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Penalized indirect inference
Blasques, Francisco; Duplinskiy, Artem - 2015
Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying economic theory. Bayesian methods have become increasingly popular as a tool for conducting inference on structural models since priors offer a way to exert control over the...
Persistent link: https://www.econbiz.de/10010464781
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Simplicity, scientific inference and econometric modelling
Keuzenkamp, Hugo A.; McAleer, Michael - 1995
Persistent link: https://www.econbiz.de/10000904872
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Misspecification in linear spatial regression models
Florax, Raymond J. G. M.; Nijkamp, Peter - 2003
spatial interactions, spatial externalities and networking effects among actors, evoked the area of spatial econometrics …. Spatial econometrics focuses on the specification and estimation of regression models explicitly incorporating such spatial … from techniques designed for the analysis of time series. With that in mind, we introduce the notion of spatial effects …
Persistent link: https://www.econbiz.de/10011334352
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Simplicity, scientific inference and econometric modelling
Keuzenkamp, Hugo A.; McAleer, Michael - 1994 - Rev.
Persistent link: https://www.econbiz.de/10000560594
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Measures of fit for multinomial discrete models
Cramer, Jan S. - 2001
In a discrete model, the predicted probabilities of a particular eventcan be matched to the observed (0, I) outcomes and this will give riseto a measure of fit for that event. Previous results for the binomialmodel are applied to multinomial models. In these models the measureof fit will vary...
Persistent link: https://www.econbiz.de/10011317446
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The analysis of stochastic volatility in the presence of daily realised measures
Koopman, Siem Jan; Scharth, Marcel - 2011
Persistent link: https://www.econbiz.de/10010191086
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Extremum Monte Carlo filters : real-time signal extraction via simulation and regression
Blasques, Francisco; Koopman, Siem Jan; Moussa, Karim - 2023 - This version: March 23, 2023
This paper introduces a novel simulation-based filtering method for general state space models. It allows for the …
Persistent link: https://www.econbiz.de/10014247627
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On importance sampling for state space models
Jungbacker, Borus; Koopman, Siem Jan - 2005
and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results …
Persistent link: https://www.econbiz.de/10011348357
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Tail distribution of the maximum of correlated Gaussian random variables
Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...
Persistent link: https://www.econbiz.de/10011431354
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Mixed hitting-time models
Abbring, Jaap H. - 2009
duration analysis. …
Persistent link: https://www.econbiz.de/10011372965