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Fuzzy sets and (fuzzy) random sets in Econometrics and Statistics

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  • Colubi, Ana
  • Ramos-Guajardo, Ana Belén

Abstract

Fuzzy sets generalize the concept of sets by considering that elements belong to a class (or fulfil a property) with a degree of membership (or certainty) ranging between 0 and 1. Fuzzy sets have been used in diverse areas to model gradual transitions as opposite to abrupt changes. In econometrics and statistics, this has been especially relevant in clustering, regression discontinuity designs, and imprecise data modelling, to name but a few. Although the membership functions vary between 0 and 1 as the probabilities, the nature of the imprecision captured by the fuzzy sets is usually different from stochastic uncertainty. The aim is to illustrate the advantages of combining fuzziness, imprecision, or partial knowledge with randomness through various key methodological problems. Emphasis will be placed on the management of non-precise data modelled through (fuzzy) sets. Software to apply the reviewed methodology will be suggested. Some open problems that could be of future interest will be discussed.

Suggested Citation

  • Colubi, Ana & Ramos-Guajardo, Ana Belén, 2023. "Fuzzy sets and (fuzzy) random sets in Econometrics and Statistics," Econometrics and Statistics, Elsevier, vol. 26(C), pages 84-98.
  • Handle: RePEc:eee:ecosta:v:26:y:2023:i:c:p:84-98
    DOI: 10.1016/j.ecosta.2022.07.001
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    as
    1. Marta García-Bárzana & Ana Belén Ramos-Guajardo & Ana Colubi & Erricos J. Kontoghiorghes, 2020. "Multiple linear regression models for random intervals: a set arithmetic approach," Computational Statistics, Springer, vol. 35(2), pages 755-773, June.
    2. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    3. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    4. Renato Coppi & Paolo Giordani & Pierpaolo D’Urso, 2006. "Component Models for Fuzzy Data," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 733-761, December.
    5. Cheng, Ching-Hsue & Wei, Liang-Ying & Liu, Jing-Wei & Chen, Tai-Liang, 2013. "OWA-based ANFIS model for TAIEX forecasting," Economic Modelling, Elsevier, vol. 30(C), pages 442-448.
    6. Ferraro, Maria Brigida & Giordani, Paolo & Vichi, Maurizio, 2021. "A class of two-mode clustering algorithms in a fuzzy setting," Econometrics and Statistics, Elsevier, vol. 18(C), pages 63-78.
    7. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, vol. 70(2), pages 519-546, March.
    8. D'Urso, Pierpaolo & Giordani, Paolo, 2006. "A weighted fuzzy c-means clustering model for fuzzy data," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1496-1523, March.
    9. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    10. Blanco-Fernández, Angela & Corral, Norberto & González-Rodríguez, Gil, 2011. "Estimation of a flexible simple linear model for interval data based on set arithmetic," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2568-2578, September.
    11. Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
    12. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    13. Marinho Bertanha & Guido W. Imbens, 2020. "External Validity in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 593-612, July.
    14. Yingying Dong, 2018. "Alternative Assumptions to Identify LATE in Fuzzy Regression Discontinuity Designs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(5), pages 1020-1027, October.
    15. Coppi, Renato & D'Urso, Pierpaolo & Giordani, Paolo & Santoro, Adriana, 2006. "Least squares estimation of a linear regression model with LR fuzzy response," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 267-286, November.
    16. Shapiro, Arnold F., 2009. "Fuzzy random variables," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 307-314, April.
    17. Cardella, Eric & Depew, Briggs, 2014. "The effect of health insurance coverage on the reported health of young adults," Economics Letters, Elsevier, vol. 124(3), pages 406-410.
    18. Ilya Molchanov & Ignacio Cascos, 2016. "Multivariate Risk Measures: A Constructive Approach Based On Selections," Mathematical Finance, Wiley Blackwell, vol. 26(4), pages 867-900, October.
    19. Christoph Basten & Frank Betz, 2013. "Beyond Work Ethic: Religion, Individual, and Political Preferences," American Economic Journal: Economic Policy, American Economic Association, vol. 5(3), pages 67-91, August.
    20. Yang, Miin-Shen & Hung, Wen-Liang & Cheng, Fu-Chou, 2006. "Mixed-variable fuzzy clustering approach to part family and machine cell formation for GT applications," International Journal of Production Economics, Elsevier, vol. 103(1), pages 185-198, September.
    21. Ilya Molchanov & Francesca Molinari, 2014. "Applications of Random Set Theory in Econometrics," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 229-251, August.
    22. Molchanov,Ilya & Molinari,Francesca, 2018. "Random Sets in Econometrics," Cambridge Books, Cambridge University Press, number 9781107121201.
