IDEAS home Printed from https://ideas.repec.org/p/zur/econwp/003.html
   My bibliography  Save this paper

Specification and estimation of rating scale models - with an application to the determinants of life satisfaction

Author

Listed:
  • Raphael Studer
  • Rainer Winkelmann

Abstract

This article proposes a new class of rating scale models, which merges advantages and overcomes shortcomings of the traditional linear and ordered latent regression models. Both parametric and semi-parametric estimation is considered. The insights of an empirical application to satisfaction data are threefold. First, the methods are easily implementable in standard statistical software. Second, the non-linear model allows for exible marginal effects, and predicted means respect the boundaries of the dependent variable. Third, average marginal effects are similar to ordinary least squares estimates.

Suggested Citation

  • Raphael Studer & Rainer Winkelmann, 2011. "Specification and estimation of rating scale models - with an application to the determinants of life satisfaction," ECON - Working Papers 003, Department of Economics - University of Zurich.
    • Handle: RePEc:zur:econwp:003
    as

    Download full text from publisher

    File URL: https://www.zora.uzh.ch/id/eprint/50777/1/econwp003.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marcel Erlinghagen & Christoph Kern & Petra Stein, 2019. "Internal Migration, Social Stratification and Dynamic Effects on Subjective Well Being," SOEPpapers on Multidisciplinary Panel Data Research 1046, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Lancée, Sascha & Veenhoven, Ruut & Burger, Martijn, 2017. "Mood during commute in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 195-208.

    More about this item

    Keywords

    Rating variables; non-linear least squares; quasi-maximum likelihood; semiparametric least squares; subjective well-being;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I00 - Health, Education, and Welfare - - General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zur:econwp:003. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Severin Oswald (email available below). General contact details of provider: https://edirc.repec.org/data/seizhch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.