Causal Relations via Econometrics

Year 2010, Volume: 2 Issue: 1, 36 - 56, 01.04.2010

Asad Zaman

Abstract

Applied econometric work takes a superficial approach to causality. Understanding economic affairs, making good policy decisions, and progress in the economic discipline depend on our ability to infer causal relations from data. We review the dominant approaches to causality in econometrics, and suggest why they fail to give good results. We feel the problem cannot be solved by traditional tools, and requires some out-of-the-box thinking. Potentially promising approaches to solutions are discussed.

Keywords

Causality, Regression, Exogeneity, Hendry Methodology, Natural Experiments

References

• Aldrich, J. (1989). Autonomy. Oxford Economic Papers New Series, 41(1), 15-34.
• Andrabi, T., D. Jishnu, A.I. Khwaja, T. Vishwanath and T. Zajonc (2007). PAKISTAN Learning and Educational Achievements in Punjab Schools (LEAPS): Insights to Inform the education policy debate. World Bank. http://go.worldbank.org/YUFOT05SA0 (accessed February 28, 2010).
• Angrist, J.D. and B. Krueger Alan (2001). Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments. Journal of Economic Perspectives, 15(4), 69-85.
• Ashley, R. (1998). A New Technique for Postsample Model Selection and Validation. Journal of Economic Dynamics and Control, 22, 647-65.
• Baba, Y., D.F. Hendry and R.M. Starr (1992). The Demand for M1 in the U.S.A., 1960-1988. Review of Economic Studies, 59, 25-61.
• Banerjee, A.V. and E. Duflo (2003). Inequality and Growth: What Can the Data Say? Journal of Economic Growth, 8(3), 267-299.
• Banerjee, A.V. and E. Duflo (2004). Growth Theory through the Lens of Development Economics. MIT Department of Economics Working Paper No. 05-01.
• Banerjee, A.V. and E. Duflo (2007). The Economic Lives of the Poor. Journal of Economic Perspectives, 21(1), 141-167.
• Barro, R.J. (1997). Determinants of Economic Growth: A Cross-Country Empirical Study. MIT Press, Cambridge, MA.
• Barberis, N. and R.H. Thaler (2002). A Survey of Behavioral Finance. NBER Working Paper No. W9222. http://ssrn.com/abstract=332266 (accessed February 28, 2010).
• Blaug, M. (1998). Disturbing Currents in Modern Economics. Challenge. May-June 1998.
• Bolch, B. (1998). Is Macroeconomics Believable? The Independent Review, 2(4) Spring.
• Burtless, G. (1995), The Case for Randomized Field Trials in Economic and Policy Research. The Journal of Economic Perspectives, 9(2), 63-84.
• Darnell, A.C. and J.L. Evans (1991). The Limits of Econometrics. Edward Elgar Publishers, Cheltenham, U.K.
• Engle, R.F., D.F. Hendry and J.F. Richard (1983). Exogeneity. Econometrica, 51(2), 77-304.
• Falk, A. and E. Fehr (2003). Why labour market experiments? Labour Economics, 10(4), 399-406.
• Faust, J. and C.H. Whiteman, 1997, General-to-specific procedures fitting a data-admissible, theory-inspired, congruent, parsimonious, encompassing, weakly-exogenous, identified, structural model to the DGP: A translation and critique. In Carnegie-Rochester Conference Series on Public Policy, North-Holland, Amsterdam, 47, 121-161.
• Freedman, D.A. (2008), On types of scientific enquiry: Nine success stories in medical research. In The Oxford Handbook of Political Methodology, ed. Janet M. Box- Steffensmeier, Henry E. Brady and David Collier. Oxford University Press, Oxford. http://www.stat.berkeley.edu/~census/anomaly.pdf (accessed February 28, 2010).
• Freedman, D.A., R. Pisani and R. Purves (2007). Statistics. Norton, New York.
• Freedman, D.A. (2005). Statistical Models: Theory and Practice. Cambridge University Press, Cambridge, MA.
• Freedman, D. A. (2004). On specifying graphical models for causation and the identification problem. Evaluation Review, 26, 267-93. Reprinted in Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, ed. D.W.K. Andrews and J.H. Stock, Cambridge University Press (2005), 56-79. http://www.stat.berkeley.edu/ ~census/rothsag.pdf (accessed February 28, 2010).
