GAMP algorithm for time-varying parameter regression
Model switching and model averaging in time-varying parameter regression models
... 4 Conclusions The Bayesian empirical researcher often faces a trade-o¤ between the desire to work with a fully speci…ed Bayesian model and the computational burden that use of MCMC methods imposes. In the DMA literature, ...
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Model Switching and Model Averaging in Time-Varying Parameter Regression Models
... Smoothed Model Probabilities, Regressor: No Change Forecasts Figure 2 The model probabilities in Figure 2 are smoothed estimates based on the entire sam- ple. Such a …gure is of interest for a retrospective analysis ...
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Model switching and model averaging in time-varying parameter regression models
... 4 Conclusions The Bayesian empirical researcher often faces a trade-o¤ between the desire to work with a fully speci…ed Bayesian model and the computational burden that use of MCMC methods imposes. In the DMA literature, ...
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Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility
... and assumed fat-tailed error distributions for the observation and state equations to control for outliers. In this paper, we generalize the approach of Stock and Watson (2007) to account for shocks that may not be ...
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Spurious regression problem in Kalman Filter estimation of time varying parameter models
... The estimation results of both with and without penalty cases can be observed in the tables 17, 18 and 19. As seen in these tables, the estimation results for this DGP strictly differ from the estimation results of the ...
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A STOCHASTIC PARAMETER REGRESSION APPROACH FOR TIME-VARYING RELATIONSHIP BETWEEN GOLD AND SILVER PRICES
... Many historical facts about gold and silver are likely of not much use to the analysis in this work. However, they provide insight on the close historical relationship between gold and silver. As far back as 3100 B.C., ...
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Analysis of time varying parameter models
... equal to that of 0 composed of o and distinct elements of u 11 2 . 4 Asymptotic I d e n t i f i a b i 1i t y Now we consider the asymptotic, local identifiability of 30 and 0 for non-stationary cases, where F is assumed ...
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Large time varying parameter VARs
... at time t, given information through time t ...at time t, we evaluate tjt 1;j for every j and use the value of and TVP-VAR dimension which maximizes ...recursive algorithm given in (8) and (9) ...
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Large Time-Varying Parameter VARs
... in time in a recursive forecasting ...a time-varying fashion. The algorithm we develop allows for the shrinkage hyperparameter to be updated automatically (in a similar fashion to the way the ...
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Large time-varying parameter VARs
... With regards to the issue of TVP-VAR dimensionality, there is no single dimension that dom- inates. Sometimes the dimension-switching feature of our TVP-VAR-DMS approach leads to the best forecasting performance, but ...
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Hierarchical Shrinkage in Time-varying Parameter Models
... using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a ...
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Hierarchical shrinkage in time-varying parameter models
... and time-varying coefficients forecasts the best when we use predictive likelihoods to evaluate forecast ...for time-varying coefficients and, thus, our model is forecasting roughly as well as ...
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Achieving shrinkage in a time-varying parameter model framework
... We show how these two data augmentation schemes can be combined through the ancillarity-sufficiency interweaving strategy (ASIS) introduced by Yu and Meng (2011) to obtain an efficient sampler combining the ‘‘best of ...
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Inducing sparsity and shrinkage in time-varying parameter models
... However, an appreciable number of other predictors have PIPs that are substantially above zero but much less than one. In terms of the error covariance matrix, a similar pattern emerges. There is only one error ...
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Time varying parameter and fixed parameter linear AIDS : an application to tourism demand forecasting
... fixed- parameter EC counterparts is examined in an empirical study of modelling and forecasting the demand for tourism in Western European destinations by UK ...filter algorithm. The evolution of demand ...
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Time Varying Parameter and Fixed Parameter Linear AIDS: An Application to Tourism Demand Forecasting
... develops time varying parameter (TVP) linear almost ideal demand system (LAIDS) models in both long-run (LR) static and short-run error correction (EC) ...filter algorithm. The evolution of ...
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A General Framework for Observation Driven Time-Varying Parameter Models
... maximization algorithm converges quickly and ...the parameter of ...of time-varying copulas in Subsection ...large parameter spaces and (perhaps even) more complicated ...
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Monetary Policy and Time Varying Parameter Vector Autoregression Model
... a time-varying parameter vector autoregressive model with sign restrictions which is estimated by using Bayesian ...The algorithm consists in looping 101000 runs out of which the first 100000 ...
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Bayesian Markov switching tensor regression for time-varying networks
... logistic regression models in terms of computational speed and higher effective sample ...the parameter vector is normal while that of the latent variable follows a P´ ...Metropolis-Hastings ...
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Forecasting tourist arrivals using time-varying parameter structural time series models
... Structural time series models (STSMs), which specify the trend, seasonal and cycle components of a variable as stochastic, and the time-varying parameter (TVP) regression approach, ...
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