宏观经济变量预测准确性的不确定性下限和上限

Victor Olkhov
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引用次数: 0

摘要

我们认为市场交易价值和交易量的随机性是描述宏观经济变量、价格和收益预测准确性的不确定性下限和上限的主要因素。我们引入随机宏观经济变量,其平均值与惯常宏观经济变量相吻合,并通过变异系数来描述其不确定性,而变异系数取决于随机值或交易量的波动率、相关性和变异系数。同样的方法还可以描述不确定性的界限以及对增长率、通货膨胀率、利率等预测准确性的限制。宏观经济变量预测准确性的限制取决于对其概率预测的确定性。预测统计时刻的数量决定了宏观经济概率的稳定性。要量化宏观经济第二统计时刻,需要额外的计量经济学方法、数据和变量的计算,这些变量被确定为市场交易价值或交易量的平方和。预测宏观经济第二统计时刻需要二阶经济理论。所有这些都不存在,而且在未来许多年里,对随机宏观经济变量、价格和收益的概率预测的准确性将受到高斯近似值的限制,而高斯近似值是由前两个统计时刻决定的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lower bounds of uncertainty and upper limits on the accuracy of forecasts of macroeconomic variables
We consider the randomness of values and volumes of market deals as a major factor that describes lower bounds of uncertainty and upper limits on the accuracy of the forecasts of macroeconomic variables, prices, and returns. We introduce random macroeconomic variables, whose average values coincide with usual macroeconomic variables, and describe their uncertainty by coefficients of variation that depend on the volatilities, correlations, and coefficients of variation of random values or volumes of trades. The same approach describes bounds of uncertainty and limits on the accuracy of forecasts for growth rates, inflation, interest rates, etc. Limits on the accuracy of forecasts of macroeconomic variables depend on the certainty of predictions of their probabilities. The number of predicted statistical moments determines the veracity of macroeconomic probability. To quantify macroeconomic 2nd statistical moments, one needs additional econometric methodologies, data, and calculations of variables determined as sums of squares of values or volumes of market trades. Forecasting of macroeconomic 2nd statistical moments requires 2nd order economic theories. All of that is absent and for many years to come, the accuracy of forecasts of the probabilities of random macroeconomic variables, prices, and returns will be limited by the Gaussian approximations, which are determined by the first two statistical moments.
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