[TS] Time Series - Stata

1 Stata TIME-SERIESREFERENCE MANUALRELEASE 13 A Stata Press PublicationStataCorp LPCollege Station, Texas Copyrightc 1985 2013 StataCorp LPAll rights reservedVersion 13 Published by Stata Press, 4905 Lakeway Drive, College Station, Texas 77845 Typeset in TEXISBN-10: 1-59718-127-7 ISBN-13: 978-1-59718-127-3 This manual is protected by copyright. All rights are reserved. No part of this manual may be reproduced, storedin a retrieval system, or transcribed, in any form or by any means electronic, mechanical, photocopy, recording, orotherwise without the prior written permission of StataCorp LP unless permitted subject to the terms and conditionsof a license granted to you by StataCorp LP to use the software and documentation. No license, express or implied,by estoppel or otherwise, to any intellectual property rights is granted by this provides this manual as is without warranty of any kind, either expressed or implied, including, butnot limited to, the implied warranties of merchantability and fitness for a particular purpose.

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3 : Release 13. Statistical Software. College Station, TX: StataCorp .. Introduction to time- Series manual1time Series .. Introduction to time- Series commands2arch .. autoregressive conditional heteroskedasticity (ARCH) family of estimators10arch postestimation .. Postestimation tools for arch43arfima .. autoregressive fractionally integrated moving-average models48arfima postestimation .. Postestimation tools for arfima66arima .. ARIMA, ARMAX, and other dynamic regression models74arima postestimation .. Postestimation tools for arima98corrgram .. Tabulate and graph autocorrelations 106cumsp .. Cumulative spectral distribution 114dfactor .. Dynamic-factor models 117dfactor postestimation .. Postestimation tools for dfactor 134dfgls .. DF-GLS unit-root test 139dfuller .. Augmented Dickey Fuller unit-root test 145estat acplot.

4 Plot parametric autocorrelation and autocovariance functions 150estat aroots .. Check the stability condition of ARIMA estimates 154fcast compute .. Compute dynamic forecasts after var, svar, or vec 159fcast graph .. Graph forecasts after fcast compute 167forecast .. Econometric model forecasting 170forecast adjust .. Adjust a variable by add factoring, replacing, etc. 184forecast clear .. Clear current model from memory 189forecast coefvector .. Specify an equation via a coefficient vector 190forecast create .. Create a new forecast model 195forecast describe .. Describe features of the forecast model 197forecast drop .. Drop forecast variables 202forecast estimates .. Add estimation results to a forecast model 204forecast exogenous .. Declare exogenous variables 214forecast identity .. Add an identity to a forecast model 216forecast list.

5 List forecast commands composing current model 218forecast query .. Check whether a forecast model has been started 220forecast solve .. Obtain static and dynamic forecasts 221irf .. Create and analyze IRFs, dynamic-multiplier functions, and FEVDs 236irf add .. Add results from an IRF file to the active IRF file 240irf cgraph .. Combined graphs of IRFs, dynamic-multiplier functions, and FEVDs 242irf create .. Obtain IRFs, dynamic-multiplier functions, and FEVDs 246irf ctable .. Combined tables of IRFs, dynamic-multiplier functions, and FEVDs 271irf describe .. Describe an IRF file 276irf drop .. Drop IRF results from the active IRF file 279irf graph .. Graphs of IRFs, dynamic-multiplier functions, and FEVDs 281irf ograph .. Overlaid graphs of IRFs, dynamic-multiplier functions, and FEVDs 287irf rename.

6 Rename an IRF result in an IRF file 292irf set .. Set the active IRF file 294irf table .. Tables of IRFs, dynamic-multiplier functions, and FEVDs 296iii Contentsmgarch .. Multivariate GARCH models 301mgarch ccc .. Constant conditional correlation multivariate GARCH models 307mgarch ccc postestimation .. Postestimation tools for mgarch ccc 322mgarch dcc .. Dynamic conditional correlation multivariate GARCH models 326mgarch dcc postestimation .. Postestimation tools for mgarch dcc 341mgarch dvech .. Diagonal vech multivariate GARCH models 345mgarch dvech postestimation .. Postestimation tools for mgarch dvech 357mgarch vcc .. Varying conditional correlation multivariate GARCH models 364mgarch vcc postestimation .. Postestimation tools for mgarch vcc 379newey .. Regression with Newey West standard errors 383newey postestimation.

7 Postestimation tools for newey 388pergram .. Periodogram 393pperron .. Phillips Perron unit-root test 401prais .. Prais Winsten and Cochrane Orcutt regression 406prais postestimation .. Postestimation tools for prais 417psdensity .. Parametric spectral density estimation after arima, arfima, and ucm 419rolling .. Rolling-window and recursive estimation 429sspace .. State-space models 437sspace postestimation .. Postestimation tools for sspace 461tsappend .. Add observations to a time- Series dataset 468tsfill .. Fill in gaps in time variable 474tsfilter .. Filter a time- Series , keeping only selected periodicities 478tsfilter bk .. Baxter King time- Series filter 497tsfilter bw .. Butterworth time- Series filter 505tsfilter cf .. Christiano Fitzgerald time- Series filter 514tsfilter hp.

8 Hodrick Prescott time- Series filter 522tsline .. Plot time- Series data 529tsreport .. Report time- Series aspects of a dataset or estimation sample 535tsrevar .. Time- Series operator programming command 541tsset .. Declare data to be time- Series data 544tssmooth .. Smooth and forecast univariate time- Series data 560tssmooth dexponential .. Double-exponential smoothing 562tssmooth exponential .. Single-exponential smoothing 568tssmooth hwinters .. Holt Winters nonseasonal smoothing 576tssmooth ma .. Moving-average filter 583tssmooth nl .. Nonlinear filter 588tssmooth shwinters .. Holt Winters seasonal smoothing 590ucm .. Unobserved-components model 599ucm postestimation .. Postestimation tools for ucm 626var intro .. Introduction to vector autoregressive models 632var .. Vector autoregressive models 639var postestimation.

9 Postestimation tools for var 651var svar .. Structural vector autoregressive models 655var svar postestimation .. Postestimation tools for svar 675varbasic .. Fit a simple VAR and graph IRFs or FEVDs 678varbasic postestimation .. Postestimation tools for varbasic 683vargranger .. Perform pairwise Granger causality tests after var or svar 686 Contents iiivarlmar .. Perform LM test for residual autocorrelation after var or svar 691varnorm .. Test for normally distributed disturbances after var or svar 694varsoc .. Obtain lag-order selection statistics for VARs and VECMs 700varstable .. Check the stability condition of VAR or SVAR estimates 706varwle .. Obtain Wald lag-exclusion statistics after var or svar 711vec intro .. Introduction to vector error-correction models 716vec .. Vector error-correction models 735vec postestimation.

10 Postestimation tools for vec 759veclmar .. Perform LM test for residual autocorrelation after vec 762vecnorm .. Test for normally distributed disturbances after vec 765vecrank .. Estimate the cointegrating rank of a VECM 768vecstable .. Check the stability condition of VECM estimates 776wntestb .. Bartlett s periodogram-based test for white noise 780wntestq .. Portmanteau (Q) test for white noise 785xcorr .. Cross-correlogram for bivariate time Series 788 Glossary ..792 Subject and author index ..801 Cross-referencing the documentationWhen reading this manual, you will find references to other Stata manuals. For example,[U] 26 Overview of Stata estimation commands[R]regress[D]reshapeThe first example is a reference to chapter 26,Overview of Stata estimation commands, in theUser sGuide; the second is a reference to theregressentry in theBase Reference Manual.