This Chapter discusses estimation, specification testing, and model selection of predictive density models. In … particular, predictive density estimation is briefly discussed. And a variety of different specifications and model evaluation …

statistics are obtained via rolling and recursive estimation schemes are developed. An empirical illustration comparing …

prediction models via cointegrating restrictions among money, prices, and output derived from a simple version of the quantity … cointegrating relations are used in a vector error correction (VEC) model, a vector autoregression (VAR) model in differences … are also reported on. The first shows that cointegration vector parameter estimation error is crucial when using VEC …

that reflect data dependence and parameter estimation error (PEE). In order to obtain asymptotically valid critical values …

This paper analyzes the conditions under which consistent estimation can be achieved in instrumental Variables (IV … (JIVE) establishes that consistent estimation depends importantly on the relative magnitudes of rn, the growth rate of the … the use of many instruments may be beneficial for estimation, as the resulting concentration parameter growth may allow …

parameter estimation error and data dependence play a crucial role in test statistic limiting distributions, a role which had … in recursive estimation frameworks. Thereafter, we present two applications where predictive accuracy tests are made …