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The Contribution of Structural Break Models to Forecasting Macroeconomic Seri...
This paper compares the forecasting performance of models that have been proposed for forecasting in the presence of structural breaks. They differ in their treatment of the... -
Learning, forecasting and structural breaks (replication data)
We provide a general methodology for forecasting in the presence of structural breaks induced by unpredictable changes to model parameters. Bayesian methods of learning and... -
An evaluation of the forecasts of the federal reserve: a pooled approach (rep...
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... -
Permanent vs transitory components and economic fundamentals (replication data)
Any non-stationary series can be decomposed into permanent (or trend) and transitory (or cycle) components. Typically some atheoretic pre-filtering procedure is applied to... -
Censored latent effects autoregression, with an application to US unemploymen...
A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond... -
Measuring predictability: theory and macroeconomic applications (replication ...
We propose a measure of predictability based on the ratio of the expected loss of a short-run forecast to the expected loss of a long-run forecast. This predictability measure... -
Forecasting exchange rates using feedforward and recurrent neural networks (r...
In this paper we investigate the out-of-sample forecasting ability of feedforward and recurrent neural networks based on empirical foreign exchange rate data. A two-step... -
Forecasting in cointegrated systems (replication data)
We consider the implications for forecast accuracy of imposing unit roots and cointegrating restrictions in linear systems of I(1) variables in levels, differences, and...
