IDEAS home Printed from https://ideas.repec.org/p/boc/bocoec/816.html
   My bibliography  Save this paper

Identification of Average Random Coefficients under Magnitude and Sign Restrictions on Confounding

Author

Listed:
  • Karim Chalak

    (Boston College)

Abstract

This paper studies measuring the average effects of X on Y in a structural system with random coefficients and confounding. We do not require (conditionally) exogenous regressors or instruments. Using proxies W for the confounders U, we ask how do the average direct effects of U on Y compare in magnitude and sign to those of U on W. Exogeneity and equi- or proportional confounding are limit cases yielding full identification. Alternatively, the elements of beta-hat are partially identified in a sharp bounded interval if W is sufficiently sensitive to U, and sharp upper or lower bounds may obtain otherwise. We extend this analysis to accommodate conditioning on covariates and a semiparametric separable specification as well as a panel structure and proxies included in the Y equation. After studying estimation and inference, we apply this method to study the financial return to education and the black-white wage gap.

Suggested Citation

  • Karim Chalak, 2012. "Identification of Average Random Coefficients under Magnitude and Sign Restrictions on Confounding," Boston College Working Papers in Economics 816, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:816
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/EC-P/wp816.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James Heckman & Edward Vytlacil, 1998. "Instrumental Variables Methods for the Correlated Random Coefficient Model: Estimating the Average Rate of Return to Schooling When the Return is Correlated with Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 974-987.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    4. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    5. Peter Arcidiacono & Patrick Bayer & Aurel Hizmo, 2010. "Beyond Signaling and Human Capital: Education and the Revelation of Ability," American Economic Journal: Applied Economics, American Economic Association, vol. 2(4), pages 76-104, October.
    6. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    7. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    8. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, vol. 56(2), pages 129-133, October.
    9. Victor Chernozhukov & Roberto Rigobon & Thomas M. Stoker, 2010. "Set identification and sensitivity analysis with Tobin regressors," Quantitative Economics, Econometric Society, vol. 1(2), pages 255-277, November.
    10. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    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. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.

    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. Thomas Lemieux, 2014. "Occupations, fields of study and returns to education," Canadian Journal of Economics, Canadian Economics Association, vol. 47(4), pages 1047-1077, November.
    2. Khan, Bilal Muhammad, 2019. "Education Occupation Mismatch in Developing countries," MPRA Paper 92324, University Library of Munich, Germany.
    3. Baris Kaymak, 2009. "Ability Bias and the Rising Education Premium in the United States: A Cohort-Based Analysis," Journal of Human Capital, University of Chicago Press, vol. 3(3), pages 224-267.
    4. Harmon, Colm & Hogan, Vincent & Walker, Ian, 2003. "Dispersion in the economic return to schooling," Labour Economics, Elsevier, vol. 10(2), pages 205-214, April.
    5. Theodore Koutmeridis, 2013. "The Market for "Rough Diamonds": Information, Finance and Wage Inequality," CDMA Working Paper Series 201307, Centre for Dynamic Macroeconomic Analysis, revised 14 Oct 2013.
    6. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
    7. Jongick Jang & Hoon Hong & Chung Sik Yoo & Jonghyun Park, 2018. "Human Capital, Positional Good, or Social Network?: Exploring a Korean Model of Education," Working papers 2018rwp-121, Yonsei University, Yonsei Economics Research Institute.
    8. James J. Heckman & John Eric Humphries & Gregory Veramendi, 2018. "Returns to Education: The Causal Effects of Education on Earnings, Health, and Smoking," Journal of Political Economy, University of Chicago Press, vol. 126(S1), pages 197-246.
    9. Stanislav Avdeev, 2020. "Zero Returns To Higher Education: Evidence From A Natural Experiment," HSE Working papers WP BRP 236/EC/2020, National Research University Higher School of Economics.
    10. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    11. Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.
    12. Bonin, Holger, 2017. "The Potential Economic Benefits of Education of Migrants in the EU," IZA Research Reports 75, Institute of Labor Economics (IZA).
    13. MacLeod, W. Bentley & Urquiola, Miguel, 2012. "Anti-Lemons: School Reputation, Relative Diversity, and Educational Quality," IZA Discussion Papers 6805, Institute of Labor Economics (IZA).
    14. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
    15. Kazi Abrar Hossain & Sharjil Muktafi Haque & A.K. Enamul Haque, 2015. "An Analysis of the Determinants of Wage and Salary Differentials in Bangladesh," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 16(2), pages 295-308, September.
    16. Paul W. Miller & Barry R. Chiswick, 2002. "Immigrant earnings: Language skills, linguistic concentrations and the business cycle," Journal of Population Economics, Springer;European Society for Population Economics, vol. 15(1), pages 31-57.
    17. Gordon Dahl, 2010. "Early teen marriage and future poverty," Demography, Springer;Population Association of America (PAA), vol. 47(3), pages 689-718, August.
    18. Emanuela di Gropello, 2006. "Meeting the Challenges of Secondary Education in Latin America and East Asia : Improving Efficiency and Resource Mobilization," World Bank Publications - Books, The World Bank Group, number 7173.
    19. Peydró, José-Luis & Jasova, Martina & Mendicino, Caterina & Panetti, Ettore & Supera, Dominik, 2021. "Monetary Policy, Labor Income Redistribution and the Credit Channel: Evidence from Matched Employer-Employee and Credit Registe," CEPR Discussion Papers 16549, C.E.P.R. Discussion Papers.
    20. Carstensen Kai & Hartmann Susanne & Gundlach Erich, 2009. "The Augmented Solow Model with Mincerian Schooling and Externalities," German Economic Review, De Gruyter, vol. 10(4), pages 448-463, December.

    More about this item

    Keywords

    causality; confounding; endogeneity; omitted variable; partial identification; proxy;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

    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:boc:bocoec:816. 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 (email available below). General contact details of provider: https://edirc.repec.org/data/debocus.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.