Testing for Threshold Effects in the Presence of Heteroskedasticity and Measurement Error With an Application to Italian Strikes

Abstract

We address the issue of testing for threshold nonlinearity in the conditional mean in the presence of conditional heteroskedasticity. We propose a supremum Lagrange multiplier approach to test a linear ARMA-GARCH model versus a TARMA-GARCH model. We derive the asymptotic null distribution of the test statistic, and this requires novel results due to nuisance parameters, absent under the null hypothesis, combined with the nonlinear moving average and GARCH-type innovations. We show that tests that do not account for heteroskedasticity fail to achieve the correct size even for large sample sizes. Moreover, the TARMA specification naturally accounts for the ubiquitous presence of measurement error that affects macroeconomic data. We apply the results to analyse the time series of Italian strikes, and we show that the TARMA-GARCH specification is consistent with the relevant macroeconomic theory while capturing the main features of the Italian strikes dynamics, such as asymmetric cycles and regime-switching.