Unit Root Testing in Heteroscedastic Panels Using the Cauchy Estimator

Demetrescu, Matei; Hanck, Christoph

doi:10.1080/07350015.2011.638839

Cited by 35 publications

(17 citation statements)

References 17 publications

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“…Recently, Demetrescu and Hanck (2012b) have demonstrated that the Cauchy tests proposed by Shin and Kang (2006) are robust to heteroskedasticity. However, the tests involve an orthogonalization procedure that demands the time dimension T to be much larger than the cross-sectional dimension N to obtain reasonable size of the tests.…”

Section: • Pooled Olsmentioning

confidence: 99%

“…The robustness of the Cauchy-based tests to time-varying volatility is argued to arise from the fact that the sign function discounts the lagged level to -1 and 1 regardless of the change in volatility over time. A particular shortcoming of A c c e p t e d M a n u s c r i p t the test in Demetrescu and Hanck (2012b) is that the employed orthogonalization scheme invokes marked finite sample size distortions if the time dimension is not larger than the cross sectional dimension. Against this background Demetrescu and Hanck (2012a) suggest to avoid the need for orthogonalization altogether by applying the Cauchy instrumenting on a White-type pooled estimator.…”

Section: Introductionmentioning

confidence: 99%

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Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions

Herwartz

Siedenburg

Walle

2014

Econometric Reviews

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Noting that many economic variables display occasional shifts in their second order moments, we investigate the performance of homogenous panel unit root tests in the presence of permanent volatility shifts. It is shown that in this case the test statistic proposed by Herwartz and Siedenburg (2008) is asymptotically standard Gaussian. By means of a simulation study we illustrate the performance of first and second generation panel unit root tests and undertake a more detailed comparison of the test in Herwartz and Siedenburg (2008) and its heteroskedasticity consistent Cauchy counterpart introduced in Demetrescu and Hanck (2012a). As an empirical illustration, we reassess evidence on the Fisher hypothesis with data from nine countries over the period 1961Q2-2011Q2. Empirical evidence supports panel stationarity of the real interest rate for the entire subperiod. With regard to the most recent two decades the test results cast doubts on market integration, since the real interest rate is diagnosed nonstationary. pt

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Section: • Pooled Olsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions

Herwartz

Siedenburg

Walle

2014

Econometric Reviews

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“…Two further heteroskedasticity-robust PURTs that we are aware of are those proposed in Demetrescu and Hanck (2012b) and Westerlund (2014). A common limitation of all these PURTs, however, is that in the presence of linear trends (i.e., δ = 0 in (1)), applying standard detrending schemes does not retain the pivotalness of the tests if the data exhibit variance breaks.…”

Section: The White-type Cauchy Testmentioning

confidence: 99%

Heteroskedasticity-Robust Unit Root Testing for Trending Panels

2017

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Simulation results reveal that the test tends to be conservative but shows remarkable power in finite samples. Terms of use: Documents in EconStor mayJEL Classification: C23, C12, Q40.

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“…Hence, applied researchers need not resort to resampling procedures, or even consult tables of critical values resulting from non‐standard null distributions, as is the case for classical cointegration tests. The nonlinear IV method has been successfully used in the unit root case: Demetrescu and Hanck () proved the t ‐statistic based on this ‘Cauchy’ estimator (introduced by So and Shin, ) to be robust to general deterministic heteroskedasticity in the time dimension and to have good local power. Technically, adapting the sign IV approach to no error correction tests is more challenging than in the unit root case.…”

Section: Introductionmentioning

confidence: 99%

Multiple Testing for No Cointegration under Nonstationary Volatility

Demetrescu

Hanck

2017

Oxf Bull Econ Stat

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With cointegration tests often being oversized under time‐varying error variance, it is possible, if not likely, to confuse error variance non‐stationarity with cointegration. This paper takes an instrumental variable (IV) approach to establish individual‐unit test statistics for no cointegration that are robust to variance non‐stationarity. The sign of a fitted departure from long‐run equilibrium is used as an instrument when estimating an error‐correction model. The resulting IV‐based test is shown to follow a chi‐square limiting null distribution irrespective of the variance pattern of the data‐generating process. In spite of this, the test proposed here has, unlike previous work relying on instrumental variables, competitive local power against sequences of local alternatives in 1/T‐neighbourhoods of the null. The standard limiting null distribution motivates, using the single‐unit tests in a multiple testing approach for cointegration in multi‐country data sets by combining P‐values from individual units. Simulations suggest good performance of the single‐unit and multiple testing procedures under various plausible designs of cross‐sectional correlation and cross‐unit cointegration in the data. An application to the equilibrium relationship between short‐ and long‐term interest rates illustrates the dramatic differences between results of robust and non‐robust tests.

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Unit Root Testing in Heteroscedastic Panels Using the Cauchy Estimator

Cited by 35 publications

References 17 publications

Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions

Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions

Heteroskedasticity-Robust Unit Root Testing for Trending Panels

Multiple Testing for No Cointegration under Nonstationary Volatility

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