Inference in continuous systems with mildly explosive regressors

New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial co...

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Main Authors: CHEN, Ye, PHILLIPS, Peter C. B., YU, Jun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/soe_research/2111
https://ink.library.smu.edu.sg/context/soe_research/article/3111/viewcontent/1_s20_S0304407617301689_main.pdf
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spelling sg-smu-ink.soe_research-31112020-01-21T06:22:12Z Inference in continuous systems with mildly explosive regressors CHEN, Ye PHILLIPS, Peter C. B. YU, Jun New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressors, and is feasible to implement in practice. Simulations show that double asymptotics deliver a good approximation to the finite sample distribution, with both finite sample and asymptotic distributions showing sensitivity to initial conditions. The methods are implemented in the US real estate market for an empirical application, illustrating the usefulness of double asymptotics in practical work. 2017-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2111 info:doi/10.1016/j.jeconom.2017.08.016 https://ink.library.smu.edu.sg/context/soe_research/article/3111/viewcontent/1_s20_S0304407617301689_main.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Cointegrated system Explosive process Moderate deviations from unity Double asymptotics Real estate market Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Cointegrated system
Explosive process
Moderate deviations from unity
Double asymptotics
Real estate market
Econometrics
spellingShingle Cointegrated system
Explosive process
Moderate deviations from unity
Double asymptotics
Real estate market
Econometrics
CHEN, Ye
PHILLIPS, Peter C. B.
YU, Jun
Inference in continuous systems with mildly explosive regressors
description New limit theory is developed for co-moving systems with explosive processes, connecting continuous and discrete time formulations. The theory uses double asymptotics with infill (as the sampling interval tends to zero) and large time span asymptotics. The limit theory explicitly involves initial conditions, allows for drift in the system, is provided for single and multiple explosive regressors, and is feasible to implement in practice. Simulations show that double asymptotics deliver a good approximation to the finite sample distribution, with both finite sample and asymptotic distributions showing sensitivity to initial conditions. The methods are implemented in the US real estate market for an empirical application, illustrating the usefulness of double asymptotics in practical work.
format text
author CHEN, Ye
PHILLIPS, Peter C. B.
YU, Jun
author_facet CHEN, Ye
PHILLIPS, Peter C. B.
YU, Jun
author_sort CHEN, Ye
title Inference in continuous systems with mildly explosive regressors
title_short Inference in continuous systems with mildly explosive regressors
title_full Inference in continuous systems with mildly explosive regressors
title_fullStr Inference in continuous systems with mildly explosive regressors
title_full_unstemmed Inference in continuous systems with mildly explosive regressors
title_sort inference in continuous systems with mildly explosive regressors
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/soe_research/2111
https://ink.library.smu.edu.sg/context/soe_research/article/3111/viewcontent/1_s20_S0304407617301689_main.pdf
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