برآورد تاثیر خصوصی سازی فرودگاه بر تقاضای خطوط هوایی: مطالعه رویدادی مبتنی بر رگرسیون /  Estimating the impact of airport privatization on airline demand: A regression-based event study

 برآورد تاثیر خصوصی سازی فرودگاه بر تقاضای خطوط هوایی: مطالعه رویدادی مبتنی بر رگرسیون  Estimating the impact of airport privatization on airline demand: A regression-based event study

  • نوع فایل : کتاب
  • زبان : انگلیسی
  • ناشر : Elsevier
  • چاپ و سال / کشور: 2017

توضیحات

رشته های مرتبط  علوم فنون هوایی

مجله   مدیریت حمل و نقل هوایی – Journal of Air Transport Management
دانشگاه  مرکز اقتصاد، موسسه فناوری هواشناسی، برزیل

نشریه  نشریه الزویر

Description

1. Introduction This paper develops an empirical model of passenger demand for routes of recently privatized airports aiming at inspecting if a privatization process producing a sequential impact on traffic. By employing a regression-based event methodology, we investigate whether the change in ownership and management control has any effect on the efficiency of both airports and airlines to generate additional demand. We perform an econometric analysis of preprivatization and post-privatization dynamic patterns of demand to infer the demand consequences of the major change in governance and its anticipation by involved enterprises and all stakeholders. Privatization is widely seen as a mechanism to promote competitiveness of a sector or a whole country by enhancing the efficiency of stated-owned enterprises (SOEs). In the air transport literature, some recent studies so far have suggested that airports operated by a majority private firm achieve higher efficiency than those operated by a majority public firm e for example, Oum et al. (2008) and Oum et al. (2006). However, the literature has not yet directly addressed the important issue of the impact of airport privatization on passenger demand. We argue that, in contrast to the state-owned enterprise, a privatized airport may be more effective not only in attracting new airlines but in producing route development strategies such as route support and risk sharing with existing airlines, which ultimately stimulates demand. We suspect that privatization produces effects not only through airport capacity expansion, the new regulatory framework and the potentially enhanced efficiency, but it also has a relevant impact in the short run. We suspect that privatization preparation, announcement, the transfer of management control, and the inevitable temporary effects of terminal and runway constructions and renovations may dictate these short run effects. By testing the effects on the dynamic pattern of passenger demand following the privatization of airports, we intend to fill the gap in the literature with respect to assessing its ceteris paribus impact on demand and also contribute to the scarce literature on the empirical modeling of airport privatization and its consequences. We consider the privatization timetable of Donaldson and Wagle (1995) to separate the short run from the long run effects in terms of sequential privatization stages. To estimate the dynamic effects of demand following privatization, we develop an econometric model of passenger market demand by considering the Brazilian airline industry and its recent airport privatization experience. We consider the effects of the privatization package of 2011e2012 that included major airports Sao Paulo/Guarulhos (GRU), Brasília (BSB) and S ~ ao Paulo/Viracopos ~ (VCP) e respectively, the country’s international gateway, the geographically centrally located domestic hub, and the only effective secondary airport in the country. From our regression-based event, we estimate a set of privatization-related coefficients and promote empirical tests of the sequential impact of privatization on demand. Our empirical model considers the endogeneity of price and therefore, makes use of an instrumental variables approach in a panel data framework. We also utilize a correction procedure for sample selectivity due to the fact that the short list of airports selected to be privatized is likely to be determined based on socioeconomic criteria and airport performance indicators, and not randomly.
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