SEMI‐PARAMETRIC ESTIMATION OF LINEAR COINTEGRATING MODELS WITH NONLINEAR CONTEMPORANEOUS ENDOGENEITY
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Publication:5176850
DOI10.1111/JTSA.12075zbMath1311.62050OpenAlexW1499592367MaRDI QIDQ5176850
Publication date: 4 March 2015
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/jtsa.12075
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05)
Cites Work
- Unnamed Item
- Statistical Inference in Instrumental Variables Regression with I(1) Processes
- A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems
- Testing for cointegration using partially linear models
- On adaptive estimation
- Adaptive estimation of cointegrating regressions with ARMA errors
- Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments.
- Optimal Inference in Cointegrated Systems
- UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
- Limiting behavior of U-statistics for stationary, absolutely regular processes
- INSTRUMENTAL VARIABLE INTERPRETATION OF COINTEGRATION WITH INFERENCE RESULTS FOR FRACTIONAL COINTEGRATION
- Fully Modified Least Squares and Vector Autoregression
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