How scale and institutional setting explain the costs of small airports? An application of spatial regression analysis

One of the main pillars of efficient airport operations is cost-minimization. Unit costs of operation with respect to the level of passengers served are a possible proxy to measure the cost efficiency of an airport. Due to compound production framework and sophisticated political-economic environment of airports, estimation of airport costs requires detailed specifications. Airport cost functions should be able to explain the total costs with the main inputs labor, material and capital as well as by taking the airport specific characteristics into account. In this paper, we apply such an approach and focus on airport specific characteristics. We use a spatial regression methodology to explain how these drive the unit costs and analyze the spatial relationship among the dependent variables. Two separate data samples from Norwegian and French airports are used in this research to test various hypotheses. Because a large number of regional airports in both countries cannot reach financial break-even, our first research question deals with the effects of subsidies, which often follow regional and political considerations. One must therefore find an efficient way to maintain these airports without any distortions on the incentives. When evaluating the relationship between subsidies and unit costs, we find negative effect of subsidies on airport cost efficiency. Second, we evaluate the importance of economies of scale by focusing on the relationship between airport size and unit costs. Finally, the results of spatial regression show that a denser spatial distribution of airports results in higher unit costs as a consequence of lower capacity utilization, indicating the negative effect of spatial competition on airport unit costs within an airport network.