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Multicointegration under measurement errors
Hassler, Uwe - In: Economics letters 96 (2007) 1, pp. 38-44
Persistent link: https://www.econbiz.de/10003485780
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On the correlations of trend-cycle errors
Wada, Tatsuma - In: Economics letters 116 (2012) 3, pp. 396-400
Persistent link: https://www.econbiz.de/10009674324
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Bias in the estimation of mean reversion in continuous-time Lévy processes
Bao, Yong; Ullah, Aman; Wang, Yun; Yu, Jun - In: Economics letters 134 (2015), pp. 16-19
Persistent link: https://www.econbiz.de/10011432138
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Bias correcting adjustment coefficients in a cointegrated VAR with known cointegrating vectors
VanGarderen, Kees Jan; Boswijk, Herman Peter - In: Economics letters 122 (2014) 2, pp. 224-228
Persistent link: https://www.econbiz.de/10010395161
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Collective mass media bias, social media, and non-partisans
Luo, Xiaoyi - In: Economics letters 156 (2017), pp. 78-81
Persistent link: https://www.econbiz.de/10011822371
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Finite sample performance of a long run variance estimator based on exactly (almost) unbiased autocovariance estimators
Yang, Jingjing; Vogelsang, Timothy J. - In: Economics letters 165 (2018), pp. 21-27
Persistent link: https://www.econbiz.de/10011973806
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Learning aversion and voting rules in collective decision making
Louis, Philippos - In: Economics letters 133 (2015), pp. 24-26
Persistent link: https://www.econbiz.de/10011431836
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An experimental study of voting with costly delay
Kwiek, Maksymilian; Marreiros, Helia; Vlassopoulos, Michael - In: Economics letters 140 (2016), pp. 23-26
Persistent link: https://www.econbiz.de/10011615776
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Asymmetries in Conditional Mean and Variance: Modelling Stock Returns by asMA-asQGARCH
Brännäs, Kurt; de Gooijer, Jan G. - 2000
variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared …
Persistent link: https://www.econbiz.de/10010324389
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Combined Forecasts from Linear and Nonlinear Time Series Models
Terui, N.; van Dijk, Herman K. - 2000
Combined forecasts from a linear and a nonlinear model areinvestigated for timeseries with possibly nonlinear characteristics. The forecasts arecombined by aconstant coefficient regression method as well as a time varyingmethod. Thetime varying method allows for a locally (non)linear model....
Persistent link: https://www.econbiz.de/10010324396