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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: Multinomial logit for panel data? |

Date |
Thu, 9 Jul 2009 16:22:20 +0100 |

Thanks for this information. -markov- certainly calculates no standard errors. Years ago in teaching I used Stata's matrix language to get limiting distributions from transition probabilities for first-order, discrete-state, discrete-time Markov chains. However, I don't know how that kind of calculation carries over to quintile-based classifications. Nick n.j.cox@durham.ac.uk Austin Nichols Nick et al.-- I think Markov-style models are still used by implication, for example in the economic mobility literature, where quintile transition matrices are popular, but probably not justified. One reason: the product of two transition matrices estimated for t-1 to t and for t-2 to t-1 often bears no resemblance to a matrix estimated from t-2 to t, contradicting assumptions required for a Markov process. If Dmitriy Krichevskiy believe he has a Markov process, he can estimate on pooled data by duplicating and reshaping data, though this seems like a bad idea--better to estimate for each pair of times. Probably he should use svy:tab to get standard errors on transition probabilities, which do not seem to be estimated by -markov- on SSC. In any case, the limiting distribution can be derived via a little linear algebra, and probably it is not too much work to get some standard errors for that distribution as well. On Thu, Jul 9, 2009 at 10:58 AM, Nick Cox<n.j.cox@durham.ac.uk> wrote: > I don't think so; that is, it does not seem that multinomial *it will be > of much use to you. As I understand it, you want a kind of Markov model > in which you estimate transition probabilities. Such models were much > discussed a few decades ago but in literature I see appear rather > unfashionable now, for no good reason obvious to me. > > I can confirm that -markov-, which I wrote in 1998 and which remains on > SSC, is no use for your purpose. I get occasional mail about it, some of > it rather indignant or at least surprised that it does not do what it > does not claim to do, namely support panels. This attitude sometimes > appears connected to the paradox that those claiming to be doing > cutting-edge research often expect that canned software is always > available already in precisely the form they need. > > Yvonne Bishop, Stephen Fienberg and Paul Holland in their text "Discrete > multivariate analysis" (MIT Press 1975; reissued more recently by > Springer) have a chapter relating Markov and log-linear modelling. So, > and this is wild surmise, -glm- or -poisson- may be of some use to you. > > Nick > n.j.cox@durham.ac.uk > > Dmitriy Krichevskiy > > I have a large panel dataset (about 14000 individuals over 84 periods > - unbalanced). I want to get to the limiting distribution of > distribution dynamics for 2 separate groups. Is anyone aware of the > way to analyze this? > -markov- does not work on panel data and -xttrans- produces a single > transition matrix by lumping all of the transitions into '1 old to 1 > new' transition. Ideally I would want a dynamic panel data model but > the dependant variable is a quintile so it seems to me that > multinomial logit or probit is in order. Thanks for all of your help > again. > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/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/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/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Multinomial logit for panel data?***From:*Dmitriy Krichevskiy <krichevskyd@gmail.com>

**st: RE: Multinomial logit for panel data?***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: RE: Multinomial logit for panel data?***From:*Austin Nichols <austinnichols@gmail.com>

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