Performance of PC and Modified PC Algorithms of Graph Theoretic Approach: A Monte Carlo Simulation Study
Abstract
Keeping in view the work of Swanson and Granger (1997) among others, the performance of PC algorithm and Modified PC algorithm of graph theoretic approach in term of size and power properties are evaluated using Monte Carlo simulation. The study recommends modified PC algorithm as the dominant approach to causality as it successfully expose the correct causal relationship between variables and best to differentiate between correct and spurious causality.
Downloads
References
Demiralp, S., & Hoover, K. D. (2003). Searching for the causal structure of a vector autoregression. Oxford Bulletin of Economics and Statistics, 65(5), 745–767.
Demiralp, S., Hoover, K. D., & Perez, S. J. (2008). A bootstrap method for identifying and evaluating a structural vector autoregression. Oxford Bulletin of Economics and Statistics.
Fazal, R., Alam, M. S., Hayat, U., & Alam, N. (2021b). Effectiveness of monetary policy: Application of modified Peter and Clark (PC) algorithms under graph-theoretic approach. Scientific Annals of Economics and Business, 68(3), 333–344. https://doi.org/10.47743/saeb-2021-0021
Fazal, R., Bhatti, M. I., & Rehman, A. U. (2022a). Causality analysis: The study of size and power based on riz-PC algorithm of graph-theoretic approach. Technological Forecasting and Social Change, 180, Article e121691. https://doi.org/10.1016/j.techfore.2022.121691
Fazal, R., Rehman, S. A. U., & Bhatti, M. I. (2022b). Graph theoretic approach to expose the energy-induced crisis in Pakistan. Energy Policy, 169, Article e113174. https://doi.org/10.1016/j.enpol.2022.113174
Fazal, R., Rehman, S. A. U., Bhatti, M. I., Rehman, A. U., Arooj, F., & Hayat, U. (2021a). A cross-sectoral investigation of the energy–environment–economy causal nexus in Pakistan: Policy suggestions for improved energy management. Energies, 14(17), Article e5495. https://doi.org/10.3390/en14175495
Fazal, R., Rehman, S. A. U., Rehman, A. U., Bhatti, M. I., & Hussain, A. (2021c). Energy–environment–economy causal nexus in Pakistan: A graph theoretic approach. Energy, 214, Article e118934.
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438.
Hicks, J. (1980). Causality in economics. Australian National University Press.
Hoover, K. D. (2001). Causality in macroeconomics. Cambridge University Press.
Hoover, K. D. (2005). Automatic inference of the contemporaneous causal order of a system of equations. Econometric Theory, 21(1), 69–77.
Lin, J. L. (2008). Notes on testing causality. Institute of Economics, Academia Sinica & Department of Economics, National Chengchi University.
Pearl, J. (1993). [Bayesian analysis in expert systems]: Comment: Graphical models, causality and intervention. Statistical Science, 8(3), 266–269.
Rehman, A. U., & Malik, M. I. (2014). The modified R: A robust measure of association for time series. Electronic Journal of Applied Statistical Analysis, 7(1), 1–13. https://doi.org/10.1285/i20705948v7n1p1
Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 62(4), 540–552.
Spirtes, P., Glymour, C. N., Scheines, R., Heckerman, D., Meek, C., Cooper, G., & Richardson, T. (2000). Causation, prediction, and search. MIT Press.
Swanson, N. R., & Granger, C. W. J. (1997). Impulse response functions based on a causal approach to residual orthogonalization in vector autoregressions. Journal of the American Statistical Association, 92(437), 357–367. https://doi.org/10.2307/2291475
Copyright (c) 2024 Tariq Majeed, Rizwan Fazal, Atiq Ur Rehman
This work is licensed under a Creative Commons Attribution 4.0 International License.
JQM follows an open-access publishing policy and full text of all published articles is available free, immediately upon publication of an issue. The journal’s contents are published and distributed under the terms of the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Thus, the work submitted to the journal implies that it is original, unpublished work of the authors (neither published previously nor accepted/under consideration for publication elsewhere). On acceptance of a manuscript for publication, a corresponding author on the behalf of all co-authors of the manuscript will sign and submit a completed Copyright and Author Consent Form.
