70 datasets found

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...

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...

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...

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...

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...

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...

This paper develops non-linear smooth transition autoregressive (STAR) models with two additive smooth transition components to capture the business cycle characteristics of UK...

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...

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...

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...

A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond...

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...

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...

Using annual data for 1872-1997, this paper re-examines the predictability of real stock prices based on price-dividend and price-earnings ratios. In line with the extant...

This paper proposes a vector equilibrium correction model of stock returns that exploits the information in the futures market, while allowing for both regime-switching...

We compare 330 ARCH-type models in terms of their ability to describe the conditional variance. The models are compared out-of-sample using DM?$ exchange rate data and IBM...

We propose a general double tree structured AR-GARCH model for the analysis of global equity index returns. The model extends previous approaches by incorporating (i) several...

This paper proposes a model to predict recessions that accounts for non-linearity and a structural break when the spread between long- and short-term interest rates is the...

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...

Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the...