Frequency domain estimation of temporally aggregated Gaussian cointegrated systems

DOI10.1016/j.jeconom.2006.03.005zbMath1418.62307OpenAlexW2041101571MaRDI QIDQ278231

J. Roderick McCrorie, Marcus J. Chambers

Publication date: 2 May 2016

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2006.03.005

zbMATH Keywords

frequency domaincointegrationcontinuous timetemporal aggregationGaussian estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (14)

DISCRETE TIME REPRESENTATIONS OF COINTEGRATED CONTINUOUS TIME MODELS WITH MIXED SAMPLE DATA ⋮ REX BERGSTROM’S CONTRIBUTIONS TO CONTINUOUS TIME MACROECONOMETRIC MODELING ⋮ ESTIMATING CONTINUOUS-TIME MODELS ON THE BASIS OF DISCRETE DATA VIA AN EXACT DISCRETE ANALOG ⋮ Cointegrated continuous-time linear state-space and MCARMA models ⋮ On model selection criteria for climate change impact studies ⋮ Robust estimation of stationary continuous‐time arma models via indirect inference ⋮ Cointegration and sampling frequency ⋮ The estimation of continuous time models with mixed frequency data ⋮ Quasi-maximum likelihood estimation for cointegrated continuous-time linear state space models observed at low frequencies ⋮ Testing for seasonal unit roots by frequency domain regression ⋮ Estimation of continuous and discrete time co-integrated systems with stock and flow variables ⋮ Frequency Domain Estimation of Continuous Time Cointegrated Models with Mixed Frequency and Mixed Sample Data ⋮ Discrete time representation of stationary and non-stationary continuous time systems ⋮ Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Granger causality and the sampling of economic processes
• The asymptotic distribution of serial covariances
• A central limit theorem for parameter estimation in stationary vector time series and its application to models for a signal observed with noise
• Discrete time representation of stationary and non-stationary continuous time systems
• The estimation of systems of joint differential-difference equations
• The problem of aliasing in identifying finite parameter continuous time stochastic models
• The problem of identification in finite parameter continuous time models
• Narrow-band analysis of nonstationary processes
• STATISTICAL INFERENCE IN COINTEGRATED VECTOR AUTOREGRESSIVE MODELS WITH NONLINEAR TIME TRENDS IN COINTEGRATING RELATIONS
• Asymptotic Likelihood Based Inference for Co-integrated Homogenous Gaussian Diffusions
• Optimal Inference in Cointegrated Systems
• The Dimensionality of the Aliasing Problem in Models With Rational Spectral Densities
• Multiple Time Series Regression with Integrated Processes
• THE ASYMPTOTIC EFFICIENCY OF COINTEGRATION ESTIMATORS UNDER TEMPORAL AGGREGATION
• TEMPORAL AGGREGATION AND THE FINITE SAMPLE PERFORMANCE OF SPECTRAL REGRESSION ESTIMATORS IN COINTEGRATED SYSTEMS A Simulation Study
• LONG-RUN STRUCTURAL MODELLING
• Error Correction and Long-Run Equilibrium in Continuous Time
• Band Spectral Regression with Trending Data
• Asymptotic Properties of Non-Linear Least Squares Estimators
• Non-linear regression for multiple time-series
• Some Limit Theorems for Stationary Processes
• Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models

This page was built for publication: Frequency domain estimation of temporally aggregated Gaussian cointegrated systems