Airlines blame taxes, fees and charges: The data says otherwise

This study by Prof. Dr. Friedrich Thießen and Prof. Dr. Christoph Brützel commissioned by T&E examines taxes, charges and fees (also known as location costs) in the aviation sector. It provides an indicative assessment as to why these costs exist and how they affect the sector.

Airlines claim nationally-imposed aviation taxes, fees and charges are driving passengers away. The data proves otherwise: demand to a large extent depends on airline strategy, market trends and travel behaviour, not on costs alone. Cutting aviation taxes, fees and charges would mean throwing away billions in public revenues without a tangible effect on passenger numbers.

This new study shows:

The conclusion is clear: airline attempts to attribute declines in passenger numbers solely to taxes, fees and charges appear to be more of a lobbying position to support industry demands for lower costs than a reflection of actual causal relationships.

Location costs in aviation are:

Below is a summary of the categories that fall under location costs in aviation in this report:

These various taxes, charges and fees are regulated at international, regional and national level. At international level they are regulated by the International Civil Aviation Organisation (ICAO). For example, the ICAO’s policies on charges for airports and air navigation services stipulate that these must be calculated on a cost basis, not for profit.

At EU level, they are regulated by directives such the Airport Charges Directive, the Energy Taxation Directive and the VAT Directive.

At the national level, there are large discrepancies in how taxes, charges and fees are regulated. For example, security charges are fully publicly funded in some countries and only partially publicly funded in other countries, depending on whether it is classified as being in the public interest. EU member states have also introduced a wide range of ticket taxes. The discrepancies in how taxes, charges and fees are regulated at national level ultimately leads to the variety in location costs at European airports.

Why comparisons of national taxes, fees and charges can be misleading

Airlines often highlight ‘unfair disparities’ in aviation location costs. However, the extent to which these cost comparisons can be accurately done is questionable.

There are several methodological challenges with such a comparison:

This means that truly accurate cost comparisons are not feasible.

However, two reputable sources have attempted such a comparison: the German Aerospace Centre (DLR) and the French Civil Aviation Authority. Both studies found a high range of aviation taxes, fees and charges across countries. The DLR found that in some cases the most expensive airports cost up to five times as much as the least expensive ones. Even if outliers are removed by taking away the highest and lowest quintiles, the cost differences at the remaining upper and lower bound airports are still around €4000 per flight.

This wide range in aviation taxes, fees and levies depending on the location of the flight opens up the important question of to what extent these cost differences affect airline route decisions and passenger traffic development.

Figure 1 shows the relationship between location-based costs and passenger volumes for 101 European airports in 2024. The result is a scatter cloud of data points, with a faint upward trend. This means airports with higher costs tend to have slightly more passengers.

Smaller airports have an enormous range of costs, without a clear impact on passenger volumes. Some airports have four times the costs of the cheapest in their category but still attract as many passengers. The same pattern holds true for Europe’s largest airports. Costs vary dramatically (in some cases by up to €11,000 per flight) yet passenger volumes remain similar. For both smaller and larger airports, both passenger numbers and costs vary widely with only a weak positive link.

The figure below takes a different approach to confirm the above results. It ranks 101 airports by their 2024 location costs, shown in blue. Heathrow, the most expensive airport, is used as the reference point, set at 1. All other airports are shown in relation to Heathrow’s costs. Passenger volumes are shown in orange.

Two patterns stand out. The highest location costs on the left of the graph also coincide with the highest passenger numbers. On the other hand, the graph shows that airports with lower costs also tend to be small.

In summary, at this order of magnitude the range of location costs across Europe only has a weak relationship with the passenger numbers at the airport. In the absence of a visible trend, further modelling will only yield a weak explanatory power.

Why is this the case?

Airline route planning is constrained by hubs, international agreements and market strategy. This means that an airport with low fees doesn’t automatically get more flights and that airports with higher costs can still attract many passengers if they are strategically important.

For legacy carriers, switching international hubs is not an option due to global traffic rights. For point-to-point carriers, the decision about where to base aircraft depends on the catchment area, available capacity, traffic rights, achievable market share and operational conditions.

This means that location costs are only a tie-breaker for airport choice in rare cases. The only time airport costs might noticeably determine airline choice of airport is for a low-cost carrier when two airports are close together and otherwise similar (e.g. Düsseldorf vs. Weeze), in which case location costs may tip the balance. But most airports do not have such a direct competitor nearby.

Finally, there are further factors that determine passenger numbers. The2025 DLR study also analyses the impact of factors such as the GDP in the country of departure and airline market concentration at an airport.

