Climate policy uncertainty and the US economic cycle
J Yang, D Dong, C Liang - Technological Forecasting and Social Change, 2024 - Elsevier
Given the concerns arising from climate change, countries, regions, and organizations
worldwide have developed and implemented policy frameworks and measures aimed at …
worldwide have developed and implemented policy frameworks and measures aimed at …
Grouped variable selection with discrete optimization: Computational and statistical perspectives
Grouped variable selection with discrete optimization: Computational and statistical
perspectives Page 1 The Annals of Statistics 2023, Vol. 51, No. 1, 1–32 https://doi.org/10.1214/21-AOS2155 …
perspectives Page 1 The Annals of Statistics 2023, Vol. 51, No. 1, 1–32 https://doi.org/10.1214/21-AOS2155 …
The boosted Hodrick‐Prescott filter is more general than you might think
The global financial crisis and Covid‐19 recession have renewed discussion concerning
trend‐cycle discovery in macroeconomic data, and boosting has recently upgraded the …
trend‐cycle discovery in macroeconomic data, and boosting has recently upgraded the …
A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series
K Webel - 2022 - papers.ssrn.com
Infra-monthly time series have increasingly appeared on the radar of official statistics in
recent years, mostly as a consequence of a general digital transformation process and the …
recent years, mostly as a consequence of a general digital transformation process and the …
The boosted HP filter is more general than you might think
The global financial crisis and Covid recession have renewed discussion concerning trend-
cycle discovery in macroeconomic data, and boosting has recently upgraded the popular HP …
cycle discovery in macroeconomic data, and boosting has recently upgraded the popular HP …
[HTML][HTML] Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea
E Hwang, SM Yu - Results in Physics, 2021 - Elsevier
This paper deals with time series analysis for COVID-19 in South Korea. We adopt
heterogeneous autoregressive (HAR) time series models and discuss the statistical …
heterogeneous autoregressive (HAR) time series models and discuss the statistical …
The statistical challenges of modelling COVID-19
P Dolton - National Institute Economic Review, 2021 - cambridge.org
In 2020–2021, the world has been gripped by a pandemic that no living person has ever
known. The coronavirus pandemic is undoubtedly the greatest challenge the world has …
known. The coronavirus pandemic is undoubtedly the greatest challenge the world has …
Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs
We present a general framework for Bayesian estimation and causality assessment in
epidemiological models. The key to our approach is the use of sequential Monte Carlo …
epidemiological models. The key to our approach is the use of sequential Monte Carlo …
Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: a dynamic intensity model
O Boldea, A Cornea-Madeira… - The Econometrics …, 2023 - academic.oup.com
In this paper, we estimate the path of daily SARS-CoV-2 infections in England from the
beginning of the pandemic until the end of 2021. We employ a dynamic intensity model …
beginning of the pandemic until the end of 2021. We employ a dynamic intensity model …
Modeling COVID-19 Infection Rates by Regime-Switching Unobserved Components Models
The COVID-19 pandemic is characterized by a recurring sequence of peaks and troughs.
This article proposes a regime-switching unobserved components (UC) approach to model …
This article proposes a regime-switching unobserved components (UC) approach to model …