Duration Dependent Transitions in a Markov Model of U.S. GNP Growth
AbstractHamilton's (1989) nonlinear Markovian filter is extend to allow state transitions to be duration dependent. Restrictions are imposed on the state transition matrix associated with a T-order Markov system such that the corresponding first-order conditional transition probabilities are functions of both the inferred current state and also the number of periods the process has been in that state. High-order structure is parsimoniously summarized by the inferred duration variable. Applied to U.S. post-war real GNP growth rates, we obtain evidence in support of nonlinearity, asymmetry between recessions and expansions, as well as strong duration dependence for recessions but not for expansions
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Bibliographic InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 887.
Length: 37 pages
Date of creation: Oct 1993
Date of revision:
time-varying transition probabilities; regime-switches; nonlinear asymmetric cycles;
Other versions of this item:
- Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-88, July.
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