Search found 90 matches
- Tue Feb 14, 2023 5:51 pm
- Forum: Add-in Support
- Topic: Non invertible MA(Q)*
- Replies: 0
- Views: 79934
Non invertible MA(Q)*
The identification of MA(q) processes using second order techniques (such as OLS, ML and Box-Jenkins) estimates the invertible representation and ignores the non-invertible representations of a time series. This add-in seeks to simulate and find the data generating mechanism of all representations o...
- Thu Jan 20, 2022 6:03 am
- Forum: Add-in Support
- Topic: Cross spectral analysis*
- Replies: 0
- Views: 16639
Cross spectral analysis*
This add-in performs cross spectral analysis between a group of time series. This cross spectral functions allows estimating covariances and correlations in the frequency domain. It also allows to know if one series anticipates or leads the other (in a similar way to Granger causality) and in what m...
- Wed Feb 24, 2021 9:05 am
- Forum: Program Repository
- Topic: An old estimator of the autocorrelation coefficient (***)
- Replies: 0
- Views: 14821
An old estimator of the autocorrelation coefficient (***)
Hello, This program estimates the usual (HAT) autocorrelation coefficient (already supported by Eviews) and estimates the autocorrelation using the "STAR" estimator p(tau)*. The only difference with HAT estimator, is that the STAR divides by (T-Tau), the HAT divides by T. Both have the sam...
- Wed Feb 24, 2021 8:40 am
- Forum: Add-in Support
- Topic: Spectral Granger Causality Test*
- Replies: 14
- Views: 50924
Re: Spectral Granger Causality Test*
Hello, In the orginal paper of Breitung and Candelon (2006), they develop the test in a time series context i.e. for VAR. I guess that it is not straigth forward to implement the test in a panel, maybe the add-in will run if you have panel data, but I would be very careful to interpret the results. ...
- Tue Dec 17, 2019 8:29 am
- Forum: Add-in Support
- Topic: STAR*
- Replies: 52
- Views: 107695
Re: STAR*
Hi,
To see some examples you can take a look to the eviews add-in documentation. With the current version of eviews you can use a built-in procedure to estimate STAR models.
Regards,
To see some examples you can take a look to the eviews add-in documentation. With the current version of eviews you can use a built-in procedure to estimate STAR models.
Regards,
- Thu Jul 26, 2018 9:19 am
- Forum: Add-in Support
- Topic: Canova Hansen*
- Replies: 0
- Views: 10978
Canova Hansen*
This thread is about the Canova Hansen add-in which performs seasonal unit root test. The add-in can handle monthly and quarterly data. The test can be considered as the KPSS version of a seasonal unit root test. With the null hypothesis of stationarity. Comments and suggestions of the add-in are we...
- Thu Jul 05, 2018 5:28 pm
- Forum: Add-in Support
- Topic: STAR*
- Replies: 52
- Views: 107695
Re: STAR*
Hi,
You can not add the lags using that command. You must type each lag individually.
Regards,
You can not add the lags using that command. You must type each lag individually.
Regards,
- Mon May 21, 2018 7:25 pm
- Forum: Add-in Support
- Topic: HEGY*
- Replies: 7
- Views: 18412
Re: HEGY*
Hello everyone,
Currently I'am working on a research regarding time series with seasonal unit roots and I need some time series with these porperty. I wonder if you know any time series with these features, independently of its frequency. Thanks.
Regards,
Currently I'am working on a research regarding time series with seasonal unit roots and I need some time series with these porperty. I wonder if you know any time series with these features, independently of its frequency. Thanks.
Regards,
- Thu Dec 21, 2017 6:08 pm
- Forum: Add-in Support
- Topic: STAR*
- Replies: 52
- Views: 107695
Re: STAR*
Hello,
I guess that the estimation of your gamma parameter is large enough, hence you can use a discrete TAR model and it is not necessary to perform a LSTAR estimation.
Regards,
I guess that the estimation of your gamma parameter is large enough, hence you can use a discrete TAR model and it is not necessary to perform a LSTAR estimation.
Regards,
- Fri Nov 03, 2017 10:31 am
- Forum: Program Repository
- Topic: Perron (1989) Breakpoint Unit Root Test
- Replies: 0
- Views: 17003
Perron (1989) Breakpoint Unit Root Test
Hi, The following code perform the Perron (1989) unit root test for time series with structural breaks. In the code the case 1 is defined as a level break, case 2 as a trend break and case 3 as a leven and trend break. 'Nicolas Ronderos Pulido '-------------------------------------------------------...
- Thu Oct 12, 2017 10:17 am
- Forum: Add-in Support
- Topic: MGARCH Tests*
- Replies: 0
- Views: 7404
MGARCH Tests*
This thread is about MGARCH tests add-in which performs tests to detect the absence of multivariate ARCH effects on the residuals of VAR or VEC model. The tests can also be used to detect remaining multivariate ARCH effects after the estimation of a MGARCH model (Diagonal VECH, CCC or BEKK) in a sys...
- Wed Oct 11, 2017 11:12 am
- Forum: Programming
- Topic: bilinear model
- Replies: 2
- Views: 4240
Re: bilinear model
You can do it with the Logl object or with NLS.
- Wed Oct 11, 2017 11:10 am
- Forum: Add-in Support
- Topic: STAR*
- Replies: 52
- Views: 107695
Re: STAR*
Hi,
I have design the add-in in such a way that the intercept must be included in the model. But you can easily do that in the STAR EViews 10 procedure.
Good luck!
I have design the add-in in such a way that the intercept must be included in the model. But you can easily do that in the STAR EViews 10 procedure.
Good luck!
- Fri Aug 25, 2017 5:02 pm
- Forum: Program Repository
- Topic: Portmanteau for VAR(p)
- Replies: 0
- Views: 16888
Portmanteau for VAR(p)
Just as an academic exercise the following code performs the estimation of the multivariate Ljung Box test for VAR already available in eviews. Best regards, 'Nicolás Ronderos Pulido - Time series analysis 'Test: Portmanteau for VAR(p) 'Lutkepohl (2005) 'H0: no autocorrelation until lag h '---------...
- Wed Mar 29, 2017 1:19 pm
- Forum: Add-in Support
- Topic: HEGY*
- Replies: 7
- Views: 18412
Re: HEGY*
Hi, You can calculate the frecuency from the equation w=2*pi*f where f is given in cycles per time unit (in the add-in I report the inverse 1/f i.e. in time units per cycle) you want the w frequency. For the frequencys you posted: - (2 month per cycle) w=2*pi*f w=2*pi*(1/2) w=pi - (4 month per cycle...