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The heterogeneous thresholds ordered response model: Identification and inference

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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.

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Bibliographic Info

Paper provided by Einaudi Institute for Economics and Finance (EIEF) in its series EIEF Working Papers Series with number 1012.

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Length: 26 pages
Date of creation: 2010
Date of revision: Apr 2012
Handle: RePEc:eie:wpaper:1012

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  1. Franklin Allen & Ana Babus & Elena Carletti, 2010. "Financial Connections and Systemic Risk," Economics Working Papers ECO2010/26, European University Institute.
  2. Cohen-Cole, Ethan, 2006. "Multiple groups identification in the linear-in-means model," Economics Letters, Elsevier, vol. 92(2), pages 157-162, August.
  3. Calvó-Armengol, Antoni & Patacchini, Eleonora & Zenou, Yves, 2008. "Peer Effects and Social Networks in Education," CEPR Discussion Papers 7060, C.E.P.R. Discussion Papers.
  4. Aureo de Paula, 2004. "Inference in a Synchronization Game with Social Interactions," PIER Working Paper Archive 07-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 May 2007.
  5. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
  6. Ethan Cohen-Cole & Giulio Zanella, 2008. "Unpacking Social Interactions," Economic Inquiry, Western Economic Association International, vol. 46(1), pages 19-24, 01.
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Cited by:
  1. 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.
  2. Carmelo León & Jorge Araña & Javier León, 2013. "Correcting for Scale Perception Bias in Measuring Corruption: an Application to Chile and Spain," Social Indicators Research, Springer, vol. 114(3), pages 977-995, December.

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