By James D. Hamilton, Baldev Raj
This publication is a set of cutting-edge papers at the houses of industrial cycles and monetary research. the person contributions disguise new advances in Markov-switching types with purposes to company cycle learn and finance. The creation surveys the present equipment and new result of the decade. person chapters learn gains of the U. S. and eu company cycles with specific specialise in the position of economic coverage, oil shocks and co pursuits between key variables. The short-run as opposed to long-run outcomes of an monetary recession also are mentioned. one other quarter that's featured is an in depth research of foreign money crises and the potential for bubbles or fads in inventory costs. A concluding bankruptcy deals necessary new effects on trying out for this type of regime-switching behaviour. total, the ebook presents a state of the art over view of latest instructions in equipment and effects for estimation and inference in response to using Markov-switching time-series research. a different characteristic of the booklet is that it contains a demonstration of quite a lot of functions in accordance with a typical technique. it's anticipated that the subject matter of the booklet should be of specific curiosity to the macroeconomics readers in addition to econometrics pros, students and graduate scholars. we want to exhibit our gratitude to the authors for his or her robust contributions and the reviewers for his or her tips and cautious consciousness to aspect of their reports.
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Additional resources for Advances in Markov-Switching Models: Applications in Business Cycle Research and Finance
Raymond and Rich (1997) have investigated the relationship between oil prices and the macroeconomy by including the net increase in the oil price 42 M. P. -M. Krolzig (NOPI) in the two-regime Markov-Switching (MS) model of US output growth of Hamilton (1989) for the period 1951-1995. Hamilton's model generated shifts between negative and positive growth states such that the former corresponded closely with the NBER recessions. The key insight of Raymond and Rich (1997) is that if oil prices are an important determinant of the periods of negative output growth, then a MS model - which includes oil prices as an explanatory variable of the conditional mean - may either no longer generate shifts that match the NBER chronology or estimate a negative growth mean.
Based on various diagnostic checks we settled on a parsimonious AR(I) specification for all components, as in Chauvet (1998). Empirical results are robust to alternative specifications. For all autoregressive structures considered, the implied factors, as well as filtered and smoothed probabilities, are virtually indistinguishable. The parameter estimates of the model and their standard errors are reported in Table I. If the factor loadings for the transitory component, Ai, i = 1,2,3,4 are all zero, our model collapses to a dynamic factor model with a regime-switching common growth component.
However, the individual hypothesis that Ai = 0 for one i does not render any parameters unidentified under the null hypothesis, and standard distribution theory is valid. 4 5 Pennanent and transitory components of recessions 27 Table 1. 583 Standard errors are in parentheses. We are now in a position to calculate the relative importance of permanent and transitory shocks during recessions. In order to do this, we set the symmetric innovation variances of the idiosyncratic components to zero. -J.
Advances in Markov-Switching Models: Applications in Business Cycle Research and Finance by James D. Hamilton, Baldev Raj