R. Ahrens, Predicting recessions with interest rate spreads: a multicountry regime-switching analysis, Journal of International Money and Finance, vol.21, issue.4, pp.519-537, 2002.
DOI : 10.1016/S0261-5606(02)00006-2

H. Akaike, A new look at the statistical model identification, IEEE Transactions on Automatic Control, vol.19, issue.6, pp.716-722, 1974.
DOI : 10.1109/TAC.1974.1100705

J. Anas and L. Ferrara, Turning points detection: The ABCD approach and two probabilistic indicators, Journal of Business Cycle Measurement and Analysis, vol.1, pp.1-36, 2004.

J. Anas, M. Billio, L. Ferrara, and M. Loduca, A turning point chronology for the Eurozone, Growth and Cycle in the Euro zone, pp.261-274, 2007.

J. Anas, M. Billio, L. Ferrara, and M. Loduca, Business cycle analysis with multivariate Markov switching models, Growth and Cycle in the Euro zone, pp.249-260, 2007.

J. Anas, M. Billio, L. Ferrara, and G. Mazzi, A SYSTEM FOR DATING AND DETECTING TURNING POINTS IN THE EURO AREA, Manchester School, vol.8, issue.3, pp.549-577, 2008.
DOI : 10.1111/j.1467-9957.2008.01076.x

M. Artis, H. Krolzig, and J. Toro, The European business cycle, Oxford Economic Papers, vol.56, issue.1, pp.1-44, 2004.
DOI : 10.1093/oep/56.1.1

M. Billio, M. Caporin, and G. Cazzavillan, Dating Euro15 monthly business cycle jointly using GDP and IPI, Journal of Business Cycle Measurement and Analysis, vol.33, pp.333-366, 2007.

M. Caporin and D. Sartore, Methodological Aspects of Time Series Back-Calculation, SSRN Electronic Journal, 2006.
DOI : 10.2139/ssrn.950923

M. Chauvet, An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching, International Economic Review, vol.39, issue.4, pp.969-996, 1998.
DOI : 10.2307/2527348

M. P. Clements and H. Krolzig, A Comparison of the Forecast Performance of Markov-switching and Threshold Autoregressive Models of US GNP, The Econometrics Journal, vol.1, issue.1, pp.47-75, 1998.
DOI : 10.1111/1368-423X.11004

P. Deschamps, Comparing smooth transition and Markov switching autoregressive models of US unemployment, Journal of Applied Econometrics, vol.39, issue.4, pp.435-462, 2008.
DOI : 10.1002/jae.1014

F. X. Diebold and G. D. Rudebusch, Measuring business cycles: A modern perspective, Review of Economics and Statistics, issue.1, pp.78-67, 1996.

L. Ferrara, A three-regime real-time indicator for the US economy, Economics Letters, vol.81, issue.3, pp.373-378, 2003.
DOI : 10.1016/S0165-1765(03)00220-9

L. Ferrara and D. Guégan, Detection of the Industrial Business Cycle using SETAR Models, Journal of Business Cycle Measurement and Analysis, vol.2005, issue.3, pp.1-20, 2006.
DOI : 10.1787/jbcma-v2005-art9-en
URL : https://hal.archives-ouvertes.fr/halshs-00201309

A. J. Filardo and S. F. Gordon, Business cycle durations, Journal of Econometrics, vol.85, issue.1, pp.99-123, 1994.
DOI : 10.1016/S0304-4076(97)00096-1

P. H. Franses and D. Van-dijk, Non-Linear Time Series Models in Empirical Finance, p.27, 2000.

J. D. Hamilton, Rational-expectations econometric analysis of changes in regime, Journal of Economic Dynamics and Control, vol.12, issue.2-3, pp.385-423, 1988.
DOI : 10.1016/0165-1889(88)90047-4

J. D. Hamilton, A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, Econometrica, vol.57, issue.2, pp.357-384, 1989.
DOI : 10.2307/1912559

J. D. Hamilton, Analysis of time series subject to changes in regime, Journal of Econometrics, vol.45, issue.1-2, pp.39-70, 1990.
DOI : 10.1016/0304-4076(90)90093-9

J. D. Hamilton and R. Susmel, Autoregressive conditional heteroskedasticity and changes in regime, Journal of Econometrics, vol.64, issue.1-2, pp.307-353, 1994.
DOI : 10.1016/0304-4076(94)90067-1