In order to understand whether figured above do not depict a correlation because a wide range of airports are mixed together, the authors of the study also conducted an analysis splitting European airports into three groups:

For the largest airports and hubs (Group 1) no clear pattern emerges between costs and passenger volumes. For example, the 5 major hubs (Istanbul, Paris, Frankfurt, Amsterdam and Heathrow) have a wide range in location costs with similar passenger numbers. The same is true within the group of tourist-focused airports in southern Europe (Group 2). What does emerge is that tourist-heavy airports have particularly low location-costs compared to the large hub airports, highlighting that tourist regions in southern Europe compete heavily for air traffic and often use low costs as a strategic advantage.

In Group 3 (smaller European airports) a slight trend can be identified: airports with lower location-based costs tend to have slightly more passengers. However, the relationship is very weak (the coefficient of determination is below 2%).

Conclusion

In summary, there is empirical evidence for only a weak relationship between low location costs and the level of airline supply or passenger volumes. This means that further factors must be at play than location costs alone. Since this study did not analyse the impacts of these further factors, the findings can be best understood as indicative patterns rather than definitive proof of cause and effect.

It becomes evident therefore that airport choice is also determined by business model factors, namely the available capacity, the catchment area, the market position that can be achieved and the operational conditions. These differ for legacy and low-cost carriers. Legacy carriers will seek at all costs to keep or obtain slots in large hubs for their cash cow: long haul flights. They operate from major airports where business travelers are ready to pay high prices for a quick connection. Low-cost carriers primarily operate from smaller, secondary airports, mostly serving tourists attracted by low fares.

This section explores how location costs influence demand, in particular whether national differences in these costs have an impact on air traffic growth.

To understand changes in demand as a result of changes in costs, the price elasticity of demand is often calculated. An elasticity coefficient shows by how much percent demand changes when the price increases or decreases by one percent.

However, there are a number of problems with applying the price elasticity of demand to aviation:

As a result, a price elasticity analysis in this case has little explanatory power for understanding the relationship between changes in passenger numbers and changes in ticket prices.

It is evident that the textbook assumptions on the relationship between prices and demand in aviation need to be reassessed. The myth that ticket prices are the sole determining factor influencing passenger demand simply doesn’t hold true for aviation.

Case study: The real reason German passenger numbers haven’t recovered post-pandemic

In order to demonstrate the above findings, the study analysed the passenger number developments in Germany post-pandemic and the causes behind it.

Despite these clear findings from the DLR, published in March 2025, the German airline and airport industry continues to falsely claim that Germany’s high location costs are responsible for lower passenger numbers post-Covid. Since Germany specific taxes, fees and charges have only a very weak empirical correlation with passenger numbers, there must be other contributing factors. In this section, we use Germany as an illustrative case study.

Germany has seen a steep decline in business travel after the pandemic. The Deutsche Reiseverband found a 44% decrease in 2024 compared to 2019. T&E analysis found an average overall emissions reduction in German companies of 40% compared to 2019. Some companies made big reductions in their business travel emissions, with SAP reducing emissions by 70% in 2024 compared to 2019 and Allianz by 60%. The growing dominance of leisure travel, compared to business travel, has had a structural impact on air transport. Business travellers usually fly to economic centres, whereas leisure travel is concentrated on holiday destinations. This is highlighted by Figure 7, which clearly shows that southern European countries with more leisure-focused travel have experienced growth, while flight activity in northern Europe has declined.

However, in Germany the most important explanation for the lower passenger numbers post-Covid is the sluggish development of the domestic market. The latest forecast from the German Aviation Association (BDL) shows that for June to November 2025 international services have almost completely recovered. Domestic traffic, however, is at just 53% of pre-pandemic levels.

This can be attributed to the de-facto monopoly Lufthansa has over this market. Air Berlin was forced out after prolonged losses, in part due to Lufthansa’s competitive strategies. Ryanair entered the German domestic market in 2016 but quit within a year after heavy losses. EasyJet briefly operated part of Air Berlin’s network, but also lost money and withdrew from the domestic market after Covid. Today, Lufthansa and Eurowings control 96% of the domestic market. This means that Lufthansa optimises capacity to maximise yields, focusing on flights between its hubs. As a result, many smaller cities lost hub connections, since Lufthansa’s strategy is focused on monopoly profitability, not maximum passenger access. Therefore, in line with Cournot competition theory, Lufthansa deliberately keeps capacity low so that only demand willing to pay above full operating cost is served (which of course does not include low-cost passengers).

Therefore, the passenger number trend German airlines attribute to national taxes, fees and levies is rather to a large extent the result of Lufthansa deliberately keeping capacity low to maximise its profits.

To summarise, the German case study highlights in practice that claims that national taxes, fees and levies alone reduce passenger numbers lacks empirical evidence - instead trends in passenger numbers can more often be associated with airline pricing and business strategies. It fails to reflect the actual business decisions and strategies that shape the aviation industry.

In light of the empirical findings that there is only a weak correlation between aviation taxes, fees and levies and passenger numbers/demand for aviation, T&E recommends the following: