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Bayesian model averaging for spatial autoregressive models based on convex combinations of different types of connectivity matrices
Debarsy, Nicolas; Lesage, James P. - In: Journal of business & economic statistics : JBES ; a … 40 (2022) 2, pp. 547-558
Persistent link: https://www.econbiz.de/10013533452
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Markov chain Monte Carlo estimation of spatial dynamic panel models for large samples
Lesage, James P.; Chih, Yao-Yu; Vance, Colin - 2018
Focus is on efficient estimation of a dynamic space-time panel data model that incorporates spatial dependence … of spatial units and T the number of time periods. Quasi-maximum likelihood (QML) estimation in cases involving large N … estimates that require numerous inversions of large matrices. We set forth a Markov Chain Monte Carlo (MCMC) estimation …
Persistent link: https://www.econbiz.de/10011954962
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Threshold models with time-varying threshold values and their application in estimating regime-sensitive Taylor rules
Zhu, Yanli; Chen, Haiqiang; Lin, Ming - In: Studies in nonlinear dynamics and econometrics : SNDE ; … 23 (2019) 5, pp. 1-17
Persistent link: https://www.econbiz.de/10012198389
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Modeling high-frequency financial data using R and Stan : a bayesian autoregressive conditional duration approach
Tabash, Mosab I.; Navas, T. Muhammed; Thayyib, P. V.; … - In: Journal of open innovation : technology, market, and … 10 (2024) 2, pp. 1-16
In econometrics, Autoregressive Conditional Duration (ACD) models use high-frequency economic or financial duration data, which mostly exhibit irregular time intervals. The ACD model is widely used to examine the duration of transaction volume and duration of price variations in stock markets....
Persistent link: https://www.econbiz.de/10014581582
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Discrete-time stochastic volatility models and MCMC-based statistical inference
Hautsch, Nikolaus (contributor); Ou, Yangguoyi (contributor) - 2008
In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...
Persistent link: https://www.econbiz.de/10003770817
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Bayesian inference for a periodic stochastic volatility model of intraday electricity prices
Smith, Michael Stanley - In: Statistical modelling and regression structures : …, (pp. 353-376). 2010
Persistent link: https://www.econbiz.de/10003964500
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Empirical analysis of affine versus nonaffine variance specifications in jump-diffusion models for equity indices
Ignatieva, Ekaterina; Rodrigues, Paulo Jorge Maurício; … - In: Journal of business & economic statistics : JBES ; a … 33 (2015) 1, pp. 68-75
Persistent link: https://www.econbiz.de/10011389699
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Risk margin quantile function via parametric and non-parametric Bayesian approaches
Dong, Alice X. D.; Chan, Jennifer S. K.; Peters, Gareth W. - In: Astin bulletin : the journal of the International … 45 (2015) 3, pp. 503-550
Persistent link: https://www.econbiz.de/10011397246
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The time-varying effects of permanent and transistory shocks to real output
Keating, John William; Valcarcel, Victor J. - In: Macroeconomic dynamics 19 (2015) 3, pp. 477-507
Persistent link: https://www.econbiz.de/10011308634
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A Bayesian analysis of female wage dynamics using Markov chain clustering
Pamminger, Christoph; Tüchler, Regina - 2011
In dieser Arbeit analysieren wir Einkommensverläufe von Frauen in Österreich. Unser Ziel ist es, mit Hilfe von zusätzlichen erklärenden Variablen wie z.B. dem Alter bei Berufseintritt, der Kinderanzahl oder einer Karenzvariable, Gruppen von erwerbst¨atigen Frauen mit ähnlichen...
Persistent link: https://www.econbiz.de/10011344851