Univariate ARIMA Forecasts of Defined Variables
比较了直接预测定义变量（如实际利率）与通过其构成变量间接预测两种方法的准确性，发现间接预测通常更优。
Many important variables in business and economics are neither measured nor measurable but are simply defined in terms of other measured variables. For instance, the real interest rate is defined as the difference between the nominal interest rate and the inflation rate. There are two ways to forecast a defined variable: one can directly forecast the variable itself, or one can derive the forecast of the defined variable indirectly from the forecasts of the constituent variables. Using Box-Jenkins univariate time series analysis for four defined variables—real interest rate, money multiplier, real GNP, and money velocity—the forecasting accuracy of the two methods is compared. The results show that indirect forecasts tend to outperform direct methods for these defined variables.