The Federal Reserve Greenbook forecasts of real GDP, inflation and unemployment are analysed for the period 1974-1997. We consider whether these forecasts exhibit systematic bias, and whether efficient use is made of information, that is, whether revisions to these forecasts over time are...

Using the Carlson and Parkin (1975) framework and employing the Pesaran–Timmermann (1992) Predictive Failure statistic, we evaluate several consensus forecast series from CESIfo's World Economic Survey. Several issues are examined related to interpreting qualitative survey responses. We define...

Recent research has documented that the Federal Reserve produces systematic errors in forecasting inflation, real GDP growth, and the unemployment rate, even though these forecasts are unbiased. We show that these systematic errors reveal that the Fed is “surprised” by real and inflationary...

This paper reconciles contradictory findings obtained from forecast evaluations: the existence of systematic errors and the failure to reject rationality in the presence of such errors. Systematic errors in one economic state may offset the opposite types of errors in the other state such that...

The relationship between two sets of GNP data, the earliest and the first revisions, is examined. This comparison enables us to determine whether the early numbers are valuable to forecasters. The analysis uses two methods. The first is based on a technique which has been used to evaluate...

The objective of the study is building and using macroeconometric model which ensures analyzing and forecasting the (short run) impacts of various policy measures and external shocks, particularly changes in the oil price, foreign price and income on the Azerbaijani economy.Cointegration and...

The knowledge production function is central to research and development-based growth models. This paper empirically investigates the knowledge production function and intertemporal spillover effects using cointegration techniques. Timeseries evidence suggests there are two long-run...