• Freedman, D.A. (1997). From Association to Causation via Regression. In Causality in Crisis? ed. V. McKim and S. Turner. University of Notre Dame Press, South Bend, (with discussion) 113-82. Reprinted in Advances in Applied Mathematics, 18, 59-110.
• Freedman, D.A. (1991). Statistical Models and Shoe Leather. Sociological Methodology, 21, 291-313.
• Gregorian, V. (1993). Technology, Scholarship, and the Humanities: The Implications of Electronic Information. http://www.cni.org/docs/tsh/Keynote.html (accessed February 28, 2010).
• Heckman, J.J., R.J. LaLonde and J.A. Smith (1999). The Economics and Econometrics of Active Labor Market Programs. In Handbook of Labor Economics, ed. O. Ashenfelter, D. Card. Elsevier Science, New York, NY, 3, 1865-2097.
• Hendry, D. F. (1995). Dynamic Econometrics. Oxford University Press, Oxford.
• Hendry, D.F. (1993). The Roles of Economic Theory and Econometrics in Time-Series Economics. In European Econometric Society, Invited address, Stockholm.
• Hendry, D.F. (2000). Econometrics: Alchemy or Science? Essays in Econometric Methodology. Oxford University Press, Oxford.
• Hendry, D.F. and N.R. Ericsson (1991). An econometric analysis of UK money demand in `Monetary Trends in the United States and the United Kingdom by Milton Friedman and Anna J. Schwartz‟. American Economic Review, 81, 8-38.
• Hey, J. (1997). The Economic Journal: Report of the Managing Editor. Royal Economic Society Newsletter, January, 3-5.
• Hoover, Kevin D. (2001). Causality in Macroeconomics. Cambridge University Press, Cambridge.
• Hoover, Kevin D. (2004). Lost Causes. Journal of the History of Economic Thought, 26(2), 149-164.
• Hoover, Kevin D. (2006). Causality in Economics and Econometrics. SSRN: http://ssrn.com/abstract=930739 (accessed April 17, 2010).
• Jensen, D. (2000). Data Snooping, Dredging and Fishing: The Dark Side of Data Mining, A SIGKDD99 Panel Report. SIGKDD Explorations, 1(2), 52-54.
• Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review, 93(5), 1449-1475.
• Keuzenkamp, H.A. (2000). Probability, Econometrics and Truth: The Methodology of Econometrics. Cambridge University Press, Cambridge.
• Leamer, E. (1978). Specification Searches: Ad Hoc Inference with Non Experimental Data. John Wiley and Sons Inc., New York.
• Leamer, E. (1983). Let's Take the Con Out of Econometrics. American Economic Review, 73, 31
• Lynn, R. and T. Vanhanen (2002). IQ and the Wealth of Nations. Praeger, Westport CT.
• Magnus, J.R. (1999). The success of econometrics. De Economist, 147(1), 50-58.
• Pearl, Judea (2000). Causality. Cambridge University Press, New York.
• Phelps, E. (1999). Seven Schools of Macroeconomics Thought. Cambridge University Press, Cambridge.
• Reuben, J. (1996). The Making of the Modern University: Intellectual Transformation and the Marginalization of Morality. University of Chicago Press, Chicago.
• Rodríguez, F. and D. Rodrik (2001). Trade Policy and Economic Growth: A Skeptic's Guide to the Cross-National Evidence. In Macroeconomics Annual 2000, ed. Ben Bernanke and Kenneth S. Rogoff. MIT Press for NBER, Cambridge, MA.
• Rodrik, D. (2005). Why We Learn Nothing from Regressing Economic Growth on Policies, Harvard University Discussion Paper.
• Rossman, A.J. (1994). Televisions, Physicians, and Life Expectancy. Journal of Statistics Education, (accessed February 28, 2010).
• http://www.amstat.org/publications/jse/v2n2/datasets.rossman.html
• Sims, C.A. (1980). Macroeconomics and Reality. Econometrica, 48, 1-48.
• Thomas, R.L. (1993). Introductory Econometrics: Theory and Applications. Second edition, Longman, New York.
• Volken, T. (2003). IQ and the Wealth of Nations. A Critique of Richard Lynn and Tatu Vanhanen's Recent Book. European Sociological Review, 19(4), 411-412.
• Zahid A. (2007). Investigation of Granger Causality, Ph.D. Thesis, Quaid-e-Azam University, Islamabad, Pakistan.