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Can inflation data improve the real-time reliability of output gap estimates?...
Potential output plays a central role in monetary policy and short-term macroeconomic policy making. Yet, characterizing the output gap involves a trend-cycle decomposition, and... -
Evaluating interval forecasts of high-frequency financial data (replication d...
A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing... -
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... -
This is what the leading indicators lead (replication data)
We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy... -
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... -
Tests for multiple forecast encompassing (replication data)
In the evaluation of economic forecasts, it is frequently the case that comparisons are made between a number of competing predictors. A natural question to ask in such contexts... -
Business cycle non-linearities in UK consumption and production (replication ...
This paper develops non-linear smooth transition autoregressive (STAR) models with two additive smooth transition components to capture the business cycle characteristics of UK... -
Exchange rates and monetary fundamentals: what do we learn from long-horizon ...
The use of a new bootstrap method for small-sample inference in long-horizon regressions is illustrated by analysing the long-horizon predictability of four major exchange... -
A Monte Carlo study of the forecasting performance of empirical SETAR models ...
In this paper we investigate the multi-period forecast performance of a number of empirical self-exciting threshold autoregressive (SETAR) models that have been proposed in the... -
Optimal univariate inflation forecasting with symmetric stable shocks (replic...
Monthly inflation in the United States indicates non-normality in the form of either occasional big shocks or marked changes in the level of the series. We develop a univariate... -
NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR-MODELS (replic...
In Bayesian analysis of vector autoregressive models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior... -
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...