Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...

Present paper considers structural break in panel AR(1) model which allows instability in mean, variance and autoregressive coefficient. This model is extension of univariate model proposed by Meligkotsiduo et al. (2004) and review of existing panel data time series model considering break...

This paper is concerned with problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or exponential down-weighting. However, these studies...