IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v7y2007i4p507-541.html
   My bibliography  Save this article

Causal inference with observational data

Author

Listed:
  • Austin Nichols

    (Urban Institute)

Abstract

Problems with inferring causal relationships from nonexperimental data are briefly reviewed, and four broad classes of methods designed to allow estimation of and inference about causal parameters are described: panel regression, matching or reweighting, instrumental variables, and regression discontinuity. Practical examples are offered, and discussion focuses on checking required assumptions to the extent possible. Copyright 2007 by StataCorp LP.

Suggested Citation

  • Austin Nichols, 2007. "Causal inference with observational data," Stata Journal, StataCorp LP, vol. 7(4), pages 507-541, December.
    • Handle: RePEc:tsj:stataj:v:7:y:2007:i:4:p:507-541
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0136
    Download Restriction: no
    File URL: http://www.stata-journal.com/software/sj7-4/st0136/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sandra E. Black, 1999. "Do Better Schools Matter? Parental Valuation of Elementary Education," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 577-599.
    2. Roberto G. Gutierrez & Jean Marie Linhart & Jeffrey S. Pitblado, 2003. "From the help desk: Local polynomial regression and Stata plugins," Stata Journal, StataCorp LP, vol. 3(4), pages 412-419, December.
    3. Steven Glazerman & Dan M. Levy & David Myers, 2003. "Nonexperimental Versus Experimental Estimates of Earnings Impacts," The ANNALS of the American Academy of Political and Social Science, , vol. 589(1), pages 63-93, September.
    4. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    5. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    6. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    7. Jens Ludwig & Douglas L. Miller, 2007. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 159-208.
    8. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    9. Doug Miller & Jens Ludwig, 2005. "Does Head Start Improve Children?s Life Chances? Evidence from a Regression Discontinuity Design," Working Papers 54, University of California, Davis, Department of Economics.
    10. Murray Leibbrandt & James Levinsohn & Justin McCrary, 2005. "Incomes in South Africa Since the Fall of Apartheid," NBER Working Papers 11384, National Bureau of Economic Research, Inc.
    11. Joao Pedro Azevedo, 2005. "DFL: Stata module to estimate DiNardo, Fortin and Lemieux Counterfactual Kernel Density," Statistical Software Components S449001, Boston College Department of Economics, revised 21 Dec 2010.
    12. John DiNardo & David S. Lee, 2002. "The Impact of Unionization on Establishment Closure: A Regression Discontinuity Analysis of Representation Elections," NBER Working Papers 8993, National Bureau of Economic Research, Inc.
    13. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    14. Baker, Michael & Benjamin, Dwayne & Stanger, Shuchita, 1999. "The Highs and Lows of the Minimum Wage Effect: A Time-Series Cross-Section Study of the Canadian Law," Journal of Labor Economics, University of Chicago Press, vol. 17(2), pages 318-350, April.
    15. James W. Hardin & Henrik Schmeidiche & Raymond J. Carroll, 2003. "Instrumental variables, bootstrapping, and generalized linear models," Stata Journal, StataCorp LP, vol. 3(4), pages 351-360, December.
    16. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    17. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    18. Doug Miller & Jens Ludwig, 2005. "Does Head Start Improve Children?s Life Chances? Evidence from a Regression Discontinuity Design," Working Papers 534, University of California, Davis, Department of Economics.
    19. Hall, Alastair R & Rudebusch, Glenn D & Wilcox, David W, 1996. "Judging Instrument Relevance in Instrumental Variables Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(2), pages 283-298, May.
    20. Brian P. Poi, 2006. "Jackknife instrumental variables estimation in Stata," Stata Journal, StataCorp LP, vol. 6(3), pages 364-376, September.
    21. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2005. "Rising Wage Inequality: The Role of Composition and Prices," Harvard Institute of Economic Research Working Papers 2096, Harvard - Institute of Economic Research.
    22. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    23. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    24. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    25. Jesse Rothstein, 2007. "Do Value-Added Models Add Value? Tracking, Fixed Effects, and Causal Inference," Working Papers 1036, Princeton University, Department of Economics, Center for Economic Policy Studies..
