Experimentalists frequently claim that human subjects playing games in the laboratory violate such solution concepts as Nash equilibrium and subgame perfection. This claim is premature. What has been rejected are certain joint hypotheses about preferences, knowledge, and behavior. This note...

This paper examines conditional convergence of OECD countries in gross domestic product (GDP) and health care expenditure (HCE) per capita. It presents estimation of the augmented Solow growth model suggested by Mankiw, Romer and Weil (1992) to explain variation in output and expenditure per...

This paper examines conditional convergence of OECD countries in gross domestic product (GDP) and health care expenditure (HCE) per capita. It presents estimation of the augmented Solow growth model suggested by Mankiw, Romer and Weil (1992) to explain variation in output and expenditure per...

This paper is a survey of recent contributions to, and developments of, the relationship between outsourcing, efficiency and productivity growth in manufacturing and services. The objective is to provide a thorough and up-to-date survey that provides a significant discussion on data, as well as...

This article is concerned with forecasting from nonlinear conditional mean models. First, a number of often applied nonlinear conditional mean models are introduced and their main properties discussed. The next section is devoted to techniques of building nonlinear models. Ways of computing...

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...

A Hidden Markov Model (HMM) is used to classify an out of sample observation vector into either of two regimes. This leads to a procedure for making probability forecasts for changes of regimes in a time series, i.e. for turning points. Instead o maximizing a likelihood, the model is estimated...

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...

This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive...

Since the true nature of a time series process is often unknown it is important to understand the effects of model choice. This paper examines how the choice between modelling stationary time series as ARMA or ARFIMA processes affects the accuracy of forecasts. This is done, for first-order...