Inference in dynamic models containing 'surprise' variables

DOI10.1016/0304-4076(87)90083-2zbMath0617.62118OpenAlexW2035910430MaRDI QIDQ1822190

Richard T. Baillie

Publication date: 1987

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(87)90083-2

zbMATH Keywords

moving average representationdynamic modelssurprise variablesmulti-period expectations horizontwo-step regression proceduresvector ARMA processes

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (10)

Econometric analysis of linearized singular dynamic stochastic general equilibrium models ⋮ Cointegration and speed of convergence to equilibrium ⋮ ON THE ASYMPTOTIC DISTRIBUTION OF IMPULSE RESPONSE FUNCTIONS WITH LONG-RUN RESTRICTIONS ⋮ Prediction in dynamic models with time-dependent conditional variances ⋮ Impulse response analysis of cointegrated systems ⋮ Econometric tests of rationality and market efficiency ⋮ A note on the asymptotic distribution of impulse response functions of estimated VAR models with orthogonal residuals ⋮ Asymptotic distributions of impulse response functions in short panel vector autoregressions ⋮ Inference for impulse response coefficients from multivariate fractionally integrated processes ⋮ On the relationship between impulse response analysis, innovation accounting and Granger causality

Cites Work

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• Consistent estimation of equations with composite moving average disturbance terms
• On the structure of moving average processes
• Nearly Efficient Estimation of Time Series Models with Predetermined, but not Exogenous, Instruments
• Econometric Issues in the Analysis of Regressions with Generated Regressors
• Forecasting and conditional projection using realistic prior distributions
• The Asymptotic Distribution of Dynamic Multipliers

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