Abstract
| Language | English |
|---|---|
| Pages | 1126-1138 |
| Number of pages | 13 |
| Journal | Journal of Economic Dynamics and Control |
| Volume | 35 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2011 |
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Keywords
- Bayesian
- state space model
- Markov chain Monte Carlo
- Metropolis–Hastings
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Time varying VARs with inequality restrictions. / Koop, Gary; Potter, Simon M.
In: Journal of Economic Dynamics and Control, Vol. 35, No. 7, 07.2011, p. 1126-1138.Research output: Contribution to journal › Article
TY - JOUR
T1 - Time varying VARs with inequality restrictions
AU - Koop, Gary
AU - Potter, Simon M.
PY - 2011/7
Y1 - 2011/7
N2 - In many applications involving time-varying parameter VARs, it is desirable to restrict the VAR coefficients at each point in time to be non-explosive. This is an example of a problem where inequality restrictions are imposed on states in a state space model. In this paper, we describe how existing MCMC algorithms for imposing such inequality restrictions can work poorly (or not at all) and suggest alternative algorithms which exhibit better performance. Furthermore, we show that previous algorithms involve an approximation relating to a key prior integrating constant. Our algorithms are exact, not involving this approximation. In an application involving a commonly used U.S. data set, we present evidence that the algorithms proposed in this paper work well.
AB - In many applications involving time-varying parameter VARs, it is desirable to restrict the VAR coefficients at each point in time to be non-explosive. This is an example of a problem where inequality restrictions are imposed on states in a state space model. In this paper, we describe how existing MCMC algorithms for imposing such inequality restrictions can work poorly (or not at all) and suggest alternative algorithms which exhibit better performance. Furthermore, we show that previous algorithms involve an approximation relating to a key prior integrating constant. Our algorithms are exact, not involving this approximation. In an application involving a commonly used U.S. data set, we present evidence that the algorithms proposed in this paper work well.
KW - Bayesian
KW - state space model
KW - Markov chain Monte Carlo
KW - Metropolis–Hastings
UR - http://www.scopus.com/inward/record.url?scp=79955966149&partnerID=8YFLogxK
U2 - 10.1016/j.jedc.2011.02.001
DO - 10.1016/j.jedc.2011.02.001
M3 - Article
VL - 35
SP - 1126
EP - 1138
JO - Journal of Economic Dynamics and Control
T2 - Journal of Economic Dynamics and Control
JF - Journal of Economic Dynamics and Control
SN - 0165-1889
IS - 7
ER -