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2015 | 2(74) |

Article title

O wartości informacyjnej testów przyczynowości w sensie Grangera

Content

Title variants

PL
On informativeness of Granger-causality tests

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Abstracts

PL
Celem artykułu jest wykazanie na podstawie przeglądu badań, że zastosowanie testów Granger-przyczynowości nie dostarcza wiarygodnych informacji o zależności pomiędzy badanymi szeregami czasowymi, jeżeli nie dysponuje się wiedzą teoretyczną na ich temat. Dotychczasowa krytyka testowania przyczynowości w sensie Grangera skupiała się przede wszystkim na wskazywaniu różnic pomiędzy tradycyjnie rozumianą przyczynowością a definicją zaproponowaną przez Grangera. Autor wykazuje, że analizowana definicja przyczynowości ma uzasadnienie filozoficzne, jednak stosowanie testów Granger-przyczynowości prowadzi do błędnych wniosków, co jest wynikiem m.in.: nieliniowości szeregów czasowych, zbyt rzadkiego próbkowania szeregów czasowych, skointegrowania zmiennych, zdeterminowania szeregów czasowych przez trzecią zmienną, istnienia zależności nieliniowej oraz racjonalnych oczekiwań podmiotów ekonomicznych. Analiza opisanych w literaturze przypadków zawodności wyników testów przyczynowości w sensie Grangera pozwala stwierdzić, że wyciągnięcie wniosków o istnieniu i kierunku zależności przyczynowej na podstawie testu Granger-przyczynowości jest możliwe tylko wtedy, gdy posiada się wiedzę o mechanizmie łączącym dwa szeregi czasowe.
EN
The purpose of this paper is to show that the application of Granger-causality tests is not informative unless one possesses additional theoretical knowledge. Previous criticism on Granger-causality testing pointed out mostly the differences between the common sense understanding of causality and Granger’s definition. The author demonstrates that Granger’s definition of causality is philosophically justified. However, the use of its tests is misleading due to: data non-linearity, too low sampling rate, time series cointegration, thirdvariable fallacy, non-linear causal dependency, and the rational expectations of economic agents. It can be said that the fallibility of Granger-causality testing described in the literature makes drawing conclusions about the existence and direction of causal relationship possible only if the researcher applying a Grangercausality test has knowledge of the mechanism connecting the two time series.

