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From |
Steve Samuels <sjsamuels@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: st: Re: st: RE: Ratio of coefficients from two regressions and standard error. |

Date |
Sun, 4 Dec 2011 00:45:18 -0500 |

Maarten Buis diagnosed this problem at http://www.stata.com/statalist/archive/2007-10/msg00201.html The second bootstrap replicate refuses to run because the variable "uhatmain" created by your -predict- statement already exists in the data set; as a result only one replicate is created. Maarten's suggestion: use a temporary variable. Or, drop "uhatmain" at the end of the program. Also drop all created scalars at the end of the program with a -scalar drop- statement; otherwise those from the last replicate will hang around. Steve On Dec 3, 2011, at 11:20 PM, meenakshi beri wrote: Hello Steve, Thanks for your reply and teaching me the way to estimate the ratio and standard error. I am using the same code (after modifying it as per panel data needs and multiple ratios needs) given by you, but I have been struggling with this insufficient observations error (otherwise my regressions are running fine without bootstrap). I have generated new identifier cluster variable also for the bootstrapped panels, as well as generated the new time variable also (whatever information I got using previously existing statalist answers for such a situation, I tried that but nothing worked). Is there something I am doing wrong? I get the following error after bootstrap command: insufficient observations to compute bootstrap standard errors no results will be saved r(2000); Here is my sample code: program my_xtboot, rclass xi: xtreg rwhappy hibp diab cancr l_inc_wealth hibp_wealth diab_wealth cancr_wealth hispanic if sample_black == 1, fe scalar define b1 = _b[hibp_wealth] scalar define b2 = _b[diab_wealth] scalar define b3 = _b[cancr_wealth] predict uhatmain, u xi: xtreg uhatmain l_inc_wealth hispanic, be scalar define b8 = _b[l_inc_wealth] return scalar ratio1 = b1/b8 return scalar ratio2 = b2/b8 return scalar ratio3 = b3/b8 end *generating new identiers for bootstrapping gen long newhhid = . replace newhhid = hhidpn gen time2 = . replace time2 = 1 if year == 1992 replace time2 = 2 if year == 1993 replace time2 = 3 if year == 1994 replace time2 = 4 if year == 1995 * declaring new panel and time variable tsset newhhid time2 * getting rid of missing values generate sample=1-missing(newhhid, time2, l_inc_wealth, rwhappy, hibp, diab, cancr, hispanic) keep if sample *bootstrap ratio bootstrap ratio1 =r(ratio1) , reps(100)cluster(hhidpn) idcluster(newhhid) nowarn: my_xtboot if sample_black == 1 estat bootstrap, all And here is what I get: bootstrap ratio1 =r(ratio1) , reps(100)cluster(hhidpn) idcluster(newhhid) nowarn: my_xtboot if sample_black == 1 (running my_xtboot on estimation sample) : : Bootstrap replications (100) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 50 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 100 insufficient observations to compute bootstrap standard errors no results will be saved r(2000); Best Regards, Meenakshi ________________________________ Meenakshi Beri Graduate Teaching Assistant Department of Economics Wayne State University dy5651@wayne.edu ---------------------------------------- > Subject: st: Re: st: RE: Ratio of coefficients from two regressions and standard error. > From: sjsamuels@gmail.com > Date: Sat, 3 Dec 2011 16:23:19 -0500 > To: statalist@hsphsun2.harvard.edu > > > > Bootstrapping the ratio should give good results with fewer assumptions about the regression coefficients. > > Steve > *************CODE BEGINS************* > sysuse auto, clear > capture program drop myboot > > program myboot, rclass > reg trunk length > scalar define b1 = _b[length] > > reg weight length > scalar define b2 = _b[length] > > return scalar ratio = b2/b1 > end > > bootstrap ratio =r(ratio) , reps(40): myboot > estat bootstrap, all > **************CODE ENDS************** > > On Dec 2, 2011, at 10:44 AM, meenakshi beri wrote: > > Thanks for your reply. One more question -- how to use Fieller's theorem and derive confidence limits using stata in this case? > > Meenakshi Beri > Graduate Teaching Assistant > Department of Economics > Wayne State University > dy5651@wayne.edu > > > From: Paul.Silcocks@liverpool.ac.uk > To: statalist@hsphsun2.harvard.edu > Subject: st: RE: Ratio of coefficients from two regressions and standard error. > Date: Fri, 2 Dec 2011 09:23:04 +0000 > > On the assumption that the two regression coefficient estimates have a Normal distribution, their ratio would have a Cauchy distribution (with no defined variance) if their correlation is zero. If the correlation is non-zero the exact distribution is complicated, though under certain conditions it tends to a Normal distribution. > > You'd be better off instead using Fieller's theorem to obtain confidence limits rather than estimating the standard error > > Paul Silcocks BM BCh, MSc , FRCPath, FFPH, CStat > Senior statistician, > Cancer Research UK Liverpool Cancer Trials Unit > University of Liverpool > Block C Waterhouse Building > 1-3 Brownlow Street > L69 3GL > > email: paul.silcocks@liverpool.ac.uk > tel: 0151 7948802 > mob: 0794 983 2775 > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of meenakshi beri > Sent: 02 December 2011 06:08 > To: statalist@hsphsun2.harvard.edu > Subject: st: Ratio of coefficients from two regressions and standard error. > > Hello Statalist, > I am running a fixed effects regression followed by an auxiliary regression to capture the coefficient of time invariant variables. I want to estimate the ratio of two coefficients from these two regressions respectively along with the standard error of the ratio. How can I estimate the ratio and standard error? > Thanks,Meenakshi BeriWayne State University > * > * 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/ * * 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: Re: st: Re: st: RE: Ratio of coefficients from two regressions and standard error.***From:*meenakshi beri <berimeenakshi@hotmail.com>

**References**:**st: Ratio of coefficients from two regressions and standard error.***From:*meenakshi beri <berimeenakshi@hotmail.com>

**st: RE: Ratio of coefficients from two regressions and standard error.***From:*"Silcocks, Paul" <Paul.Silcocks@liverpool.ac.uk>

**RE: st: RE: Ratio of coefficients from two regressions and standard error.***From:*meenakshi beri <berimeenakshi@hotmail.com>

**st: Re: st: RE: Ratio of coefficients from two regressions and standard error.***From:*Steve Samuels <sjsamuels@gmail.com>

**RE: st: Re: st: RE: Ratio of coefficients from two regressions and standard error.***From:*meenakshi beri <berimeenakshi@hotmail.com>

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