Pooling forecasts in linear rational expectations models
Estimating linear rational expectations models in a limited-information setting requires replacing the expectations of future, endogenous variables either with instrumented, actual values or with forecast survey data. Applying the method of Gottfries and Persson [Empirical examinations of the information sets of economic agents. Quarterly Journal of Economics 103, 251-259], I show how to augment these methods with actual, future values of the endogenous variables to improve statistical efficiency. The method is illustrated with an application to the US hybrid new Keynesian Phillips curve, where traditional, lagged instruments and the median forecast from the Survey of Professional Forecasters both appear to miss significant information used by price-setters, so that forecast pooling with actual values improves the statistical fit to inflation.
Year of publication: |
2009
|
---|---|
Authors: | Smith, Gregor W. |
Published in: |
Journal of Economic Dynamics and Control. - Elsevier, ISSN 0165-1889. - Vol. 33.2009, 11, p. 1858-1866
|
Publisher: |
Elsevier |
Keywords: | Forecast pooling Recursive projection New Keynesian Phillips curve |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Great moderations and US interest rates: Unconditional evidence
Nason, James M., (2008)
-
Interwar Deflation and Depression
Dorval, Bill, (2013)
-
Measuring the Slowly Evolving Trend in US Inflation with Professional Forecasts
Nason, James M., (2013)
- More ...