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经济时间序列中测量误差的度量
A spectral decomposition method is described for obtaining an upper bound on the amount of measurement error in a time series. The method is applied to generated data and to M1b, real GNP, and the CPI. The bounds provide insight into both the amount of measurement error in these series and the stochastic specification of the errors.
解释变量的次优预测如何得到最优利用
Ashley (1983) gave a simple condition for determining when a forecast of an explanatory variable (Xt ) is sufficiently inaccurate that direct replacement of Xt by the forecast yields worse forecasts of the dependent variable than does respecification of the equation to omit Xt . Many available macroeconomic forecasts were shown to be of limited usefulness in direct replacement. Direct replacement, however, is not optimal if the forecast's distribution is known. Here optimal…