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反向回归、公平与就业歧视AI 解读

Possible salary discrimination can be studied by comparing mean salaries of, say, males and females, after statistical adjustment for differences in job qualifications. The adjustment is often made by regression, with salary as dependent variable, and job qualifications and sex as independent variables. One might also regress job qualifications on salary and sex, a procedure called reverse regression. Ideas about fairness as well as technical concepts are relevant to…

货币总量的季节调整：美联储委员会报告概要AI 解读

The Committee of Experts on Seasonal Adjustment Techniques was formed by the Federal Reserve Board to examine and make recommendations concerning the Board's procedures for seasonally adjusting the money supply and related series. This article summarizes the report of that committee.

新的货币供应量指数与灵活 Laurent 需求系统AI 解读

The article begins by surveying the existing results on the new Divisia monetary aggregates. Charts display the differences in behavior between the Divisia aggregates and the Federal Reserve's official simple-sum monetary aggregates. The article then compares system-wide fit for the simple-sum and Divisia monetary aggregates when used as data in the joint estimation of a system of demand equations. The demand system is derived from a new Laurent expansion approximation to…

多元时间序列模型中永久与暂时影响的分析AI 解读

Several multiple time series models are developed and applied to the analysis and forecasting of the M1 and M2 money supply aggregates. These models feature a decomposition of the time series into permanent and transient influences or components. This decomposition appears to enhance forecasting accuracy and is associated with a variance-covariance allocation parameter that is also estimated from the data. Conditional maximum likelihood estimates for model parameters are…

多元时间序列建模与扩展样本互相关AI 解读

This article provides an expository account of the multivariate autoregressive moving average models and proposes an extended sample cross-correlation approach for practical model identification. An iterative model building procedure for applying these models to real data is discussed and demonstrated by analyzing the 5-series U.S. Hog Data.