Comparison and Empirical Evaluation of Classical Tests of Skewness versus Bootstrap Tests of Skewness
DOI:
https://doi.org/10.58329/criss.v3i2.130Abstract
Abstract Views: 73This study compares classical (SK-1, SK-2, SSS, MED, STDM, PRSN)and bootstrap (KS and Student’s t) tests on the basis of size and power properties for six different data generating processes (chi-square distribution, beta distribution, lognormal distribution, mixture of two normal distribution, and mixture of two uniform and normal distribution) via Monte Carlo Simulations. In general, the classical tests for skewness perform better than bootstrap tests, however, in certain situations the bootstrap tests perform better. Therefore, this study recommends a strategy for choice of test to be applied in different situations. If the data histogram shows deviation from symmetry and the third moment is close to zero then the bootstrap tests should be used. In other cases the classical tests of skewness, in particular SK-2 which is the best performing test, should be used.
Keywords:
Bootstrap tests, Classical tests, Skewed distribution, Skewness, SymmetryReferences
Adil, I. H. (2011). Robust Outlier Detection Techniques for Skewed Distributions and Applications to Real Data, International Islamic University Islamabad.
Akbar, S., Raza, A., & Riaz, Y. (2019). A Monte Carlo Simulation Analysis of Panel Stationarity Tests under a Single Framework. European Online Journal of Natural and Social Sciences: Proceedings, 8(1 (s)), 34-41.
Brys, G., Hubert, M., and Struyf, A. (2003). "A Comparison of some New Measures of Skewness", Developments in Robust Statistics, Springer: 98-113.
Brys, G., Hubert, M., and Struyf, A. (2004). ”A Robust Measure of Skewness.” Journal of Computational and Graphical Statistics 13(4): 996-1017.
Doane, D. P., and Seward, L. E. (2011). ”Measuring Skewness: A Forgotten Statistic?” Journal of Statistics Education 19(2).
Efron, B. (1979). ”Bootstrap Methods: Another Look at the Jackknife.” The Annals of Statistics 7(1): 1-26.
Efron, B. (1982). The Jackknife, The Bootstrap, and other Resampling Plans, Siam.
Gosset, W. S. (1908). Student. The Application of the’Law of Error’to the Work of the Brewery,
Hussan, M., & Akbar, S. (2019). "A Monte Carlo Comparative Simulation Study for Identification of the Best Performing Panel Cointegration Tests", European Online Journal of Natural and Social Sciences, 8(2), pp:366-373.
Jarque, C. M., & Bera, A. K. (1980). "Efficient tests for normality, homoscedasticity and serial independence of regression residuals", Economics Letters, 6(3), 255-259. doi:10.1016/0165-1765(80)90024-5.
Modarres, R. (2002). ”Efficient Nonparametric Estimation of a Distribution Function.” Computational Statistics & Data Analysis 39(1): 75-95.
Pearson, K. (1895). ”Contributions to the Mathematical Theory of Evolution, II: Skew Variation in Homogeneous Material.” Transactions of the Royal Philosophical Society, Series A 186: 343-414.
Raza, A., Azam, K, & Tariq, M. (2020). “The Impact of Greenfield-FDI on Socio-Economic Development of Pakistan”. HSE Economic Journal, 24(3): 415-433. DOI: 10.17323/1813-8691-2020-24-3-415-433
Raza, A., Azam, M. & Bakhtyar, B. (2024). "Exploring the Linkage between Energy Consumption and Economic Growth in BRICS Countries through Disaggregated Analysis", Journal of the Knowledge Economy, 15(2), 1-24. https://doi.org/10.1007/s13132-024-02045-1
Raza, A., Nadeem, M. I., Ahmed, K., Hassan, I., Eldin, S. M., & Ghamry, N. A. (2023). Is Greenfield investment improving welfare: A quantitative analysis for Latin American and Caribbean developing countries. Heliyon, 9(10), e20703. https://doi.org/10.1016/j.heliyon.2023.e20703
Riaz, Y., Raza, A., & Rashid, M. (2018). "Comparison of Residual based Co-integration Tests: Evidence from Monte Carlo", European Online Journal of Natural and Social Sciences, 7(2), 494-500.
Smirnov, N. V. e. (1947). ”On Criteria for The Symmetry of Distribution Laws of Random Variables.” Rossiiskaya Akademiya Nauk 56: 13-16.
Stuart, A. and Ord, K. (1994). "Kendall’s Advanced Theory of Statistics", Volume 1: Distribution Theory. 6th Edition, Edward Arnold, London.
Tabor, J. (2010). ”Investigating the Investigative Task: Testing for Skewness: An Investigation of Different Test Statistics and Their Power to Detect Skewness.” Journal of Statistics Education 18(2).
Tibshirani, R. J., and Efron, B. (1993). ”An Introduction to The Bootstrap.” Monographs on Statistics and Applied Probability 57: 1-436.
Waheed, A., Rashid, A., & Akbar, S. (2021). "Detecting the Best Performing Time-Variant Cointegration Test Using the Consumption Function", International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(4), 1-5.
Whaeed, A., Akbar, S., Siddiq, S. A. B., & Raza, A. (2023). "Testing and Identifying Multiple Bubbles in Pak Rupee-Chinese Yuan Exchange Rate", Journal of Positive School Psychology, 7(2), 1937-1951.
Zheng, T., and Gastwirth, J. L. (2010). ”On Bootstrap Tests of Symmetry about an Unknown Median.” Journal of Data Science: JDS 8(3): 413.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 CARC Research in Social Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.