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Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017

Author

Listed:
  • Koop, Gary

    (University of Strathclyde)

  • McIntyre, Stuart

    (University of Strathclyde)

  • Mitchell, James

    (University of Warwick)

  • Poon, Aubrey

    (University of Strathclyde)

Abstract

Output growth estimates for the regions of the UK are currently published at the annual frequency only, released with a long delay and offer limited historical coverage. To improve the regional database this paper develops a mixed-frequency multivariate model and uses it to produce consistent estimates of quarterly regional output growth dating back to 1970. We describe how these estimates are updated and evaluated on an ongoing, quarterly basis to publish online (at www.escoe.ac.uk/regionalnowcasting) more timely regional growth estimates. We illustrate how the new quarterly data can contribute to our historical understanding of business cycle dynamics and connectedness between regions.

Suggested Citation

  • Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
  • Handle: RePEc:wrk:wrkemf:20
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Meredith M. Paker, 2020. "The Jobless Recovery After the 1980-1981 UK Recession," Oxford Economic and Social History Working Papers _182, University of Oxford, Department of Economics.
    2. Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.
    3. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
    4. Marianne Sensier & Fiona Devine, 2019. "Understanding Regional Economic Performance and Resilience in the UK: Trends Since the Global Financial Crisis," Economics Discussion Paper Series 1912, Economics, The University of Manchester.
    5. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
    6. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
    7. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
    8. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    9. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org.

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    More about this item

    Keywords

    Regional data; Mixed frequency; Temporal disaggregation; Nowcasting; Bayesian methods; Real-time data; Vector autoregressions; JEL Classification Numbers: C32 ; C51 ; C53; E37;
    All these 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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