IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v133y2006i1p1-29.html
   My bibliography  Save this article

Estimation of models with grouped and ungrouped data by means of "2SLS"

Author

Listed:
  • Dhrymes, Phoebus J.
  • Lleras-Muney, Adriana

Abstract

This paper deals with a special case of estimation with grouped data, where the dependent variable is only available for groups, whereas the endogenous regressor(s) is available at the individual level. By estimating the first stage using the available individual data, and then estimating the second stage at the aggregate level, it might be possible to gain efficiency relative to the OLS and 2SLS estimators that use only grouped data. We term this the Mixed- 2SLS estimator (M2SLS). The M2SLS estimator is consistent and asymptotically normal. We also provide a test of efficiency of M2SLS relative to OLS and 2SLS estimators.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Dhrymes, Phoebus J. & Lleras-Muney, Adriana, 2006. "Estimation of models with grouped and ungrouped data by means of "2SLS"," Journal of Econometrics, Elsevier, vol. 133(1), pages 1-29, July.
    • Handle: RePEc:eee:econom:v:133:y:2006:i:1:p:1-29
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(05)00081-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Raphael, Steven & Winter-Ember, Rudolf, 2001. "Identifying the Effect of Unemployment on Crime," Journal of Law and Economics, University of Chicago Press, vol. 44(1), pages 259-283, April.
    2. Lara Shore-Sheppard, 1996. "The Precision of Instrumental Variables Estimates With Grouped Data," Working Papers 753, Princeton University, Department of Economics, Industrial Relations Section..
    3. 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.
    4. Angrist, Joshua D., 1991. "Grouped-data estimation and testing in simple labor-supply models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 243-266, February.
    5. repec:fth:prinin:374 is not listed on IDEAS
    6. Lant Pritchett & Lawrence H. Summers, 1996. "Wealthier is Healthier," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 841-868.
    7. Feige, Edgar L & Watts, Harold W, 1972. "An Investigation of the Consequences of Partial Aggregation of Micro-Economic Data," Econometrica, Econometric Society, vol. 40(2), pages 343-360, March.
    8. Dhrymes, Phoebus J, 1973. "Restricted and Unrestricted Reduced Forms: Asymptotic Distribution and Relative Efficiency," Econometrica, Econometric Society, vol. 41(1), pages 119-134, January.
    9. Blackburn, McKinley L., 1997. "Misspecified skedastic functions in grouped-data models," Economics Letters, Elsevier, vol. 55(1), pages 1-8, August.
    10. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records: Errata," American Economic Review, American Economic Association, vol. 80(5), pages 1284-1286, December.
    11. Lara D. Shore-Sheppard, 1996. "The Precision of Instrumental Variables Estimates With Grouped Data," Working Papers 753, Princeton University, Department of Economics, Industrial Relations Section..
    12. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
    13. So Im, Kyung, 1998. "Efficient estimation with grouped data," Economics Letters, Elsevier, vol. 59(2), pages 169-174, May.
    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. Fu, Shihe & Viard, V. Brian & Zhang, Peng, 2022. "Trans-boundary air pollution spillovers: Physical transport and economic costs by distance," Journal of Development Economics, Elsevier, vol. 155(C).
    2. Mick Silver, 2009. "The Hedonic Country Product Dummy Method and Quality Adjustments for Purchasing Power Parity Calculations," IMF Working Papers 2009/271, International Monetary Fund.
    3. Matilde Giaccherini & Joanna Kopinska & Gabriele Rovigatti, 2022. "Vax Populi: The Social Costs of Online Vaccine Skepticism," CESifo Working Paper Series 10184, CESifo.
    4. Fu, Shihe & Viard, Brian & Zhang, Peng, 2017. "Air Quality and Manufacturing Firm Productivity: Comprehensive Evidence from China," MPRA Paper 78914, University Library of Munich, Germany.
    5. Lee, Chien-Chiang & Wang, Chih-Wei & Ho, Shan-Ju, 2022. "The dimension of green economy: Culture viewpoint," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 122-138.
    6. Peter Z. Schochet, 2020. "Analyzing Grouped Administrative Data for RCTs Using Design-Based Methods," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 32-57, February.
    7. Massa, Massimo & Žaldokas, Alminas, 2014. "Investor base and corporate borrowing: Evidence from international bonds," Journal of International Economics, Elsevier, vol. 92(1), pages 95-110.

