Time-Series Reference Manual
This manual includes features that are part of StataNow™.
| Publisher: | Stata Press |
| Copyright: | 2023 |
| ISBN-13: | 978-1-59718-402-1 |
| Pages: | 1003 |
Suggested citation
StataCorp. 2023. Stata 18 Time-Series Reference Manual. College Station, TX: Stata Press.
Supplemental materials
Introduction to Time Series Using Stata, Revised Edition
Sean Becketti
Financial Econometrics Using Stata
Simona Boffelli and Giovanni Urga
Environmental Econometrics Using Stata
Christopher F. Baum and Stan Hurn
NetCourse® 461: Univariate time series with Stata
Time-series analysis using Stata training course
Table of contents
| Intro | Introduction to time-series manual |
| Time series | Introduction to time-series commands |
| arch | Autoregressive conditional heteroskedasticity (ARCH) family of estimators |
| arch postestimation | Postestimation tools for arch |
| arfima | Autoregressive fractionally integrated moving-average models |
| arfima postestimation | Postestimation tools for arfima |
| arfimasoc | Obtain lag-order selection statistics for ARFIMAs |
| arima | ARIMA, ARMAX, and other dynamic regression models |
| arima postestimation | Postestimation tools for arima |
| arimasoc | Obtain lag-order selection statistics for ARMAs |
| corrgram | Tabulate and graph autocorrelations |
| cumsp | Graph cumulative spectral distribution |
| dfactor | Dynamic-factor models |
| dfactor postestimation | Postestimation tools for dfactor |
| dfgls | DF-GLS unit-root test |
| dfuller | Augmented Dickey–Fuller unit-root test |
| estat acplot | Plot parametric autocorrelation and autocovariance functions |
| estat aroots | Check the stability condition of ARIMA estimates |
| estat sbcusum | Cumulative sum test for parameter stability |
| estat sbknown | Test for a structural break with a known break date |
| estat sbsingle | Test for a structural break with an unknown break date |
| fcast compute | Compute dynamic forecasts |
| fcast graph | Graph forecasts after fcast compute |
| forecast | Econometric model forecasting |
| forecast adjust | Adjust variables to produce alternative forecasts |
| forecast clear | Clear current model from memory |
| forecast coefvector | Specify an equation via a coefficient vector |
| forecast create | Create a new forecast model |
| forecast describe | Describe features of the forecast model |
| forecast drop | Drop forecast variables |
| forecast estimates | Add estimation results to a forecast model |
| forecast exogenous | Declare exogenous variables |
| forecast identity | Add an identity to a forecast model |
| forecast list | List forecast commands composing current model |
| forecast query | Check whether a forecast model has been started |
| forecast solve | Obtain static and dynamic forecasts |
| irf | Create and analyze IRFs, dynamic-multiplier functions, and FEVDs |
| irf add | Add results from an IRF file to the active IRF file |
| irf cgraph | Combined graphs of IRFs, dynamic-multiplier functions, and FEVDs |
| irf create | Obtain IRFs, dynamic-multiplier functions, and FEVDs |
| irf ctable | Combined tables of IRFs, dynamic-multiplier functions, and FEVDs |
| irf describe | Describe an IRF file |
| irf drop | Drop IRF results from the active IRF file |
| irf graph | Graphs of IRFs, dynamic-multiplier functions, and FEVDs |
| irf ograph | Overlaid graphs of IRFs, dynamic-multiplier functions, and FEVDs |
| irf rename | Rename an IRF result in an IRF file |
| irf set | Set the active IRF file |
| irf table | Tables of IRFs, dynamic-multiplier functions, and FEVDs |
| ivlpirf | Instrumental-variables local-projection impulse–response functions StataNow |
| ivlpirf postestimation | Postestimation tools for ivlpirf StataNow |
| lpirf | Local-projection impulse–response functions |
| lpirf postestimation | Postestimation tools for lpirf |
| mgarch | Multivariate GARCH models |
