IDEAS home Printed from https://ideas.repec.org/p/eoe/escoed/escoe-dp-2023-08.html

Nowcasting with Backcalculated Short Time Series Simulations & Empirical Evidence

Author

Listed:
  • Kapetanios, George
  • Papailias, Fotis

Abstract

This paper is concerned with the backcalculation of short explanatory time series when the dependent variable is longer. In particular, we consider two competing linear regression models: (i) the main model which is estimated in the overlapping period when all time series are available, and (ii) the suggested model which produces the estimates in two steps; first, we create backcalculated values of the explanatory time series using some auxiliary variables (which are observed at the same -longer- time history as the target variable) in the overlapping time period and, using these coefficient estimates, we extend the short explanatory time series and estimate a model which regresses the dependent variable on this new set of variables. This research provides both simulations and empirical evidence in favour of the suggested method.

Suggested Citation

  • Kapetanios, George & Papailias, Fotis, 2023. "Nowcasting with Backcalculated Short Time Series Simulations & Empirical Evidence," Discussion Papers escoe-dp-2023-08, Economic Statistics Centre of Excellence.
    • Handle: RePEc:eoe:escoed:escoe-dp-2023-08
    as

    Download full text from publisher

    File URL: https://www.repository-escoe.com/id/eprint/17/1/ESCoE%20DP%202023-08.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:eoe:escoed:escoe-dp-2023-08. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Communications Manager (email available below). General contact details of provider: https://edirc.repec.org/data/escoeuk.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.