    26. Austin Nichols, 2006. "Weak Instruments: An Overview and New Techniques," North American Stata Users' Group Meetings 2006 3, Stata Users Group.
    27. Jesse Rothstein, 2007. "Do Value-Added Models Add Value? Tracking, Fixed Effects, and Causal Inference," Working Papers 1036, Princeton University, Department of Economics, Center for Economic Policy Studies..
    28. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    29. David S. Lee, 2001. "The Electoral Advantage to Incumbency and Voters' Valuation of Politicians' Experience: A Regression Discontinuity Analysis of Elections to the U.S..," NBER Working Papers 8441, National Bureau of Economic Research, Inc.
    30. Anna Mikusheva & Brian P. Poi, 2006. "Tests and confidence sets with correct size when instruments are potentially weak," Stata Journal, StataCorp LP, vol. 6(3), pages 335-347, September.
    31. Justin McCrary, 2007. "Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test," NBER Technical Working Papers 0334, National Bureau of Economic Research, Inc.
    32. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    33. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
    34. repec:mpr:mprres:3694 is not listed on IDEAS
    35. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    2. Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
    3. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    4. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    5. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    6. Abbott, Joshua K. & Klaiber, H. Allen, 2011. "The Value Of Water As An Urban Club Good: A Matching Approach To Hoa-Provided Lakes," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103781, Agricultural and Applied Economics Association.
    7. Roberto ESPOSTI, 2014. "To match, not to match, how to match: Estimating the farm-level impact of the CAP-first pillar reform (or: How to Apply Treatment-Effect Econometrics when the Real World is;a Mess)," Working Papers 403, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    8. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    9. Uematsu, Hiroki & Mishra, Ashok K., 2012. "Organic farmers or conventional farmers: Where's the money?," Ecological Economics, Elsevier, vol. 78(C), pages 55-62.
    10. Marinho Bertanha & Guido W. Imbens, 2020. "External Validity in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 593-612, July.
    11. Esposti, Roberto, 2015. "To match, not to matchm how to match: Estimating the farm-level impact of the 2005 CAP-first pillar reform," 2015 Conference, August 9-14, 2015, Milan, Italy 211625, International Association of Agricultural Economists.
    12. Olivier Dagnelie & Philippe Lemay‐Boucher, 2012. "Rosca Participation in Benin: A Commitment Issue," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 235-252, April.
    13. Martin Binder & Alex Coad, 2013. "Life satisfaction and self-employment: a matching approach," Small Business Economics, Springer, vol. 40(4), pages 1009-1033, May.
    14. Hill, Ruth Vargas & Viceisza, Angelino, 2010. "An experiment on the impact of weather shocks and insurance on risky investment," IFPRI discussion papers 974, International Food Policy Research Institute (IFPRI).
    15. Subervie, Julie & Vagneron, Isabelle, 2013. "A Drop of Water in the Indian Ocean? The Impact of GlobalGap Certification on Lychee Farmers in Madagascar," World Development, Elsevier, vol. 50(C), pages 57-73.
    16. Chiang, Hanley, 2009. "How accountability pressure on failing schools affects student achievement," Journal of Public Economics, Elsevier, vol. 93(9-10), pages 1045-1057, October.
    17. Bruno Arpino & Arnstein Aassve, 2013. "Estimating the causal effect of fertility on economic wellbeing: data requirements, identifying assumptions and estimation methods," Empirical Economics, Springer, vol. 44(1), pages 355-385, February.
    18. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    19. Zeqin Liu & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201904, University of Kansas, Department of Economics, revised Mar 2019.
    20. Bronfman, Javier & Floro, Maria, 2014. "How well has the Social Protection Scheme Reduced Vulnerability in Chile?," MPRA Paper 63255, University Library of Munich, Germany.

    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:tsj:stataj:v:7:y:2007:i:4:p:507-541. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.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.