Improving Unemployment Rate Forecasts Using Survey Data
This paper investigates whether forecasts of the Swedish unemployment rate can be improved by using business or household survey data. We conduct a simulated out-of-sample forecast exercise in which the performance of a Bayesian VAR model with only macroeconomic variables is compared to that when the model also includes variables based on survey data. Results show that the forecasting performance at short horizons can be improved. The improvement is largest when forward-looking variables based on data from the manufacturing industry are employed.
Volume (Year): 23 (2010)
Issue (Month): 1 (Spring)
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