B. E. Hansen, Inference in TAR Models, Studies in Nonlinear Dynamics & Econometrics, vol.2, issue.1, pp.1-14, 1997.
DOI : 10.2202/1558-3708.1024

D. Harding and A. Pagan, Dissecting the cycle: a methodological investigation, Journal of Monetary Economics, vol.49, issue.2, pp.365-381, 2002.
DOI : 10.1016/S0304-3932(01)00108-8

D. A. Jones, Nonlinear Autoregressive Processes, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.360, issue.1700, pp.71-95, 1978.
DOI : 10.1098/rspa.1978.0058

S. Kaufmann, Measuring business cycles with a dynamic Markov switching factor model: an assessment using Bayesian simulation methods, The Econometrics Journal, vol.3, issue.1, pp.39-65, 2000.
DOI : 10.1111/1368-423X.00038

C. Kim and C. R. Nelson, Business Cycle Turning Points, A New Coincident Index, and Tests of Duration Dependence Based on a Dynamic Factor Model With Regime Switching, Review of Economics and Statistics, vol.82, issue.400, pp.188-201, 1998.
DOI : 10.2307/2290410

C. Kim and C. R. Nelson, State-Space Models with Regime Switching: Classical and Gibbs-sampling Approaches with Applications, 1999.

H. Krolzig, Markov-Switching Vector Autoregressions: Modelling, Statistical Inference, and Application to Business Cycle Analysis, Lecture Notes in Economics and Mathematical Systems, vol.454, 1997.
DOI : 10.1007/978-3-642-51684-9

H. Krolzig, Constructing turning point chronologies with Markov-switching vector autorgressive models: the Euro-zone business cycle, Eurostat Colloquium on Modern Tools for Business Cycle Analysis, 2003.

H. Krolzig and J. Toro, A new approach to the analysis of shocks and the cycle in a model of output and employment, pp.99-129, 1999.

H. Krolzig and M. Sensier, A Disaggregated Markov-Switching Model of the Business Cycle in UK Manufacturing, The Manchester School, vol.68, issue.4, pp.442-460, 2000.
DOI : 10.1111/1467-9957.00204

A. P. Layton, Dating and predicting phase changes in the U.S. business cycle, International Journal of Forecasting, vol.12, issue.3, pp.417-428, 1996.
DOI : 10.1016/0169-2070(95)00663-X

A. P. Layton and D. R. Smith, Business cycle dynamics with duration dependence and leading indicators, Journal of Macroeconomics, vol.29, issue.4, pp.855-875, 2007.
DOI : 10.1016/j.jmacro.2006.02.003

A. Montgomery, V. Zarnowitz, R. Tsay, and G. Et-tiao, Forecasting the U.S. Unemployment Rate, Journal of the American Statistical Association, vol.48, issue.2, pp.442-478, 1998.
DOI : 10.1080/01621459.1984.10477068

S. Neftçi, Optimal prediction of cyclical downturns, Journal of Economic Dynamics and Control, vol.4, pp.307-327, 1982.
DOI : 10.1016/0165-1889(82)90014-8

S. Neftçi, Are Economic Time Series Asymmetric over the Business Cycle?, Journal of Political Economy, vol.92, issue.2, pp.307-328, 1984.
DOI : 10.1086/261226

T. Proietti, Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models, Studies in Nonlinear Dynamics & Econometrics, vol.3, issue.3, pp.141-156, 1998.
DOI : 10.2202/1558-3708.1045

R. E. Quandt, The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes, Journal of the American Statistical Association, vol.42, issue.284, pp.873-880, 1958.
DOI : 10.1080/01621459.1958.10501484

G. C. Tiao and R. S. Tsay, Some advances in non-linear and adaptive modelling in time-series, Journal of Forecasting, vol.84, issue.2, pp.109-131, 1994.
DOI : 10.1002/for.3980130206

H. Tong and K. S. Lim, Threshold Autoregression, Limit Cycles and Cyclical Data, Journal of the Royal Statistical Society, B, vol.42, pp.245-292, 1980.
DOI : 10.1142/9789812836281_0002

H. Tong, Non-linear Time Series: A Dynamical Approach, 1990.