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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models
Giesen, Sebastian; Scheufele, Rolf - 2013
characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and … potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including … the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model …
Persistent link: https://www.econbiz.de/10010314773
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Effects of incorrect specification on the finite sample properties of full and limited information estimators in DSGE models
Giesen, Sebastian; Scheufele, Rolf - 2013
significance tests are mostly reliable. -- FIML ; GMM ; finite sample bias ; misspecification ; Monte Carlo ; DSGE … characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and … mit begrenzter Information (hier GMM) unverzerrt bleiben und auch Signifikanztests zuverlässiger sind. -- FIML ; GMM …
Persistent link: https://www.econbiz.de/10009735826
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Effects of incorrect specification on the finite sample properties of full and limited information estimators in DSGE models
Giesen, Sebastian; Scheufele, Rolf - In: Journal of macroeconomics 48 (2016), pp. 1-18
Persistent link: https://www.econbiz.de/10011711024
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Impulse response analysis in a misspecified DSGE model : a comparison of full and limited information techniques
Giesen, Sebastian; Scheufele, Rolf - In: Applied economics letters 23 (2016) 1/3, pp. 162-166
Persistent link: https://www.econbiz.de/10011414505
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Efficient Inference with Time-Varying Identification Strength
Antoine, Bertille; Boldea, Otilia - Department of Economics, Simon Fraser University - 2014
In the last two decades, there has been a lot of empirical evidence suggesting that many macroeconometric and financial models (e.g. for inflation, interest rates, or exchange rates) are subject to both parameter instability and identification problems. In this paper, we address both issues in a...
Persistent link: https://www.econbiz.de/10010818165
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GMM Estimation with Noncausal Instruments Under Rational Expectations
Lof, Matthijs - 2011
There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is … distributional assumptions, that do not always hold. In particular under rational expectations, the GMM estimator is found to be …
Persistent link: https://www.econbiz.de/10013117256
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Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version
Cheng, Xu - 2015
This paper studies the averaging generalized method of moments (GMM) estimator that combines a conservative GMM … estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment … misspecification, whereas the pre-test estimators reduce the risk in parts of the parameter space and increase it in other parts. To …
Persistent link: https://www.econbiz.de/10013025551
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Solutions-driven specification of DSGE models
Blasques, Francisco - 2013
Persistent link: https://www.econbiz.de/10010191405
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Serially correlated measurement errors in time series regression: The potential of instrumental variable estimators
Biørn, Erik - 2014
The measurement error problem in linear time series regression, with focus on the impact of error memory, modeled as nite-order MA processes, is considered. Three prototype models, two bivariate and one univariate ARMA, and ways of handling the problem by using instrumental variables (IVs) are...
Persistent link: https://www.econbiz.de/10011335598
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Serially correlated measurement errors in time series regression : the potential of instrumental variable estimators
Biørn, Erik - 2014 - This version December 2014
The measurement error problem in linear time series regression, with focus on the impact of error memory, modeled as nite-order MA processes, is considered. Three prototype models, two bivariate and one univariate ARMA, and ways of handling the problem by using instrumental variables (IVs) are...
Persistent link: https://www.econbiz.de/10010459136