Year

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Physical description

Dates

published
2015

Contributors

References

  • Ashrafulla S., Haldar J., Joshi A., Leahy R. 2012 Canonical Granger causality applied to functional brain data, „Biomedical Imaging”, 9, IEEE International Symposium on IEEE.
  • Beebee H. 2009 Introduction, [in:] The Oxford Handbook of Causation, H. Beebee (ed.), Oxford University Press, Oxford.
  • Bressler S. L., Seth A. K. 2010 Wiener-Granger Causality: A well established methodology, „NeuroImage”, t. 58, no. 2.
  • Cartwright N. 2006 Where Is the Theory in Our „Theories” of Causality?, „The Journal of Philosophy”, t. 103, no. 2.
  • Chu T., Danks D., Glymour C. 2004 Data Driven Methods for Granger Causality and Contemporaneous Causality with Non-Linear Corrections: Climate Teleconnection Mechanisms, dokument elektroniczny, tryb dostępu: [http://www.hss.cmu.edu/philosophy/ glymour/chudanksglymour2004.pdf, data wejścia: 28.12.2013].
  • Conway R. K., Swamy P., Yanagida J. 1984 The impossibility of causality testing, „Agricultural Economics Research”, t. 36, no. 3.
  • Cooley Th., LeRoy S. 1985 Atheoretical Macroeconometrics. A Critique, „Journal of Monetary Economics”, no. 16.
  • Dufour, J. M., Taamouti A. 2010 Short and long run causality measures: Theory and inference, „Journal of Econometrics”, t. 154, no. 1.
  • Eichler M. 2007 Causal inference from time series: What can be learned from granger causality?, „Proceedings of the 13th International Congress of Logic, Methodology and Philosophy of Science”.
  • Feige E. L., McGee R. 1977 Monen Supply Control and Lagged Reverve Accounting, „Journal of Money, Credit and Banking”, t. 9, no. 4.
  • Geweke J., Meese R., Dent W. 1983 Comparing alternative tests of causality in temporal systems: Analytic results and experimental evidence, „Journal of Econometrics”, t. 21, no. 2.
  • Glasure Y. U., Lee A. R. 1998 Cointegration, error-correction and the relatioship between GDP and energy: The case of South Korea and Singapore, „Resource and Energy Economics”, t. 20, no. 1.
  • Glymour C., Sprites P. 1988 Latent Variables, Causal Models and Overidentifying Constraints, „Journal of Econometrics”, t. 39.
  • Granger C. W. J. 1969 Investigating Causal Relations by Econometric Models and Crossspectral Methods, „Econometrica”, t. 37, no. 3.
  • Granger C. W. J. 1980 Testing for Causality. A personal Viewpoint, „Journal of Economic Dynamic and Control”, t. 2, no. 4.
  • Granger C. W. J. 1988 Some recent developments in a concept of causality, „The Economic Record”, t. 64.
  • Granger C. W. J. 2012 Forecasting, [in:] Philosophy of Economics, U. Maki (ed.), Elsevier, Amsterdam.
  • Hacker R. S., Abdulnasser H. 2006 Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and applications, „Applied Economics”, t. 38, no. 13.
  • Harvey A. C., Stock J. H. 1989 Estimating Integrated Higher-Order Continuous Time Autoregressions with an Application to Money-Income Causality, „Journal of Econometrics”, t. 42.
  • Hoover K. D. 2001 Causality in macroeconomics, Cambridge University Press, Cambridge.
  • Hoover K. D. 2006 Causality in Economics and Econometrics. An Entry for the New Palgrave Dictionary of Economics, Palgrave Macmillan.
  • Hume D. 1739 A treatise of human nature, „British Moralists” (1978).
  • Jascó P. 2005 Google Scholar: the pros and the cons, „Online Information Review”, t. 29, no. 2.
  • Leamer E. E. 1985 Vector autoregressions for causal inference?, „Carnegie-Rochester Conference Series on Public Policy”, t. 22.
  • Lee H. Y., Lin K. S. Wu J. L. 2002 Pitfalls in using Granger causality tests to find an engine of growth, „Applied Economics Letters”, t. 9, no. 6.
  • LeRoy S. 2004 Causality in Economics, Causality: Metaphysics and method, Centre for Philosophy of Natural and Social Science, London.
  • Liu Y., Bahadori M. T. 2012 A Survey on Granger Causality: A computational View, University of Southern California.
  • Madrak-Grochowska M., Żurek M. 2011 Testowanie przyczynowości w wariancji między wybranymi indeksami rynków akcji na świecie, „Oeconomia Copernica”, no. 4.
  • McCrorie J. R., Chambers M. J. 2006 Granger causality and the sampling of economic processes, „Journal of Econometrics”, t. 132.
  • Mills T. C. 1990 Time Series Techniques for Economists, Cambridge University Press, Cambridge, New York.
  • Nelson C. R., Schwert G. W. 1982 Tests for predictive relationships between time series variables: A Monte Carlo investigation, „Journal of the American Statistical Association”, t. 77 (377).
  • Nelson Ch. R. 1981 Adjustment Lags Versus Information Lags, Journal of Money, „Credit and Banking”, luty.
  • Noble N. R. 1982 Causality and Expectational Rationality: Note, „Journal of Money, Credit and Banking”, t. 14, no. 4, część 1.
  • Osińska M. 2008 Ekonometryczna analiza zależności przyczynowych, Wydawnictwo Naukowe Uniwersytetu Mikołaja Kopernika, Toruń.
  • Renault E., Sekkat K., Szafarz A. 1998 Testing for spurious causality in exchange rates, „Journal of Empirical Finance”, t. 6, no. 1.
  • Roberts D. L., Nord S. 1985 Causality tests and functional forms, „Applied Economics”, t. 17, no. 1.
  • Russo F. 2008 Methodology of Causal Modelling, [in:] Causality and Causal Modelling in the Social Sciences, F. Russo (ed.), Springer Science & Business Media, New York.
  • Sargent Th. 1976 A Classical Macroeconomic Model for the United States, „Journal of Political Economy”, no. 84.
  • Schwert W. G. 1979 Tests of causality: The message in the innovations, „Carnegie-Rochester Conference Series on Public Policy”, t. 10, North-Holland.
  • Sims C. A. 1972 Money, Income and Causality, „The American Economic Review”, t. 62, no. 4.
  • Sims Ch. A., Sargent Th. J. 1977 Business cycle modeling without pretending to have too much a priori economic theory, „Working Papers”, no. 55, Bank Rezerwy Federalnej w Minneapolis.
  • Slaugh J. R. 1981 Granger-Sims Causality. A Brief Survey of Its Use and Misuse, National Science Foundation.
  • Smith A. 1776 An Inquiry into the Nature and Causes of the Wealth of Nations, W. Strahan and T. Cadell, London.
  • Stern D. 2011 From Correlation to Granger Causality, „Crawford School Research Paper”, no. 13, Crawford School of Public Policy.
  • Sugihara G., May R., Ye H., Hsieh C., Deyle E., Fogarty M. 2012 Detecting Causality in Complex Ecosystems, „Science”, no. 338.
  • Suppes P. 1970 A Probabilistic Theory of Causality, „Acta Philosophica Fennica”, Fasc. XXIV, North-Holland, Amsterdam.
  • Triacca, U. 2007 Granger causality and contiguity between stochastic processes, „Physics Letters A”, t. 362, no. 4.
  • Wiener N. 1956 The Theory of Prediction, „Modern Mathematics for Engineers”, McGraw-Hill, New York.
  • Woodward J. 2007 Causation with a Human Face, [in:] Causation, Physics and the Constitution of Reality: Russell’s Republic, H. Price, R. Corry (eds.), Oxford University Press, New York.
  • Yu E. S. H., Choi J. 1985 The causal relationship between energy and GNP: An international comparison, „The Journal of Energy and Development”, wiosna.

Document Type

Publication order reference

Identifiers

URI
http://hdl.handle.net/11320/3268

YADDA identifier

bwmeta1.element.hdl_11320_3268
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