    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. repec:pri:cheawb:adriana_estimationofmodels is not listed on IDEAS
    2. Florence Kondylis & Valerie Mueller, 2014. "Economic consequences of conflict and environmental displacement," Chapters, in: Robert E.B. Lucas (ed.), International Handbook on Migration and Economic Development, chapter 14, pages 388-424, Edward Elgar Publishing.
    3. Paul A. Bekker & Jan van der Ploeg, 2000. "Instrumental Variable Estimation Based on Grouped Data," Econometric Society World Congress 2000 Contributed Papers 1862, Econometric Society.
    4. 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.
    5. Cornelissen, Thomas & Dustmann, Christian & Raute, Anna & Schönberg, Uta, 2016. "From LATE to MTE: Alternative methods for the evaluation of policy interventions," Labour Economics, Elsevier, vol. 41(C), pages 47-60.
    6. de Walque, Damien, 2007. "Does education affect smoking behaviors?: Evidence using the Vietnam draft as an instrument for college education," Journal of Health Economics, Elsevier, vol. 26(5), pages 877-895, September.
    7. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 278-287, July.
    8. Peter Siminski & Simon Ville & Alexander Paull, 2013. "Does the Military Train Men to be Violent Criminals? New Evidence from Australia’s Conscription Lotteries," Economics Working Papers wp13-01, School of Economics, University of Wollongong, NSW, Australia.
    9. Deborah A. Cobb‐Clark & Thomas Crossley, 2003. "Econometrics for Evaluations: An Introduction to Recent Developments," The Economic Record, The Economic Society of Australia, vol. 79(247), pages 491-511, December.
    10. Courtney C. Coile & Mark G. Duggan, 2019. "When Labor's Lost: Health, Family Life, Incarceration, and Education in a Time of Declining Economic Opportunity for Low-Skilled Men," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 191-210, Spring.
    11. de Walque, Damien, 2004. "Education, information, and smoking decisions : evidence from smoking histories, 1940-2000," Policy Research Working Paper Series 3362, The World Bank.
    12. Adrien Montalbo, 2020. "Industrial activities and primary schooling in early nineteenth-century France," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 14(2), pages 325-365, May.
    13. John Bound & Sarah Turner, 2002. "Going to War and Going to College: Did World War II and the G.I. Bill Increase Educational Attainment for Returning Veterans?," Journal of Labor Economics, University of Chicago Press, vol. 20(4), pages 784-815, October.
    14. Adrien Montalbo, 2018. "Industrial activities and primary schooling in early nineteenth-century France," Working Papers halshs-01826346, HAL.
    15. A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 318, University of California, Davis, Department of Economics.
    16. Montalbo, Adrien, 2021. "Schools without a law: Primary education in France from the Revolution to the Guizot Law," Explorations in Economic History, Elsevier, vol. 79(C).
    17. Peter Siminski & Simon Ville & Alexander Paull, 2016. "Does the military turn men into criminals? New evidence from Australia’s conscription lotteries," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(1), pages 197-218, January.
    18. Adrien Montalbo, 2019. "Education and economic development. The influence of primary schooling on municipalities in nineteenth-century France," PSE Working Papers halshs-02286126, HAL.
    19. Adrien Montalbo, 2022. "Primary education and economic growth in nineteenth-century France," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 16(2), pages 277-332, May.
    20. Raphael, Steven & Rice, Lorien, 2002. "Car ownership, employment, and earnings," Journal of Urban Economics, Elsevier, vol. 52(1), pages 109-130, July.
    21. William Bentley MacLeod & Daniel Parent, 1998. "Job Characteristics and the Form of Compensation," CIRANO Working Papers 98s-08, CIRANO.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

    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:eee:econom:v:133:y:2006:i:1:p:1-29. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.