Testing for Common Features

Robert F. Engle · Sharon Kozicki

196 citations0/0 files storedJournal of Business and Economic Statistics

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Financial Risk and Volatility Modeling Monetary Policy and Economic Impact Spatial and Panel Data Analysis

Abstract

This article introduces a class of statistical tests for the hypothesis that some feature that is present in each of several variables is common to them. Features are data properties such as serial correlation, trends, seasonality, heteroscedasticity, autoregressive conditional hetero-scedasticity, and excess kurtosis. A feature is detected by a hypothesis test taking no feature as the null, and a common feature is detected by a test that finds linear combinations of variables with no feature. Often, an exact asymptotic critical value can be obtained that is simply a test of overidentifying restrictions in an instrumental variable regression. This article tests for a common international business cycle.

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References

1987Co-Integration and Error Correction: Representation, Estimation, and Testing 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1988Statistical analysis of cointegration vectors 1991Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models 1987Forecasting and testing in co-integrated systems 1988Testing for Common Trends 1991Critical Values for Cointegratio11 Tests*1989The dynamics of exchange rate volatility: A multivariate latent factor ARCH model

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