can equally estimate a univariate model with the variable of concern adding trend to know

which is better. for instance, GDP. estimate In eviews. ... gdp can @trend .. if the pvalue

of the trend is significant then you choose with trends and intercept ,if only intercept is

significant then choose only intercept but no trend and if none is significant you can

choose none. although I can't vividly remember which journal coz its been long.

root) test?

tells tht you should start from ''with trend and intercept'' then 'with intercept but no trend''

then 'no interecpt and no trend'' and stop where you find the series is stationary. you can

learn more details in ENDERS APPLIED TIME SERIES.

optimum lag length for unit root test 1. general to specific: choose a maximum lag length

like 8, 12 etc. based on size of observation. Then start removing higher lags if the

coefficient of lag is not significant in estimated ADF model. 2. use information criteria AIC,

SBC etc. eviews and other softwarss has option for this. 3. choose any lag where you find

no serial correlation. Basically including longer lags is to avoid serial correlation. So You

can choose any lag even no lag if ADF estimated model is not suffering from serial

correlation

root) test?

http://shishirshakya.blogspot.com/2015/11/exact-process-to-do-adf-unit-root-test.html

data for autocorrelation testing as per Baltagi.

autocorrelation testing but it has one limitation that if there are lags in model, we cannot

use this.

disadvantages. 1. If models comtain lagged variables DW test cannot use for detecting

autocorrelation. 2.It has indesicion area. 3. DW test derermine only first order

autocorrelation.

Professor Vahe Nazaryan commented > Since Prob<0.05, this means that you can reject

the null of non stationary (has a unit root = non stationary) and conclude that your series

are stationary. I think yes you can Like · Reply · November 19, 2016 at 4:11pm

Professor Keith Araneo-Yowell commented> you have to check the values of the Dickey-

Fuller distribution for the kind of Dickey-Fuller test you are doing. The critical tau value is

in the dickey-fuller table. It will be different based on the number of observations and

whether you are testing for a Unit root, unit root with a drift, or a unit root with a drift and a

time trend.

Professor Festus Nkwo commented> It is ok to reject the null at 5% and 10% and

conclude that the sequence is stationary. However, it is not save to accept the alternate at

1% in the first difference level.

Ade Kutu

Afolabi Luqman

Abdullah Sonnet

Asad Zaman

Atiq Rehman

Burcu Özcan

Ghumro Niaz Hussain

Muhammad Anees

Mohammad Zhafran

Muzammil Bhatti

Monis Syed

Mine PD

Moulana N. Cholovik

Muili Adebayo Hamid

Nicat Gasim

Najid Iqbal

Nasiru Inuwa

Noman Arshed

Rapelanoro Nady

Seye Olasehinde-Williams

Suborno Aditya

Sayed Hossain

Shishir Sakya

Sheikh Muzammil Naseer

Tella Oluwatoba Ibrahim

Younes Azzouz

Meo School of Research

Shishir Shakya

Noman Arshed

Hossain Academy Note

Univariate Models |