdi & Serdar Varlik & Hakan Berument, 2018. "Cycle Duration in Production with Periodicity – Evidence from Turkey," International Econometric Review (IER), Econometric Research Association, vol. 10(2), pages 24-32, September.
    9. Willie Lahari, 2011. "Assessing Business Cycle Synchronisation - Prospects for a Pacific Islands Currency Union," Working Papers 1110, University of Otago, Department of Economics, revised Oct 2011.
    10. Perron, Pierre, 1992. "Racines unitaires en macroéconomie : le cas d’une variable," L'Actualité Economique, Société Canadienne de Science Economique, vol. 68(1), pages 325-356, mars et j.
    11. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    12. Alain Guay & Pierre St-Amant, 1996. "Do Mechanical Filters Provide a Good Approximation of Business Cycles?," Technical Reports 78, Bank of Canada.
    13. Morley, James & Piger, Jeremy, 2008. "Trend/cycle decomposition of regime-switching processes," Journal of Econometrics, Elsevier, vol. 146(2), pages 220-226, October.
    14. Catherine Doz & Guillaume Rabault & Nicolas Sobczak, 1995. "Décomposition tendance-cycle : estimations par des méthodes statistiques univariées," Économie et Prévision, Programme National Persée, vol. 120(4), pages 73-93.
    15. Everts, Martin, 2006. "Duration of Business Cycles," MPRA Paper 1219, University Library of Munich, Germany.
    16. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    17. Biolsi, Christopher, 2023. "Do the Hamilton and Beveridge–Nelson filters provide the same information about output gaps? An empirical comparison for practitioners," Journal of Macroeconomics, Elsevier, vol. 75(C).
    18. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Further evidence on forecasting international GNP growth rates using unobserved components transfer function models," Documentos de Trabajo del ICAE 9312, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    19. Arkadiusz Kijek, 2017. "Spectral analysis of business cycles in Poland and its major trading partners," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 57-75.
    20. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.

    More about this item

    Keywords

    economic conditions - United States; Inflation (Finance); Business cycles;
    All these keywords.

    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:fip:fedhwp:wp-99-22. 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: Lauren Wiese (email available below). General contact details of provider: https://edirc.repec.org/data/frbchus.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.