Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/bes/jnlbes/v14y1996i3p374-86.html
   My bibliography  Save this article

Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?

Author

Listed:
  • Ghysels, Eric
  • Granger, Clive W J
  • Siklos, Pierre L
Abstract
The authors investigate whether seasonal adjustment procedures are linear data transformations. This question was addressed by A. H. Young (1968) and is important for the estimation of regression models with seasonally adjustment data. The authors focus on the X-11 program and rely on simulation evidence, involving linear unobserved component autorgressive integrated moving average models. They define and test a set of properties for the adequacy of a linear approximation to a seasonal adjustment filter. Next, the authors study the effect of X-11 on regression statistics assessing the statistical significance between economic variables. Several empirical results involving economic data are also reported.

Suggested Citation

  • Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    • Handle: RePEc:bes:jnlbes:v:14:y:1996:i:3:p:374-86
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nabeya, S. & Perron, P., 1994. "Approximations to Some Exact Distributions in the First Order Autogressive Model with Dependent Errors," Cahiers de recherche 9420, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    3. Burridge, Peter & Wallis, Kenneth F, 1984. "Unobserved-Components Models for Seasonal Adjustment Filters," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 350-359, October.
    4. Ghysels, Eric & Perron, Pierre, 1993. "The effect of seasonal adjustment filters on tests for a unit root," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 57-98.
    5. Cannings, Kathy & Montmarquette, Claude & Mahseredjian, Sophie, 1996. "Entrance quotas and admission to medical schools: a sequential probit model," Economics of Education Review, Elsevier, vol. 15(2), pages 163-174, April.
    6. Cannings, K. & Montmarquette, C. & Mahseredjian, S., 1994. "Major Choice: Undergraduate Concentrations and the Probability of Graduation," Cahiers de recherche 9419, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Ghysels, Eric, 1997. "Seasonal Adjustment and Other Data Transformations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 410-418, October.
    8. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    9. Ng, Serena & Schaller, Huntley, 1996. "The Risky Spread, Investment, and Monetary Policy Transmission: Evidence on the Role of Asymmetric Information," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 375-383, August.
    10. Luiz Koodi Hotta, 1989. "Identification Of Unobserved Components Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(3), pages 259-270, May.
    11. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    12. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
    13. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    14. Fisher, Timothy C G & Martel, Jocelyn, 1995. "The Creditors' Financial Reorganization Decision: New Evidence from Canadian Data," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 11(1), pages 112-126, April.
    15. Vogelsang, Timothy J & Perron, Pierre, 1998. "Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1073-1100, November.
    16. Boyer, Marcel & Laffont, Jean-Jacques, 1997. "Environmental risks and bank liability," European Economic Review, Elsevier, vol. 41(8), pages 1427-1459, August.
    17. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-287, April.
    18. Parent, Daniel, 1996. "Survol des contributions théoriques et empiriques liées au capital humain," L'Actualité Economique, Société Canadienne de Science Economique, vol. 72(3), pages 315-356, septembre.
    19. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
    20. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
    21. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    22. Schwert, G. William, 1987. "Effects of model specification on tests for unit roots in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 20(1), pages 73-103, July.
    23. Grether, D M & Nerlove, M, 1970. "Some Properties of 'Optimal' Seasonal Adjustment," Econometrica, Econometric Society, vol. 38(5), pages 682-703, September.
    24. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Time Series: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 343-349, October.
    25. Maravall, Agustin, 1988. "A note on minimum mean squared error estimation of signals with unit roots," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 589-593.
    26. Ghysels, E. & Lieberman, O., 1993. "Dynamic Regression and Filtered Data Series: A Laplace Approximation to the Effects of Filtering in Small Samples," Cahiers de recherche 9335, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    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. Yves Sprumont, 1998. "On the Game-Theoretic Structure of Public-Good Economies," International Journal of Game Theory, Springer;Game Theory Society, vol. 26(4), pages 455-472.
    2. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, April.
    3. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    4. Andreas Humpe & Peter Macmillan, 2007. "Can macroeconomic variables explain long term stock market movements? A comparison of the US and Japan," CDMA Working Paper Series 200720, Centre for Dynamic Macroeconomic Analysis.
    5. Vicente Esteve, 2004. "Política fiscal y productividad del trabajo en la economía española: un análisis de series temporales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 3-29, June.
    6. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    7. Kaiser, Regina & Maravall, Agustin, 2005. "Combining filter design with model-based filtering (with an application to business-cycle estimation)," International Journal of Forecasting, Elsevier, vol. 21(4), pages 691-710.
    8. Ghysels, E., 1993. "A Time Series Model with Periodic Stochastic Regime Switching," Cahiers de recherche 9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Christopher J. Neely & David E. Rapach, 2008. "Real interest rate persistence: evidence and implications," Review, Federal Reserve Bank of St. Louis, vol. 90(Nov), pages 609-642.
    10. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
    11. Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Irma Hindrayanto & Jan Jacobs & Denise Osborn, 2014. "On trend-cycle-seasonal interactions," DNB Working Papers 417, Netherlands Central Bank, Research Department.
    13. A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," Economics Discussion Paper Series 0304, Economics, The University of Manchester.
    14. Tomas del Barrio Castro & Denise R. Osborn, 2006. "A Random Walk through Seasonal Adjustment: Noninvertible Moving Averages and Unit Root Tests," Economics Discussion Paper Series 0612, Economics, The University of Manchester.
    15. Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    16. Rapach, David E. & Weber, Christian E., 2004. "Are real interest rates really nonstationary? New evidence from tests with good size and power," Journal of Macroeconomics, Elsevier, vol. 26(3), pages 409-430, September.
    17. Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2004. "On Markov error-correction models, with an application to stock prices and dividends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 69-88.
    18. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.
    19. Pesaran, M.H. & Ruge-Murcia, F.J., 1995. "A Discrete-Time Version of Target Zone Models with Jumps," Cahiers de recherche 9530, Universite de Montreal, Departement de sciences economiques.
    20. Muhammad Ahad, 2016. "Nexus between Income Inequality, Crime, Inflation and Poverty: NewEvidence fromStructural Breaksfor Pakistan," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 4(3), pages 133-145, March.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:bes:jnlbes:v:14:y:1996:i:3:p:374-86. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main .

    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.