What statistical models have been formulated?
A. Much of the analysis in the literature has focused on “continuous variables,” data series whose values can in principle be any real numbers. Examples of these series are growth rates in GNP, GDP, industrial production, consumption, and investment. To predict these series, analysts have generally relied on relatively standard regression equations, taking care to deal with some important statistical issues. The most common issue results from the presence of overlapping observations in many of the applications. For example, suppose that we are interested in forecasting GDP growth over the next year using quarterly data. Then, two consecutive observations of the variable being forecasted correspond to time periods that have three quarters in common. Standard measures of statistical significance are in general inconsistent, and must be adjusted by using, for instance, the generalized method of moments estimators of Hansen (1982) or Newey and West (1987). When the objective is to predict
