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The Relation of Different Concepts of Causality in Econometrics

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Author Info
Michael Lechner ()

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Abstract

Granger and Sims non-causality (GSNC) are compared to non-causality based on concepts popular in the microeconometrics and programme evaluation literature (potential outcome non-causality, PONC). GSNC is defined as a set of restrictions on joint distributions of random variables with observable sample counterparts, whereas PONC combines restrictions on partially unobservable variables (potential outcomes) with different identifying assumptions that relate potential to observable outcomes. Based on a dynamic model of potential outcomes, we find that in general neither of the concepts implies each other without further assumptions. However, identifying assumptions of the sequential selection on observable type provide the link between those concepts, such that GSNC implies PONC, and vice versa.

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Paper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2006 with number 2006-15.

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Length: 25 pages
Date of creation: Jun 2006
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Handle: RePEc:usg:dp2006:2006-15

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Related research
Keywords: Granger causality Sims causality Rubin causality potential outcome model dynamic treatments

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Find related papers by JEL classification:
C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Lechner, Michael, 2004. "Sequential Matching Estimation of Dynamic Causal Models," IZA Discussion Papers 1042, Institute for the Study of Labor (IZA). [Downloadable!]
    Other versions:
  2. Jaap Abbring & James Heckman, 2008. "Dynamic policy analysis," CeMMAP working papers CWP05/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July. [Downloadable!] (restricted)
  4. James J. Heckman, 2000. "Causal Parameters And Policy Analysis In Economics: A Twentieth Century Retrospective," The Quarterly Journal of Economics, MIT Press, vol. 115(1), pages 45-97, February. [Downloadable!] (restricted)
    Other versions:
  5. Heckman, James J & Smith, Jeffrey, 1997. "Making the Most Out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts," Review of Economic Studies, Blackwell Publishing, vol. 64(4), pages 487-535, October. [Downloadable!] (restricted)
  6. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March. [Downloadable!] (restricted)
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  7. Michael Lechner, 2006. "Matching Estimating of Dynamic Treatment Models: Some Practical Issues," University of St. Gallen Department of Economics working paper series 2006 2006-03, Department of Economics, University of St. Gallen. [Downloadable!]
  8. Michael Lechner & Ruth Miquel, 2005. "Identification of the Effects of Dynamic Treatments by Sequential Conditional Independence Assumptions," University of St. Gallen Department of Economics working paper series 2005 2005-17, Department of Economics, University of St. Gallen. [Downloadable!]
  9. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
  10. Joshua D. Angrist & Guido M. Kuersteiner, 2004. "Semiparametric Causality Tests Using the Policy Propensity Score," NBER Working Papers 10975, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Florens, Jean-Pierre & Mouchart, Michel, 1985. "A Linear Theory for Noncausality," Econometrica, Econometric Society, vol. 53(1), pages 157-75, January. [Downloadable!] (restricted)
  12. Engle, Robert F & Hendry, David F & Richard, Jean-Francois, 1983. "Exogeneity," Econometrica, Econometric Society, vol. 51(2), pages 277-304, March. [Downloadable!] (restricted)
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  13. Dufour, Jean-Marie & Tessier, David, 1993. "On the relationship between impulse response analysis, innovation accounting and Granger causality," Economics Letters, Elsevier, vol. 42(4), pages 327-333. [Downloadable!] (restricted)
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  14. Florens, J P & Mouchart, M, 1982. "A Note on Noncausality," Econometrica, Econometric Society, vol. 50(3), pages 583-91, May. [Downloadable!] (restricted)
  15. Ruth Miquel, 2002. "Identification of Dynamic Treatment Effects by Instrumental Variables," University of St. Gallen Department of Economics working paper series 2002 2002-11, Department of Economics, University of St. Gallen. [Downloadable!]
  16. Chamberlain, Gary, 1982. "The General Equivalence of Granger and Sims Causality," Econometrica, Econometric Society, vol. 50(3), pages 569-81, May. [Downloadable!] (restricted)
  17. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-52, September. [Downloadable!] (restricted)
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