Appendix В Elasticities

This Appendix gives greater detail on how each measure affects aviation demand.

Price elasticities

A number of factors influence air travel demand, as outlined by IATA’s Air Travel Demand study (Smyth and Pearce, 2008). In most general terms, increasing the cost of flying reduces its demand. The reduction is not universal across the market, as it depends on factors such as the choice and utility of other modes of transport to undertake the journey (such as train, bus or car), and how wealthy the passenger is. In this study, price and income elasticities are calculated based on Air Travel Demand and are described in further detail in this Appendix. Furthermore, the income elasticities are modified in the context of more recent studies, such as Gallet and Doucouliagos (2014) and Department for Transport (2017).

In the first step, the relevant elasticity coefficients for the flight segments based on distance band, price increase coverage, and geography are listed (Table 9.4).

Combining the appropriate factors gives the following price-based demand elasticities (Table 9.5).

According to these elasticities, an increase in ticket price of 10% for an intra-EU flight will result in a 8.4% reduction in demand.

Income elasticities

The price elasticities just described will not tend to be constant in time. Another key driver of aviation demand is wealth, whereby as people become richer, they tend to fly more. Income elasticities are computed from the segments for flights originating from developed economies. An elasticity of greater than 1 tends to indicate a luxury item (Table 9.6).

Combining the appropriate factors gives the following income-based demand elasticities (Table 9.7):

Table 9.5 Demand elasticities (based on segments)

Table 9.7 Income elasticities (based on segments)

According to these income elasticities, a per capita increase in wealth (or increase in GDP per capita) of 10% will result in an increase in 15% of intra-EU flights, ceteris paribus, assuming ticket prices remain stable. As can be seen from Appendix A, Europeans are projected to be 62% wealthier in 2050 than they were in 2015 based on GDP. It is not clear to what extent the EU Reference Scenario has used these elasticities, but it is assumed that these elasticities are causes in accelerating aviation demand to the levels that are projected. These elasticities have been used to compute the passenger share evolution in each flight segment, as described later.

There is evidence that as markets mature, these elasticities reduce. Gallet and Doucouliagos (2014) suggest that when taking both income and price elasticities into account, the income elasticity would be 0.633. The UK Department for transport foresees long-term income elasticities of 0.6, also significantly lower than those presented in the IATA study. This assumes that the market is mature.

Accounting for price and income elasticities

When combining price and income elasticities, the standard approach would be to sum the net effects of both elasticities on the demand. For example, if a ticket price increase would result in a 10% reduction in passengers, but an increase in wealth would increase demand by 5%, the net effect would be a 5% reduction. In this analysis, however, passenger demand is assumed to have price and income elasticities built in. Therefore, the standard approach is not suitable in this case.

In this study, the income elasticity of 0.6 is applied directly to the price demand in 2050. If wealth considerations were not included, the segment weighted elasticity in 2050 would be —0.79. However, adjusting the elasticities based on wealth considerations gives a final segment and wealth-adjusted price demand elasticity of—0.48 in 2050.This indicates a mature market where wealthier travellers are less affected by price increases.

The underlying reasoning behind using price and income elasticities is to see how pricing mechanisms such as a CO, price can reduce aviation passenger demand, which will reduce the amount of electrofuels the EU would need to produce.These elasticities are highly uncertain, however.To have a clearer view of how this can change the results, a sensitivity analysis is conducted and is presented in Appendix C.

Evolution of aviation segments projections

The income demand elasticities show that long-haul and very-long-haul flights are expected to increase at a greater rate than domestic and intra-EU flights. The departing passenger numbers, P, of 2016 provided by Eurostat (2018) have their 2050 projections weighted by the income elasticities, E, as per the following formula:

_ . , E -L (14-G)

P = LP L • (1 + G) —!————

.p_2ii,₅.l,.(i ₊ g)

Table 9.8 Passenger numbers and growth rates

For the domestic, intra-EU and extra-EU segments, i, with total passenger number growth measured in pkm G = 75%, taken directly from the reference scenario projections between 2015 and 2050.The passenger-weighted average length of the domestic and intra-EU segments are calculated from transponder data in 2016 and are assumed to be constant. Extra-EU flight segment lengths are assumed to be 7000 km on average. This results in the following growth rates for each segment, shown in passenger numbers (Table 9.8).