[R-SIG-Finance] time series regression (demand for higher education)

Spencer Graves spencer.graves at pdf.com
Mon Apr 14 22:28:03 CEST 2008

      1.  Did you not receive a reply yesterday from Matthieu Stigler, 
reading as follows: 

For the analysis of multivariate time series use package vars for VAR 
models and urca for VECM models, unit root and cointegration tests. 
The author of these package wrote also a  book "analysis of integrated 
and cointegrated time series with R" which can be usefull. See 

      2.  Before posting the same question again, PLEASE do read the 
posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.  If 
you provide a self-contained example, you increase the pool of potential 
respondents by a factor of 10 or 100, because even people who don't know 
the answer can copy your pseudo-code from your email into R and take you 
to the next step. 

      Hope this helps. 

bereket weldeslassie wrote:
> Dear All,
> I am doing a time series regression with one dependent time series variable,
> 7 independent time series variables and 32 annual observations in an attempt
> to model the demand for higher education. The dependent variable is
> Enrollment and the independent variables are like tuition, income and so on.
> The main purpose of my analysis is to investigate the impact of economic
> factors (like tuition and income) on enrollment. I am considering an error
> correction model of the form:
> diff(lnY(t))=a+b1*lnY(t-1)+b2*lnX(t-1)+b3*diff(lnX(t))+error
> to model the demand and solve the problem of cointegration, autocorrelation
> and multicollinearity. But this is not been able to solve all these
> problems. Is that a right way to estimate the elacticities?
> Any suggestion how to built a good model that solves these problems? I
> appreciate your help.
> Thanks,
> Bereket
> 	[[alternative HTML version deleted]]
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