It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean squared error (PMSE) in simulated out-of-sample (SOOS) forecasts. Alternatively, forecast models may be selected using information criteria (IC). We compare the asymptotic and...

In this paper, we propose a new Empirical Information Criterion (EIC) for model selection which penalizes the likelihood of the data by a function of the number of parameters in the model. It is designed to be used where there are a large number of time series to be forecast. However, a...

Automated model searches using information criteria are used for the estimation of linear single equation models. Genetic algorithms are described and used for this purpose. These algorithms are shown to be a practical method for model selection when the number of sub-models are very large....

The purpose of the paper is to present and apply the accumulative one-step-ahead prediction error (APE) not only as a method (strategy) of model selection, but also as a tool of model selection strategy (meta-selection). The APE method is compared with the information approach to model selection...

The purpose of the paper is to present and apply the accumulative one-step-ahead prediction error (APE) not only as a method (strategy) of model selection, but also as a tool of model selection strategy (meta-selection). The APE method is compared with the information approach to model selection...

In this paper, we present an econometric analysis for the effects of a price floor on price dynamics and price volatility. A price floor (implemented as a part of government pricing policy) provides a censoring mechanism for price determination. We specify and estimate a dynamic Tobit model...

This paper argues that the sometimes-conflicting results of a modern revisionist literature on data mining in econometrics reflect different approaches to solving the central problem of model uncertainty in a science of non-experimental data. The literature has entered an exciting phase with...

Total factor productivity (TFP) computed as Solow-residuals could be subject to input-substitution bias for two reasons. First, the Cobb-Douglas (CD) production function restricts all input substitutions to one. Second, observed inputs generally differ from optimal inputs, so that inputs...

A specification search algorithm is proposed that aims to assist the user in the process of constructing Vector Error Correction Models. The algorithm automates testing the cointegration rank of the system and performs simplifications based on possible weak exogeneity of some variables....