Testing for Threshold Effects in Presence of Heteroskedasticity and Measurement Error with an application to Italian Strikes
Francesco Angelini, Massimiliano Castellani, Simone Giannerini, and Greta Goracci

TL;DR
This paper develops a new statistical test for detecting threshold effects in macroeconomic time series with heteroskedasticity and measurement error, demonstrated through an application to Italian strikes.
Contribution
It introduces a supremum Lagrange Multiplier test for TARMA-GARCH models, addressing issues of nuisance parameters and measurement error in macroeconomic data.
Findings
The proposed test correctly maintains size under heteroskedasticity.
TARMA-GARCH models capture asymmetric cycles and regime-switching in Italian strikes.
Ignoring heteroskedasticity leads to incorrect inference.
Abstract
Many macroeconomic time series are characterised by nonlinearity both in the conditional mean and in the conditional variance and, in practice, it is important to investigate separately these two aspects. Here 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 against the alternative of a TARMA-GARCH model. We derive the asymptotic null distribution of the test statistic and this requires novel results since the difficulties of working with nuisance parameters, absent under the null hypothesis, are amplified by the non-linear moving average, combined with 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, we show…
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Taxonomy
TopicsItaly: Economic History and Contemporary Issues · Monetary Policy and Economic Impact · Economic Policies and Impacts
Methodsfail
