The Dutch railway network experiences about three large disruptions per day on average. In this paper, we present an algorithm to reschedule the crews when such a disruption occurs. The algorithm is based on column generation techniques combined with Lagrangian heuristics. Since the number of...

In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AO's). We show analytically that both the asymptotic size and power are adversely affected...

Direct extrapolation of survey results on purchase intentions may give a biased view on actual consumer behavior. This is because the purchase intentions of consumers may be affected by the survey itself. On the positive side, such effects can be incorporated in econometric models to get...

In this paper we deal with sensitivity analysis in convex quadratic programming, without making assumptions on nondegeneracy, strict convexity of the objective function, and the existence of a strictly complementary solution. We show that the optimal value as a function of a right--hand side...

Forecasts from various experts are often used in macroeconomic forecasting models. Usually the focus is on the mean or median of the survey data. In the present study we adopt a different perspective on the survey data as we examine the predictive power of disagreement amongst forecasters. The...

Econometric models for economic time series may include harmonic regressors to describe cyclical patterns in the data. This paper focuses on the possibility that the cycle periods in these regressors change over time. To this end, a smooth regime-switching harmonic regression is proposed, and a...

The high ranking of the Econometric Institute, as listed in recent leading scientific journals, is examined for a fifty year period using similar standard measures. The distribution of the publications over different research areas is analyzed and a time-series model is specified to describe and...

Scanner data for fast moving consumer goods typically amount to panels of time series where both N and T are large. To reduce the number of parameters and to shrink parameters towards plausible and interpretable values, multi-level models turn out to be useful. Such models contain in the second...

In this paper we examine the forecasting performance of five nonlinear GARCH(1,1) models. Four of these have recently been proposed in literature, while the fifth model is a new one. All five models allow for switching persistence of shocks, depending on the value and/or sign of recent returns....

To enable answering the question in the title, we introduce a bivariate censored latent effects autoregression, and discuss representation, parameter estimation, diagnostics and inference. We show that this bivariate nonlinear model is very useful for examining common nonlinearity. We apply the...