This paper is concerned with modelling time series by single hidden-layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...

This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three well-known neural network modelling...

In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...

Behavioral economics provides several motivations for the common observation that agents appear somewhat unwilling to deviate from recent choices: salience, inertia, the formation of habits, the use of rules of thumb, or the locking in on certain modes of behavior due to learning by doing. This...

This paper identifies the pertinent institutions governing the structure of payoffs with regard to female career progression. Drawing on recent insights in behavioral economics, we hypothesize that interactions between psychological mechanisms and the institutional setup may be important...

This paper deals with the question how to model health effects after the cessation of a randomised controlled trial (RCT). Using clinical trial data on severe congestive heart failure patients we illustrate how survival beyond the cessation of a RCT can be predicted based on parametric survival...