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Export Reference (APA) 
Suleman, A., Suleman, F. & Reis, E. (2016). Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium. Journal of Business Economics and Management. 17 (3), 414-429
Export Reference (IEEE) 
A. K. Suleman et al.,  "Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium", in Journal of Business Economics and Management, vol. 17, no. 3, pp. 414-429, 2016
Export BibTeX 
@article{suleman2016_1775266273906,
	author = "Suleman, A. and Suleman, F. and Reis, E.",
	title = "Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium",
	journal = "Journal of Business Economics and Management",
	year = "2016",
	volume = "17",
	number = "3",
	doi = "10.3846/16111699.2014.978361",
	pages = "414-429",
	url = "http://www.tandfonline.com/doi/abs/10.3846/16111699.2014.978361"
}
Export RIS 
TY  - JOUR
TI  - Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium
T2  - Journal of Business Economics and Management
VL  - 17
IS  - 3
AU  - Suleman, A.
AU  - Suleman, F.
AU  - Reis, E.
PY  - 2016
SP  - 414-429
SN  - 1611-1699
DO  - 10.3846/16111699.2014.978361
UR  - http://www.tandfonline.com/doi/abs/10.3846/16111699.2014.978361
AB  - Measures of stock of skills alternative to human capital have raised fresh difficulties, especially in data managing. We propose to empirically compare the efficiency of a hierarchical cluster analysis and a fuzzy clustering in reducing discrete skill data. The outcomes of both methods are subsequently used to measure the impact of skills on earnings in addition to human capital. The proposed methodological comparison was made using an original dataset of retail bankers’ skills assessed by supervisors. Empirical evidence shows that the fuzzy approach is more efficient than the hierarchical clustering: the resulting clusters are fewer and easier to interpret. Furthermore, the earnings equation enriched with skill variables allowed us to correct the education premium, and provides information on monetary incentives related to individual skills. Our paper attempts to raise researchers’ and practitioners’ awareness of data reducing methods, and their implications for wage determinants.
ER  -