State Space Methods in Stata

State Space Methods in Stata

We illustrate how to estimate parameters of linear state-space models using the Stata program sspace. We provide examples of how to use sspace to estimate the parameters of unobserved-component models, vector autoregressive moving-average models, and dynamic-factor models. We also show how to comput...

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Bibliographic Details
Main Authors: David M. Drukker, Richard B. Gates
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2011-05-01
Series:Journal of Statistical Software
Subjects:
state-space
unobserved-components models
local-level model
local-linear-trend model
basic structural model
dynamic-factor model
vector autoregressive moving-average model
sspace
Online Access:http://www.jstatsoft.org/v41/i10/paper
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spelling doaj-456bd16f194841318b246b924adecb192020-11-24T22:49:20ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602011-05-014110State Space Methods in StataDavid M. DrukkerRichard B. GatesWe illustrate how to estimate parameters of linear state-space models using the Stata program sspace. We provide examples of how to use sspace to estimate the parameters of unobserved-component models, vector autoregressive moving-average models, and dynamic-factor models. We also show how to compute one-step, filtered, and smoothed estimates of the series and the states; dynamic forecasts and their confidence intervals; and residuals.http://www.jstatsoft.org/v41/i10/paperstate-spaceunobserved-components modelslocal-level modellocal-linear-trend modelbasic structural modeldynamic-factor modelvector autoregressive moving-average modelsspace
collection DOAJ
language English
format Article
sources DOAJ
author David M. Drukker
Richard B. Gates
spellingShingle David M. Drukker
Richard B. Gates
State Space Methods in Stata
Journal of Statistical Software
state-space
unobserved-components models
local-level model
local-linear-trend model
basic structural model
dynamic-factor model
vector autoregressive moving-average model
sspace
author_facet David M. Drukker
Richard B. Gates
author_sort David M. Drukker
title State Space Methods in Stata
title_short State Space Methods in Stata
title_full State Space Methods in Stata
title_fullStr State Space Methods in Stata
title_full_unstemmed State Space Methods in Stata
title_sort state space methods in stata
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2011-05-01
description We illustrate how to estimate parameters of linear state-space models using the Stata program sspace. We provide examples of how to use sspace to estimate the parameters of unobserved-component models, vector autoregressive moving-average models, and dynamic-factor models. We also show how to compute one-step, filtered, and smoothed estimates of the series and the states; dynamic forecasts and their confidence intervals; and residuals.
topic state-space
unobserved-components models
local-level model
local-linear-trend model
basic structural model
dynamic-factor model
vector autoregressive moving-average model
sspace
url http://www.jstatsoft.org/v41/i10/paper
work_keys_str_mv AT davidmdrukker statespacemethodsinstata
AT richardbgates statespacemethodsinstata
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