Estimation of Structural Vector Autoregressive (SVAR)
In search of Q: results on identification in structural vector autoregressive models
... There are two potential next steps for the analyses carried out in this thesis. First, draw- ing on the ideas in Ludvigson, Ma, and Ng (2017) one can possibly further restrict the identified sets in Chapters 2 and 4. The ...
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GMM Estimation of Non-Gaussian Structural Vector Autoregression
... The structural vector autoregressive (SVAR) model is one of the most popular tools in empirical macroeconomics and ...a vector autoregression (VAR), which is a purely statistical model ...
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Identification and estimation of non-Gaussian structural vector autoregressions
... Conventional structural vector autoregressive (SVAR) models with Gaussian errors are not identified, and additional identifying restrictions are needed in applied ...error vector consists of ...
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Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
... of structural vector autoregressive (SVAR) models popular in econometric theory, in which numerous attempts have been made for its estimation, see, for example, Swanson and Granger (1997), ...
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A No-Arbitrage Structural Vector Autoregressive Model of the UK Yield Curve
... The vector Y t Er of the remaining bond yields is instead observed with independently distributed zero-mean ...two-step estimation procedure, which drastically decreases the number of parameters to be ...
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A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines
... Abstract: This study reports on the performance assessment of Chinese airlines from 2006- 2014 using a stochastic distance function where technical efficiency and a measure of flight delays follow a joint ...
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Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis
... Douc, Moulines and Ryd´en (2004). The case of cointegrated VARs seems less well explored. We use a two-step estimation procedure. In the first step the cointegration relation is estimated by Johansen’s reduced ...
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Identification and estimation issues in Structural Vector Autoregressions with external instruments
... the autoregressive coefficients and a particular constrained structure in the matrix which maps the reduced form disturbances to the structural ...instrumented structural shocks, but it is possible ...
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An empirical analysis of how oil price changes influence the Norwegian economy : a structural vector autoregressive approach
... 45 activity and field development, implying a long term effect. This argument would apply for most oil producers, but could be weakened by the fact that some significant oil producers have large excess capacity. The ...
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Structural Breaks in the Cointegrated Vector Autoregressive Model
... Table 5.4: Estimation results. Testing the expectations hypothesis in the cointegrated VAR with- out structural breaks. Note that the p-value is invalid because model 5 is strongly rejected against model 1. ...
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Penalized Estimation of Panel Vector Autoregressive Models
... penalized estimation reduces computational burdens by relying on a coordinate descent algorithm compared to Bayesian alternatives for PVAR models which use Markov Chain Monte Carlo algorithms that are limited for ...
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Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks
... factor vector autoregressive model (F-VAR) framework, is ...of structural shocks are responsible for the observed comovement in economic data; it is, however, also assumed that commonalities across ...
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Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks
... and structural breaks is a well known issue in the literature (see, for instance, Diebold and Inoue, 2001); the …ndings, however, provide some additional interesting insights, as the discrimination between the two ...
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Bayesian analysis of a vector autoregressive model with multiple structural breaks
... a vector autoregressive model with multiple structural breaks based on MCMC simulation methods, extending a method developed for the univariate case by Wang and Zivot ...of structural breaks ...
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Bayesian analysis of the predictive power of the yield curve using a vector autoregressive model with multiple structural breaks
... 4 Estimation Results We use a VAR model with structural breaks in the intercept term µ and the volatility Ω described in (3) to analyze the predictive power of the yield curve on output ...of ...
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Identification in structural vector autoregressive models with structural changes
... uses structural changes and di¤erent het- eroskedasticity regimes found in the data constructively to improve the identi…cation of structural parameters in Structural Vector Autoregressions ...
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PC VAR Estimation of Vector Autoregressive Models
... PC-VAR estimation of vector autoregressive models (VAR) is ...The estimation strategy success- fully lessens the curse of dimensionality affecting VAR models, when estimated using sample sizes ...
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A Structural Vector Autoregressive (SVAR) model for the Hungarian labour market
... a Structural Vector Autoregressive (SVAR) model with particular attention to the Hungarian labour ...of structural shocks is based on sign ...four structural shocks: a labour supply, an ...
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A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models
... is typically generated by a VARMA, not by a VAR process. The VARMA class includes many models of interest such as unobserved component models. It is well known that linearized dynamic stochastic general equilibrium ...
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Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms
... 6. Conclusions This study has explored partial cointegrated vector autoregressive models subject to structural breaks in deterministic terms, a linear trend and constant. The Granger–Johansen ...
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