IDEAS home Printed from https://ideas.repec.org/p/ifs/cemmap/59-13.html
   My bibliography  Save this paper

High dimensional methods and inference on structural and treatment effects

Author

Listed:
  • Alexandre Belloni

    (Institute for Fiscal Studies)

  • Victor Chernozhukov

    (Institute for Fiscal Studies and MIT)

  • Christian Hansen

    (Institute for Fiscal Studies and Chicago GSB)

Abstract

The goal of many empirical papers in economics is to provide an estimate of the causal or structural effect of a change in a treatment or policy variable, such as a government intervention or a price, on another economically interesting variable, such as unemployment or amount of a product purchased. Applied economists attempting to estimate such structural effects face the problems that economically interesting quantities like government policies are rarely randomly assigned and that the available data are often high-dimensional. Failure to address either of these issues generally leads to incorrect inference about structural effects, so methodology that is appropriate for estimating and performing inference about these effects when treatment is not randomly assigned and there are many potential control variables provides a useful addition to the tools available to applied economists.

Suggested Citation

  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:59/13
    as

    Download full text from publisher

    File URL: http://www.cemmap.ac.uk/wps/cwp591313.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. John J. Donohue III & Steven D. Levitt, 2008. "Measurement Error, Legalized Abortion, and the Decline in Crime: A Response to Foote and Goetz," The Quarterly Journal of Economics, Oxford University Press, vol. 123(1), pages 425-440.
    2. Chen, Xiaohong & Pouzo, Demian, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," Journal of Econometrics, Elsevier, vol. 152(1), pages 46-60, September.
    3. Eric Gautier & Alexandre Tsybakov, 2011. "High-Dimensional Instrumental Variables Regression and Confidence Sets," Working Papers 2011-13, Center for Research in Economics and Statistics.
    4. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    5. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    6. Leeb, Hannes & Pötscher, Benedikt M., 2008. "Can One Estimate The Unconditional Distribution Of Post-Model-Selection Estimators?," Econometric Theory, Cambridge University Press, vol. 24(2), pages 338-376, April.
    7. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107016064.
    8. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.
    9. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107627314.
    10. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107016040.
    11. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107638105.
    12. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    13. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107016057.
    14. Acemoglu,Daron & Arellano,Manuel & Dekel,Eddie (ed.), 2013. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9781107674165.
    15. Christopher L. Foote & Christopher F. Goetz, 2008. "The Impact of Legalized Abortion on Crime: Comment," The Quarterly Journal of Economics, Oxford University Press, vol. 123(1), pages 407-423.
    16. Newey, Whitney K., 1997. "Convergence rates and asymptotic normality for series estimators," Journal of Econometrics, Elsevier, vol. 79(1), pages 147-168, July.
    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. Daron Acemoglu & Gino Gancia & Fabrizio Zilibotti, 2015. "Offshoring and Directed Technical Change," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(3), pages 84-122, July.
    2. Carlos A. Manzanares & Ying Jiang & Patrick Bajari, 2015. "Improving Policy Functions in High-Dimensional Dynamic Games," NBER Working Papers 21124, National Bureau of Economic Research, Inc.
    3. Antonio Romero-Medina & Matteo Triossi, 2017. "Take-it-or-leave-it contracts in many-to-many matching markets," Documentos de Trabajo 328, Centro de Economía Aplicada, Universidad de Chile.
    4. David Strömberg, 2015. "Media and Politics," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 173-205, August.
    5. Philippe Aghion & Peter Howitt & Susanne Prantl, 2015. "Patent rights, product market reforms, and innovation," Journal of Economic Growth, Springer, vol. 20(3), pages 223-262, September.
    6. Pierpaolo Battigalli & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2017. "Mixed extensions of decision problems under uncertainty," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(4), pages 827-866, April.
    7. Pierpaolo Battigalli & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2015. "Self-Confirming Equilibrium and Model Uncertainty," American Economic Review, American Economic Association, vol. 105(2), pages 646-677, February.
    8. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2012. "Niveloids and Their Extensions:Risk Measures on Small Domains," Working Papers 458, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Cao, Shutao, 2017. "Accounting for productivity growth in a small open economy: Sector-specific technological change and relative prices of trade," Working Paper Series 6203, Victoria University of Wellington, School of Economics and Finance.
    10. Massimo Marinacci, 2015. "Model Uncertainty," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1022-1100, December.
    11. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    12. Xiaohong Chen & Andres Santos, 2018. "Overidentification in Regular Models," Econometrica, Econometric Society, vol. 86(5), pages 1771-1817, September.
    13. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org.
    14. Nishanth Dikkala & Greg Lewis & Lester Mackey & Vasilis Syrgkanis, 2020. "Minimax Estimation of Conditional Moment Models," Papers 2006.07201, arXiv.org.
    15. Escanciano, Juan Carlos & Li, Wei, 2021. "Optimal Linear Instrumental Variables Approximations," Journal of Econometrics, Elsevier, vol. 221(1), pages 223-246.
    16. Yu Zhu, 2020. "Inference in nonparametric/semiparametric moment equality models with shape restrictions," Quantitative Economics, Econometric Society, vol. 11(2), pages 609-636, May.
    17. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls," Papers 1201.0224, arXiv.org, revised May 2012.
    18. Xiaohong Chen & Demian Pouzo, 2015. "Sieve Wald and QLR Inferences on Semi/Nonparametric Conditional Moment Models," Econometrica, Econometric Society, vol. 83(3), pages 1013-1079, May.
    19. Chaohua Dong & Jiti Gao & Oliver Linton, 2017. "High dimensional semiparametric moment restriction models," Monash Econometrics and Business Statistics Working Papers 17/17, Monash University, Department of Econometrics and Business Statistics.
    20. Centorrino Samuele & Feve Frederique & Florens Jean-Pierre, 2017. "Additive Nonparametric Instrumental Regressions: A Guide to Implementation," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-25, January.

    More about this item

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    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:ifs:cemmap:59/13. 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: . General contact details of provider: https://edirc.repec.org/data/cmifsuk.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 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: Emma Hyman (email available below). General contact details of provider: https://edirc.repec.org/data/cmifsuk.html .

    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.