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Dynamic Treatment Effect Analysis of TV Effects on Child Cognitive Development

Author

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  • Fali Huang

    (School of Economics, Singapore Management University)

  • Myoung-jae Lee

    (Department of Economics, Korea University)

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 SY79. 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 t at 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," Working Papers 10-2007, Singapore Management University, School of Economics.
    • Handle: RePEc:siu:wpaper:10-2007
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    References listed on IDEAS

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    1. 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, vol. 15(4), pages 69-85, Fall.
    2. 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.
    3. Michael Lechner, 2008. "Matching estimation of dynamic treatment models: Some practical issues," Advances in Econometrics, in: Modelling and Evaluating Treatment Effects in Econometrics, pages 289-333, Emerald Group Publishing Limited.
    4. James Heckman, 2011. "Policies to foster human capital," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 3, pages 73-137.
    5. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    6. 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, vol. 29(2), pages 471-522, June.
    7. Michael Lechner, 2006. "The Relation of Different Concepts of Causality in Econometrics," University of St. Gallen Department of Economics working paper series 2006 2006-15, Department of Economics, University of St. Gallen.
    8. 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.
    9. 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.
    10. Abbring, Jaap H. & Heckman, James J., 2007. "Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72, Elsevier.
    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, President and Fellows of Harvard College, 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. 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.
    14. 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.
    15. 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..
    16. 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.
    17. 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, July.
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    Cited by:

    1. Fali Huang & Myoung‐jae Lee, 2009. "Does Television Viewing Affect Children'S Behaviour?," Pacific Economic Review, Wiley Blackwell, vol. 14(4), pages 474-501, October.
    2. Stefano DellaVigna & Eliana La Ferrara, 2015. "Economic and Social Impacts of the Media," NBER Working Papers 21360, National Bureau of Economic Research, Inc.
    3. Ruben Durante & Paolo Pinotti & Andrea Tesei, 2019. "The Political Legacy of Entertainment TV," American Economic Review, American Economic Association, vol. 109(7), pages 2497-2530, July.
    4. Elena Claudia Meroni & Daniela Piazzalunga & Chiara Pronzato, 2022. "Allocation of time and child socio-emotional skills," Review of Economics of the Household, Springer, vol. 20(4), pages 1155-1192, December.
    5. Myoung‐jae Lee & Young‐sook Kim, 2012. "Zero‐Inflated Endogenous Count In Censored Model: Effects Of Informal Family Care On Formal Health Care," Health Economics, John Wiley & Sons, Ltd., vol. 21(9), pages 1119-1133, September.
    6. Ruben Durante & Paolo Pinotti & Andrea Tesei, 2019. "The Political Legacy of Entertainment TV," American Economic Review, American Economic Association, vol. 109(7), pages 2497-2530, July.
    7. 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.
    8. repec:hal:spmain:info:hdl:2441/gjf8d7tah8ah9mq53gkdj73cq is not listed on IDEAS
    9. Elena Claudia Meroni & Daniela Piazzalunga & Chiara Pronzato, 2019. "Use of extra-school time and child behaviour," FBK-IRVAPP Working Papers 2019-02, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
    10. Ruben Durante & Paolo Pinotti & Andrea Tesei, 2019. "The Political Legacy of Entertainment TV," American Economic Review, American Economic Association, vol. 109(7), pages 2497-2530, July.

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    More about this item

    Keywords

    TV watching; treatment effect; panel data; dynamic model; Granger causality;
    All these keywords.

    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

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