Biography for William Swan Chief Economist, Seabury-Airline Planning Group AGIFORS Senior Fellow ATRG Senior Fellow Retired Chief Economist for Boeing Commercial Aircraft 1996-2005 Previous to Boeing, worked at American Airlines in Operations Research and Strategic Planning and United Airlines in Research and Development Areas of work included Yield Management, Fleet Planning, Aircraft Routing, and Crew Scheduling Also worked for Hull Trading, a major market maker in stock index options, and on the staff at MIT’s Flight Transportation Lab Education: Master’s, Engineer’s Degree, and Ph D at MIT Bachelor of Science in Aeronautical Engineering at Princeton Likes dogs and dark beer (bill.swan@cyberswans.com) © Scott Adams Boeing 11-Year World Airline Traffic Outlook Short Form of what we for a living in my shop Growth is an Average over Cycles Growth is an Average Over Cycles 2.5 GDP growth for world: 2.8% RPK growth for the world: 4.4% 1.5 GDP We predict these averages 0.5 1970 1975 1980 1985 1990 1995 2000 2005 2010 Tables, regional growth, charts, lots of stuff on resultant aircraft fleets: http://www.boeing.com/commercial/cmo 2015 Underlying Theme • A TREND is a projection of past growth • A FORECAST includes reasons why • The FUTURE includes acts of will My Forecast Could Have been a “Trend” ASK index World ASK Growth Growth Fit with 1% Annual Reduction 1970 1975 1980 1985 1990 1995 2000 Three Forecasting Mistakes • We now have a new forecasting method • We still have similar results ASK index World ASK Growth Growth Fit with 1% Annual Reduction William M Swan 1970 Chief Economist Boeing Marketing 1975 1980 1985 1990 1995 2000 Three Lessons (our mistakes) Do not let the model’s form determine the answer algebra can force interpretation Statistics not preclude the use of reason logical demonstrations are also valid Do not give up statistics can see through scatter Plus our Bonus lesson: An example of business sleaze (“Occam’s Toothbrush”) Do Not Let the Model’s Form Determine the Answer Our traditional formula: 4.0 γ RPKs ~ GDP * Yield γ is the “GDP elasticity” ε is the “price elasticity” -ε 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Problems with algebra: 1996 1998 2000 2002 2004 2006 2008 2010 • GDP did not distinguish between sources of growth per-capita wealth increase GDP or population growth GDP? • Yield is a poor surrogate for ticket prices • All growth MUST be attributed to GDP or Yield 2012 2014 2016 2018 Error #1: Travel Does Not Grow as GDP1.5 Cross-sectional data: Travel Share not rising with incomes: • Travel Share of GDP measured as ASK/GDP ratio • Data shows small negative correlation with per-capita income • No acceleration of travel share after joining middle class Time-series data confirmed pattern: • Growth of Travel Share was independent of growth of GDP • Based on Country-by-Country data Conclusion: • Travel grows linearly with GDP growth • Remaining 1/3 of travel growth is “something else” Useful question: “What Else?” Air Travel Share of GDP Independent of Income of Income Air TravelIsShare of GDP Independent ASK/GDP index 250 200 150 100 50 $- $10 $20 $30 $40 1996 Per Capita Income (US$000) $50 Same Data, Different Display: Say Good-Bye to the S-Curve ASK/Capita (index) 500 400 300 200 100 $0 $10,000 $20,000 Per Capita Income $30,000 Hard Lesson: Work the Data • It is easy to grab data a run with it • It takes work to muck about in the data • Learn what is being measured • Play with the data, examine outliers • You will gain more from good data than good modeling • Professors only publish modeling Error #2: Value of Service Can be Measured It has proven almost impossible to calibrate service elasticities But that does not preclude the use of reasoning Here is the reasoning: ASKs doubled with almost no growth in aircraft size: • Lots of new flights, new times, new places It could have gone the other way: • Just bigger airplanes would have saved 1.5%/year Cost Savings foregone represent value added by new services: • Market produced high-service result • Implication is that value exceeds cost savings Surprise! – Value growth exceeds fare reductions in size Value of Better Service Approximated by Cost Growth 1985-1995 Schedules ASK Flow km range added FREQUENCIES Americas Eur/Af/ME Asia Atlantic Pacific Asia-Europe 1106 937 1089 7011 8743 8845 +29% +52% +159% +83% +143% +200% WORLD AVG 1282 +55% added freq SEATS/AC VALUE +11% -1% +17% -3% +25% 0% +13% -10% +13% +7% +18% -3% +15% +4% • Growth