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 |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Coefficients resulting from Cross-Sectional Regressions |

Date |
Fri, 6 Apr 2012 18:49:27 +0100 |

What does "different amounts of yearly observations" mean? Perhaps you seek -rolling-. I'm not an economist, or at least no longer studying it, so economists and econometricians on the list may have a better sense of what you want. Nick 2012/4/6 Fabian Schönenberger <fabian.schoenenberger@gmail.com>: > I try to explain the research idea. Based on the expression yid,t = a + > bid,t*xid,t + e I am looking for bid,t, where id = firm and t = firm years. > Y = lnebit, x = lnsales; for every firm on different amounts of yearly > observations. The coefficient b measures the sensitivity of ebit resulting > from business activity. I will further analyse the coefficients and try to > find out what financial policies (for instance equity-ratio) this dependence > creates. In order to do that I (think I) need b for each individual for > every point in time. Clustered b (on id) are not sufficient to reuse the > coefficients for regressions based on yearly observations. One way would be > to merge id with t, in order to get yearly coefficients. Doesn't this make > sense? > > Fabian > > > -----Ursprüngliche Nachricht----- > Von: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Nick Cox > Gesendet: Freitag, 6. April 2012 18:39 > An: statalist@hsphsun2.harvard.edu > Betreff: Re: st: Coefficients resulting from Cross-Sectional Regressions > > That sounds like a series of regressions based on precisely one data point > each. > > And that makes no sense to me. > > Nick > > 2012/4/6 Fabian Schönenberger <fabian.schoenenberger@gmail.com>: >> Then I am on the wrong track anyway. Which is the right formula to do >> panel regressions with ID and t, for every single ID on each point in >> time in order to get coefficients individualised by ID and t? >> Many thanks in advance. >> >> >> -----Ursprüngliche Nachricht----- >> Von: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Nick Cox >> Gesendet: Freitag, 6. April 2012 17:20 >> An: statalist@hsphsun2.harvard.edu >> Betreff: Re: st: Coefficients resulting from Cross-Sectional >> Regressions >> >> statsby _b, by(gvkey) saving(coefsales): regress lnebit lnsales >> >> conducts separate regressions for each firm. The coefficient does not >> differ by year, as different years are pooled in each regression. >> >> You can put the results of -statsby- back in the original dataset by >> using -merge-. >> >> Alternatively, >> >> egen group = group(gvkey) >> gen coeff = . >> su group, meanonly >> >> qui forval i = 1/`r(max)' { >> regress lnebit lnsales if group == `i' >> replace coeff = _b[lnsales] if group == `i' >> } >> >> Nick >> >> 2012/4/6 Fabian Schönenberger <fabian.schoenenberger@gmail.com>: >> >>> I am an absolute beginner in Stata and face now some challenges with >>> generating regression coefficients as new variable for further >> computations. >>> I use tsset id t to conduct cross-sectional regressions. ID is gvkey >>> which identifies firm (about 4’000 firms in my sample), t is fyear >>> which identifies the specific year (ranging from 1984 to 2010). What >>> I am looking for is the function to run cross-sectional regressions >>> and generating coefficients as new variable to my list of variables. >>> In other words: I am looking for b, specified for each ID for every t >>> (yi,t = >> ai + bi,t*xi,t). >>> I have tried the following: >>> statsby _b, by(gvkey) saving(coefsales): regress lnebit lnsales >>> However, two problems arise. First, the major problem, I only get >>> coefficients for gvkey, but not specified for every point in time > (fyear). >>> Second, the coefsales are safed in a new file, but I would prefer a >>> new variable in my list of variable. >>> Any suggestions to solve the two problems are highly appreciated. > > * > * 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/

**Follow-Ups**:**AW: st: Coefficients resulting from Cross-Sectional Regressions***From:*Fabian Schönenberger <fabian.schoenenberger@gmail.com>

**References**:**st: Coefficients resulting from Cross-Sectional Regressions***From:*Fabian Schönenberger <fabian.schoenenberger@gmail.com>

**Re: st: Coefficients resulting from Cross-Sectional Regressions***From:*Nick Cox <njcoxstata@gmail.com>

**AW: st: Coefficients resulting from Cross-Sectional Regressions***From:*Fabian Schönenberger <fabian.schoenenberger@gmail.com>

**Re: st: Coefficients resulting from Cross-Sectional Regressions***From:*Nick Cox <njcoxstata@gmail.com>

**AW: st: Coefficients resulting from Cross-Sectional Regressions***From:*Fabian Schönenberger <fabian.schoenenberger@gmail.com>

- Prev by Date:
**AW: st: Coefficients resulting from Cross-Sectional Regressions** - Next by Date:
**st: Remedy for serial correlation in Panel Data** - Previous by thread:
**AW: st: Coefficients resulting from Cross-Sectional Regressions** - Next by thread:
**AW: st: Coefficients resulting from Cross-Sectional Regressions** - Index(es):