Holmes, J.M., & Hutton, P.A. (1990a). On the causal relationship between government expenditure and national income. Reviews of Economics Statistics, 72(1), 87-95.
Holmes, J.M., & Hutton, P.A. (1990b). Small sample properties of the multiple rank F-test with lagged dependent variables. Economics Letters, 33, 55-61.
the moethod was also usein this paper:
Wan Kyu Park, (1998). Granger Causality between Government Revenues and Expenditures in Korea. Journal of Economic Development, 23(1), 145-155.
happy
----- Original Message -----
> From: JVerkuilen (Gmail) <jvverkuilen@gmail.com>
> To: statalist@hsphsun2.harvard.edu
> Cc:
> Sent: Tuesday, April 23, 2013 3:26 PM
> Subject: Re: st: Regressing ranked variables for causality testing
>
> None of us know what that paper is. Please be sure to provide a
> complete reference.
>
>
> On Tue, Apr 23, 2013 at 8:48 AM, Happy Phiri <hapephiri@yahoo.com> wrote:
>> I want to use Multiple Rank F Test as developed by Holmes and Hutton
> (1990a, 1990b). To perform the multiple rank test, all the variables
>> including lagged variables should be transformed to the corresponding
>> rank representation. the ranked value of each observation is used to test
> for the causality relationship using the folowing
>>
>> R(.)=α+∑δR(.)+∑λR(.)+∑θR(.)+ε
>> Thanks
>> Happy
>>
>>
>>
>> ----- Original Message -----
>>> From: Nick Cox <njcoxstata@gmail.com>
>>> To: "statalist@hsphsun2.harvard.edu"
> <statalist@hsphsun2.harvard.edu>
>>> Cc:
>>> Sent: Tuesday, April 23, 2013 1:11 PM
>>> Subject: Re: st: Regressing ranked variables for causality testing
>>>
>>> Ranking is easy enough: see -help egen-.
>>>
>>> What that has to do with causality tests I do not know.
>>>
>>> Even more crucially, I think you need to spell out precisely which way
>>> of assessing causality you have in mind, with precise names and
>>> literature references.
>>>
>>> Nick
>>> njcoxstata@gmail.com
>>>
>>>
>>> On 23 April 2013 07:50, Happy Phiri <hapephiri@yahoo.com> wrote:
>>>> I have data for 3 variables (time series data) which I would like
> to rank
>>> using stata, and then run a regression on rank-transformed variables in
> order to
>>> test for causality. How is this done in stata?
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>> * http://www.ats.ucla.edu/stat/stata/
>>>
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>> * http://www.ats.ucla.edu/stat/stata/
>
>
>
> --
> JVVerkuilen, PhD
> jvverkuilen@gmail.com
>
> “He uses statistics as a drunken man uses lamp-posts – for support
> rather than illumination.”--Andrew Lang
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/
