Efficiency Driver in Nigerian Airports: A Bootstrap DEA–Censored Quantile Regression Approach

Journal of Aviation Technology and Engineering

Wanke, Peter¹  Azad, Abul Kalam²  Nwaogbe, Obioma Reuben³  Ogwude, Innocent Chukwuka⁴  Barros, Carlos Pestana⁵ 

[1] COPPEAD Graduate Business School, Federal University of Rio de Janeiro;Department of Applied Statistics, Faculty of Economics and Administration, University of Malaya;Department of Transport Management Technology, Federal University of Technology, Minna, Nigeria;Department of Transport Management, Federal University of Technology Owerri State Nigeria;Instituto Superior de Economia e Gestao, University of Lisbon

关键词: airports;    DEA;    bootstrap;    Nigeria;    censored quantile regression;   

DOI  :  10.7771/2159-6670.1171

学科分类：社会科学、人文和艺术（综合）

来源: Purdue University

【 摘 要 】

This paper reports on the use of a novel two-stage approach for assessing the efficiency of 30 major Nigerian airports from 2003 to 2013 based on bootstrapped data envelopment analysis (DEA) and censored quantile regression. In the first stage, bootstrapped efficiency estimates are computed. They enable bias correction and testing for significant differences in efficiency levels among airports. Subsequently, bootstrapped DEA results are combined with censored quantile regression to assess the impact of contextual variables—related to the airports’ ownership, location, and network connectivity—on different efficiency percentiles. The results reveal that the intensity of significant impacts regarding airports’ contextual variables may vary between high-/low-efficiency airports. Policy implications are derived accordingly.

【 授权许可】

Free