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.
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