Graphical models, causal inference, and econometric models

Journal of Economic Methodology

Volumn 12, Issue 1, 2005, Pages 3-34

  Spirtes, Peter ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Causal inference; Graphical models; Model search; Model testing

Indexed keywords

EID: 14644432340     PISSN: 1350178X     EISSN: None     Source Type: Journal    
DOI: 10.1080/1350178042000330887     Document Type: Article

References (24)

1. Andersson, S., Madigan, D. and Perlman, M. (1995) A characterization of Markov equivalence classes for acyclic diagrams, Technical Report 287, Department of Statistics, University of Washington.
2. Bessler, David A. and Lee, Seongpyo (2002) 'Money and prices: US data 1869-1914 (a study with directed graphs)', Empirical Economics 27: 427-46.
3. Chickering, D. (1995) 'A transformational characterization of equivalent Bayesian network structures', in Phillippe Besnard and Steve Hanks (eds) Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, CA: Morgan Kaufmann Publishers.
4. Chickering, M. (2002) 'Optimal structure identification with greedy search', Journal of Machine Learning Research 3: 507-54.
5. Demiralp, S. and Hoover, K. (2003) 'Searching for the causal structure of a vector autoregression', Oxford Bulletin of Economics and Statistics 65: 745-67.
6. Hoover, K. (2001) Causality in Macroeconomics, Cambridge, UK: Cambridge University Press.
7. Hoover, K. (2003) 'Non-stationary time series, co-integration, and the principle of the common cause', British Journal for the Philosophy of Science 54: 527-51.
8. Jordan, M. (1999) Learning Graphical Models, Cambridge, MA: MIT Press.
9. Lauritzen, S. (2001) 'Causal inference from graphical models', in O. Barnsdorff-Nielsen, D. Cox and C. Kluppenlberg (eds) Complex Stochastic Systems, pp. 63-107, London: Chapman and Hall.
10. Lauritzen, S., Dawid, A., Larsen, B. and Leimer, H. (1990) 'Independence properties of directed Markov fields', Networks 20: 491-505.
11. Meek, C. (1995) 'Causal inference and causal explanation with background knowledge', in Besnard. Philippe and Hanks. Steve (eds) Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, pp. 403-10, San Mateo, CA: Morgan Kaufmann Publishers, Inc.
12. Moneta, A. (2003) 'Graphical models for structural vector autoregressions', LEM working paper 2003/07, Sant' Anna School of Advanced Studies (Pisa).
13. Pearl, J. (1988) Probabilistic Reasoning in Intelligent Systems, San Mateo, CA: Morgan Kaufman.
14. Pearl, J. (2000) Causality: Models, Reasoning, and Inference, Cambridge: Cambridge University Press.
15. Richardson, T. (1996) 'A discovery algorithm for directed cyclic graphs', in F. Jensen and E. Horvitz (eds) Uncertainty in Artificial Intelligence: Proceedings of the Twelfth Conference, pp. 462-9, San Francisco: Morgan Kaufmann.
16. Robins, J., Schemes, R., Spirtes, P. and Wasserman, L. (2003) 'Uniform consistency in causal inference', Biometrika 90: 491-515.
17. Spirtes, P. (1995) 'Directed cyclic graphical representation of feedback models', in P. Besnard and S. Hanks (eds) Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo: Morgan Kaufmann Publishers, Inc.
18. Spirtes, P., Glymour, C. and Scheines, R. (2000) Causation, Prediction, and Search, 2nd ed, Cambridge, MA: MIT Press.
19. Spirtes, P., Meek, C., Scheines, R. and Richardson, T. (1999) 'An algorithm for causal inference in the presence of latent variables and selection bias', in C. Glymour and G. Cooper (eds) Computation, Causality, and Discovery, Menlo Park, CA: AAAI/MIT Press, pp. 211-52.
20. Strotz, R. and Wold, H. (1960) 'Recursive versus nonrecursive systems: an attempt at synthesis', Econometrica 28: 417-27.
21. Swanson, Norman R. and Granger, Clive W.J. (1997) 'Impulse response functions, based on a causal approach to residual orthogonalization in vector autoregressions', Journal of the American Statistical Association 92: 357-67.
22. Verma, T. and Pearl, J. (1990) 'Equivalence and synthesis of casual models', in P. Bonissone, M. Henrion, L. Kanal and J. Lemmer (eds) Proceedings of the Sixth Conference on Uncertainty in AI, Mountain View, CA: Association for Uncertainty in AI, Inc.
23. York, J. (1992) 'Use of the Gibbs sampler in expert systems', Artificial Intelligence 56: 115-30.
24. Yule, G. (1926) 'Why do I sometimes get nonsensical relations between time-series? A study in sampling and the nature of time series', Journal of the Royal Statistical Society 89: 1-64.