Forecasting Inflation using Labour Market Indicators

Abstract

There are a large number of labour market indicators that could be used by monetary policy makers to assess the state of the labour market and the associated implications for inflationary pressure. This paper attempts to assess their relative merits by evaluating their past performance in forecasting movements in price and wage inflation. This is done by considering both their ex post performance in predicting inflation - using conventional in-sample Granger causality tests - and their performance ex ante - using simulated out-of-sample forecasting tests over the period 1985-2000, based on both recursive and rolling-window estimation. These criteria lead to rather different conclusions. In sample, most labour market indicators appear to be statistically significant in an inflation-forecasting equation, but out of sample a much smaller number of labour market indicator models are better at forecasting inflation than a simple autoregression, with virtually none outperforming this benchmark over the period since 1995. The labour market indicator models that perform relatively well out of sample tend to be sensitive to the precise choice of inflation measure, sample period and estimation method, though there is some evidence that pooling across individual forecasts produces more reliable results. One apparently robust result, however, is that the unemployment rate gap, the most commonly used measure of labour market tightness, performs poorly in out-of-sample forecasts across a range of specifications.