Locally time-varying parameter regression

I discuss a framework to allow dynamic sparsity in time-varying parameter regression models. The conditional variances of the innovations of time-varying parameters are time varying and equal to zero adaptively via thresholding. The resulting model allows the dynamics of the time-varying parameters...

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Published inEconometric reviews Vol. 43; no. 5; pp. 269 - 300
Main Author He, Zhongfang
Format Journal Article
LanguageEnglish
Published New York Taylor & Francis 27.05.2024
Taylor & Francis Ltd
Subjects
Bayesian shrinkage
Econometrics
economic time series
Innovations
MCMC
Parameters
Regression models
TVP
Online AccessGet full text
ISSN0747-4938
1532-4168
DOI10.1080/07474938.2024.2330127

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Abstract I discuss a framework to allow dynamic sparsity in time-varying parameter regression models. The conditional variances of the innovations of time-varying parameters are time varying and equal to zero adaptively via thresholding. The resulting model allows the dynamics of the time-varying parameters to mix over different frequencies of parameter changes in a data driven way and permits great flexibility while achieving model parsimony. A convenient strategy is discussed to infer if each coefficient is static or dynamic and, if dynamic, how frequent the parameter change is. An MCMC scheme is developed for model estimation. The performance of the proposed approach is illustrated in studies of both simulated and real economic data.
AbstractList I discuss a framework to allow dynamic sparsity in time-varying parameter regression models. The conditional variances of the innovations of time-varying parameters are time varying and equal to zero adaptively via thresholding. The resulting model allows the dynamics of the time-varying parameters to mix over different frequencies of parameter changes in a data driven way and permits great flexibility while achieving model parsimony. A convenient strategy is discussed to infer if each coefficient is static or dynamic and, if dynamic, how frequent the parameter change is. An MCMC scheme is developed for model estimation. The performance of the proposed approach is illustrated in studies of both simulated and real economic data.
Author He, Zhongfang
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Cites_doi 10.1214/17-EJS1337SI
10.1093/biomet/asq017
10.1080/07350015.2020.1713796
10.1214/ss/1177011137
10.1016/j.jeconom.2013.10.012
10.1093/biomet/89.3.603
10.1016/j.jfineco.2012.04.003
10.1111/j.1467-9892.1994.tb00184.x
10.1111/rssb.12325
10.1080/01621459.2000.10474273
10.1080/01621459.1993.10476364
10.3390/econometrics8020020
10.26509/frbc-wp-202034
10.1109/LSP.2015.2503725
10.1016/j.jeconom.2019.10.008
10.1080/10618600.2020.1725523
10.1080/03610926.2014.936562
10.1016/j.jeconom.2016.09.005
10.1007/s11222-012-9367-z
10.1016/j.csda.2010.07.009
10.1198/jcgs.2009.08108
10.1111/j.1467-937X.2005.00353.x
10.1016/j.csda.2013.01.002
10.1016/j.red.2004.10.009
10.1515/9780691218632
10.1002/jae.2804
10.1002/for.2276
10.1016/j.jeconom.2006.07.008
10.1198/jcgs.2011.203main
10.1002/jae.2844
10.1198/073500107000000241
10.1016/j.jeconom.2009.07.003
10.1162/003465303322369777
10.1080/07350015.2012.747847
10.1007/s11222-018-9846-y
10.1080/07350015.1996.10524626
10.1111/1467-9868.00288
10.1002/jae.2680
10.1214/20-BA1199
10.1093/oso/9780198522249.001.0001
10.1093/rfs/hhm014
10.1016/j.jeconom.2018.11.006
10.1016/S1574-0706(05)01001-3
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References e_1_3_4_4_1
