Add to ORKGWe present a new technical approach based on the autocorrelation function, widely used in physics, to determine and to analyze the business cycle turning points of an economic activity. This method is adapted to stochastic processes and does not require a smoothing technique. The application of this method to the industrial production seasonally adjusted of Tunisia, for the period 1994:4 –2006:8 gives similar results to these obtained by two-state Markov switching model
International audienceIn this paper, we aim at assessing Markov switching and threshold models in th...
I investigate cointegrating relationships such that, even though the long-run at-tractors are assume...
A two-step procedure to produce a statistical measure of the probability of being in an accelerating...
We apply sequential Monte Carlo (SMC) to the detection of turning points in the business cycle and t...
This paper identifies turning points for the U.S. business cycle using different time series. The mo...
We propose a new approach for detecting turning points and forecasting the level of economic activit...
One of the most effective methods of modeling the current and prediction of the future economic situ...
We propose a new approach for detecting turning points and forecasting the level of economic activit...
In the paper the procedure, based on hidden Markov chains with conditional normal distributions and ...
The article presents an example of the idea of the Markov processes (chains) to identify phases and ...
This paper addresses the issues of identification and dating of the Euro-zone business cycle by usin...
This paper proposes a new framework for the impulse-response analysis of business cycle transitions....
This dissertation proposes a dynamic factor model with regime switching as an empirical characteriza...
We develop a twofold analysis of how the information provided by several economic indicators can be ...
The class of Markov switching models can be extended in two main directions in a multivariate framew...
International audienceIn this paper, we aim at assessing Markov switching and threshold models in th...
I investigate cointegrating relationships such that, even though the long-run at-tractors are assume...
A two-step procedure to produce a statistical measure of the probability of being in an accelerating...
We apply sequential Monte Carlo (SMC) to the detection of turning points in the business cycle and t...
This paper identifies turning points for the U.S. business cycle using different time series. The mo...
We propose a new approach for detecting turning points and forecasting the level of economic activit...
One of the most effective methods of modeling the current and prediction of the future economic situ...
We propose a new approach for detecting turning points and forecasting the level of economic activit...
In the paper the procedure, based on hidden Markov chains with conditional normal distributions and ...
The article presents an example of the idea of the Markov processes (chains) to identify phases and ...
This paper addresses the issues of identification and dating of the Euro-zone business cycle by usin...
This paper proposes a new framework for the impulse-response analysis of business cycle transitions....
This dissertation proposes a dynamic factor model with regime switching as an empirical characteriza...
We develop a twofold analysis of how the information provided by several economic indicators can be ...
The class of Markov switching models can be extended in two main directions in a multivariate framew...
International audienceIn this paper, we aim at assessing Markov switching and threshold models in th...
I investigate cointegrating relationships such that, even though the long-run at-tractors are assume...
A two-step procedure to produce a statistical measure of the probability of being in an accelerating...