STATE SPACE VECTOR BASED ADVANCED DIRECT POWER CONTROL OF MATRIX CONVERTER AS UPFC
Enhancing State-Space Tree Diagrams for Collaborative Problem Solving
About a coincident index for the state of the economy
Parameter Estimation for Semiparametric Models with CMARS and Its Applications
An Active Input Current Waveshaping with Zero Switching Losses for Three-Phase Circuit Using Power Diode
Gold Heart Shaped Pendants Models With Price
Adorning A New Born's Space Together With Baby Wall Decals
Red State Hotels Along With Eurodisney Hotels _ Perfect Destinations For The Particular Vacation S
Asymmetric Effects of Government Spending: Does the Level of Real Interest Rates Matter?
Code-switching in bilingual children with specific language impairment
Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
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