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Violating Ignorability Of Treatment By Controlling For Too Many Factors

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Author Info

  • Wooldridge, Jeffrey M.

Abstract

This problem shows how the key ignorability-of-treatment assumption used in estimating treatment effects can be violated when certain factors are included among the covariates. The case considered is when there are J + 1 treatment levels, treatment is randomized with respect to potential outcomes, but the distribution of included covariates differs across treatment levels.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 21 (2005)
Issue (Month): 05 (October)
Pages: 1026-1028

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Handle: RePEc:cup:etheor:v:21:y:2005:i:05:p:1026-1028_05

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Cited by:
  1. Gueorgui Kambourov & Iourii Manovskii & Miana Plesca, 2012. "Occupational Mobility and the Returns to Training," Working Papers tecipa-444, University of Toronto, Department of Economics.
  2. Channing Arndt & Sam Jones & Finn Tarp, 2009. "Aid and Growth: Have We Come Full Circle?," Discussion Papers 09-22, University of Copenhagen. Department of Economics.
  3. Dionissi Aliprantis, 2013. "Covariates and causal effects: the problem of context," Working Paper 1310, Federal Reserve Bank of Cleveland.
  4. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
  5. Henson, Spencer & Masakure, Oliver & Cranfield, John, 2011. "Do Fresh Produce Exporters in Sub-Saharan Africa Benefit from GlobalGAP Certification?," World Development, Elsevier, vol. 39(3), pages 375-386, March.
  6. Aliou Diagne & Steven Glover & Ben Groom & Jonathan Phillips, 2012. "Africa's Green Revolution? The determinants of the adoption of NERICAs in West Africa," Working Papers 174, Department of Economics, SOAS, University of London, UK.

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