The small sample properties of several limited information estimators in interdependent structures with scalar and vector autoregressive errors

1982 ◽  
Vol 7 (1) ◽  
pp. 63-73 ◽  
Author(s):  
M. Robertson
Keyword(s):  
Small Sample ◽  
Limited Information ◽  
Vector Autoregressive ◽  
Small Sample Properties ◽  
Autoregressive Errors

scholarly journals TESTING FOR THE COINTEGRATING RANK OF A VAR PROCESS WITH AN INTERCEPT

2000 ◽  
Vol 16 (3) ◽  
pp. 373-406 ◽  
Author(s):  
Pentti Saikkonen ◽  
Helmut Lütkepohl
Keyword(s):  
Likelihood Ratio ◽  
Autoregressive Process ◽  
Small Sample ◽  
Local Power ◽  
Vector Autoregressive ◽  
Vector Autoregressive Process ◽  
Small Sample Properties

Testing the cointegrating rank of a vector autoregressive process with an intercept is considered. In addition to the likelihood ratio (LR) tests developed by Johansen and Juselius (1990, Oxford Bulletin of Economics and Statistics, 52, 169–210) and others we also consider an alternative class of tests that is based on estimating the trend parameters of the deterministic term in a different way. The asymptotic local power of these tests is derived and compared to that of the corresponding LR tests. The small sample properties are investigated by simulations. The new tests are seen to be substantially more powerful than conventional LR tests.

scholarly journals Testing identification via heteroskedasticity in structural vector autoregressive models

2020 ◽  
Author(s):  
Helmut Lütkepohl ◽  
Mika Meitz ◽  
Aleksei Netšunajev ◽  
Pentti Saikkonen
Keyword(s):  
Covariance Matrices ◽  
Small Sample ◽  
Test Statistics ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Null Distributions ◽  
Small Sample Properties ◽  
Structural Vector ◽  
Autoregressive Analysis ◽  
Time Point

Summary Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald-type tests for which only the unrestricted model, including the covariance matrices of the two volatility states, has to be estimated. The residuals of the model are assumed to be from the class of elliptical distributions, which includes Gaussian models. The asymptotic null distributions of the test statistics are derived, and simulations are used to explore their small-sample properties. Two empirical examples illustrate the usefulness of the tests in applied work.

Small-Sample Properties of Factor Mimicking Portfolio Estimates

2013 ◽  
Author(s):  
Zhuo Chen ◽  
Gregory Connor ◽  
Robert A. Korajczyk
Keyword(s):  
Small Sample ◽  
Small Sample Properties
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