Estimation results in linear regression models are sometimes in contrast with what was expected on the basis of a certain set of hypotheses or theory, in the sense that one or more parameters have the "wrong sign". One could be inclined to think that this is due to collinearity across...

This book has grown out of half a century of experience of teaching undergraduate econometrics at the Econometric Institute in Rotterdam. It combines a solid exposition of econometric methods with the application-oriented approach that is characteristic of the Rotterdam tradition in...

Purpose: The purpose of this paper is to show that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias. Design/methodology/approach: A forecast model integrates historical...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...