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From |
meenakshi beri <berimeenakshi@hotmail.com> |

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

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

Date |
Sun, 4 Dec 2011 17:16:58 +0000 |

Hello Steve, Thanks a lot for your suggestions. I appreciate your time and effort. Here is an issue: 1. I am using panel data and I found that xtreg is not supported by suest 2. If I use the previous code (as was suggested by you earlier) and create uhatmain as a temporary variable, I get the following error: **************************************** bootstrap ratio1 =r(ratio1) , reps(100)cluster(hhidpn) idcluster(newhhid) nowarn : my_xtboot (running my_xtboot on estimation sample) : variable uhatmain not found an error occurred when bootstrap executed my_xtboot **************************************** Best, Meenakshi ________________________________ Meenakshi Beri Graduate Teaching Assistant Department of Economics Wayne State University dy5651@wayne.edu ---------------------------------------- > Subject: st: Re: st: Re: st: Re: st: RE: Ratio of coefficients from two regressions and standard error. > From: sjsamuels@gmail.com > Date: Sun, 4 Dec 2011 10:51:31 -0500 > To: statalist@hsphsun2.harvard.edu > > You are welcome. After re-reading's Maarten's post, I recommend that you use temporary scalars (via -tempname-) and variables throughout the program, not permanent ones. Here the -bootstrap- automatically takes care of the cross-equation correlations. Many people would use -suest- for doing this. There are several advantages: 1) you can debug a complex program before -bootstrapping it; 2) you don't need to create scalars; 3) the equation names and coefficient names are used in the definition of the returned scalars, so there's less possibility of a mix-up. > > Here's the -suest- version. > > ********************************* > program myboot, rclass > reg trunk length > estimates store m1 > > reg weight length > estimates store m2 > > suest m1 m2 > return scalar ratio = /// > [m2_mean]length/[m1_mean]length > end > *********************************** > > > The disadvantage is that -suest- cannot handle commands, like -stcox- that do not create a score variable for each observation. > > > On Dec 4, 2011, at 1:39 AM, meenakshi beri wrote: > > Thanks a lot! I highly appreciate that. > > Best,Meenakshi > > ________________________________ > Meenakshi Beri > Graduate Teaching Assistant > Department of Economics > Wayne State University > dy5651@wayne.edu > > > ---------------------------------------- > > Subject: st: Re: st: Re: st: RE: Ratio of coefficients from two regressions and standard error. > > From: sjsamuels@gmail.com > > Date: Sun, 4 Dec 2011 00:45:18 -0500 > > To: statalist@hsphsun2.harvard.edu > > > > > > > > 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/ > > * > * 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**:**st: Re: st: Re: st: Re: st: Re: st: RE: Ratio of coefficients from two regressions and standard error.***From:*Steve Samuels <sjsamuels@gmail.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>

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

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

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

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