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Bounding a linear causal effect using relative correlation restrictions

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.

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File URL: http://www.sfu.ca/econ-research/RePEc/sfu/sfudps/dp11-02.pdf
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Paper provided by Department of Economics, Simon Fraser University in its series Discussion Papers with number dp11-02.

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Length: 43
Date of creation: Aug 2011
Handle: RePEc:sfu:sfudps:dp11-02
Contact details of provider: Postal:
Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada

Phone: (778)782-3508
Fax: (778)782-5944
Web page: http://www.sfu.ca/economics.html

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Order Information: Postal: Working Paper Coordinator, Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
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Keywords: sensitivity analysis; partial identification; endogeneity;

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Find related papers by 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

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  1. repec:taf:jnlbes:v:30:y:2012:i:1:p:67-80 is not listed on IDEAS
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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).
  7. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, 07.
  8. 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.
  9. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 497-532.
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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.

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