ARMAX model specification testing, with an application to unemployment in the Netherlands
From MaRDI portal
Publication:1090051
DOI10.1016/0304-4076(87)90086-8zbMath0621.62106OpenAlexW2791675963MaRDI QIDQ1090051
Publication date: 1987
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/1871/11860
time seriesconditional expectationGranger causalitymisspecificationstrictly stationaryARMAX model specificationNetherlands unemployment ratenew model specification testrational expectations - natural rate hypothesisvector ARMAX model
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Related Items
ARMAX model specification testing, with an application to unemployment in the Netherlands, Basic structure of the asymptotic theory in dynamic nonlineaerco nometric models, part i: consistency and approximation concepts, Testing for multivariate volatility functions using minimum volume sets and inverse regression, Consistent GMM Residuals-Based Tests of Functional Form, The Bierens test under data dependence, Revisiting Tests for Neglected Nonlinearity Using Artificial Neural Networks, Testing for neglected nonlinearity in time series models. A comparison of neural network methods and alternative tests, TAIL AND NONTAIL MEMORY WITH APPLICATIONS TO EXTREME VALUE AND ROBUST STATISTICS, The Bierens test for certain nonstationary models
Cites Work
- Unnamed Item
- Unnamed Item
- Consistent model specification tests
- Non-linear regression with discrete explanatory variables, with an application to the earnings function
- Model specification testing of time series regressions
- ARMAX model specification testing, with an application to unemployment in the Netherlands
- Estimation of vector Armax models
- A maximal inequality and dependent strong laws
- Nonlinear Regression with Dependent Observations
- Uniform Consistency of Kernel Estimators of a Regression Function Under Generalized Conditions
- Testing Non-Nested Nonlinear Regression Models
- Testing Against General Autoregressive and Moving Average Error Models when the Regressors Include Lagged Dependent Variables
- Testing for Higher Order Serial Correlation in Regression Equations when the Regressors Include Lagged Dependent Variables
- Forecasting and conditional projection using realistic prior distributions
- A uniform weak law of large numbers under π‐mixing with application to nonlinear least squares estimation
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Martingale Central Limit Theorems
- Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models