Testing for Coefficient Stability of AR(1) Model When the Null is an Integrated or a Stationary Process
AbstractIn this paper, we propose a test for coefficient stability of an AR(1) model against the random coefficient autoregressive model of order 1 or RCA(1) model without assuming a stationary nor a non- stationary process under the null hypothesis of constant coefficient. The proposed test is obtained as a modification of the locally best invariant (LBI) test by Lee (1998). We examine finite sample properties of the proposed test by Monte Carlo experiments comparing with other existing tests including the LBI test by McCabe and Tremayne (1995), which is for the null of unit root against the alternative of stochastic unit root.
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Bibliographic InfoPaper provided by Institute for Monetary and Economic Studies, Bank of Japan in its series IMES Discussion Paper Series with number 07-E-20.
Date of creation: Nov 2007
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Random Coefficient Autoregressive Model; Stability; Constancy;
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
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