Comparing Enhanced Models for Evaluating the Economic Impact of Airports

Abstract

Evaluating the economic impact of airports is crucial for understanding the benefits they bring to a region. However, when an area has more than one airport, it becomes essential to analyze each airport’s contribution to the local economy to make informed investment and policy decisions. Thus, studying economic models that can distinguish each airport’s impact on the region’s economy becomes essential. In this context, this paper aims to compare three different approaches to determine the economic contributions of airports in a given region and identify their social and economic benefits. The International Civil Aviation Organization recommends using input–output analysis in this context. The study considered three weight factors for the input–output basic model: circular buffer, displacement time, and Huff’s gravitational model. The analysis was performed using the three largest airports in São Paulo state, Brazil, due to their proximity and influence on the surrounding areas. The models were compared based on their efficiency and accuracy in reflecting the reality of the case study context. The study identified the most suitable model for establishing correlations between investments made in airport infrastructure and the generation of gross domestic product, employment, and added value. This study fills a gap in the existing literature by proposing improvements to the methods for evaluating airports’ economic and social benefits. In recent times, airport investors, both in the government and private sectors, have become increasingly demanding in their need for accurate analyses before making investments. Therefore, the results of this paper will provide valuable insights into the benefits of investing in airport infrastructure and help policymakers and investors make informed decisions.

Keywords

• economic impacts of airports
• airport investments
• input–output analysis
• data science