| mgarch ccc | Constant conditional correlation multivariate GARCH models |
| mgarch ccc postestimation | Postestimation tools for mgarch ccc |
| mgarch dcc | Dynamic conditional correlation multivariate GARCH models |
| mgarch dcc postestimation | Postestimation tools for mgarch dcc |
| mgarch dvech | Diagonal vech multivariate GARCH models |
| mgarch dvech postestimation | Postestimation tools for mgarch dvech |
| mgarch vcc | Varying conditional correlation multivariate GARCH models |
| mgarch vcc postestimation | Postestimation tools for mgarch vcc |
| mswitch | Markov-switching regression models |
| mswitch postestimation | Postestimation tools for mswitch |
| newey | Regression with Newey–West standard errors |
| newey postestimation | Postestimation tools for newey |
| pergram | Periodogram |
| pperron | Phillips–Perron unit-root test |
| prais | Prais–Winsten and Cochrane–Orcutt regression |
| prais postestimation | Postestimation tools for prais |
| psdensity | Parametric spectral density estimation after arima, arfima, and ucm |
| rolling | Rolling-window and recursive estimation |
| sspace | State-space models |
| sspace postestimation | Postestimation tools for sspace |
| threshold | Threshold regression |
| threshold postestimation | Postestimation tools for threshold |
| tsappend | Add observations to a time-series dataset |
| tsfill | Fill in gaps in time variable |
| tsfilter | Filter a time series for cyclical components |
| tsfilter bk | Baxter–King time-series filter |
| tsfilter bw | Butterworth time-series filter |
| tsfilter cf | Christiano–Fitzgerald time-series filter |
| tsfilter hp | Hodrick–Prescott time-series filter |
| tsline | Time-series line plots |
| tsreport | Report time-series aspects of a dataset or estimation sample |
| tsrevar | Time-series operator programming command |
| tsset | Declare data to be time-series data |
| tssmooth | Smooth and forecast univariate time-series data |
| tssmooth dexponential | Double-exponential smoothing |
| tssmooth exponential | Single-exponential smoothing |
| tssmooth hwinters | Holt–Winters nonseasonal smoothing |
| tssmooth ma | Moving-average filter |
| tssmooth nl | Nonlinear filter |
| tssmooth shwinters | Holt–Winters seasonal smoothing |
| ucm | Unobserved-components models |
| ucm postestimation | Postestimation tools for ucm |
| var intro | Introduction to vector autoregression models |
| var | Vector autoregression models StataNow |
| var postestimation | Postestimation tools for var |
| var ivsvar | Instrumental-variables structural vector autoregressive models StataNow |
| var ivsvar postestimation | Postestimation tools for ivsvar StataNow |
| var svar | Structural vector autoregression models |
| var svar postestimation | Postestimation tools for svar |
| varbasic | Fit a simple VAR and graph IRFs or FEVDs |
| varbasic postestimation | Postestimation tools for varbasic |
| vargranger | Pairwise Granger causality tests |
| varlmar | LM test for residual autocorrelation |
| varnorm | Test for normally distributed disturbances |
| varsoc | Obtain lag-order selection statistics for VAR and VEC models |
| varstable | Check eigenvalue stability condition |
| varwle | Obtain Wald lag-exclusion statistics |
| vec intro | Introduction to vector error-correction models |
| vec | Vector error-correction models |
| vec postestimation | Postestimation tools for vec |
| veclmar | LM test for residual autocorrelation after vec |
| vecnorm | Test for normally distributed disturbances after vec |
| vecrank | Estimate the cointegrating rank of a VECM |
| vecstable | Check the stability condition of VEC model estimates |
| wntestb | Bartlett's periodogram-based test for white noise |
| wntestq | Portmanteau (Q) test for white noise |
| xcorr | Cross-correlogram for bivariate time series |
| Glossary | |
| Combined author index | |
| Combined subject index | |
