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A new bootstrap test for the validity of a set of marginal models for multiple dependent time series : an application to risk analysis
Ardia, David; Gatarek, Lukasz; Hoogerheide, Lennart F. - 2014
A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken "directly" from the observed data. The procedure is useful when one wants to summarize the test results for several time...
Persistent link: https://www.econbiz.de/10010250513
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Heteroskedasticity-and-autocorrelation-consistent bootstrapping
Davidson, Russell; Monticini, Andrea - 2014
In many, if not most, econometric applications, it is impossible to estimate consistently the elements of the white-noise process or processes that underlie the DGP. A common example is a regression model with heteroskedastic and/or autocorrelated disturbances,where the heteroskedasticity and...
Persistent link: https://www.econbiz.de/10011774249
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An Introduction to Bootstrap Theory in Time Series Econometrics
Cavaliere, Giuseppe - 2020
is discussed in terms of the leading example of bootstrap-based hypothesis testing in the well-known first order auto … conditions and their implications for possible improvements in terms of (empirical) size and power for bootstrap-based testing …, when compared to asymptotic testing, are illustrated by simulations. Following this, an overview of selected recent …
Persistent link: https://www.econbiz.de/10012835479
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Asymmetries in conditional mean and variance : modelling stock returns by asMA-asQGARCH
Brännäs, Kurt; Gooijer, Jan G. de - 2000
The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
Persistent link: https://www.econbiz.de/10011303289
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Modelling seasonalities in nonlinear inflation rates using SEASETARs
Gooijer, Jan G. de; Vidiella-i-Anguera, Antoni - 2000
In this paper, we present a new time series model, whichdescribes self-exciting threshold autoregressive (SETAR) nonlinearityand seasonality simultaneously. The model is termed multiplicativeseasonal SETAR (SEASETAR). It can be viewed as a special case of ageneral non-multiplicativeSETAR model...
Persistent link: https://www.econbiz.de/10011304390
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Are linear models really unuseful to describe business cycle data?
Lopes, Artur C. B. da Silva; Zsurkis, Gabriel Florin - 2017
on testing only. The authors aim to maximize power to detect non-linearities and, simultaneously, they purport avoiding …
Persistent link: https://www.econbiz.de/10011596878
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Homogenous vs. heterogenous transition functions in smooth transition regressions : a LM-type test
Demetrescu, Matei; Leppin, Julian Sebastian; Reitz, Stefan - 2017
(Panel) Smooth Transition Regressions substantially gained in popularity due to their flexibility in modeling regression coefficients as homogeneous or heterogeneous functions of transition variables. In the estimation process, however, researchers typically face a trade-off in the sense that a...
Persistent link: https://www.econbiz.de/10011749886
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A Sharp Test for the Judge Leniency Design
Coulibaly, Mohamed; Hsu, Yu-Chin; Mourifié, Ismael; … - National Bureau of Economic Research - 2024
We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed...
Persistent link: https://www.econbiz.de/10014544734
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An introduction to bootstrap theory in time series econometrics
Cavaliere, Giuseppe; Bohn Nielsen, Heino; Rahbek, Anders - 2020
Persistent link: https://www.econbiz.de/10012319239
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Testing for near I(2) trends when the signal-to-noise ratio is small
Jusélius, Katarina - 2014
Researchers seldom find evidence of I(2) in exchange rates, prices, and other macroeconomics time series when they test the order of integration using univariate Dickey-Fuller tests. In contrast, when using the multivariate ML trace test they frequently find double unit roots in the data. The...
Persistent link: https://www.econbiz.de/10010355373