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Extending Unobserved Heterogeneity - A Strategy for Accounting for Respondent Perceptions in the Absence of Suitable Data

  • Timothy A. Weterings


  • Mark N. Harris
  • Bruce Hollingsworth

This research proposes that, in cases where threshold covariates are either unavailable or difficult to observe, practitioners should treat these characteristics as latent, and use simulated maximum likelihood techniques to control for them. Two econometric frameworks for doing so in a more flexible manner are proposed. The finite sample performance of these new specifications are investigated with the use of Monte Carlo simulation. Applications of successively more flexible models are then given, with extensive post-estimation analysis utilised to better assess the likely implications of model choice on conclusions made in empirical research.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 12/12.

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Length: 31 pages
Date of creation: May 2012
Date of revision:
Handle: RePEc:msh:ebswps:2012-12
Contact details of provider: Postal: PO Box 11E, Monash University, Victoria 3800, Australia
Phone: +61 3 99052489
Fax: +61 3 99055474
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  1. William Greene & Mark N. Harris & Bruce Hollingsworth & Timothy A. Weterings, 2014. "Heterogeneity In Ordered Choice Models: A Review With Applications To Self-Assessed Health," Journal of Economic Surveys, Wiley Blackwell, vol. 28(1), pages 109-133, 02.
  2. Thomas Cornelißen & Christian Pfeifer, 2007. "The Impact of Participation in Sports on Educational Attainment: New Evidence from Germany," SOEPpapers on Multidisciplinary Panel Data Research 68, DIW Berlin, The German Socio-Economic Panel (SOEP).
  3. N Powdthavee, 2008. "Ill-Health as a Household Norm: Evidence from Other People's Health Problems," Discussion Papers 08/21, Department of Economics, University of York.
  4. Julie Litchfield & Barry Reilly & Mario Veneziani, 2010. "An Analysis of Life Satisfaction in Albania: An Heteroscedastic Ordered Probit Model Approach," Working Paper Series 0310, Department of Economics, University of Sussex.
  5. Stephen Pudney & Michael Shields, 2000. "Gender, race, pay and promotion in the British nursing profession: estimation of a generalized ordered probit model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(4), pages 367-399.
  6. Ziebarth, Nicolas, 2010. "Measurement of health, health inequality, and reporting heterogeneity," Social Science & Medicine, Elsevier, vol. 71(1), pages 116-124, July.
  7. Stefan Boes & Rainer Winkelmann, 2005. "Ordered Response Models," SOI - Working Papers 0507, Socioeconomic Institute - University of Zurich.
  8. Cunha, Flavio & Heckman, James J. & Navarro, Salvador, 2007. "The Identification and Economic Content of Ordered Choice Models with Stochastic Thresholds," IZA Discussion Papers 2940, Institute for the Study of Labor (IZA).
  9. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521142373, October.
  10. García-Gómez, Pilar & Jones, Andrew M. & Rice, Nigel, 2010. "Health effects on labour market exits and entries," Labour Economics, Elsevier, vol. 17(1), pages 62-76, January.
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