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...

The purpose of this paper is to use the bootstrap resampling technique to calculate confidence intervals for efficiency measures and Malmquist productivity indices. The efficiency and productivity measures are obtained from non-parametric linear programming models using primal production data....

This paper shows that the bootstrap algorithm for average technical efficiency by Atkinson and Wilson (1995) should be applied with great care for the Data Envelopment Analysis (DEA) estimator if the production frontier is stochastic. A stochastic frontier implies that the DEA estimator is...

This paper presents a Monte Carlo simulation study of the bootstrap algorithm proposed by Löthgren and Tambour (1997) for calculation of bootstrap confidence intervals for the firm-specific Data Envelopment Analysis (DEA) Malmquist productivity index. The simulation results indicate that the...

This paper evaluates the performance of three bootstrap algorithms for the data envelopment analysis (DEA) estimator using a Monte Carlo simulation study. The Löthgren and Tambour (1997) (LT) algorithm; the Simar and Wilson (1997b) (SW) algorithm; and a combination of the LT and SW algorithms...

In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Teräsvirta (2005) by including...

In this paper we propose a Lagrange multiplier test for volatility interactions among markets or assets. The null hypothesis is the Constant Conditional Correlation GARCH model in which volatility of an asset is described only through lagged squared innovations and volatility of its own. The...

In this paper we introduce the STAR-STGARCH model that can characterize nonlinear behaviour both in the conditional mean and the conditional variance. A modelling cycle for this family of models, consisting of specification, estimation, and evaluation stages is constructed. Misspecification...

In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...

In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change in the...