Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model

Authors

  • Mohammad Jasim Mohammad Department of Statistics, College of Administration & Economics, University of Baghdad, Iraq
  • Sajad Sammer Abd Al-Razzaq Department of Statistics, College of Administration & Economics, University of Baghdad, Iraq

DOI:

https://doi.org/10.51173/jt.v5i1.1080

Keywords:

Fuzzy Regression Discontinuity, Robust Local Polynomial Regression Estimators, method Mean Squared Error Approximation and Optimal Bandwidth, Monte Carlo experiment

Abstract

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

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References

Angrist and Rokkanen. (2015).” Wanna Get Away? Regression Discontinuity Estimation of Exam School Effects Away From the Cutoff”. Journal of the American Statistical Association.Vol.110,No.512,PP 1331-1344.

Cattaneo, M. D., Jansson, M., Ma, X.( 2017).” Simple Local Polynomial Density Estimators”. Journal of the American Statistical Association. 115(531) PP1449-1455.

Bloom, B. S. (1984). “The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring”. Educational Researcher. Vol.13, No.6, PP. 4-16.

Bloom et al.(1997).” The Benefits and Costs of JTPA Title II-A Programs: Key Findings from the National Job Training Partnership Act Study”. The Journal of Human Resources. Vol.32, No.3, PP. 549-576.

Jacob, R. et al.(2012).” A Practical Guide to Regression Discontinuity”. MDRC.

Fan, J. and Gijbels, I. (1996).” Local Polynomial Modelling and Its Applications”. Chapman and Hall, London. Introductory Econometrics (4th Edition) A Modern Approach, by Jeffrey M. Wooldridge Hardcover, 888 Pages, Published 2008 by South-Western.

Calonico, S., M. D. Cattaneo, and M. H. Farrell. (2017). “On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference”. Journal of the American Statistical Association. Vol.113, No.522, PP. 767-779.

Silverman, B.W. (1986).” Density Estimation for Statistics and Data Analysis”.Chapman & Hall, London. 30(7) PP 876-877.

Gelman and Imbens. (2019)." Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs”. Journal of Business & Economic Statistics. Vol.37, No3, PP. 447-456.

Epanechnikov, V.A. (1969). “Non-parametric estimation of a multivariate probability density”. Theory of Probability and its Applications. Vol.14, No.1, PP. 153-158.

Rong Ma et al.(2016).” Robust Inference in Fuzzy Regression Discontinuity with Multiple Forcing Variables”. Central University of Finance and Economics.

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Published

2023-04-04

How to Cite

Mohammad Jasim Mohammad, & Sajad Sammer Abd Al-Razzaq. (2023). Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model. Journal of Techniques, 5(1), 203–207. https://doi.org/10.51173/jt.v5i1.1080

Issue

Section

Management

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