This paper describes and analyzes the 1990-92 economic forecasts of a Bayesian vector autoregression model developed by researchers at the Minneapolis Fed. The model's 1990 forecast was pretty bad - too optimistic about both inflation and economic growth, especially growth in consumption and...

This paper reports an optimistic forecast of U.S. output and inflation trends in 1990_91. Generated by a Bayesian vector autoregression (BVAR) model of the U.S. economy using data available on November 30, 1989, the forecast is more optimistic than a consensus forecast. The key to the model's...

This paper discusses at an undergraduate level how forecast rationality can be tested. It explains that forecasters should correctly use any relevant information they knew in making their predictions. It shows that forecast rationality can be tested by determining whether the forecasters'...

The method proposed here includes two innovations which should improve the accuracy of econometric forecasting. First, it replaces the subjective, judgmental adjustments commonly used with a more formal, objective econometric procedure. Second, it includes a methodology for testing the...

The paper discusses a new, fully recursive approach to the adaptive modeling, forecasting and seasonal adjustment of nonstationary economic time-series. The procedure is based around a time variable parameter (TVP) version of the well known “component” or “structural” model. It employs a...

This paper describes recent modifications to the mixed-frequency model vector autoregression (MF-VAR) constructed by Schorfheide and Song (2012). The changes to the model are restricted solely to the set of variables included in the model; all other aspects of the model remain unchanged....

Some argue that central banks can improve monetary policy by including confidential supervisory assessments of banking organizations in their forecasts of inflation and unemployment. In this study we examine the extent to which forecasts of these variables would have been improved with the...

Doan, Litterman, and Sims (DLS) have suggested using conditional forecasts to do policy analysis with Bayesian vector autoregression (BVAR) models. Their method seems to violate the Lucas critique, which implies that coefficients of a BVAR model will change when there is a change in policy...

This model extends one originally constructed by Robert Litterman in 1980 and used continuously since then to prepare quarterly forecasts. The current version is 3 variables larger than Litterman’s original model, and it now allows time variation in coefficients, predictable time variation in...