1. Homework: Airline Operating Costs and Airline Productivity Rui Neiva, April 9, 2012 Definitions: RPM: revenue passenger miles; ∑ i = 1 to All Flights (Number of Passengers (Flight i) * Distance Flown (Flight i) ASM: available seat miles; ∑ i = 1 to All Flights (Number of Seats (Flight i) * Distance Flown (Flight i) RASM: revenue per ASM; Revenue/ASM CASM: Operating expense per ASM; Operating expenses/ASM Yield: average airfare paid by passenger per mile flown; Total revenue/RPM PRASM: passenger revenue per ASM; Total revenue/RPM Fuel consumed: amount of fuel used (in a flight, in a year, etc.) Fuel costs per ASM: Fuel costs/ASM Non-fuel costs per ASM: (operatin expenses – fuel costs)/ASM Airline analyzed: Continental. Legacy Carrier. Using the framework on figure 5.6, Continental does not have a single type of aircraft; has unions; has connecting hubs; does not have single cabin service and has premium class; has seat assignment; has a loyalty program; uses GDS Rui Neiva

2. Question 3. a) Load factors are on a continuously ascending trend, from ~70% in 2001 to ~82% in 2009. RPM and ASM also increase continuously along the years, with the latter increasing less than the former. The spikes in Q1 of 2005 and 2006 appear to be a glitch in the data (they are present in the regional affiliates of the airlines, and represent values 9 times higher than the months Immediately before)-

3. Question 3. b) Until the recession of 2008 there is a continuous increase of both operating expenses and revenues. After that period they both plummet. Income before taxes as a very erratic behavior, with 14 quarters in the black (maximum of $261 million in Q3 2003), and 22 in the red (minimum of $-310 million in Q1 2003)

4. Question 3. c) All the data is affected by the probable problem with the dataset in Q1 in 2005 and 2006. Yield per RPM is on a downward trend in 2001, until it bounces back in 2005, to drop again in 2008. This closely follows the economic cycle (dotcom bubble burst, expansion of the economy, and then the Great Recession). All the other variables follow a similar path, except for CASM which start to the upwards trend in 2003, not 2005.

5. Question 3. d) The amount of money spent on fuel more than triples between 2001 and the summer of 2008 (when the barrel of oil reached an historic nominal maximum). After the beginning of the recession, and the consequently drop in fuel prices, fuel OPEX also dropped considerably. Somewhat surprisingly, non-fuel OPEX follows the same overall trend of fuel OPEX, including the peak in 2008 and the drop that followed.

6. Rui Neiva Question 3. e) As expected, fuel OPEX per ASM closely follows the price of fuel (the drops in 2005 and 2005 are most likely of the problems in the data already mentioned). Non-fuel OPEX remains relatively stable along the entire time period (besides the problems with the data in 2005 and 2006).

7. Rui Neiva Question 4 a) Total operating expenses follow fuel drops prices very closely (fuel OPEX correlation: 0.96; non-fuel OPEX correlation: 0.89;), with slight in 2001, then almost continuous growth until 2008, and a great fall in the recession period. In terms of OPEX per ASM, only fuel OPEX is correlated with fuel prices (0.91), non-fuel OPEX per ASM is slightly uncorrelated (-0.08). RASM, CASM and PRASM all have correlations with fuel prices around 0.5, with yield per RPM having a lower correlation of 0.24. b) Operating expenses follow the same overall trend as fuel prices, as does operating revenues (correlations above 0.9 in both cases). It does not seem to exist a relation between fuel prices and losses or profits (correlation: 0.08). c) Network structure is slightly correlated with fuel prices, with ASM having a correlation of 0.52. RPM have a correlation of 0.60, and load factor a correlation of 0.68, which seems to indicate that higher fuel prices make airlines not to expand so much, and they rather try to increase load factors instead.