Figure 1 Concentration at the National Level Concentration Ratios

Transcription

1 Figure 1 Concentration at the National Level Concentration Ratios Data Sources and Variable Construction: Calculated by the author from the U.S. Department of Transportation s Data Bank 1A(DB1A), a ten percent sample of airline tickets. Figure 2 Competition at the Route Level Data Sources and Variable Construction: The number of effective competitors at the route level is calculated from the Department of Transportation s ten percent sample of airline tickets (Data Bank 1A). Each airline s share of passengers on each domestic route was calculated from a subsample of Data Bank 1A consisting of one-way tickets with two or fewer segments and roundtrip tickets with two or fewer segments on the outbound and return legs. These route-level measures were aggregated across routes based on the fraction of sampled passengers and passenger miles on each route. (See text for explanation of effective competitors.)

2 Figure 3 Percentage of Passengers Flying on Carriers with >90% Route Market Share Data Source and Variable Construction: Calculated by the author from the U.S. Department of Transportation s Data Bank 1A(DB1A), a ten percent sample of airline tickets. Figure 4 Percentage of Passengers Flying on Carriers with <20% Route Market Share Data Sources and Variable Construction: Calculated by the author from the U.S. Department of Transportation s Data Bank 1A(DB1A), a ten percent sample of airline tickets

3 Figure 5 Domestic Airline Yield Adjusted for Inflation (1993 dollars) Data Sources and Variable Construction: Domestic yield is from Air Transport Association, Air Transport 19xx: The Annual Report of the U.S. Scheduled Airline Industry, various issues. Real yield was calculated by adjusting nominal yield using the Consumer Price Index. Figure 6 Percentage Change in Domestic Air Fares by Distance, Adjusted for Inflation Data Sources and Variable Construction: Yield in each period (for 100 mile bands) was calculated from a subsample of the U.S. Department of transportation s ten percent sample of airline tickets (Data Bank 1A). This subsample was all domestic round trip ticket with two or fewer segments outbound and two or fewer segments return. (To correct for possible coding errors in the data airlines submitted, a fare screen was used to screen out tickets with fares that seemed unreasonably high or low.) Fares were adjusted for inflation using the Consumer Price Index

4 Figure 7 Actual Yield vs. Regulated Yield Data Sources and Variable Construction: See text. Figures in the graph are nominal, i.e., not adjusted for inflation. Figure 8 Distribution of Air Fares Relative to Each Route s Average Fare Data Sources and Variable Construction: The distribution of air fares was calculated from a subsample of the U.S. Department of Transportation s ten percent sample of airline tickets (Data Bank 1A). This subsample was all domestic round trip tickets with two or fewer segments outbound and two or fewer segments return. (To correct for possible coding errors in the data airlines submitted, a fare screen was used to screen out tickets with fares that seemed unreasonably high or low. Thus, frequent flier tickets are excluded.)

5 Figure 9 Measures of Yield Premium at 15 GAO Concentrated Airports Data Sources and Variable Construction: Fares at each of the fifteen GAO concentrated airports are from a subsample of the U.S. Department of Transportation s ten percent sample of airline tickets (Data Bank 1A). This subsample was all domestic round trip tickets with two or fewer segments outbound and two or fewer segments return. See text for more details. Figure 10 The Distribution of Domestic Fares in 1993:4 Relative to Regulated Fares Data Sources and Variable Construction: Fares actually paid in 1993:4 are from a subsample of the U.S. Department of Transportation s ten percent sample of airline tickets (Data Bank 1A). This subsample was all domestic round trip tickets with two or fewer segments outbound and two or fewer segments return. To correct for possible coding errors in the data the airlines submitted, a fare screen was used to eliminate tickets with fares that seemed unreasonably high. Tickets with low fares were not removed in order not to remove valid frequent flier tickets. However, the percentage of zero fare tickets was reduced by 1.7 percent of total tickets (2.5 percent of total passenger miles) to correct for coding errors. (See footnote 6 in this chapter for the origin of these correction factors.) For each ticket in the subsample, the fare factually paid was compared with an estimate of the regulated fare that would have been charged if fares were based on our adjusted Standard Industry Fare Level (SIFL) fare formula. The reason the passenger mile figure is more favorable than the passenger figure is because, on average, long-haul fares have fallen and short-haul fares have risen

6 Figure 11 Percentage of Seats Filled with Revenue Passengers Data Sources and Variable Construction: Load factor is the percentage of seats filled with revenue passengers. It is calculated by dividing revenue passenger miles by available seat miles (for both international and domestic service). The source of the data is Air Transport Association, Air Transport 19xx: The Annual Report of the U.S. Scheduled Airline Industry, various issues. Figure 12 Load Factor by Distance: 1978 and 1993 Data Sources and Variable Construction: Calculated by the author based on data in the U.S. Department of Transportation s Service Segment Data base, a (complete) census of airline flights

