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Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)

Author

Listed:
  • Miroslav Klucik

    (Council for Budget Responsibility)

Abstract

Real GDP and its structure are available within 70 days after the end of the reference quarter. By using leading indicators of higher frequency, it is possible to nowcast GDP in real-time. With an assumption of unobserved factor driving the business cycle we estimate dynamic factor models for real GDP, its demand components, inflation, wages and employment using statistically significant domestic and foreign indicators. To ensure the consistency of out-of-sample forecasts for GDP and its components, past forecast deviations and correlation coefficients are used to adjust the forecast, which helps to reduce the bias of individual models. Forecasts using real-time database are carried out since the 1st January of 2017 using daily data vintages. Real-time forecasts display a reduction of forecasting error with the arrival of new data in the last month of the quarter until the official publication. The main role of nowcasting in CBR is to track the actual positive and negative macroeconomic risks of the Slovak economy in relation to the latest official national macroeconomic forecast by the Macroeconomic Forecasting Committee. Additionally, the nowcast models help to improve precision of estimates of initial conditions of the economy by bridging the short-term forecast and mid-term forecast.

Suggested Citation

  • Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
    • Handle: RePEc:cbe:wpaper:201901
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    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
    3. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    4. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    5. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
    6. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    7. Eddie Casey & Diarmaid Smyth, 2016. "Revisions to Macroeconomic Data: Ireland and the OECD," The Economic and Social Review, Economic and Social Studies, vol. 47(1), pages 33-68.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Nowcasting; dynamic factor model; business cycle; Kalman filter; Slovak economy; demand components; short-term forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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