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Maximum Likelihood Estimation of Endogenous Switching And Sample Selection Models for Binary, Count, And Ordinal Variables

Author

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  • Alfonso Miranda

    () (Department of Economics, Keele,)

  • Sophia Rabe-Hesketh

    (Graduate Schoolof Education,)

Abstract

Studying behaviour in economics, sociology, and statistics often involves fitting models in which the response variable depends on a dummy variable (also known as a regime switch variable) or in which the response variable is observed only if a particular selection condition is met. In either case, standard regression techniques deliver inconsistent estimators if unobserved factors that affect the response are correlated with unobserved factors that affect the switching or selection variable. Consistent estimators can be obtained by maximum likelihood estimation of a joint model of the outcome and switching or selection variable. This paper describes a ‘wrapper’ program, ssm, that calls gllamm (Rabe-Hesketh et al. 2004a) to fit such models. The wrapper accepts data in a simple structure, has a straightforward syntax, and reports output in a manner that is easily interpretable. One important feature of ssm is that the log-likelihood can be evaluated using adaptive quadrature (Rabe- Hesketh and Skrondal 2002; Rabe-Hesketh et al. 2005)

Suggested Citation

  • Alfonso Miranda & Sophia Rabe-Hesketh, 2005. "Maximum Likelihood Estimation of Endogenous Switching And Sample Selection Models for Binary, Count, And Ordinal Variables," Keele Economics Research Papers KERP 2005/14, Centre for Economic Research, Keele University.
  • Handle: RePEc:kee:kerpuk:2005/14
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    File URL: http://www.keele.ac.uk/depts/ec/wpapers/kerp0514.pdf
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    Cited by:

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    2. Ehsan Khoman & James Mitchell & Martin Weale, 2008. "Incidence-based estimates of life expectancy of the healthy for the UK: coherence between transition probabilities and aggregate life-tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 203-222.
    3. Broström, Anders, 2010. "Working with distant researchers--Distance and content in university-industry interaction," Research Policy, Elsevier, vol. 39(10), pages 1311-1320, December.
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    5. Cornelissen, Thomas & Heywood, John S. & Jirjahn, Uwe, 2011. "Performance pay, risk attitudes and job satisfaction," Labour Economics, Elsevier, vol. 18(2), pages 229-239, April.
    6. César Alonso-Borrego & Antonio Romero-Medina, 2016. "Wage Expectations for Higher Education Students in Spain," LABOUR, CEIS, vol. 30(1), pages 1-17, March.
    7. Dawson, Peter & Jones, Philip, 2010. "How are They Spending my Taxes? Tax Compliance and Citizens’ Interest in Politics," Department of Economics Working Papers 21047, University of Bath, Department of Economics.
    8. 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, July.
    9. Sakurai, Takeshi, 2013. "Intensification of Lowland Cropping Systems and Informal Land Ownership in West Africa: Comparison of Two Large Inland Markets in Côte d’Ivoire and Ghana," Discussion Paper Series 586, Institute of Economic Research, Hitotsubashi University.
    10. repec:eid:wpaper:11/10 is not listed on IDEAS
    11. David Roodman, 2011. "Fitting fully observed recursive mixed-process models with cmp," Stata Journal, StataCorp LP, vol. 11(2), pages 159-206, June.
    12. David Roodman, 2009. "Estimating Fully Observed Recursive Mixed-Process Models with cmp," Working Papers 168, Center for Global Development.

    More about this item

    Keywords

    Endogenous switching; sample selection; binary variable; count data; ordinal variable; probit; poisson regression; adaptive quadrature; gllamm; wrapper; ssm.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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