IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/6213.html
   My bibliography  Save this paper

Data graduation based on statistical time series methods

Author

Listed:
  • Guerrero, Victor M.
  • Juárez, Rodrigo
  • Poncela, Pilar

Abstract

Whittaker's method is one of the most frequently employed techniques to graduate mortality tables. In order for the method to work and produce reasonable results, some subjective input is required from the graduator. In this paper we show that Whittaker' s solution to the graduation problem can be approached from a statistical time series model-based perspective that reduces the subjectivity in its application. It also serves to interpret the graduation problem as a classical estimation problem. In fact, on the basis of some suitable assumptions, we are able to show thatthe Best Linear Unbiased Estimator of the true mortality rates has the form of Whittaker's solution. We also provide some complementary analytical tools aimed at helping the graduator to employ the method in practice and interpret its results from a statistical standpoint. A numerical illustration is shown in detail to exemplify the application of our proposal.

Suggested Citation

  • Guerrero, Victor M. & Juárez, Rodrigo & Poncela, Pilar, 1997. "Data graduation based on statistical time series methods," DES - Working Papers. Statistics and Econometrics. WS 6213, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:6213
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/6075ef59-78ea-409c-a48c-17360e2cbc98/content
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Verrall, R. J., 1993. "A state space formulation of Whittaker graduation, with extensions," Insurance: Mathematics and Economics, Elsevier, vol. 13(1), pages 7-14, September.
    2. Taylor, Greg, 1992. "A Bayesian interpretation of Whittaker--Henderson graduation," Insurance: Mathematics and Economics, Elsevier, vol. 11(1), pages 7-16, April.
    3. Guerrero, Victor M., 1993. "Combining historical and preliminary information to obtain timely time series data," International Journal of Forecasting, Elsevier, vol. 9(4), pages 477-485, December.
    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. Victor M. Guerrero, 2008. "Estimating Trends with Percentage of Smoothness Chosen by the User," International Statistical Review, International Statistical Institute, vol. 76(2), pages 187-202, August.
    2. Guerrero, Victor M., 2007. "Time series smoothing by penalized least squares," Statistics & Probability Letters, Elsevier, vol. 77(12), pages 1225-1234, July.
    3. Cortez, Willy Walter & Islas-Camargo, Alejandro, 2009. "How Correlated are Mexico’s Salaries and Us Output? an Inquiry on Some Us Border Cities," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(08), pages 35-62, primer se.

    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. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    2. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    3. Victor Guerrero, 2005. "Restricted estimation of an adjusted time series: application to Mexico's industrial production index," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(2), pages 157-177.
    4. Ruiz, Edilberto & Nieto, Fabio H., 2000. "A note on linear combination of predictors," Statistics & Probability Letters, Elsevier, vol. 47(4), pages 351-356, May.
    5. Dean Croushore, 2009. "Commentary on Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 371-382.
    6. Weinert, Howard L., 2007. "Efficient computation for Whittaker-Henderson smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 959-974, October.
    7. Victor Guerrero & Edmundo Berumen, 1998. "Forecasting electricity consumption with extra-model information provided by consumers," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 283-299.
    8. Ciccarelli, Matteo & Altavilla, Carlo, 2007. "Information combination and forecast (st)ability evidence from vintages of time-series data," Working Paper Series 846, European Central Bank.

    More about this item

    Keywords

    Best linear unbiased estimation;

    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:cte:wsrepe:6213. 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: Ana Poveda (email available below). General contact details of provider: http://portal.uc3m.es/portal/page/portal/dpto_estadistica .

    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.