Forecasting Inflation With A Financial Conditions Index: The Case Of Singapore

This paper explores whether a financial conditions index (FCI) can serve as a good predictor of inflation and hence, a useful guide to monetary policy in the context of Singapore by constructing an index that comprises interest rates, exchange rates, credit expansions, stock prices and house prices. The choice of these variables is motivated by the role they play in the monetary transmission mechanism and how they contribute to inflationary pressures in an economy. A weighted-sum approach is adopted for index construction whereby the weight assigned to each component is derived from the generalized impulse responses of a monetary VAR model estimated using quarterly data. Cross-correlations and Granger causality tests confirm the proposed index possesses good in-sample leading qualities over consumer price inflation. Using this index to generate predictions recursively from a direct multistep forecasting methodology yields substantial gains in out-of-sample prediction performance when compared with forecasts of a benchmark autoregressive model for inflation within the one-year forecast horizon.