[R-SIG-Finance] panel data in R

[Alexander Chernyakov]

Hi Richard,
Thanks for your response.  One issue I have run into with PLM is it
seems to be fairly slow with large data sets (14 mil date, firm
points).  Any tricks with this? Also, it seems to not handle
irregularly spaced time points.. it fills in the missing ones with NA
so when doing lagging or differencing things don't work correctly.  Do
you have any advice on fixing this?

Thanks,
Alex

On Sat, May 5, 2012 at 8:43 AM, Richard Herron
<richard.c.herron at gmail.com> wrote:
> What kind of models do plan on using?
>
> If you plan on using time series models, then I suggest generating a
> list where each entry is one firm. This will make it easy to fit
> models with lapply.
>
> If you plan on using panel models, then I suggest using PLM. It is
> easy enough to manually code within and between estimators, but if you
> use clustered standard errors or dynamic panel models, then PLM will
> make you life a lot easier.
>
> Richard Herron
>
>
> On Fri, May 4, 2012 at 6:30 PM, Alexander Chernyakov
> <alexander.chernyakov at gmail.com> wrote:
>>
>> Hi,
>> This question is of a general nature: How do people handle panel data
>> in R?  For example,  I have returns of firms and each firm has daily
>> observations.  One way is to use the plm package.. another is to use
>> plyr and just do the operations on (date, firmid) units using
>> something like zoo as a container for each firm so that lagging and
>> differencing can be done.  For regression it seems that plm might be
>> the better option?  Just curious if somebody has a well worked out
>> system for this.
>>
>> Thanks
>> Alex
>>
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