Vector autoregressive moving average identification for macroeconomic modeling: a new methodology
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Publication:281054
DOI10.1016/j.jeconom.2016.02.011zbMath1420.62395OpenAlexW2185330090MaRDI QIDQ281054
Publication date: 10 May 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2016.02.011
spectral factorizationcointegrationinstrumental variablescanonical correlationsechelon formKronecker invariants
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Measures of association (correlation, canonical correlation, etc.) (62H20)
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Cites Work
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- Making a match: combining theory and evidence in policy-oriented macroeconomic modeling
- Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
- Asymptotic properties of projections with applications to stochastic regression problems
- Identification of echelon canonical forms for vector linear processes using least squares
- Business cycle analysis without much theory: A look at structural VARs
- Consistency and relative efficiency of subspace methods
- Multivariate linear time series models
- ON THE IDENTIFICATION AND ESTIMATION OF NONSTATIONARY AND COINTEGRATED ARMAX SYSTEMS
- A complete VARMA modelling methodology based on scalar components
- USING SUBSPACE METHODS FOR ESTIMATING ARMA MODELS FOR MULTIVARIATE TIME SERIES WITH CONDITIONALLY HETEROSKEDASTIC INNOVATIONS
- Optimal instrumental variable estimates of the AR parameters of an ARMA process
- ARMA models, their Kronecker indices and their McMillan degree
- Recursive estimation of mixed autoregressive-moving average order
- Stochastic theory of minimal realization
- A canonical analysis of multiple time series
- Multiple Time Series Analysis and the Final Form of Econometric Models
- Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
- Co-Integration and Error Correction: Representation, Estimation, and Testing
- Forecasting and conditional projection using realistic prior distributions
- Estimation and Testing for Unit Roots in a Partially Nonstationary Vector Autoregressive Moving Average Model
- Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form
- A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models
- A Note on the Specification and Estimation of ARMAX Systems
- Factorization of the Covariance Generating Function of a Pure Moving Average Process
- Non-linear time series regression
- ESTIMATING LINEAR DYNAMICAL SYSTEMS USING SUBSPACE METHODS
- Elements of multivariate time series analysis.
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