Real-time data on national accounts statistics typically undergo an extensive revision process, leading to multiple vintages on the same generic variable. The time between the publication of the initial and final data is a lengthy one and raises the question of how to model and forecast the...

In an almost unreferenced article Carmichael (1928), writing of the period around the First World War, noted that “During the past twelve years many economic series have undergone what appears to be a permanent change in level.” These are prescient words that are widely applicable today....

The problem of optimal linear filtering, smoothing and trend extraction for m-period differences of processes with a unit root is studied. Such processes arise naturally in economics and finance, in the form of rates of change (price inflation, economic growth, financial returns) and finding an...

The development of the methods of correlation and regression analysis at the turn of the 20th century, led to their use in attempting to identify relationships between economic variables. However, caution was soon expressed that correlating series with ‘secular’ trends was likely to be...

This study evaluates a number of methods of reducing the bias and mean squared error of log-periodogram (LP) based methods to estimate the long-memory parameter and, in addition, assesses the actual coverage of the associated confidence intervals, considering both tails and the width of the...

This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook...

Does theory aid inflation forecasting? To date, the evidence suggests that there is no systematic advantage of theory-based models of inflation dynamics over their astructural counterparts. This study reconsiders the issue by developing a “semi-structural” forecasting procedure comprised of...

The detection of long-range dependence in time series analysis is an important task to which this paper contributes by showing that whilst the theoretical definition of a long-memory (or long-range dependent) process is based on the autocorrelation function, it is not possible for long memory to...