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, Un Indicateur d'Entrée et Sortie de Récession: Application aux Etats Unis, 2002.

J. Anas and L. Ferrara, A Comparative Assessment of Parametric and Non- Parametric Turning Points Methods: The Case of the Euro-zone Economy " , paper presented at the 3rd Eurostat Colloquium on Modern Tools for Business Cycle Analysis, 2002.

J. Anas, M. Billio, L. Ferrara, and M. Loduca, A Turning Point Chronology for the Euro-zone Classical and Growth Cycles " , paper presented at the 4th Eurostat Colloquium on Modern Tools for Business Cycle Analysis, 2003.

M. Artis, H. M. Krolzig, and J. Toro, The European business cycle, Oxford Economic Papers, vol.56, issue.1, 2003.
DOI : 10.1093/oep/56.1.1

K. S. Chan, Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model, The Annals of Statistics, vol.21, issue.1, pp.520-533, 1993.
DOI : 10.1214/aos/1176349040

M. Chauvet and J. M. Piger, Identifying Business Cycle Turning Points in Real Time, Review of the Federal Reserve Bank of St. Louis, pp.47-61, 2003.

M. P. Clements and J. Smith, A Monte Carlo study of the forecasting performance of empirical SETAR models, Journal of Applied Econometrics, vol.42, issue.2, pp.123-141, 1999.
DOI : 10.1002/(SICI)1099-1255(199903/04)14:2<123::AID-JAE493>3.0.CO;2-K

M. P. Clements and J. Smith, Evaluating the forecast densities of linear and non-linear models: applications to output growth and unemployment, Journal of Forecasting, vol.39, issue.2, pp.255-276, 2000.
DOI : 10.1002/1099-131X(200007)19:4<255::AID-FOR773>3.0.CO;2-G

M. P. Clements and H. M. Krolzig, Business Cycle Asymmetries, Journal of Business & Economic Statistics, vol.21, issue.1, pp.196-211, 2003.
DOI : 10.1198/073500102288618892

D. Van-dijk, T. Terasvirta, and P. H. Franses, SMOOTH TRANSITION AUTOREGRESSIVE MODELS ??? A SURVEY OF RECENT DEVELOPMENTS, Econometric Reviews, vol.15, issue.1, pp.1-47, 2002.
DOI : 10.1111/j.1467-9965.1994.tb00058.x

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.2003-2015, 2003.
DOI : 10.1787/jbcma-v2005-art9-en

URL : https://hal.archives-ouvertes.fr/halshs-00201309

J. G. De-goojier and P. T. De-bruin, On forecasting SETAR processes, Statistics & Probability Letters, vol.37, issue.1, pp.7-14, 1999.
DOI : 10.1016/S0167-7152(97)00092-8

D. Guégan, Point de Vue Personnel sur leProbì eme de Contagion en Economie et l'Intéraction entre Cycle Réel et Cycle Financier, Note de Recherche MORA-IDHE 06-2003, 2003.

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

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, A comparison of two business cycle dating methods, Journal of Economic Dynamics and Control, vol.27, issue.9, 2001.
DOI : 10.1016/S0165-1889(02)00076-3

W. Ip, H. Wong, Y. Li, and H. An, Testing and estimation of thresholds based on wavelets in heteroscedastic threshold autoregressive models, Biometrika, vol.90, issue.3, pp.703-716, 2003.
DOI : 10.1093/biomet/90.3.703

H. M. Krolzig, Markov-Switching Procedures for Dating the Euro-Zone Business Cycle, Vierteljahrshefte zur Wirtschaftsforschung, vol.70, issue.3, pp.339-351, 2001.
DOI : 10.3790/vjh.70.3.339

H. M. Krolzig, Constructing Turning Point Chronologies with Markov-Switching Vector Autoregressive Models: the Euro-zone Business Cycle " , paper presented at the 3rd Eurostat Colloquium on Modern Tools for Business Cycle Analysis, 2002.

H. M. Krolzig and J. Toro, Classical and modern business cycle measurement: The European case, Spanish Economic Review, vol.7, issue.1, 2001.
DOI : 10.1007/s10108-004-0088-0

K. Lahiri, W. , and J. G. , Predicting cyclical turning points with leading index in a markov switching model, Journal of Forecasting, vol.49, issue.3, pp.245-263, 1994.
DOI : 10.1002/for.3980130302

S. M. Potter, A nonlinear approach to US GNP, Journal of Applied Econometrics, vol.1, issue.2, pp.109-125, 1995.
DOI : 10.1002/jae.3950100203

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

D. E. Sichel, Inventories and the Three Phases of the Business Cycle, Journal of Business & Economic Statistics, vol.31, issue.3, pp.269-277, 1994.
DOI : 10.1080/07350015.1994.10524542

T. Terasvirta, A. , and H. M. , Characterizing nonlinearities in business cycles using smooth transition autoregressive models, Journal of Applied Econometrics, vol.1, issue.21, pp.119-136, 1992.
DOI : 10.1002/jae.3950070509

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

R. S. Tsay, Testing and Modeling Threshold Autoregressive Processes, Journal of the American Statistical Association, vol.7, issue.405, pp.231-240, 1989.
DOI : 10.1080/01621459.1989.10478760