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对美国商务部领先指标方法的检验AI 解读

Bivariate time series models are built that describe the empirical relationships between industrial production and components of the Composite Index of Leading Indicators (CLI). This reveals the indicators' average lead times at all points of the business cycle, the forms of the distributed lags involved, and their ability to explain later movements in economic activity. The relationship between industrial production and the CLI is also examined and used to test the…

利用互相关模式检验两条时间序列的独立性AI 解读

The Haugh (1976) test for independence employs the univariate residual cross-correlation function. However, it ignores information about a possible pattern in successive cross-correlation coefficients. An asymptotic test is developed that incorporates this information and includes the Haugh test as a special case. A Monte Carlo study indicates that the proposed test is more powerful than the Haugh s and regression F tests for certain models. Two empirical examples are…

利用交叉相关函数潜在模式检验两条时间序列的独立性AI 解读

The Haugh (1976) test for independence employs the univariate residual cross-correlation function. However, it ignores information about a possible pattern in successive cross-correlation coefficients. An asymptotic test is developed that incorporates this information and includes the Haugh test as a special case. A Monte Carlo study indicates that the proposed test is more powerful than the Haugh s and regression F tests for certain models. Two empirical examples are…