[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
bmilanovic@worldbank.org |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: using xtabond and xtabond2 |

Date |
Sat, 28 Jul 2007 20:41:27 -0400 |

Michael Binder (Dynamic panel data models with homogeneous slopes) shows that the bias in the dynamic FE models is equal to (Embedded image moved to file: pic25996.jpg) where ë is the true coefficient, and AT and BT complicated expressions that tend respectively to 0 and 1 when the time dimension T tends to infinity. Consequently, with a very large T (say, more than 50), the bias is quasi non-existent. However, I had T>150 and one of the referees strongly complained why I am using FE, and not Arellano-Bond. Branko Development Research, World Bank Email: bmilanovic@worldbank.org or branko_mi@yahoo. tel: 202-473-6968 World Bank, Room MC 3-581 1818 H Street NW Washington D.C. 20433 For "Worlds Apart" see http://www.pupress.princeton.edu/titles/7946.html Website: http://econ.worldbank.org/projects/inequality For papers see also: http://econpapers.hhs.se/ http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=149002 Michael Hanson <mshanson@mac.c om> To Sent by: statalist@hsphsun2.harvard.edu owner-statalist cc @hsphsun2.harva rd.edu Subject Re: st: using xtabond and xtabond2 07/28/2007 07:55 PM Please respond to statalist@hsphs un2.harvard.edu On Jul 28, 2007, at 6:56 PM, natalie chan wrote: > Maybe this is a question more about econometrics than about Stata but > I can't find anywhere more appropriate to ask this question. Thanks in > advance. > > I am doing regressions on economic growth equations with a panel data > of 20 years for 48 countries. I wanted to use dynamic panel approach > with xtabond or xtabond2, however, the Arellano-Bond methods are > specified for data with small T and large N. On the other hand, I > have seen some researchers using Arellano-Bond methods on growth > models, including Bond himself. Could anyone give me some advice on > this? Thanks a lot. I would like to expand Natalie's question: I have an application of dynamic panel data in which T/N is nearly 3, with N = 50. In David Roodman's excellent discussion of -xtabond2- [1], he writes, "If T is large, dynamic panel bias becomes insignificant, and a more straightforward fixed effects estimator works." (p. 42) However, I have never been able to find a discussion of how "large" of a T is "large enough" in the literature (which I interpret is part of Natalie's question). In the only textbook reference I have found, Baltagi (2005) [2] writes, "FE, GMM, and LIML exhibit a bias term in their asymptotic distributions; the biases are of the order 1/T, 1/N, and 1/(2N-T), respectively." (p. 153) Would it be reasonable, therefore, to conclude that in Natalie's case (T/N < 1/2), GMM (i.e. AB-type estimators) or LIML would be preferred, whereas in my case (T/N > 2.5), FE would be preferred? (I realize that this claim is based on asymptotic arguments, and that the N & T discussed here are probably too small. Any information about the small-sample properties of these estimators in a dynamic panel context would be appreciated as well.) I also recognize that this question is at least as much about statistics (econometrics) as about Stata, and I appreciate any help or suggestions. [1] <http://repec.org/nasug2006/howtodoxtabond2.cgdev.pdf> [2] <http://www.stata.com/bookstore/eapd.html> -- Mike * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Attachment:
pic25996.jpg**

**Follow-Ups**:**Re: st: using xtabond and xtabond2***From:*"Rodrigo A. Alfaro" <raalfaroa@gmail.com>

**References**:**Re: st: using xtabond and xtabond2***From:*Michael Hanson <mshanson@mac.com>

- Prev by Date:
**Re: st: using xtabond and xtabond2** - Next by Date:
**Re: st: using xtabond and xtabond2** - Previous by thread:
**Re: st: using xtabond and xtabond2** - Next by thread:
**Re: st: using xtabond and xtabond2** - Index(es):

© Copyright 1996–2014 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |