- 97 Views
- Uploaded on
- Presentation posted in: General

Econometrics (NA3011)

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Econometrics (NA3011)

Reza Mortazavi

2014

Stata Lecture 4

- use http://users.du.se/~rem/icecream.dta
- Browse
- tsset time
- Note: ”tsset ” is the commandthatinforms the data aretime series, the variable ”time” in this data set is the timevariable.
- Do we have any reason to suspect autocorrelation (also called serial correlation)?
- regr cons price income
- predict resid,residual

- twoway (scatter resid time, yline(0))
- regr cons price income temp
- predict ehat,residual
- twoway (scatter ehat time, yline(0))
- Still autocorrelation
- estatdwatson
- H0: H1:
- At 5% significancelevelwehave (for T=30, K=4), . So werejectH0: .

- estatbgodfrey
- This so called Breusch-Godfrey test is more general and is sufficient for this course. What is the conclusion?
- prais cons price income temp, rhotype(regress) corc

- gen lagtemp=L.temp
- regr cons price income temp lagtemp
- estatdwatson
- estatbgodfrey

- newey cons price income temp, lag(1)
- newey cons price income temp, lag(2)