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The heterogeneous thresholds ordered response model: Identification and inference

Author

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  • Franco Peracchi

    (Tor Vergata University and EIEF)

  • Claudio Rossetti

    (LUISS)

Abstract

Although surveys routinely ask respondents to evaluate various aspects of their life on an ordered scale, there is concern about interpersonal comparability of these self-assessments. Statistically, the problem is one of identification in ordered response models with heterogeneous thresholds. As a solution to the identification problem, King et al. (2004) proposed using anchoring vignettes, namely brief descriptions of hypothetical people or situations that survey respondents are asked to evaluate on the same scale they use to rate their own situation. While vignettes have been introduced in several social surveys and are increasingly employed in a variety of fields, reliability of this approach hinges crucially on the validity of the assumptions of response consistency and vignette equivalence. This paper proposes a joint test of these key assumptions based on the fact that the underlying statistical model is overidentified if the two assumptions hold. Monte Carlo results show that the proposed test has good size and power properties in finite samples. We apply our test to self-assessment of pain using data from the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE). We find that, when using only one of the three available vignettes, or when the test is carried out separately by subgroups of respondents, the overidentifying restrictions are less likely to be rejected.

Suggested Citation

  • Franco Peracchi & Claudio Rossetti, 2010. "The heterogeneous thresholds ordered response model: Identification and inference," EIEF Working Papers Series 1012, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2012.
  • Handle: RePEc:eie:wpaper:1012
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    References listed on IDEAS

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    Cited by:

    1. Bertoni, Marco, 2015. "Hungry today, unhappy tomorrow? Childhood hunger and subjective wellbeing later in life," Journal of Health Economics, Elsevier, vol. 40(C), pages 40-53.
    2. G. Fiorentini & S. Robone & R. Verzulli, 2016. "How do hospital-specialty characteristics influence health system responsiveness? An empirical evaluation of in-patient care in the Italian Region of Emilia-Romagna," Working Papers wp1077, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. repec:eee:socmed:v:190:y:2017:i:c:p:247-255 is not listed on IDEAS
    4. Knott, R. & Lorgelly, P. & Black, N. & Hollingsworth, B., 2016. "Differential item functioning in the EQ-5D: An exploratory analysis using anchoring vignettes," Health, Econometrics and Data Group (HEDG) Working Papers 16/14, HEDG, c/o Department of Economics, University of York.
    5. Andrew M. Jones; Nigel Rice, Silvana Robone; & Nigel Rice; & Silvana Robone:, 2012. "A comparison of parametric and non-parametric adjustments using vignettes for self-reported data," Health, Econometrics and Data Group (HEDG) Working Papers 12/10, HEDG, c/o Department of Economics, University of York.
    6. Carmelo León & Jorge Araña & Javier León, 2013. "Correcting for Scale Perception Bias in Measuring Corruption: an Application to Chile and Spain," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(3), pages 977-995, December.
    7. repec:eee:econom:v:206:y:2018:i:1:p:258-278 is not listed on IDEAS
    8. Arthur van Soest & Hana Vonkova, 2014. "Testing the specification of parametric models by using anchoring vignettes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 115-133, January.

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