Business cycle asymmetry and duration dependence: An international perspective

Journal of Applied Statistics

Volumn 28, Issue 6, 2001, Pages 713-724

  Mills, T C ^a  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BUSINESS CYCLE; DATA SET; GLOBAL PERSPECTIVE; MACROECONOMICS;

EID: 0034919529     PISSN: 02664763     EISSN: None     Source Type: Journal    
DOI: 10.1080/02664760120059246     Document Type: Article

References (22)

1. Business cycles in international historical perspective
2. Measuring business cycles: Approximate band-pass filters for economic time series
3. A regression test for exponentiality: Censored and complete samples
4. Asymmetric time series and temporal aggregation
5. A nonparametric investigation of duration dependence in the American business cycle
6. Further evidence on business cycle duration dependence
7. A new approach to the economic analysis of nonstationary time series and the business cycle
8. Postwar US business cycles: An empirical investigation
9. Business cycle turning points, a new coincident index, and tests of duration dependence based on a dynamic factor model with regime switching
10. The Monte Carlo cycle in business activity
11. Business cycle growth and volatility: A reassessment
12. After the golden age: A long run perspective on growth rates that speeded up, slowed down and still differ
13. Distribution-free test for symmetry based on Bonferroni's measure
14. A nonparametric investigation of duration dependence in the American business cycle: A note
15. Some non-parametric tests for duration dependence: An application to UK business cycle data
16. A simple positive semi-definite, heteroskedasticity and auto-correlation consistent covariance matrix
17. An analysis of variance test for the exponential distribution (complete samples)
18. Business cycle asymmetry: A deeper look
19. Business cycle fluctuations in US macroeconomic time series
20. Characterising nonlinearities in business cycles using smooth transition autoregressive models