Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Chan JCC"'
Publikováno v:
International Journal of Nanomedicine, Vol Volume 13, Pp 261-271 (2018)
Bor-Shiunn Lee,1,2 Hong-Ping Lin,3 Jerry Chun-Chung Chan,4 Wei-Chuan Wang,2 Ping-Hsuan Hung,2 Yu-Hsin Tsai,4 Yuan-Ling Lee1,2 1Graduate Institute of Oral Biology, 2Graduate Institute of Clinical Dentistry, School of Dentistry, National Taiwan Univers
Externí odkaz:
https://doaj.org/article/d354df21eacd4627b7d70128efcc7002
Autor:
Chan, JCC
Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. The key to making these highly parameterized VARs useful is the use of shrinkage priors. We develop a family of priors that captures the best features o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::8b1eae6a4a213909e1839ca5f124d8d3
https://hdl.handle.net/10453/154312
https://hdl.handle.net/10453/154312
We estimate the dynamics of a speculative bubble subject to a surviving and a collapsing regime together with the dynamics of dividends and returns in a tractable state space specification of the present-value model. To estimate this new high-dimensi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::ab4ebf489ef4a6014dd37a089f69c3e5
https://hdl.handle.net/10453/155948
https://hdl.handle.net/10453/155948
Autor:
Chan, JCC, Strachan, RW
State space models play an important role in macroeconometric analysis and the Bayesian approach has been shown to have many advantages. This paper outlines recent developments in state space modelling applied to macroeconomics using Bayesian methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::d1b2efed3bf858c79dbf5fe33b3fe596
https://hdl.handle.net/10453/150097
https://hdl.handle.net/10453/150097
Autor:
Chan, JCC
© 2020, © 2020 American Statistical Association. We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-Gaussian, heteroscedastic, and serially dependent innovations. To make estimation computationally tractable,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::26f02eddc67fa0ecb60e340722f1df29
https://hdl.handle.net/10453/139991
https://hdl.handle.net/10453/139991
© 2019 Walter de Gruyter GmbH, Berlin/Boston. A flexible multivariate model of a time-varying joint distribution of asset returns is developed which allows for regime switching and a joint skew-normal distribution. A suite of tests for linear and no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::c28d9cc7cf97ec1ce51a0e810dd035f4
https://hdl.handle.net/10453/139992
https://hdl.handle.net/10453/139992
Autor:
Chan, JCC, Eisenstat, E
© 2018 Elsevier B.V. Empirical questions such as whether the Phillips curve or the Okun's law is stable can often be framed as a model comparison—e.g., comparing a vector autoregression (VAR) in which the coefficients in one equation are constant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::b88ee00a898a4eef86b52b1a9e245d47
https://hdl.handle.net/10453/130080
https://hdl.handle.net/10453/130080
Autor:
Chan, JCC
© 2016 Taylor & Francis Group, LLC. We propose an easy technique to test for time-variation in coefficients and volatilities. Specifically, by using a noncentered parameterization for state space models, we develop a method to directly calculate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::c73b781926a6f088b28f571c5e1ceda6
https://hdl.handle.net/10453/130428
https://hdl.handle.net/10453/130428
© 2018 The Ohio State University Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well-anchored the inflation expectations are. We construct a model-based measu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::7f14ac1fe02115fadaac8dc5ebef9721
https://hdl.handle.net/10453/130364
https://hdl.handle.net/10453/130364