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....

Experts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and...

This paper conjectures that the behaviour of experts who adjust statistical-model-based forecasts obeys the Law of Small Numbers [LSN]. To put this hypothesis to an empirical test, I propose a simple but effective methodology. It is applied to a database containing information on many experts...

The brand choice problem in marketing has recently been addressed with methods from computational intelligence such as neural networks. Another class of methods from computational intelligence, the so-called ensemble methods such as boosting and stacking have never been applied to the brand...

In this paper we give a short novel proof of the well-known Lagrange multiplier rule, discuss the sources of the power of this rule and consider several applications of this rule. The new proof does not use the implicit function theorem and combines the advantages of two of the most well-known...

This paper builds on De Groot and Franses (2005) (Econometric Institute Report 2005-01). It modifies the EICIE, the Econometric Institute Current Indicator of the Economy, by allowing for two regimes. These regimes are marked by positive or negative annual growth in the staffing services data....