Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
John Antonakis <john.antonakis@unil.ch> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Estimating firm level data on regional level data using a within estimator. |

Date |
Sun, 06 Jun 2010 14:17:35 +0200 |

Hi Natasha:

Best, J. ____________________________________________________

Department of Organizational Behavior University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 Faculty page: http://www.hec.unil.ch/people/jantonakis Personal page: http://www.hec.unil.ch/jantonakis ____________________________________________________ On 06.06.2010 13:56, Maarten buis wrote:

--- On Sun, 6/6/10, natasha agarwal wrote:I estimate it with a within estimator, i.e. ur fixedeffects. When I do so the minute I include all the timedummies, FDI goes insig but thats my main variable ofinterest. The problem that I have found out is that FDI is behaving like a time dummy because all the firms within a region for each year will have the same valueof FDI.The problem with macro quantities is that they are usually highlycorrelated with other macro quantities and time, so it is hard todisentangle the effects. Moreover, there are only so manyobservations possible on the macro level. These two together meansthat often you have very little statistical power to play with.The advantage of fixed effects regression is that it provides astrong reason for believing that you controlled for some of theunobserved and possible confounding variables on the the regionlevel. However, the price you have to pay is that you loose a lotof power; i.e. you loose all the information from the comparisonbetween regions. Since you don't have a lot to begin with, thatis very bad news.Random effects don't allow you to controll for unobservedconfounding variables on the region level (the random effects areassumed to be uncorrelated with the observed variables), but it does allow you to also use the information from the comparison between regions. Then you have rather pragmatic discipline specific reasons: e.g. within economics they tend to be so obsessed with fixed effectsregression, that you will have a hard time getting a randomeffects model published.Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl --------------------------* * 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/

**Follow-Ups**:**Re: st: Estimating firm level data on regional level data using a within estimator.***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**Re: st: Estimating firm level data on regional level data using a within estimator.***From:*Maarten buis <maartenbuis@yahoo.co.uk>

- Prev by Date:
**Re: st: RE: bar graph with showyvar** - Next by Date:
**st: graph aspect ratio** - Previous by thread:
**Re: st: Estimating firm level data on regional level data using a within estimator.** - Next by thread:
**Re: st: Estimating firm level data on regional level data using a within estimator.** - Index(es):