Burns, A. F., W.C. Mitchell (1946), Measuring business cycles, New York: NBER.
Chauvet, M. (1998), An econometric characterization of business cycle dynamics with factor structure and regime switches, International Economic Review 39, (4), 969-996.
Chauvet, M. (2001), A monthly indicator of Brazilian GDP, The Brazilian Review of Econometrics Vol. 21, No. 1, (Revista de Econometrcia).
Clements, M.P., Krolzig, H.-M. (2002). Can oil shocks explain asymmetries in the US business cycle?, Empirical Economics 27, 185-204. Reprinted as pages 91-112 of: Hamilton, J.D. and B. Raj (eds) (2002) `Advances in Markov-switching models', Heidelberg: Physica.
Clements, M.P., Krolzig, H.-M. (2003), Business cycle asymmetries: characterization and testing based on Markov-switching autoregressions, Journal of Business and Economic Statistics, 21, 196 - 211
Dempster, A.P., N.M. Laird & D.B. Rubin (1977), Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, B39, 1-38.
Diebold, F. X., G.D. Rudebusch (1996), Measuring business cycles: A modern perspective, The Review of Economics and Statistics 78 (1), 67-77.
Diebold, F.X., J.H. Lee, G.C. Weinbach (1994), Regime switching with time-varying transition probabilities, in: C. Hargreaves (ed.), Nonstationary Time Series Analysis and Cointegration, Oxford: Oxford University Press, 283-302.
Ehrmann, M., Ellison, M., Valla, N., (2003) Regime dependent impulse response functions in a vector Markov-switching model , Bank of Finland-Discussion Papers 11/2001.
Filardo, A. J. (1994), Business cycle phases and their transitional dynamics, Journal of Business and Economic Statistics 12, 299-308.
Granger, C., T. Terasvirta, H. Anderson (1993), Modeling nonlinearity over the business cycle, in: J.H. Stock and M.W. Watson (eds.) Business Cycles, Indicators and Forecasting, Chicago: University of Chicago Press for NBER, 311-325.
Hamilton, J. D. (1989), A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57, 357-384.
Hamilton, J. D. (1990), Analysis of time series subject to changes in regimes, Journal of Econometrics 45, 39-70.
Hamilton, J., Perez-Quiros, G. (1996), What do the leading indicators lead?, Journal of Business 69, 27-49.
Hansen, B. E. (1992), The likelihood ratio test under non-standard conditions: Testing the Markov trend model of GNP, Journal of Applied Econometrics 7, 61-82.
Hansen, B. E. (1997), Inference in TAR Models, Studies in Nonlinear Dynamics and Econometrics 2, (1), 1-14.
Kim, C.J., C. R. Nelson (1998), 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, 80, 188-201.
Krolzig, H.-M. (1997), Markov Switching Vector Autoregressions: Modelling, Statistical Inference and Application to Business Cycle Analysis: Lecture Notes in Economics and Mathematical Systems, 454, Springer-Verlag, Berlin.
Krolzig, H.-M. (2000), Predicting Markov-switching vector autoregressive processes, Journal of Forecasting, forthcoming.
Krolzig, H.-M. (2001), Markov switching procedures for dating the Euro-zone business cycle, Vierteljahreshefte zur Wirtschaftsforschung, 70 (3), 339-351.
Krolzig, H.-M., Marcellino, M., Mizon, G. (2002), A Markov-switching vector equilibrium correction model of the UK labour market, Empirical Economics, 27, 233-254. Reprinted as pages 41-60 of: Hamilton, J.D.and B.Raj (eds),(2002),Advances in Markov-Switching Model,Heidelberg: Physica.
Ferrara,L.(2003), A three-regime real-time indicator for the US economy, Economics Letters,81373-378.
Pelagatti, M. (2002), Duration-dependent Markov-switching VAR models with applications to the business cycle analysis, Universita di Milano-Bicocca.
)