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Ordered response models and non-random personality traits: Monte Carlo simulations and a practical guide

  • Geishecker, Ingo
  • Riedl, Maximilian

The paper compares different estimation strategies of ordered response models in the presence of non-random unobserved heterogeneity. By running Monte Carlo simulations with a range of randomly generated panel data of differing cross-sectional and longitudinal dimension sizes, we assess the consistency and efficiency of standard models such as linear fixed effects, ordered and conditional logit, and several different binary recoding procedures. Among the binary recoding procedures analyzed are the conditional ordered logit estimator proposed by Ferrer-i-Carbonell and Frijters (2004) that recently has gained some popularity in the analysis of individual well-being, as well as the new developed "Blow-Up and Cluster" (BUC) estimator of Baetschmann et al. (2011). The Ferrer-i-Carbonell and Frijters estimator (FCF) performs best if the number of observations is large and the number of categories on the ordered scale is small. However, the BUC method performs similarly well and even outperforms the FCF estimator if the number of categories on the ordered scale is large. If the researcher is only interested in the relative size of coefficients with respect to a baseline, however, the easy-to-compute linear fixed effects model delivers essentially the same results as the more elaborate binary recoding schemes.

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File URL: http://econstor.eu/bitstream/10419/70220/1/116_revised.pdf
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Paper provided by University of Goettingen, Department of Economics in its series Center for European, Governance and Economic Development Research Discussion Papers with number 116.

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Date of creation: 2012
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Handle: RePEc:zbw:cegedp:116
Contact details of provider: Postal: Platz der Göttinger Sieben 3, 37073 Göttingen
Web page: http://www.cege.wiso.uni-goettingen.de/
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  1. Senik, Claudia, 2004. "When information dominates comparison: Learning from Russian subjective panel data," Journal of Public Economics, Elsevier, vol. 88(9-10), pages 2099-2123, August.
  2. Simon Luechinger, 2009. "Valuing Air Quality Using the Life Satisfaction Approach," Economic Journal, Royal Economic Society, vol. 119(536), pages 482-515, 03.
  3. Andrew Clark, 2001. "Unemployment As A Social Norm: Psychological Evidence from Panel Data," DELTA Working Papers 2001-17, DELTA (Ecole normale supérieure).
  4. Simon Luechinger & Stephan Meier & Alois Stutzer, 2008. "Why Does Unemployment Hurt the Employed? Evidence from the Life Satisfaction Gap between the Public and the Private Sector," Working papers 2008/02, Faculty of Business and Economics - University of Basel.
  5. Ada Ferrer-i-Carbonell & Paul Frijters, 2004. "How Important is Methodology for the estimates of the determinants of Happiness?," Economic Journal, Royal Economic Society, vol. 114(497), pages 641-659, 07.
  6. Clark, Andrew & Knabe, Andreas & Rätzel, Steffen, 2010. "Boon or bane? Others' unemployment, well-being and job insecurity," Labour Economics, Elsevier, vol. 17(1), pages 52-61, January.
  7. Winkelmann, Liliana & Winkelmann, Rainer, 1998. "Why Are the Unemployed So Unhappy? Evidence from Panel Data," Economica, London School of Economics and Political Science, vol. 65(257), pages 1-15, February.
  8. Robert J. MacCulloch & Rafael Di Tella & Andrew J. Oswald, 2001. "Preferences over Inflation and Unemployment: Evidence from Surveys of Happiness," American Economic Review, American Economic Association, vol. 91(1), pages 335-341, March.
  9. Paul Frijters & Ingo Geishecker & John P. Haisken-DeNew & Michael A. Shields, 2006. "Can the Large Swings in Russian Life Satisfaction be Explained by Ups and Downs in Real Incomes?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 108(3), pages 433-458, October.
  10. Thomas Cornelißen, 2009. "The Interaction of Job Satisfaction, Job Search, and Job Changes. An Empirical Investigation with German Panel Data," Journal of Happiness Studies, Springer, vol. 10(3), pages 367-384, June.
  11. J. S. Cramer, 2007. "Robustness of Logit Analysis: Unobserved Heterogeneity and Mis-specified Disturbances," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(4), pages 545-555, 08.
  12. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
  13. Baetschmann, Gregori & Staub, Kevin E. & Winkelmann, Rainer, 2011. "Consistent Estimation of the Fixed Effects Ordered Logit Model," IZA Discussion Papers 5443, Institute for the Study of Labor (IZA).
  14. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
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