Based on simple time series plots and periodic sample autocorrelations, we document that monthly river flow data display long memory, in addition to pronounced seasonality. In fact, it appears that the long memory characteristics vary with the season. To describe these two properties jointly, we...

We discuss computational aspects of likelihood-based specification, estimation,inference, and forecasting of possibly nonstationary series with long memory. We use the \ARFIMA$(p,d,q)$ model with deterministic regressors and we compare sampling characteristics of approximate and exact...

We discuss specification, frequency domain estimation and application of flexible fractionally integrated seasonal long memory time series models, which allow for 'chi-squared' (seasonal) unit root testing. We suggest periodogram regression and approximate ML estimation. We successfully apply a...

A key application of long memory time series models concerns inflation. Long memory implies that shocks have a long-lasting effect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for inflation,...

-Theory- Two theories about trends in left-right political orientations are juxtaposed: the persistence theory claiming that left-right orientations are highly resistant to change versus the irrelevance theory anticipating a move of mass publics towards the center of the left-right continuum....

Trends in software development for applied econometrics emerge from an analysis of the research articles and software reviews of the Journal of Applied Econometrics, appearing since 1986. The data and code archive of the journal provides more specific information on software use for applied...

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...