    23. Arie Beresteanu & Francesca Molinari, 2008. "Asymptotic Properties for a Class of Partially Identified Models," Econometrica, Econometric Society, vol. 76(4), pages 763-814, July.
    24. Murray, Paula M. & Browne, Ryan P. & McNicholas, Paul D., 2017. "A mixture of SDB skew-t factor analyzers," Econometrics and Statistics, Elsevier, vol. 3(C), pages 160-168.
    25. Ignacio Cascos & Ilya Molchanov, 2013. "Multivariate risk measures: a constructive approach based on selections," Papers 1301.1496, arXiv.org, revised Jul 2016.
    26. Sahin, Özge & Czado, Claudia, 2022. "Vine copula mixture models and clustering for non-Gaussian data," Econometrics and Statistics, Elsevier, vol. 22(C), pages 136-158.
    27. Karun Adusumilli & Taisuke Otsu, 2017. "Empirical Likelihood for Random Sets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1064-1075, July.
    28. Ramos-Guajardo, Ana Belén & Lubiano, María Asunción, 2012. "K-sample tests for equality of variances of random fuzzy sets," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 956-966.
    29. Kasa, Siva Rajesh & Rajan, Vaibhav, 2022. "Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation," Econometrics and Statistics, Elsevier, vol. 22(C), pages 67-97.
    30. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    31. Ferraty, Frédéric & Zullo, Anthony & Fauvel, Mathieu, 2019. "Nonparametric regression on contaminated functional predictor with application to hyperspectral data," Econometrics and Statistics, Elsevier, vol. 9(C), pages 95-107.
    32. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.
    33. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
    34. Lima Neto, Eufrasio de A. & de Carvalho, Francisco de A.T., 2008. "Centre and Range method for fitting a linear regression model to symbolic interval data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1500-1515, January.
    35. Gil, Maria Angeles & Gonzalez-Rodriguez, Gil & Colubi, Ana & Montenegro, Manuel, 2007. "Testing linear independence in linear models with interval-valued data," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3002-3015, March.
    36. González-Rodríguez, Gil & Colubi, Ana, 2017. "On the consistency of bootstrap methods in separable Hilbert spaces," Econometrics and Statistics, Elsevier, vol. 1(C), pages 118-127.
    37. Qu, Xiaohui & Zhang, Guohua, 2010. "Measuring the convergence of national accounting standards with international financial reporting standards: The application of fuzzy clustering analysis," The International Journal of Accounting, Elsevier, vol. 45(3), pages 334-355, September.
    38. Choi, Jin-young & Lee, Myoung-jae, 2018. "Relaxing conditions for local average treatment effect in fuzzy regression discontinuity," Economics Letters, Elsevier, vol. 173(C), pages 47-50.
    39. Rajna Gibson & Sébastien Gyger, 2007. "The Style Consistency of Hedge Funds," European Financial Management, European Financial Management Association, vol. 13(2), pages 287-308, March.
    40. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    41. Cameron, Trudy Ann & Huppert, Daniel D., 1989. "OLS versus ML estimation of non-market resource values with payment card interval data," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 230-246, November.
    42. D'Urso, Pierpaolo & Gastaldi, Tommaso, 2000. "A least-squares approach to fuzzy linear regression analysis," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 427-440, October.
    43. Matsui, Hidetoshi, 2020. "Quadratic regression for functional response models," Econometrics and Statistics, Elsevier, vol. 13(C), pages 125-136.
    44. Kim, Kwang Jae & Moskowitz, Herbert & Koksalan, Murat, 1996. "Fuzzy versus statistical linear regression," European Journal of Operational Research, Elsevier, vol. 92(2), pages 417-434, July.
    45. Choirat, Christine & Seri, Raffaello, 2014. "Bootstrap confidence sets for the Aumann mean of a random closed set," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 803-817.
    46. Chi-Chen Wang & Yun-Sheng Hsu & Cheng-Hwai Liou, 2011. "A comparison of ARIMA forecasting and heuristic modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1095-1102.
    47. Berry-Stölzle, Thomas R. & Koissi, Marie-Claire & Shapiro, Arnold F., 2010. "Detecting fuzzy relationships in regression models: The case of insurer solvency surveillance in Germany," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 554-567, June.
    48. González-Rodríguez, Gil & Colubi, Ana & Gil, María Ángeles, 2012. "Fuzzy data treated as functional data: A one-way ANOVA test approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 943-955.
    49. Liudmyla Маlyaretz & Oleksandr Dorokhov & Liudmyla Dorokhova, 2018. "Method of Constructing the Fuzzy Regression Model of Bank Сompetitiveness," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 7(2), pages 139-164.
    50. Manski, Charles F. & Molinari, Francesca, 2010. "Rounding Probabilistic Expectations in Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 219-231.
    51. Maria Ferraro & Paolo Giordani, 2012. "A multiple linear regression model for imprecise information," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1049-1068, November.
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