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Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency

Author

Listed:
  • Chinara Azizova
  • Bruno Feunou
  • James Kyeong

Abstract

In this paper, we estimate the distribution of future inflation and growth in real gross domestic product (GDP) for the Canadian economy at a daily frequency. To do this, we model the conditional moments (mean, variance, skewness and kurtosis) of inflation and GDP growth as moving averages of economic and financial conditions. Then, we translate the conditional moments into conditional distributions using a flexible parametric distribution known as the skewed generalized error distribution. We show that the probabilities of inflation and GDP growth derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022. Our methodology offers daily-frequency forecasts with flexible forecasting horizons. This is highly useful in an environment of elevated uncertainty surrounding the inflation and growth outlook.

Suggested Citation

  • Chinara Azizova & Bruno Feunou & James Kyeong, 2023. "Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency," Discussion Papers 2023-19, Bank of Canada.
    • Handle: RePEc:bca:bocadp:23-19
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    References listed on IDEAS

    as
    1. Nathan Bedock & Dalibor Stevanovic, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics, Canadian Economics Association, vol. 50(2), pages 541-570, May.
    2. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    3. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
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    More about this item

    Keywords

    Econometric and statistical methods; Business fluctuations and cycles;

    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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