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From |
Reshmi Sengupta <sengupta.r12@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Censored Least Absolute Deviation and Probit |

Date |
Sun, 4 Mar 2012 18:29:05 -0600 |

Dear Cameron, Thank you so much for your help and guidance. I sincerely appreciate. Just for a final confirmation..... so if I have comprehended your answers correctly then (A) you believe that theoretically there is no problem in estimating a non-parametric CLAD and a parametric Probit, simultaneously. Am I correct? (B) If that is the case then what shall be my assumption about the distribution of the errors in the two models (i.e., e1 and e2)? Can I assume that the errors are bivariate normally distributed? Also about -cmp-: ------------------------- I think -cmp- is for recursive models and cannot fit models with simultaneous causation (as is my case). Also it is based on normality assumption (since, -cmp- is a ML estimator), therefore, would not be appropriate in my case. Please correct me if I am wrong. Nevertheless, I will explore more on it and will also try to contact the author for more information. I have few more questions, it would be very helpful if you could provide me with your valued guidance: (1) Can you give me any insight on the Box-Cox Tobit or the Box-Cox Double Hurdle estimation: In Box-Cox Tobit estimation (or, Box-Cox Double Hurdle), can I simple transform my dependent variable using the Box-Cox transformation and then use simple -tobit- (or, -craggit-) command for estimation? Can that take into account the change in the likelihood function of the Tobit model (or, the Hurdle model) that is occurring due to the Box-Cox transformation? (2) Do you know of any STATA command for any semi-parametric methods for binary response model (e.g., Klein and Spady's Single Index Model). Please let me know. Please help. Regards, Reshmi On Sun, Mar 4, 2012 at 4:54 PM, Cameron McIntosh <cnm100@hotmail.com> wrote: > Reshmi, > Well, I thought I did help. Theoretically, it should be reasonable to estimate that 2-equation model with the link functions you describe, but I am not sure if -cmp- can invoke the CLAD estimator for a tobit model, so I would encourage you to check on that. The author of -cmp- is on the list, so he may chime in on that point. I might also suggest that you have a look at: > > Li, L., Simonoff, J.S., & Tsai, C.-L. (2007). Tobit model estimation and sliced inverse regression. Statistical Modelling, 7(2), 107-123. > > Holden, D. (2011). Testing for heteroskedasticity in the tobit and probit models. Journal of Applied Statistics, 38(4), 735-744. > > Newey, W.K. (1987). Specification tests for distributional assumptions in the Tobit model. Journal of Econometrics, 34(1-2), 125-145. > > Wilhelm, M.O. (2008). Practical Considerations for Choosing Between Tobit and SCLS or CLAD Estimators for Censored Regression Models with an Application to Charitable Giving. Oxford Bulletin of Economics and Statistics, 70(4), 559-582. > > Reynolds, A., & Shonkwiler, J.S. (1991). Testing and correcting for distributional misspecifications in the Tobit model: An application of the Information Matrix test. Empirical Economics, 16(3), 313-323. > > Holloway, G., Nicholson, C., Delgado, C., Staal, S., & Ehui, S. (2004). A revised Tobit procedure for mitigating bias in the presence of non-zero censoring with an application to milk-market participation in the Ethiopian highlands. Agricultural Economics, 31(1), 97–106. > > Carson, R.T., & Sun, Y. (2007). The Tobit model with a non-zero threshold. Econometrics Journal, 10, 488–502.http://econ.ucsd.edu/~rcarson/papers/TobitEJ07.pdf > > Barros, M., Galea, M., González, M., & Leiva, V. (2010). Influence diagnostics in the tobit censored response model. Statistical Methods & Applications, 19(3), 379-397.http://staff.deuv.cl/leiva/archivos/leiva_art/barros_galea_gonzalez_leiva_2010.pdf > > Sullivan, C.J., McGloin, J.-M., & Piquero, A.R. (2008). Modeling the Deviant Y in Criminology: An Examination of the Assumptions of Censored Normal Regression and Potential Alternatives. Journal of Quantitative Criminology, 24(4), 399-421. > > Cam > > ---------------------------------------- >> Date: Sun, 4 Mar 2012 16:29:14 -0600 >> Subject: Re: st: Censored Least Absolute Deviation and Probit >> From: sengupta.r12@gmail.com >> To: statalist@hsphsun2.harvard.edu >> >> Hello Cameron, >> >> Thank you so much for your reply. Actually, I want to relax the >> distributional assumptions in estimating my Eq( 2 ) (the censored >> Tobit type model), because, I have non-normality in errors (which I >> checked using -tobcm- in STATA after a tobit estimation), and >> therefore, I was contemplating of using CLAD. >> >> However, I do not know the code for any other semi or non-parametric >> estimation for the binary response model that can estimate Eq(1), >> except for Manski's Maximum Score estimator. But because of large N >> (around 13000 observations), I cannot use this estimation, and instead >> trying to estimate it using a Probit ML (normality of errors is >> satisfied using Probit ML). >> >> Since, CLAD satisfies asymptotic normality of the distribution of the >> error term, so I was wondering whether estimating the equations using >> CLAD and Probit simultaneously, would be a reasonable and >> statistically correct choice. >> >> Please help. >> >> Thank you. >> >> Regards, >> >> RSG >> >> On Sun, Mar 4, 2012 at 3:34 PM, Cameron McIntosh <cnm100@hotmail.com> wrote: >> > Hi, >> > >> > I think -cmp- would be your best bet. It does allow for simultaneous equations with a mix of link functions for accommodating a variety of particular response variable types: >> > >> > Roodman, D. (2011). Fitting fully observed recursive mixed-process models with cmp. The Stata Journal, 11(2), 159-206.http://www.stata-journal.com/article.html?article=st0224http://ideas.repec.org/c/boc/bocode/s456882.html >> > >> > Cam >> >> Date: Sun, 4 Mar 2012 10:58:15 -0600 >> >> Subject: st: Censored Least Absolute Deviation and Probit >> >> From: sengupta.r12@gmail.com >> >> To: statalist@hsphsun2.harvard.edu >> >> >> >> Dear Friends, >> >> >> >> I need your help on the following question: >> >> >> >> Can I estimate a CLAD (Censored Least Absolute Deviation) and a Probit >> >> model simultaneously? >> >> >> >> I have the following 2 equations: >> >> >> >> (1) Y1*=a0 + a1*Y2* + a2*X1 + e1 >> >> >> >> where Y1=1 if Y1*>0 >> >> and Y1=0 if otherwise >> >> >> >> (2) Y2*=b0 + b1*Y1*+ b2*X2+e2 >> >> >> >> where Y2=Y2* if Y2*>0 >> >> and Y2=0 if otherwise >> >> >> >> I am trying to estimate equation (1) using Probit Maximum Likelihood >> >> (ML) and equation (2) using CLAD. >> >> >> >> Please let me know. >> >> >> >> I will sincerely appreciate any help. >> >> >> >> Best Regards, >> >> >> >> R. Sengupta >> >> * >> >> * 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/

**References**:**st: Censored Least Absolute Deviation and Probit***From:*Reshmi Sengupta <sengupta.r12@gmail.com>

**RE: st: Censored Least Absolute Deviation and Probit***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: Censored Least Absolute Deviation and Probit***From:*Reshmi Sengupta <sengupta.r12@gmail.com>

**RE: st: Censored Least Absolute Deviation and Probit***From:*Cameron McIntosh <cnm100@hotmail.com>

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