Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports

Abstract

We study the effects of ownership forms on airports' cost efficiency by applying stochastic frontier analysis to a panel data of the world's major airports. Our key findings are: (a) Countries considering privatization of airports should transfer majority shares to the private sector; (b) Mixed ownership of airport with a government majority should be avoided in favor of even 100% government owned public firm; (c) U.S. airports operated by port authorities should consider to transfer ownership/management to independent airport authorities; and (d) Privatization of one or more airports in cities with multiple airports would improve the efficiency of all airports.2

Group and individual heterogeneity in a stochastic frontier model: Container terminal operators

“…Studies of multinational service industries have received increased attention from researchers, e.g., multinational banks (Chang et al, 1998), hotels (Shang et al, 2008), insurance companies (Fenn et al, 2008), and airports (Oum et al, 2008).…”

Untitled

“…Despite the vast discussion that this issue has caused in the literature (e.g. [37]), it seems that the privatisation benefits are unequivocal to airport performance [9]. Accordingly, we expect a positive influence of privatisation on airport efficiency scores.…”

“…Nevertheless, there are several papers that study the influence of a particular feature of the operational environment on efficiency. For example, Oum et al [9] estimated the effect of ownership on efficiency of worldwide airports concluding that private airports are more efficient than the public ones. Oum et al [10] analysed the different types of airport organisation concluding that mixed ownership and multi-level government ownership should be avoided.…”

Review and Systematization of Efficiency Measurement Methods Used in the Transport Sector

“…In case of a deterministic function, the corrected ordinary least squares method (COLS) or linear programming (LP) can be used. If the SFA method is selected, these two can still be applied (see [14]), or the maximum likelihood estimation (MLE) (see [15]) or the Markov Chain Monte Carlo simulation (MCMC) (see [16]) can also be employed.…”

“…Oum et al [16] use SFA with a translog function to evaluate the efficiency of 109 worldwide airports, Diana [13] utilizes SFA with a log-linear Cobb-Douglas form for the examination of airport performance, Tsionas [17] combines SFA with a non-parametric method to investigate the efficiency of 10 US airlines over a 14 year long period, Cullinane et al [15] look into the efficiency of 28 internationally very important container ports with an SFA method using a log-linear Cobb-Dougles production function, Coelli and Perelman [14] estimate the efficiency of 17 European railway companies with this method, employing a translog function and applying the LP and the COLS technique and Tovar and Martín-Cejas [9] use SFA as the basic method to calculate the efficiency rankings to be used in Malmquist productivity indexes in order to evaluate the efficiency of Spanish airports.…”