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From |
"Degas Wright" <degasw@decaturcapital.com> |

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

Subject |
RE: st: Using Rolling Regression with Panel Data |

Date |
Wed, 30 Sep 2009 13:13:43 -0400 |

Brian & Martin, Thank you for your response This seems to be a tough application of the xt commands. Gustave from the STATA staff sent the following to me on this question: Dear Degas, We do not have a one line command to perform the regressions that you Require and store the coefficient estimates. As I mentioned in my previous mail, "You may rather need to write a short program including a loop and using the -postfile- command". The code below reproduces an example with one of the datasets available from our website: webuse grunfeld,clear xtset company year tempname vector postfile `vector' time1 time2 /// beta_mvalue beta_kstock beta_const /// se_mvalue se_kstock se_const /// using mybeta, replace set more off forvalues i=1935/1952 { local j=`i'+2 display _n(3) in white _col(30) /// "Time period:" `i' "-" `j' xtreg invest mvalue kstock if year>=`i' & year<=`j' post `vector' /// (`i') (`j') /// (_b[mvalue]) (_b[kstock]) (_b[_cons]) /// (_se[mvalue]) (_se[kstock]) (_se[_cons]) local j=`j'+1 } postclose `vector' set more on use mybeta,clear I hope this helps. Sincerely, Gustavo I plan to try this solution and the others that you suggested. Using the xt commands in this way appears to be an efficient means to increase the R-square of the model as compared to simply using a one period cross sectional regression. Thank you, Degas A. Wright, CFA Chief Investment Officer Decatur Capital Management, Inc. 250 East Ponce De Leon Avenue, Suite 325 Decatur, Georgia 30030 Voice: 404.270.9838 Fax:404.270.9840 Website: www.decaturcapital.com -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss Sent: Wednesday, September 30, 2009 12:19 PM To: statalist@hsphsun2.harvard.edu Subject: AW: st: Using Rolling Regression with Panel Data <> Degas, when I try to replicate your dataset, I do not even manage to get -rolling- to estimate a single coefficient. It complains about insufficient observations. How is your real dataset different from the one I concoct? ************* clear* set obs 2000 set seed 14234 gen xticker=_n gen alpha=rnormal(0,0.02) expand 88 bys xticker: gen period=_n forv i=1/20{ gen var`i'=rnormal(0,0.03) } egen total=rowtotal(var*) gen return= /* */ 0.02+0.05*total+alpha+ /* */ rnormal(0,0.03) xtset xticker period rolling _b _se, window(3) clear: /* */ xtreg return var*, /* */ vce(cluster xticker) ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Brian R. Landy Gesendet: Mittwoch, 30. September 2009 17:28 An: statalist@hsphsun2.harvard.edu Betreff: Re: st: Using Rolling Regression with Panel Data Hi, I'm not really sure what your question is, but I'm guessing you find rolling: to be slow with a panel? I observed this a while back (and did report to Stata but have never seen notice that it was fixed), I found that -rolling- in conjunction with panels is far slower than the time implied by (# panels)*(time for rolling regression on just one panel). In my case a regression was taking over 1 hour on a 4 CPU box, this was for somewhere around 100 panels, 4 years of daily data, and a 2 year rolling regression. My workaround was to use foreach to loop over the panels, saving and merging the results of each somewhat like this: // prep data tsset id date gen end=date // for later merging tempfile stats levelsof id, local(ids) foreach id of local ids { keep if id==`id' quietly: rolling, window(`window') saving(`stats', replace) /// nodots: regress y x merge id end using "`stats'", sort update replace nokeep drop _merge } This took my 1+ hour runtime down to just a few minutes. Regards, Brian Quoting Degas Wright <degasw@decaturcapital.com>: > I have a longitudinal dataset that has 2000 stocks as xticker (id) and > dependent variable, return (t+1), with 20 independent variables (t) over 88 > periods (months). > > I am trying to run a , xtreg, regression over three periods and then use the > coefficients from the regression to forecast the t+1 return. When I use the > following command: > > . rolling _b _se, window (3) clear: xtreg return, var1, var2,.var20, > vce(cluster xticker) > > (running regress on estimation sample) > > -> xticker = 1 > > Rolling replications (86) > ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 > ......... > > -> xticker = 2 > > Rolling replications (86) > ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 > ........ > > It starts going through each of the 2000 stocks, by listing xticker1, > xticker 2, etc.. I have stopped it prior to the run being completed because > it will take a long time to go through all 2000 stocks. > > Is there another command that I should be using? For instance I use the > forvalues command to run the regression, xtreg, one period at a time for all > of the periods, Period 1, Period 2, etc. > > Thank you for your assistance. > > > > > Degas A. Wright, CFA > Chief Investment Officer > Decatur Capital Management, Inc. > 250 East Ponce De Leon Avenue, Suite 325 > Decatur, Georgia 30030 > Voice: 404.270.9838 > Fax:404.270.9840 > Website: www.decaturcapital.com > > > > > > * > * 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/ * * 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**:**Re: st: Using Rolling Regression with Panel Data***From:*"Brian R. Landy" <landy@alumni.caltech.edu>

**AW: st: Using Rolling Regression with Panel Data***From:*"Martin Weiss" <martin.weiss1@gmx.de>

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