In this paper, an autoregressive moving average (ARMA) model with threshold generalized autoregressive conditional heteroscedasticity (TGARCH) innovations is considered to model Chilean economic uncertainty time series. Uncertainty is measured through the Business Confidence Index (BCI) and...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. The method calculates the conditional expectations of the coefficients, given the observations. A penalized least squares estimation is linked to the GLS (Aitken) estimates of...

Financial markets witness high levels of activity at certain times but remain calm at others. This makes the flow of physical time discontinuous. Therefore, to use physical time scales for studying financial time series runs the risk of missing important activities. An alternative approach is to...

This metadata relates to an electronic version of an article published in Journal of statistical computation and simulation, 2002, vol. 72, no. 6, pp. 507-516. Journal of Statistical Computation and Simulation is available online at informaworldTM at...

The field of time-series analysis has made important contributions to a wide spectrum of applications such as tide-level studies in hydrology, natural resource prospecting in geo-statistics, speech recognition, weather forecasting, financial trading, and economic forecasts and...

This paper examines causality and parameter instability in the long-run relationshipbetween fertility and women’s employment. This is done by a cross-national comparisonof macro-level time series data from 1960–2000 for France, West Germany, Italy,Sweden, the UK, and the USA. By applying...

Market growth is driven by product innovation. Beyond functional satiation the marginal utility of product performance and variety decreases. We argue that social comparisons underlying innovation diffusion results in consumer motivations for upward assimilation toward the behavior of better...