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Analyzing and forecasting business cycles in a small open economy: A dynamic factor model for Singapore

Author

Listed:
  • Hwee Kwan Chow

  • Keen Meng Choy

Abstract

A dynamic factor model is applied to a large panel dataset of Singapore’s macroeconomic variables and global economic indicators with the initial objective of analysing business cycles in a small open economy. The empirical results suggest that four common factors – which can broadly be interpreted as world, regional, electronics and domestic economic cycles – capture a large proportion of the co-variation in the quarterly time series. The estimated factor model also explains well the observed fluctuations in real economic activity and price inflation, leading us to use it in forecasting Singapore’s business cycles. We find that the forecasts generated by the factors are generally more accurate than the predictions of univariate models and vector autoregressions that employ leading indicators.

Suggested Citation

  • Hwee Kwan Chow & Keen Meng Choy, 2009. "Analyzing and forecasting business cycles in a small open economy: A dynamic factor model for Singapore," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2009(1), pages 19-41.
    • Handle: RePEc:oec:stdkab:5ksb9df5nqbs
    DOI: 10.1787/jbcma-v2009-art3-en
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    Cited by:

    1. Mariano, Roberto S. & Ozmucur, Suleyman, 2015. "High-Mixed-Frequency Dynamic Latent Factor Forecasting Models for GDP in the Philippines/Modelos de factores dinámicos latentes con datos mixtos de alta frecuencia aplicados a la predicción del PIB en," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 451-462, Mayo.
    2. Mapa, Dennis S. & Simbulan, Maria Christina, 2014. "Analyzing and Forecasting Movements of the Philippine Economy using the Dynamic Factor Models (DFM)," MPRA Paper 54478, University Library of Munich, Germany.
    3. Hwee Kwan Chow & Keen Meng Choy, 2009. "Monetary Policy And Asset Prices In A Small Open Economy: A Factor-Augmented Var Analysis For Singapore," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-23.
    4. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    5. Mendoza, Liu & Morales, Daniel, 2013. "Construyendo un índice coincidente de recesión: Una aplicación para la economía peruana," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 26, pages 81-100.
    6. Mendoza, Liu & Morales, Daniel, 2012. "Constructing a real-time coincident recession index: an application to the Peruvian economy," Working Papers 2012-020, Banco Central de Reserva del Perú.
    7. Kong Yam Tan & Tilak Abeysinghe & Khee Giap Tan, 2015. "Shifting Drivers of Growth: Policy Implications for ASEAN-5," Asian Economic Papers, MIT Press, vol. 14(1), pages 157-173, Winter/Sp.

    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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