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State-Space modeling of shape-constrained functional time series

Published in arXiv preprint, 2024

Functional time series data frequently appears in econometric analyses, where the functions of interest are subject to some shape constraints, including monotonicity and convexity, as typical of the estimation of the Lorenz curve. This paper proposes a state-space model for time-varying functions to extract trends and serial dependence from functional time series while imposing the shape constraints on the estimated functions.

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Stochastic volatility in mean: Efficient analysis by a generalized mixture sampler

Published in Journal of Econometrics, 2025

In this paper we consider the simulation-based Bayesian analysis of stochastic volatility in mean (SVM) models.

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Dynamic factor stochastic volatility-in-mean VAR for large macroeconomic panels

Published in arXiv preprint, 2026

We develop a dynamic factor stochastic volatility-in-mean (SVM) specification for vector autoregressions (VARs) that embeds an SVM component within a dynamic factor stochastic volatility structure.

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Unified mixture sampler for state-space models: Application to stochastic conditional duration models

Published in arXiv preprint, 2026

We propose a unified mixture sampler (UMS) that provides a universal estimation framework for nonlinear state-space models with “exp-exp” likelihood kernels.

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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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