Finite sample behavior of tests for grouped heteroskedasticity

Article Abstract:

Grouped heteroskedasticity exists when error variances vary across data subsets but remain constant within subsets. Various tests for grouped heteroskedasticity, based on an asymptotic Chi-squared variable, are evaluated using Monte Carlo methods. The results suggest that Bartlett's procedure, despite being the simplest, may be the most efficient test. Should its reliability come into question, its result may be verified using a more powerful method such as the Breusch-Pagan test.

Methods, Testing, Statistics, Statistics (Data), Heteroscedasticity

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Finding cointegration rank in high dimensional systems using the Johansen test: an illustration using data based Monte Carlo simulations

Article Abstract:

Data based Monte Carlo simulation methods are used to evaluate the performance of the Johansen (1991) likelihood ratio test for cointegrating vector quantity in small samples. Asymptotic critical values are used to evaluate the validity of inference. Results show that researchers should be cautious when using the Johansen estimator, since it exhibits excessive cointegration when the lag order is misspecified.

Research, Numerical integration

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Finite-sample properties of percentile and percentile-t bootstrap confidence intervals for impulse responses

Article Abstract:

A multivariate forecast evaluation method is proposed for the detection and correction of defects found in percentile-t intervals.

Science & research, Econometrics & Model Building, Statistical Data Included, Models, Econometrics, Forecasting, Business models

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