The econometric estimation of airports’ cost function
The econometric estimation of airports’ cost function
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DOI：
10.1016/j.trb.2010.05.001
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发表时间：
2011
影响因子：
6.8
通讯作者：
Juan Carlos Martín;Augusto Voltes-Dorta
中科院分区：
文献类型：
--
作者：
Juan Carlos Martín;Augusto Voltes-Dorta
成本函数的计量经济学估计已在文献中提出，作为一个合适的方法，以获得运输行业的边际成本，效率水平和规模弹性的估计。然而，关于机场业，没有重视制定机场专用的估算方法，而是采用适用于其他行业的程序。缺乏可比较的机场数据是解释过去这种文献稀缺的原因之一，以及使用非常有限的方法来解释机场技术。本文试图克服这些局限性，通过开发一个机场特定的方法来估计一个多输出的长期成本函数，使用不平衡的汇集数据库在全球161个机场。在输出向量中，讨论了经享乐调整的飞机运营、国内和国际乘客、货物和商业收入的规格，以及输入价格的计算。技术和配置的低效率指定在模型中使用的随机前沿方法，已估计通过贝叶斯推理和马尔可夫链蒙特卡罗方法。
The econometric estimation of cost functions has been proposed in the literature as a suitable approach in order to obtain estimations of marginal costs, efficiency levels and scale elasticities for transport industries. However, regarding the airport industry, no significant attention has been paid in developing an airport-specific estimation methodology rather than adapting the procedures applied to other industries. The lack of comparable airport data is one of the causes which could explain the scarcity of this literature in the past, as well as the use of very limited approaches to explain airport technology. This paper tries to overcome these limitations by developing an airport-specific methodology to estimate a multi-output long-run cost function using an unbalanced pooled database on 161 airports worldwide. The specification of hedonically-adjusted aircraft operations, domestic and international passengers, cargo and commercial revenues in the output vector, as well as the calculation of input prices are discussed. Both technical and allocative inefficiencies are specified in the model using a Stochastic Frontier method that has been estimated through Bayesian Inference and Markov Chain Monte Carlo methods.