IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v25y2020i3p81-91n1.html
   My bibliography  Save this article

Finding correct elasticities in log-linear and exponential models allowing heteroskedasticity

Author

Listed:
  • Lee Myoung-jae

    (Department of Economics, Korea University, Seoul, 02841, South Korea)

Abstract

Log-linear models are popular in practice because the slope of a log-transformed regressor is believed to give an unit-free elasticity. This widely held belief is, however, not true if the model error term has a heteroskedasticity function that depends on the regressor. This paper examines various mean – and quantile-based elasticities (mean of elasticity, elasticity of conditional mean, quantile of elasticity, and elasticity of conditional quantile) to show under what conditions these are equal to the slope of a log-transformed regressor. A particular attention is given to the ‘elasticity of conditional mean (i.e., regression function)’, which is what most researchers have in mind when they use log-linear models, and we provide practical ways to find it in the presence of heteroskedasticity. We also examine elasticities in exponential models which are closely related to log-linear models. An empirical illustration for health expenditure elasticity with respect to income is provided to demonstrate our main findings.

Suggested Citation

  • Lee Myoung-jae, 2020. "Finding correct elasticities in log-linear and exponential models allowing heteroskedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(3), pages 81-91, June.
  • Handle: RePEc:bpj:sndecm:v:25:y:2020:i:3:p:81-91:n:1
    DOI: 10.1515/snde-2018-0099
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2018-0099
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/snde-2018-0099?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Iwona Bąk & Katarzyna Cheba, 2022. "Green Transformation: Applying Statistical Data Analysis to a Systematic Literature Review," Energies, MDPI, vol. 16(1), pages 1-22, December.

    More about this item

    Keywords

    exponential model; log-linear model; mean elasticity; quantile elasticity;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • I10 - Health, Education, and Welfare - - Health - - - General

    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:bpj:sndecm:v:25:y:2020:i:3:p:81-91:n:1. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.