IDEAS home Printed from https://ideas.repec.org/p/sfu/sfudps/dp11-02.html
   My bibliography  Save this paper

Bounding a linear causal effect using relative correlation restrictions

Author

Abstract

This paper describes and implements a simple approach to the most common problem in applied microeconometrics: estimating a linear causal effct when the explanatory variable of interest might be correlated with relevant unobserved variables. The main idea is to place restrictions on the correlation between the variable of interest and relevant unobserved variables relative to the correlation between the variable of interest and observed control variables. These relative correlation restrictions allow a researcher to construct informative bounds on parameter estimates, and to assess the sensitivity of conventional estimates to plausible deviations from the identifying assumptions. The estimation method and its properties are described, and two empirical applications are demonstrated.

Suggested Citation

  • Brian Krauth, 2011. "Bounding a linear causal effect using relative correlation restrictions," Discussion Papers dp11-02, Department of Economics, Simon Fraser University.
    • Handle: RePEc:sfu:sfudps:dp11-02
    as

    Download full text from publisher

    File URL: http://www.sfu.ca/econ-research/RePEc/sfu/sfudps/dp11-02.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:taf:jnlbes:v:30:y:2012:i:1:p:67-80 is not listed on IDEAS
    2. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 497-532.
    3. Arthur Lewbel, 2010. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80, December.
    4. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    5. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    6. Jennifer M. Mellor & Jeffrey Milyo, 2002. "Income Inequality and Health Status in the United States: Evidence from the Current Population Survey," Journal of Human Resources, University of Wisconsin Press, vol. 37(3), pages 510-539.
    7. Brent Kreider & Steven C. Hill, 2009. "Partially Identifying Treatment Effects with an Application to Covering the Uninsured," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    8. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    9. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 40(4), pages 791-821.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. E. Somanathan & Randall Bluffstone, 2015. "Biogas: Clean Energy Access with Low-Cost Mitigation of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 265-277, October.
    2. Dujardin, Claire & Goffette-Nagot, Florence, 2010. "Neighborhood effects on unemployment?: A test à la Altonji," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 380-396, November.
    3. Halkos, George E. & Paizanos, Epameinondas Α., 2013. "The effect of government expenditure on the environment:An empirical investigation," Ecological Economics, Elsevier, vol. 91(C), pages 48-56.
    4. Amin, Vikesh & Flores, Carlos A. & Flores-Lagunes, Alfonso & Parisian, Daniel J., 2016. "The effect of degree attainment on arrests: Evidence from a randomized social experiment," Economics of Education Review, Elsevier, vol. 54(C), pages 259-273.
    5. Halkos, George & Paizanos, Epameinondas, 2014. "Exploring the effect of economic growth and government expenditure on the environment," MPRA Paper 56084, University Library of Munich, Germany.
    6. Ransom, Michael R. & Ransom, Tyler, 2017. "Do High School Sports Build or Reveal Character?," IZA Discussion Papers 11110, Institute for the Study of Labor (IZA).

    More about this item

    Keywords

    sensitivity analysis; partial identification; endogeneity;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:sfu:sfudps:dp11-02. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Working Paper Coordinator). General contact details of provider: http://edirc.repec.org/data/desfuca.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.