e_1_3_4_3_1
e_1_3_4_2_1
e_1_3_4_9_1
e_1_3_4_8_1
e_1_3_4_42_1
e_1_3_4_20_1
e_1_3_4_41_1
e_1_3_4_6_1
e_1_3_4_40_1
e_1_3_4_5_1
Clements M. (e_1_3_4_7_1) 1999
e_1_3_4_23_1
e_1_3_4_46_1
e_1_3_4_24_1
e_1_3_4_45_1
e_1_3_4_21_1
e_1_3_4_44_1
e_1_3_4_22_1
e_1_3_4_43_1
e_1_3_4_27_1
e_1_3_4_28_1
e_1_3_4_25_1
e_1_3_4_26_1
e_1_3_4_47_1
e_1_3_4_29_1
e_1_3_4_31_1
e_1_3_4_30_1
e_1_3_4_12_1
e_1_3_4_35_1
e_1_3_4_13_1
e_1_3_4_34_1
e_1_3_4_10_1
e_1_3_4_33_1
e_1_3_4_11_1
e_1_3_4_32_1
e_1_3_4_16_1
e_1_3_4_39_1
e_1_3_4_17_1
e_1_3_4_38_1
e_1_3_4_14_1
e_1_3_4_37_1
e_1_3_4_15_1
e_1_3_4_36_1
e_1_3_4_18_1
e_1_3_4_19_1
References_xml – ident: e_1_3_4_39_1
  doi: 10.1214/17-EJS1337SI
– ident: e_1_3_4_5_1
  doi: 10.1093/biomet/asq017
– ident: e_1_3_4_27_1
  doi: 10.1080/07350015.2020.1713796
– ident: e_1_3_4_20_1
  doi: 10.1214/ss/1177011137
– ident: e_1_3_4_29_1
  doi: 10.1016/j.jeconom.2013.10.012
– ident: e_1_3_4_13_1
  doi: 10.1093/biomet/89.3.603
– ident: e_1_3_4_9_1
  doi: 10.1016/j.jfineco.2012.04.003
– ident: e_1_3_4_15_1
  doi: 10.1111/j.1467-9892.1994.tb00184.x
– ident: e_1_3_4_31_1
  doi: 10.1111/rssb.12325
– ident: e_1_3_4_18_1
  doi: 10.1080/01621459.2000.10474273
– ident: e_1_3_4_35_1
  doi: 10.1080/01621459.1993.10476364
– ident: e_1_3_4_4_1
  doi: 10.3390/econometrics8020020
– ident: e_1_3_4_24_1
  doi: 10.26509/frbc-wp-202034
– ident: e_1_3_4_33_1
  doi: 10.1109/LSP.2015.2503725
– ident: e_1_3_4_12_1
  doi: 10.1016/j.jeconom.2019.10.008
– ident: e_1_3_4_32_1
  doi: 10.1080/10618600.2020.1725523
– volume-title: Forecasting Non-Stationary Economic Time Series
  year: 1999
  ident: e_1_3_4_7_1
– ident: e_1_3_4_17_1
  doi: 10.1080/03610926.2014.936562
– ident: e_1_3_4_6_1
  doi: 10.1016/j.jeconom.2016.09.005
– ident: e_1_3_4_10_1
  doi: 10.1007/s11222-012-9367-z
– ident: e_1_3_4_34_1
  doi: 10.1016/j.csda.2010.07.009
– ident: e_1_3_4_38_1
  doi: 10.1198/jcgs.2009.08108
– ident: e_1_3_4_40_1
  doi: 10.1111/j.1467-937X.2005.00353.x
– ident: e_1_3_4_30_1
  doi: 10.1016/j.csda.2013.01.002
– ident: e_1_3_4_8_1
  doi: 10.1016/j.red.2004.10.009
– ident: e_1_3_4_23_1
  doi: 10.1515/9780691218632
– ident: e_1_3_4_28_1
  doi: 10.1002/jae.2804
– ident: e_1_3_4_2_1
  doi: 10.1002/for.2276
– ident: e_1_3_4_37_1
  doi: 10.1016/j.jeconom.2006.07.008
– ident: e_1_3_4_47_1
  doi: 10.1198/jcgs.2011.203main
– ident: e_1_3_4_11_1
  doi: 10.1002/jae.2844
– ident: e_1_3_4_21_1
  doi: 10.1198/073500107000000241
– ident: e_1_3_4_45_1
– ident: e_1_3_4_16_1
  doi: 10.1016/j.jeconom.2009.07.003
– ident: e_1_3_4_14_1
  doi: 10.1162/003465303322369777
– ident: e_1_3_4_36_1
  doi: 10.1080/07350015.2012.747847
– ident: e_1_3_4_22_1
  doi: 10.1007/s11222-018-9846-y
– ident: e_1_3_4_43_1
  doi: 10.1080/07350015.1996.10524626
– ident: e_1_3_4_42_1
  doi: 10.1111/1467-9868.00288
– ident: e_1_3_4_25_1
– ident: e_1_3_4_26_1
  doi: 10.1002/jae.2680
– ident: e_1_3_4_41_1
  doi: 10.1214/20-BA1199
– ident: e_1_3_4_44_1
  doi: 10.1093/oso/9780198522249.001.0001
– ident: e_1_3_4_46_1
  doi: 10.1093/rfs/hhm014
– ident: e_1_3_4_3_1
  doi: 10.1016/j.jeconom.2018.11.006
– ident: e_1_3_4_19_1
  doi: 10.1016/S1574-0706(05)01001-3
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Snippet I discuss a framework to allow dynamic sparsity in time-varying parameter regression models. The conditional variances of the innovations of time-varying...
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SubjectTerms Bayesian shrinkage
Econometrics
economic time series
Innovations
MCMC
Parameters
Regression models
TVP
Title Locally time-varying parameter regression
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