The Taylor (1993) rule for determining interest rates is generalized to account for three additional variables: The money supply, money velocity, and the unemployment rate. Thus, five parameters, i.e. weights assigned to the deviation in the inflation rate, the deviation in real GDP (Gross Domestic Product), the deviation in money supply, the deviation in the money velocity, and the deviation in unemployment rate, are introduced and estimated. The article explores and tests various combinations of the Taylor rule, the Quantity Equation (Friedman, 1970), and the Phillips (1958) curve. The monthly US January 1, 1959 to March 31, 2022 data are adopted to test the optimal parameter values. Estimating the parameters with the least squares method gives better results than the Taylor rule. The optimal parameter values involve a relatively high weight to the deviation in unemployment rate, and moderate weights are assigned to the deviation in the inflation rate, the deviation in real GDP, the deviation in money supply, and the deviation in the money velocity. The corresponding sum of squares decreases by 42.95% when compared with the Taylor rule.

中文翻译：

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对影响利率的因素建模

用于确定利率的 Taylor (1993) 规则被推广以考虑三个附加变量：货币供应量、货币流通速度和失业率。由此，引入通货膨胀率偏差、实际GDP（国内生产总值）偏差、货币供应量偏差、货币流通速度偏差、失业率偏差五个权重参数，估计的。本文探讨并测试了泰勒规则、数量方程（弗里德曼，1970 年）和菲利普斯 (1958 年) 曲线的各种组合。采用美国1959年1月1日至2022年3月31日的月度数据对最优参数值进行检验。用最小二乘法估计参数给出比泰勒法则更好的结果。最优参数值对失业率偏差的权重较高，对通货膨胀率偏差、实际GDP偏差、货币供应量偏差和货币流通速度偏差的权重适中。与泰勒规则相比，相应的平方和减少了 42.95%。