Advanced Search
MyIDEAS: Login

Estimation of ordered response models with sample selection

Contents:

Author Info

Abstract

We introduce two new Stata commands for the estimation of an ordered response model with sample selection. The opsel command uses a standard maximum likelihood (ML) approach to fit a parametric specification of the model where errors are assumed to follow a bivariate Gaussian distribution. The snpopsel command uses the semi-nonparametric (SNP) approach of Gallant and Nychka (1987) to fit a semiparametric specification of the model where the bivariate density function of the errors is approximated by a Hermite polynomial expansion. The snpopsel command extends the set of Stata routines for SNP estimation of discrete response models. Compared to the other SNP estimators, our routine is relatively faster because it is programmed in MATA. In addition, we provide new post-estimation routines to compute linear predictions, predicted probabilities and marginal effects. These improvements are also extended to the set of SNP Stata commands originally written by Stewart (2004) and De Luca (2008). An illustration of the new opsel and snpopsel commands is provided through an empirical application on self-reported health with selectivity due to sample attrition.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: ftp://www.ceistorvergata.it/repec/rpaper/RP168.pdf
File Function: Main text
Download Restriction: no

Bibliographic Info

Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 168.

as in new window
Length: 27 pages
Date of creation: 03 Jun 2010
Date of revision: 03 Jun 2010
Handle: RePEc:rtv:ceisrp:168

Contact details of provider:
Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
Phone: +390672595601
Fax: +39062020687
Email:
Web page: http://www.ceistorvergata.it
More information through EDIRC

Order Information:
Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
Email:
Web: http://www.ceistorvergata.it

Related research

Keywords: Ordered response models; sample selection; parametric ML estimation; semi-nonparametric estimation.;

Other versions of this item:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Mark Stewart, 2002. "Semi-nonparametric estimation of extended ordered probit models," United Kingdom Stata Users' Group Meetings 2003 04, Stata Users Group.
  2. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
  3. Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
  4. Coppejans, Mark, 2007. "On efficient estimation of the ordered response model," Journal of Econometrics, Elsevier, vol. 137(2), pages 577-614, April.
  5. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
  6. Giuseppe De Luca, 2008. "SNP and SML estimation of univariate and bivariate binary-choice models," Stata Journal, StataCorp LP, vol. 8(2), pages 190-220, June.
  7. Arthur Lewbel, 1999. "Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables," Boston College Working Papers in Economics 454, Boston College Department of Economics.
  8. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
  9. Stewart, Mark B., 2005. "A comparison of semiparametric estimators for the ordered response model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 555-573, April.
  10. Meng, Chun-Lo & Schmidt, Peter, 1985. "On the Cost of Partial Observability in the Bivariate Probit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 71-85, February.
  11. Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "The dynamics of health in the British Household Panel Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(4), pages 473-503.
  12. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
  13. Alfonso Miranda & Sophia Rabe-Hesketh, 2006. "Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables," Stata Journal, StataCorp LP, vol. 6(3), pages 285-308, September.
  14. Coppejans, Mark & Gallant, A. Ronald, 2000. "Cross Validated SNP Density Estimates," Working Papers 00-10, Duke University, Department of Economics.
  15. Roger W. Klein & Robert P. Sherman, 2002. "Shift Restrictions and Semiparametric Estimation in Ordered Response Models," Econometrica, Econometric Society, vol. 70(2), pages 663-691, March.
  16. Chen, Songnian & Khan, Shakeeb, 2003. "Semiparametric Estimation Of A Heteroskedastic Sample Selection Model," Econometric Theory, Cambridge University Press, vol. 19(06), pages 1040-1064, December.
  17. Cheti Nicoletti & Franco Peracchi, 2005. "Survey response and survey characteristics: microlevel evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 763-781.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Sdiri, Hanen & Ayadi, Mohamed, 2012. "Innovation et externalisation des services: une analyse empirique sur données d'entreprises tunisiennes
    [Innovation and outsourcing of services: a firm-level analysis]
    ," MPRA Paper 39359, University Library of Munich, Germany.
  2. Omar Paccagnella, 2011. "Anchoring vignettes with sample selection due to non‐response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 665-687, 07.
  3. David ARISTEI & Manuela Gallo, 2012. "The Drivers of Household Over-Indebtedness and Delinquency on Mortgage Loans: Evidence from Italian Microdata," Quaderni del Dipartimento di Economia, Finanza e Statistica 105/2012, Università di Perugia, Dipartimento Economia, Finanza e Statistica.
  4. Edwin S. Wong, 2013. "Gender preference and transfers from parents to children: an inter-regional comparison," International Review of Applied Economics, Taylor & Francis Journals, vol. 27(1), pages 61-80, January.
  5. Bastien Bernela & Rachel Levy, 2014. "Collaboration networks in a French cluster: do partners really interact with each other?," Working Papers hal-00995175, HAL.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:rtv:ceisrp:168. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Barbara Piazzi).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.