In time series analysis, tests for independence, symmetry, and goodness-of-fit based on divergence measures, such as the Kullback-Leibler divergence or Hellinger distance are currently receiving much interest.We consider replacing the divergence measures in these tests by kernel-based positive...

We consider the Bovespa economic index (Ibovespa) from January 1994 to the present. Starting directly from this high resolution data we study the statistical properties of the time evolution of the Ibovespa. In order to obtain price dynamics information we find the probability density function...

There is no shortage of opinions and discussion about recent productivity growth trends. In contrast, relatively little attention is paid to the degree of uncertainty surrounding recent estimates of such growth trends. This paper makes two contributions to the scant body of research that...

In this paper, we provide empirical evidence for some European countries, over the period 1963-2000, on whether business cycle affects convergence process or catching-up. To do so, we first evaluate beta-convergence. We find evidence in favour of this type of convergence for six countries...

This paper introduces model uncertainty into a simple Lucas-type monetary model. Inflation depends on agents' expectations and a vector of exogenous random variables. Following (Branch and Evans 2004) agents are assumed to underparameterize their forecasting models. A Misspecification...

This paper presents a rigurous framework for evaluating alternative forecasting methods for Chilean industrial production and sales. While nonlinear features appear to be important for forecasting the very short term, simple univariate linear models perform about as well for almost every...

The empirical evidence from financial markets suggests that the pattern of response of market volatility to shocks is highly dependent on the magnitude of shocks themselves. Markov-Switching GARCH (MS-GARCH) models are a valuable tool for modelling state dependence in the dynamics of the...

This paper is a step towards the econometric foundation of computational intelligence in finance. Financial time series modeling and forecasting are addressed with an artificial neural network, examining issues of its topology dependency. Structural dependency of results is viewed not as a...