IDEAS home Printed from https://ideas.repec.org/p/eab/develo/22445.html
   My bibliography  Save this paper

Dynamic Treatment Effect Analysis of TV Effects on Child Cognitive Development

Author

Listed:
  • Fali Huang

    (SMU)

  • Myoung-jae Lee

Abstract

We investigate whether TV watching at ages 6-7 and 8-9 affects cognitive development measured by math and reading scores at ages 8-9 using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child-specific factor, endogeneity of TV watching, and dynamic nature of the causal relation. A special emphasis is put on the last aspect where TV watching affects cognitive development which in turn affects the future TV watching. When this feedback occurs, it is not straightforward to identify and estimate the TV effect. We adopt estimation methods available in the biostatistics literature which can deal with the feedback feature; we also apply the standard econometric panel data IV approaches. Overall, for math score at ages 8-9, we find that watching TV for more than two hours per day during ages 6-9 has a negative total effect mostly due to a large negative effect of TV watching at the younger ages 6-7. For reading score, there are evidences that TV watching between 2-4 hours per day has a positive effect whereas the effect is negative outside this range. In both cases, however, the effect magnitudes are economically small.

Suggested Citation

  • Fali Huang & Myoung-jae Lee, 2007. "Dynamic Treatment Effect Analysis of TV Effects on Child Cognitive Development," Development Economics Working Papers 22445, East Asian Bureau of Economic Research.
  • Handle: RePEc:eab:develo:22445
    as

    Download full text from publisher

    File URL: http://www.eaber.org/node/22445
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Juster, F Thomas & Stafford, Frank P, 1991. "The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement," Journal of Economic Literature, American Economic Association, pages 471-522.
    2. James Heckman, 2011. "Policies to foster human capital," Educational Studies, Higher School of Economics, issue 3, pages 73-137.
    3. James R. Hines Jr. & Hilary W. Hoynes & Alan B. Krueger, 2001. "Another Look at Whether a Rising Tide Lifts All Boats," NBER Working Papers 8412, National Bureau of Economic Research, Inc.
    4. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    5. Joshua Angrist & Alan Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Working Papers 834, Princeton University, Department of Economics, Industrial Relations Section..
    6. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    7. Zavodny, Madeline, 2006. "Does watching television rot your mind? Estimates of the effect on test scores," Economics of Education Review, Elsevier, vol. 25(5), pages 565-573, October.
    8. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    9. Juster, F Thomas & Stafford, Frank P, 1991. "The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement," Journal of Economic Literature, American Economic Association, pages 471-522.
    10. Myoung-Jae Lee & Satoru Kobayashi, 2001. "Proportional treatment effects for count response panel data: effects of binary exercise on health care demand," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 411-428.
    11. Matthew Gentzkow & Jesse M. Shapiro, 2008. "Preschool Television Viewing and Adolescent Test Scores: Historical Evidence from the Coleman Study," The Quarterly Journal of Economics, Oxford University Press, vol. 123(1), pages 279-323.
    12. Michael Lechner, 2004. "Sequential Matching Estimation of Dynamic Causal Models," University of St. Gallen Department of Economics working paper series 2004 2004-06, Department of Economics, University of St. Gallen.
    13. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, pages 69-85.
    14. Matthew Gentzkow & Jesse M. Shapiro, 2006. "Does Television Rot Your Brain? New Evidence from the Coleman Study," NBER Working Papers 12021, National Bureau of Economic Research, Inc.
    15. Keane, Michael P & Wolpin, Kenneth I, 1997. "The Career Decisions of Young Men," Journal of Political Economy, University of Chicago Press, vol. 105(3), pages 473-522, June.
    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. Ruben Durante & Paolo Pinotti & Andrea Tesei, 2015. "The Political Legacy of Entertainment TV," Sciences Po publications info:hdl:2441/gjf8d7tah8a, Sciences Po.
    2. DellaVigna, Stefano & La Ferrara, Eliana, 2015. "Economic and Social Impacts of the Media," CEPR Discussion Papers 10667, C.E.P.R. Discussion Papers.
    3. Agne Suziedelyte, 2012. "Can video games affect children's cognitive and non-cognitive skills?," Discussion Papers 2012-37, School of Economics, The University of New South Wales.

    More about this item

    Keywords

    TV watching; treatment effect; panel data; dynamic model; Granger Causality;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - 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:eab:develo:22445. 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: (Shiro Armstrong). General contact details of provider: http://edirc.repec.org/data/eaberau.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 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.

    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.