7 Figure 13 Composition of Connecting Passengers: Domestic Trips Data Sources and Variable Construction: The percentage and composition of connecting passengers was calculated from a subsample of domestic trips in the U.S. Department of Transportation s ten percent sample of airline tickets (Data Bank 1A). This subsample consisted of one-way tickets with two or fewer segments and roundtrip tickets with two or fewer segments on the outbound and return legs. Figure 14 Change in Aircraft Size by Distance between 1978 and 1993 Data Sources and Variable Construction: Calculated by the author based on data in the U.S. Department of Transportation s Service Segment Data base, a (complete) census of airline flights

8 Figure 15 Change in Flight Time Since 1978 (1978 passenger weights) Data Sources and Variable Construction: Calculated by the author based on data in the U.S. Department of Transportation s Service Segment Data base, a (complete) census of airline flights. Figure 16 Airline Industry Employment Data Sources and Variable Construction: Data are from Air Transport Association, Air Transport 19xx: The Annual Report of the U.S. Scheduled Airline Industry, various issues

9 Figure 17 Operating Profit Margin (All Services): U.S. Scheduled Airlines Data Sources and Variable Construction: Operating Profit Margin is the percentage by which revenue exceeds cost, where cost does not include interest on long term debt and income taxes, and includes both domestic and international operations of the airlines. The source of the data is Air Transport Association, Air Transport 19xx: The Annual Report of the U.S. Scheduled Airline Industry, various issues. Figure 18 Air Travel Safety: Chance of Death per Million Departures Data Sources and Variable Construction: Aircraft accident data, for both air carriers (Part 121) and commuters (Part 135), are from the National Transportation Safety Board. The probability of death is calculated by multiplying fatal accidents per departure by the fraction of passengers involved in fatal accidents who die

10 Figure 19 Percentage of U.S. Domestic Travelers Flying on Zero Fare Tickets Source: Calculated by the author from the U.S. Department of Transportation s Data Bank 1A, a ten percent sample of airline tickets. Figure 20 Traffic Commissions Paid by U.S. Airlines per Revenue Passenger Mile (1993 cents) Source: Calculated by author from data in Air Transport Association, Airline Cost Index. Conversion to 1993 dollars was done using the Consumer Price Index

11 Figure 21 Traffic Commissions Paid by U.S. Airlines as a Percent of Fare Revenue Source: Calculated by author from data in Air Transport Association, Airline Cost Index

12 Table 1. How Often Travel Agents Reported that Business Clients Choose Flights to Build Up Frequent Flyer Miles How often business clients choose flights to build up frequent flier miles Percentage of travel agents reporting Always of almost always 57 More than half the time 24 About half the time 9 Less than half the time 4 Rarely, if ever 2 Other a 3 Total b 100 a The other response category includes those who answered Don t know or Other to this question. b Total does not add to 100 percent because of rounding. Source: U.S. General Accounting Office (1990), Table 6.1, based on a survey of 520 travel agents. Table 2. Market Share Percentage Change in Market Share from Simultaneous Elimination of All Frequent Flier Programs Carrier Domestic Market Share Percentage Change in Market Share if All Carriers Eliminate Frequent Flier Programs American United Delta Continental USAir Southwest Northwest TWA Eastern America West Midway Alaska Source: Morrison and Winston (forthcoming)

13 Table 3. Effects of Computer Reservation Systems on Travelers Welfare and Airlines Revenue ($1990 million) Assumption a Base Case Alternative 1 Alternative 2 Welfare Loss: Business Travelers Welfare Loss: Pleasure Travelers Total Loss Revenue Transfer: Business Travelers Revenue Transfer: Pleasure Travelers Total Transfer Deadweight Loss a In all cases below, one alternative is randomly eliminated. The assumptions are as follows: Base Case: A carrier alternative is not eliminated if a traveler who pays for his ticket has accumulated between 3,500 and 80,000 frequent flier miles on that carrier or if a traveler who does not pay for his ticket has accumulated any frequent flier miles on that carrier. Alternative 1: A carrier alternative is not eliminated if a traveler who pays for his ticket has accumulated between 3,500 and 80,000 frequent flier miles on that carrier or if a traveler who does not pay for his ticket has accumulated any frequent flier miles on that carrier or if that carrier developed and managed its own computer reservation system. Alternative 2: A carrier alternative can be eliminated regardless of whether it has a computer reservation system or whether a traveler has accumulated any frequent flier miles on that carrier. Figures in the table are the average effects from repeated simulations eliminating the type of carrier detailed above. Source: Morrison and Winston (forthcoming). Totals may not add due to rounding. Table 4. Effects of Computer Reservation Systems on Distribution of Revenue among Airlines ($1990 million, positive value indicates a revenue gain) a Total does not add due to rounding. Source: Morrison and Winston (forthcoming). Airline Revenue Change American United 10.8 Delta 5.8 Continental USAir Southwest -3.4 Northwest TWA 2.6 America West Midway -0.2 Eastern Alaska 0.0 TOTAL a