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

  • Tilak Abeysinghe

    (Singapore Centre for Applied and Policy Economics)

  • Gu Jiaying

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 countrys growth performance, it is difficult to attribute this effect solely to the one-child policy implemented after 1978.

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File URL: http://www.eaber.org/node/22758
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Paper provided by East Asian Bureau of Economic Research in its series Microeconomics Working Papers with number 22758.

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Date of creation: Jan 2009
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Handle: RePEc:eab:microe:22758
Contact details of provider: Postal: JG Crawford Building #13, Asia Pacific School of Economics and Government, Australian National University, ACT 0200
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  1. 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.
  2. Feder, Gershon, 1983. "On exports and economic growth," Journal of Development Economics, Elsevier, vol. 12(1-2), pages 59-73.
  3. Joshua Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," NBER Working Papers 8456, National Bureau of Economic Research, Inc.
  4. Judith A. Giles & Cara L. Williams, 2000. "Export-Led Growth: A Survey of the Empirical Literature and Some Noncausality Results, Part 1," Econometrics Working Papers 0001, Department of Economics, University of Victoria.
  5. repec:ner:tilbur:urn:nbn:nl:ui:12-3125519 is not listed on IDEAS
  6. Steve Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Guido W. Imbens, 2009. "Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)," NBER Working Papers 14896, National Bureau of Economic Research, Inc.
  8. Richard A. Easterlin, 1980. "Population and Economic Change in Developing Countries," NBER Books, National Bureau of Economic Research, Inc, number east80-1.
  9. Abeysinghe, Tilak, 1993. "Time Cost, Relative Income and Fertility in Canada," Journal of Population Economics, Springer, vol. 6(2), pages 189-98, May.
  10. Rajaguru, Gulasekaran & Abeysinghe, Tilak, 2008. "Temporal aggregation, cointegration and causality inference," Economics Letters, Elsevier, vol. 101(3), pages 223-226, December.
  11. 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.
  12. Rajaguru GULASEKARAN & Tilak ABEYSINGHE, 2002. "The Distortionary Effects Of Temporal Aggregation On Granger Causality," Departmental Working Papers wp0204, National University of Singapore, Department of Economics.
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