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Nowcasting with Backcalculated Short Time Series Simulations & Empirical Evidence

Author

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  • 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
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    References listed on IDEAS

    as
    1. Tommaso Fonzo, 2003. "Constrained retropolation of high-frequency data using related series: A simple dynamic model approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 109-119, February.
    2. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    3. George Kapetanios & Fotis Papailias, 2022. "Real Time Indicators During the COVID-19 Pandemic Individual Predictors & Selection," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-15, Economic Statistics Centre of Excellence (ESCoE).
    4. Massimiliano Caporin & Domenico Sartore, 2006. "Methodological aspects of time series back-calculation," Working Papers 2006_56, Department of Economics, University of Venice "Ca' Foscari".
    5. George Kapetanios & Fotis Papailias, 2022. "An Evaluation Framework for Targeted Indicators Aggregates vs. Disaggregates," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-17, Economic Statistics Centre of Excellence (ESCoE).
    6. George Kapetanios & Fotis Papailias, 2021. "UK Economic Conditions during the Pandemic: Assessing the Economy using ONS Faster Indicators," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-10, Economic Statistics Centre of Excellence (ESCoE).
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    More about this item

    Keywords

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    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

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