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Finite-sample size distortion of the AESTAR unit root test : GARCH, corrected variance-covariance matrix estimators and adjusted critical values

Cook, Steven - In: Applied economics letters 23 (2016) 4/6, pp. 318-323

Persistent link: https://www.econbiz.de/10011430513

Restricted likelihood ratio tests in predictive regression

Phillips, Peter C. B.; Chen, Ye - 2014

Persistent link: https://www.econbiz.de/10010464129

The finite-sample size of the BDS test for GARCH standardized residuals

Fernandes, Marcelo; Preumont, Pierre-Yves - In: Brazilian review of econometrics : BRE ; the review of … 32 (2012) 2, pp. 241-260

Persistent link: https://www.econbiz.de/10011538566

A practical guide to weak instruments

Keane, Michael P.; Neal, Timothy - 2021

Persistent link: https://www.econbiz.de/10012628852

Bootstrap model averaging unit root inference

Hansen, Bruce E.; Racine, Jeffrey - In: Essays in honor of Subal Kumbhakar, (pp. 81-98). 2024

Persistent link: https://www.econbiz.de/10014559143

Instrument strength in IV estimation and inference : a guide to theory and practice

Keane, Michael P.; Neal, Timothy - In: Journal of econometrics 235 (2023) 2, pp. 1625-1653

Persistent link: https://www.econbiz.de/10014471419

Commodity prices and the US money supply in the long run

Azar, Samih Antoine - In: International journal of trade and global markets 5 (2012) 3/4, pp. 316-335

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Volatility in cereal prices : intra- versus inter-annual volatility

Ott, Hervé - In: Journal of agricultural economics 65 (2014) 3, pp. 557-578

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Robust tests for a linear trend with an application to equity indices

Astill, Sam; Harvey, David I.; Leybourne, Stephen James; … - In: Journal of empirical finance 29 (2014), pp. 168-185

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Robust critical values for unit root tests for series with conditional heteroscedasticity errors : an application of the simple NoVaS transformation

Mantalos, Panagiotis - In: Cogent economics & finance 5 (2017) 1, pp. 1-12

In this paper, we introduce a set of critical values for unit root tests that are robust in the presence of conditional heteroscedasticity errors using the normalizing and variance-stabilizing transformation (NoVaS) and examine their properties using Monte Carlo methods. In terms of the size of...

Persistent link: https://www.econbiz.de/10011877334