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

Bibliographic Data

ID21512914
AuthorsFrancesco Angelini (0000-0002-7903-964X, Department of Statistical Sciences University of Bologna Italy), Massimiliano Castellani (0000-0002-5814-5902, Department of Statistical Sciences University of Bologna Italy), Simone Giannerini (0000-0002-0710-668X, Department of Economics and Statistics University of Udine Italy), Greta Goracci (0000-0001-5212-0539, Faculty of Economics and Management Free University of Bozen‐Bolzano Italy)
Year2025
Volume87
Issue3
Pages659-689
Publication date2025-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueOxford Bulletin of Economics and Statistics (JOURNAL)
Journal identifiersISSN: 0305-9049 • E-ISSN: 1468-0084
PublisherWiley (PUBLISHER • GB)
DOI10.1111/obes.12647
OpenAlexW4404543148
LanguageEN
References cited56

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

Econometrics · Economics · Heteroscedasticity · Observational error · Statistics · Advanced Statistical Methods and Models · Mathematics · Monetary Policy and Economic Impact · Probabilistic and Robust Engineering Design

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