absorbed almost entirely with frequencies • Foregone cost savings approximately 15% in 10 years • Value created approximately 15% in 10 years • This should stimulate as much travel as a fare decrease Humility: Service got Worse Half the time an Economist talks, he talks about measures, not answers We estimated cost=value of more direct services and frequencies We did not estimate the loss of value associated with: • • • • • • • • • Lower reliability More delays Smaller personal space on airplane Higher load factors Worse food Busier flight attendants Worse airport access Longer airport processing times More trouble finding the best fare So we may have overstated the net quality effect Error #3: Scatter is Not Noise Do not give up the statistics 200 150 "Error" in Travel Share 100 50 $0 $5,000 $10,000 $15,000 $2 0,000 $ 25,000 -50 -100 -150 1995 Per Capita Income (1990 US$) $30,000 $35,000 Cheating on Statistics what explains scatter? • Quality of cuisine hypothesis untasted • A “Statistically Significant” result is at 95% – Means 5% chance of being random coincidence • Ran 40 regressions, found “Significant” results – % women in the workforce • Politically incorrect, not pursue – International trade as % of GDP • Tells a good story, makes sense, follow this up • Moral of the story: statistics can find new ideas • If in “publish or perish” world – Write two papers, get two brownie points Travel Grows With Trade International Trade drives some Air Travel Growth • Travel Share (ASK/GDP Ratio) grows with increased Trade: “Trade” measured as Imports+Exports as % of GDP Trade growing nearly twice as fast as GDPs • Cross-sectional data significant: “Trade” explains some of the scatter in Travel Share • Time-series data also significant: Change in Trade creates change in Travel Service\ • Same ratios, either way Bonus Lesson: An example of business sleaze Proof by Assumptions “Test”: (Occam’s Toothbrush) Introducing a technique often used in business Occam’s Toothbrush Is there a reasonable set of assumptions that fit all known data AND Allow my answer to be “right”? Final Surprise: Business Demand is growing almost as fast as Pleasure Demand (“Demand” is the demand curve, not the traffic count) Proof by Occam’s Toothbrush: “What is the most reasonable set of assumptions that allow data?” Business travel share (survey data) declines only 3% in 10 years • We expect trade growth to drive business travel • We expect service quality business travel Overall traffic has been growing 5% annually Fares are declining only for pleasure demands What is minimum business demand growth beyond the 3% from GDP? it turns out pretty high Business Share of Traffic Declines Slowly What set of assumptions fits all the available data? 1975 $ 100 $ 80 $ 87 1985 $ 102 $ 69 $ 80 1995 $ 104 $ 59 $ 72 2005 $ 106 $ 51 $ 66 50.0 50.0 50.0 50.0 49.5 68.5 56.3 76.4 49.0 93.9 63.5 116.8 48.5 128.6 71.5 178.6 48.0 176.3 80.6 272.9 0.50 Price Elasticity 3.2% GDP growth 1.2% Trade, Service Grow 4.3% Net Growth 88.9 88.9 88.9 88.9 1.14 111.5 121.8 91.6 157.4 1.17 139.9 166.9 94.4 278.9 1.20 175.5 228.7 97.2 493.9 1.23 220.1 313.4 100.2 874.8 1.26 1.50 Price Elasticity 3.2% GDP growth 0.3% Trade, Service Grow 5.9% Net Growth Total Demand Growth 139 234 5.4% 396 5.4% 672 5.5% 1148 5.5% 5.4% Total RPK Growth Business Share 36% 33% 30% 27% 24% 60% 100 $ 52.32 63% 160 $ 50.23 66% 258 $ 48.00 70% 417 $45.66 Business Fare Pleasure Fare Average Fare Business Traffic Price Elasticity GDP growth Non-GDP growth Total Demand Pleasure Traffic Price Elasticity GDP growth Non-GDP growth Total Demand Market Elasticity Load Factor ASK $/seat 2015 $ 108 0.20% fare growth per year $ 44 -1.50% fare growth per year $ 59 -0.94% fare growth per year -0.3% Decline/yr 73% 0.50% Gain/yr 677 4.9% ASK Growth $43.27 -0.4% Gain/yr Conclusion: Data is a Nuisance Continually upsetting well-established platitudes Nobody can tell if a forecast is right Everybody can tell if a forecast has changed We have not changed total trends of growth We have changed: • Where in the world the growth may be • What we look for if trends are to change • How we explain it “It is better to light one poor candle than to curse the darkness.” William Swan: Data Troll Story Teller Economist ... Growth Fit with 1% Annual Reduction 1970 1975 1980 1985 1990 1995 2000 Three Forecasting Mistakes • We now have a new forecasting method • We still have similar results ASK index World ASK Growth