Sup-tests for linearity in a general nonlinear AR(1) model when the supremum is taken over the full parameter space
AbstractWe consider linearity testing in a general class of nonlinear time series model of order 1, involving a nonnegative nuisance parameter which (i) is not identified under the null hypothesis and (ii) gives the linear model when equal to zero. This paper studies the asymptotic distribution of the Likelihood Ratio test and asymptotically equivalent supremum tests. The asymptotic distribution is described as a functional of chi-square processes and is obtained without imposing a positive lower bound for the nuisance parameter. The finite sample properties of the sup-tests are studied by simulations.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 16669.
Date of creation: 2008
Date of revision:
Diagnostic checking; Exponential autoregressive (EXPAR) model; Lagrange Multiplier (LM) tests; Least Squares Estimator; Likelihood Ratio (LR); Non Linear models; Supremum Tests; Smooth Transition Autoregressive (STAR); Threshold AR (TAR); Wald test;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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