IDEAS home Printed from https://ideas.repec.org/p/ecj/ac2002/157.html

Why Run a Million Regressions? Endogenous Policy and Cross-Country Growth Empirics

Author

Listed:
  • Rehme, G¸nther

    (Technische Universit”t Darmstadt)

Abstract

This paper analyses the link between growth and public policy when the latter depends on economically important fundamentals. When policy is endogenous the measured effects of policy on growth will generally be biased. Using a widely quoted theoretical model, the signs of the biases are derived. It is shown that the usually reported effects on growth of tax rate variables related to GDP, the ratio of public investment to total investment and the ratio of redistributive transfers to GDP are generally biased downwards. Based on these signed biases the paper discusses some empirical results that seem puzzling from a theoretical viewpoint.

Suggested Citation

  • Rehme, G¸nther, 2002. "Why Run a Million Regressions? Endogenous Policy and Cross-Country Growth Empirics," Royal Economic Society Annual Conference 2002 157, Royal Economic Society.
  • Handle: RePEc:ecj:ac2002:157
    as

    Download full text from publisher

    File URL: http://repec.org/res2002/Rehme.pdf
    File Function: full text
    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. Rehme, Günther, 2014. "Endogenous (re-)distributive policies and economic growth: A comparative static analysis," Economic Modelling, Elsevier, vol. 40(C), pages 355-366.
    2. Günther Rehme, 2011. "Endogenous Policy And Cross‐Country Growth Empirics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(2), pages 262-296, May.

    More about this item

    JEL classification:

    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • D3 - Microeconomics - - Distribution
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    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:ecj:ac2002:157. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.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.