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Consistency of model averaging estimators

Zhang, Xinyu - In: Economics letters 130 (2015), pp. 120-123

Persistent link: https://www.econbiz.de/10011422458

Consistency of the least squares estimator in threshold regression with endogeneity

Yu, Ping - In: Economics letters 131 (2015), pp. 41-46

Persistent link: https://www.econbiz.de/10011422546

Consistent estimation of structural parameters in regression models with adaptive learning

Christopeit, Norbert; Massmann, Michael - 2010

In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...

Persistent link: https://www.econbiz.de/10011381034

Estimating structural parameters in regression models with adaptive learning

Christopeit, Norbert; Massmann, Michael - 2015

This paper examines the ordinary least squares (OLS) estimator of the structural parameters in a class of stylised macroeconomic models in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable. The popularity of this type of model...

Persistent link: https://www.econbiz.de/10011333062

Nonlinear regressions with nonstationary time series

Chan, Nigel; Wang, Qiying - In: Journal of econometrics 185 (2015) 1, pp. 182-195

Persistent link: https://www.econbiz.de/10011339876

Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models

Tinkl, Fabian - 2013

In this article consistency and asymptotic normality of the quasi-maximum likelihood esti- mator (QMLE) in the class of … introduced by (Duan, 1997) which contains many commonly employed GARCH models as special cases. The conditions for consistency … normality ; consistency ; polynomial augmented GARCH models ; quasi-maximum likelihood estimation …

Persistent link: https://www.econbiz.de/10009725214