Effects of filtering data on testing asymmetry in threshold autoregressive models

2016 ◽  
Vol 20 (5) ◽  
Author(s):  
Jing Li
Keyword(s):  
Time Series ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Business Cycle ◽  
Error Term ◽  
Economic Time Series ◽  
Threshold Autoregressive ◽  
Threshold Autoregression ◽  
Power Of The Test ◽  
Economic Time

AbstractEmpirical macroeconomic research on business cycle typically filters economic time series in order to obtain cyclical components. This paper examines the effects of filtering data on the test for a linear autoregression against a threshold autoregression. Monte Carlo simulation shows that (1) filtering data in general reduces the power of the test, (2) the power is sensitive to the choice of filters and the specification of the trend and cyclical components, (3) regime-varying variance of the error term can affect the rejection frequency. Empirical evidences for cyclical asymmetry are provided for the quarterly US real GNP.

scholarly journals Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany

2021 ◽  
Author(s):  
Agnieszka Gehringer ◽  
Thomas Mayer
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Gross Domestic Product ◽  
Business Cycle ◽  
Economic Activity ◽  
Principal Component ◽  
Economic Time Series ◽  
Economic Time ◽  
The Business Cycle ◽  
Cycle Indicator

AbstractThis paper introduces a Business Cycle Indicator to compile a transparent and reliable chronology of past business cycle turning points for Germany. The Indicator is derived applying the statistical method of Principal Component Analysis, based on information from 20 economic time series. In this way, the Business Cycle Indicator grasps the development of the broader economic activity and has several advantages over a business cycle assessment based on quarterly series of Gross Domestic Product.

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