Estimation of ordered response models with sample selection
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.
|Date of creation:||03 Jun 2010|
|Date of revision:||03 Jun 2010|
|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|
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|
Web: http://www.ceistorvergata.it Email:
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.:
- John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998.
"An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of income Dynamics,"
Economics Working Paper Archive
379, The Johns Hopkins University,Department of Economics.
- 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.
- John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," NBER Technical Working Papers 0220, National Bureau of Economic Research, Inc.
- J. Fitzgerald & P. Gottschalk & R. Moffitt, "undated". "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Institute for Research on Poverty Discussion Papers 1156-98, University of Wisconsin Institute for Research on Poverty.
- John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1997. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Boston College Working Papers in Economics 394, Boston College Department of Economics.
- Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
- 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.
- Giuseppe De Luca & Franco Peracchi, 2012.
"Estimating Engel curves under unit and item nonresponse,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 27(7), pages 1076-1099, November.
- 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.
- Coppejans, Mark & Gallant, A. Ronald, 2002.
"Cross-validated SNP density estimates,"
Journal of Econometrics,
Elsevier, vol. 110(1), pages 27-65, September.
- 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.
- Mark B. Stewart, 2004.
"Semi-nonparametric estimation of extended ordered probit models,"
StataCorp LP, vol. 4(1), pages 27-39, March.
- Mark Stewart, 2002. "Semi-nonparametric estimation of extended ordered probit models," United Kingdom Stata Users' Group Meetings 2003 04, Stata Users Group.
- 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.
- 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.
- Coppejans, Mark, 2007. "On efficient estimation of the ordered response model," Journal of Econometrics, Elsevier, vol. 137(2), pages 577-614, April.
- 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.
- 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.
- Agar Brugiavini & Tullio Jappelli & Guglielmo Weber, 2002. "The Survey on Health, Aging and Wealth," CSEF Working Papers 86, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
- Yingying Dong & Arthur Lewbel, 2012. "Simple Estimators for Binary Choice Models with Endogenous Regressors," Working Papers 111204, University of California-Irvine, Department of Economics.
- Lewbel, Arthur, 2000.
"Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables,"
Journal of Econometrics,
Elsevier, vol. 97(1), pages 145-177, July.
- 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.
- 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.
- 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.
- 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.
- Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
- 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.
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.