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Does the IV estimator establish causality? Re-examining Chinese fertility-growth relationship

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  • Tilak Abeysinghe

    ()
    (Department of Economics, National University of Singapore)

  • Jiaying Gu

    (Department of Economics, National University of Singapore)

Abstract

The instrumental variable (IV) estimator in a cross-sectional or panel regression model is often taken to provide valid causal inference from contemporaneous correlations. In this exercise we point out that the IV estimator, like the OLS estimator, cannot be used effectively for causal inference without the aid of non-sample information. We present three possible cases (lack of identification, accounting identities, and temporal aggregation) where IV estimates could lead to misleading causal inference. In other words, a non-zero IV estimate does not necessarily indicate a causal effect nor does the causal direction. In this light, we re-examine the relationship between Chinese provincial birth rates and economic growth. This exercise highlights the potential pitfalls of using too much temporal averaging to compile the data for cross sectional and panel regressions and the importance of estimating both (x on y and y on x) regressions to avoid misleading causal inferences. The GMM-SYS results from dynamic panel regressions based on five-year averages show a strong negative relationship running both ways, from births to growth and growth to births. This outcome, however, changes to a more meaningful one-way relationship from births to growth if the panel analysis is carried out with the annual data. Although falling birth rates in China have enhanced the country’s growth performance, it is difficult to attribute this effect solely to the one-child policy implemented after 1978.

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Bibliographic Info

Paper provided by National University of Singapore, Department of Economics, SCAPE in its series SCAPE Policy Research Working Paper Series with number 0902.

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Length: 18 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:sca:scaewp:0902

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Web page: http://www.fas.nus.edu.sg/ecs/scape/index.html
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Keywords: IV estimator and causality inference; identification; accounting identities; temporal aggregation; spurious causality; Chinese provincial growth and fertility relationship.;

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  1. Judith A. Giles & Cara L. Williams, 2000. "Export-Led Growth: A Survey of the Empirical Literature and Some Noncausality Results, Part 2," Econometrics Working Papers 0002, Department of Economics, University of Victoria.
  2. Abeysinghe, Tilak, 1993. "Time Cost, Relative Income and Fertility in Canada," Journal of Population Economics, Springer, vol. 6(2), pages 189-98, May.
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  7. Sergio Urzua & James J. Heckman, 2009. "Comparing IV with Structural Models: What Simple IV Can and Cannot Identify," Working Papers 200906, Geary Institute, University College Dublin.
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  10. Beck, T.H.L. & Levine, R. & Loayza, N., 2000. "Financial intermediation and growth: Causality and causes," Open Access publications from Tilburg University urn:nbn:nl:ui:12-3125519, Tilburg University.
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  13. Guido W. Imbens, 2010. "Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 399-423, June.
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