IDEAS home Printed from https://ideas.repec.org/p/van/wpaper/1111.html

Examining the Distributional Effects of Military Service on Earnings: A Test of Initial Dominance

Author

Listed:
  • Christopher J. Bennett

    (Department of Economics, Vanderbilt University)

  • Ricardas Zitikis

    (Department of Statistical and Actuarial Sciences, University of Western Ontario)

Abstract

Existing empirical evidence suggests that the effects of Vietnam veteran status on earnings in the decade-and-a-half following service may be concentrated in the lower tail of the earnings distribution. Motivated by this evidence, we develop a formal statistical procedure which is specifically designed to test for lower tail dominance in the distributions of earnings. When applied to the same data as in previous studies, the test reveals that the distribution of earnings for veterans is indeed dominated by the distribution of earnings for non-veterans up to $12,610 (in 1978 dollars), thereby indicating that there was higher social welfare and lower poverty experienced by non-veterans in the decade-and-a-half following military service.

Suggested Citation

  • Christopher J. Bennett & Ricardas Zitikis, 2011. "Examining the Distributional Effects of Military Service on Earnings: A Test of Initial Dominance," Vanderbilt University Department of Economics Working Papers 1111, Vanderbilt University Department of Economics.
    • Handle: RePEc:van:wpaper:1111
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/VUECON/vu11-w11.pdf
    File Function: First version, September 2011
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, March.
    2. Joshua D. Angrist & Alan B. Krueger, 1991. "Estimating the Payoff to Schooling Using the Vietnam-era Draft Lottery," Working Papers 670, Princeton University, Department of Economics, Industrial Relations Section..
    3. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6a.
    4. Saraswata Chaudhuri & Elaina Rose, 2009. "Estimating the Veteran Effect with Endogenous Schooling when Instruments are Potentially Weak," Working Papers UWEC-2009-07, University of Washington, Department of Economics.
    5. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records," American Economic Review, American Economic Association, vol. 80(3), pages 313-336, June.
    6. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    7. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6b.
    8. Angrist, Joshua & Chen, Stacey H., 2008. "Long-Term Economic Consequences of Vietnam-Era Conscription: Schooling, Experience and Earnings," IZA Discussion Papers 3628, Institute of Labor Economics (IZA).
    9. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    10. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 70, Elsevier.
    11. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    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. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
    2. Eva Deuchert & Martin Huber, 2017. "A Cautionary Tale About Control Variables in IV Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(3), pages 411-425, June.
    3. Andrew M. Jones, 2007. "Identification of treatment effects in Health Economics," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1127-1131.
    4. Heckman, James & Pinto, Rodrigo, 2024. "Econometric causality: The central role of thought experiments," Journal of Econometrics, Elsevier, vol. 243(1).
    5. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    6. Berg, Gerard J. van den & Bonev, Petyo & Mammen, Enno, 2016. "Nonparametric instrumental variable methods for dynamic treatment evaluation," Working Papers 16-02, University of Mannheim, Department of Economics.
    7. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
    8. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "ddml: Double/debiased machine learning in Stata," Stata Journal, StataCorp LLC, vol. 24(1), pages 3-45, March.
    9. 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.
    10. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    11. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    12. Matthew A. Kraft, 2014. "How to Make Additional Time Matter: Integrating Individualized Tutorials into an Extended Day," Education Finance and Policy, MIT Press, vol. 10(1), pages 81-116, November.
    13. H. Evans & A. Basu, 2011. "Exploring comparative effect heterogeneity with instrumental variables: prehospital intubation and mortality," Health, Econometrics and Data Group (HEDG) Working Papers 11/26, HEDG, c/o Department of Economics, University of York.
    14. Peter Howard-Jones & Jens Hölscher & Dragana Radicic, 2017. "Firm Productivity In The Western Balkans: The Impact Of European Union Membership And Access To Finance," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 62(215), pages 7-52, October –.
    15. Imbens, Guido W., 2014. "Instrumental Variables: An Econometrician's Perspective," IZA Discussion Papers 8048, Institute of Labor Economics (IZA).
    16. Francesco Agostinelli & Emilio Borghesan & Giuseppe Sorrenti, 2020. "Welfare, Workfare and Labor Supply: A Unified Evaluation," Working Papers 2020-083, Human Capital and Economic Opportunity Working Group.
    17. David M. Kaplan, 2019. "Interpreting Unconditional Quantile Regression with Conditional Independence," Working Papers 1912, Department of Economics, University of Missouri, revised 08 Nov 2020.
    18. Michel Mouchart & Renzo Orsi, 2016. "Building a Structural Model: Parameterization and Structurality," Econometrics, MDPI, vol. 4(2), pages 1-16, April.
    19. Guido W. Imbens, 2015. "Matching Methods in Practice: Three Examples," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 373-419.
    20. Nikhil Agarwal & Eric Budish, 2021. "Market Design," NBER Working Papers 29367, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    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:van:wpaper:1111. 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: John P. Conley (email available below). General contact details of provider: http://www.vanderbilt.edu/econ/wparchive/index.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.