Dynamic threshold modelling and the US business cycle

Leading economic indicators are often used to anticipate changes in key economic variables. Understanding the dynamics of these indicators is of primary interest for policy-making objectives and for sustainable economic welfare. We are concerned with the problem of setting a dynamic threshold above...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society 2013-08, Vol.62 (4), p.535-550
Main Authors: de Carvalho, M., Turkman, K. F., Rua, A.
Format: Article
Language:English
Subjects:
Box-Jenkins method
Business
Business cycles
Dynamic modeling
Dynamic models
Dynamics
Econometrics
Economic fluctuations
Economic indicators
Economic models
Economic statistics
Economic theory
Economics
Extreme value econometrics
Extreme values
Indicators
Mathematical models
Modelling
Non-stationary process
Parametric models
Peaks over threshold
Policy making
Series convergence
Statistical analysis
Statistics of extremes
Studies
Thresholds
Time series
Time series forecasting
Time series models
U.S.A
Unemployment
Unemployment data
Unemployment insurance
US business cycle
Welfare economics
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Summary:Leading economic indicators are often used to anticipate changes in key economic variables. Understanding the dynamics of these indicators is of primary interest for policy-making objectives and for sustainable economic welfare. We are concerned with the problem of setting a dynamic threshold above which the value of leading indicators would be considered as extreme. We propose a dynamic threshold modelling approach based on fractionally integrated processes where a semiparametric method is used to determine the amount of differencing that is required to obtain a weakly stationary process—to which standard methods of statistics of extremes apply. Given that our approach is linked to the Box-Jenkins method, we refer to the procedure proposed and applied herein as the Box-Jenkins-Pareto procedure. We use our approach to analyse the weekly number of unemployment insurance claims in the USA and explore the connection between its threshold exceedances and the US business cycle.
ISSN:0035-9254
1467-9876
DOI:10.1111/rssc.12008