biography for william swan chief economist, seabury-airline planning group. agifors senior fellow....
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Biography for William SwanChief 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. ([email protected])
© Scott Adams
Boeing 11-Year World Airline Traffic OutlookShort Form of what we do for a living in my shop
GDP growth for world: 2.8%
RPK growth for the world: 4.4%
We predict these averages
Tables, regional growth, charts, lots of stuff on resultant aircraft fleets:
http://www.boeing.com/commercial/cmo
Growth is an Average over Cycles
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Growth is an Average Over Cycles
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”
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Growth Fit with 1% Annual Reduction
Three Forecasting Mistakes
We now have a new forecasting method
We still have similar results
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William M. SwanChief EconomistBoeing Marketing
Three Lessons (our mistakes)
1. Do not let the model’s form determine the answer
-- algebra can force interpretation
2. Statistics do not preclude the use of reason
--logical demonstrations are also valid
3. 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:
RPKs ~ GDP * Yield-
is the “GDP elasticity”
is the “price elasticity”
Problems with algebra:
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
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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 GDPIs Independent of Income
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Same Data, Different Display:Say Good-Bye to the S-Curve
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GDP Elasticity Absorbed All GrowthLousy data on fares: price elasticity understated.
Therefore, GDP picked up price effect:
RPK(t) = GDP(t) * Yield(t)-
became
RPK(t) = GDP(t)
but should have been
ASK/GDP = GDP0 * F(t)
Travel Share (ASK/GDP) grows with time (t)
Time trend F(t) confounded earlier analyses
because there wasn’t one in the algebra
Another Reason GDP Was Over-EmphasizedBeware Heteroscedasticity
Traffic in short term responds to consumer confidence
Consumer confidence moves when GDP moves are large
Therefore large GDP moves show large traffic responses
Least-squared calibration weights large moves more
Result:
Calibrations over-stated GDP elasticity of travel
Long-term growth must expect average consumer confidence
The “What Else?” questionTime trend is “other effects”
Price effects
More nonstops stimulate travel
Global trade stimulates travel
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Yield is an average: Average yield declines with more long trips Average yield declines with more discount (pleasure) trips
Under half of 2.2% yield decline is decline in fares: Business fares have gone up Pleasure fares have gone down, and quality to match
Yield Overstates Fare DeclinesYield is an Imperfect Statistic
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Trend of -2.2%/year
Humility: Measurement BiasesHalf the time an Economist talks, he talks about measures, not answers
Taxes and airport fees seem to keep going up: Added 0.4% /year to ticket price in US last decade Greater increases for international flying Reported “yields” are net to the airline Actual fare changes had tax and fee increases
The other messy nit – inflation: In the US, CPI inflation is 0.3% higher than GDP inflation
– CPI overstates inflation 0.3% growth is not negligible In the UK, similar answer but smaller difference Elsewhere, not so bad
Please do not compare GDP growth using GDP deflator with airline revenue growth without taxes deflated by CPI
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 MeasuredIt 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
km added added freq.
ASK Flow range FREQUENCIES SEATS/AC VALUE Americas 1106 +29% -1% +11% Eur/Af/ME 937 +52% -3% +17%
Asia 1089 +159% 0% +25% Atlantic 7011 +83% -10% +13% Pacific 8743 +143% +7% +13%
Asia-Europe 8845 +200% -3% +18%
WORLD AVG. 1282 +55% +4% +15%
Growth 1985-1995 Schedules
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 WorseHalf 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 NoiseDo not give up the statistics
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Cheating on Statisticswhat 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 2 “Significant” results
– % women in the workforce• Politically incorrect, do 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 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
Travel Grows With TradeInternational Trade drives some Air Travel Growth
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
1975 1985 1995 2005 2015 Business Fare $ 100 $ 102 $ 104 $ 106 $ 108 0.20% fare growth per year Pleasure Fare $ 80 $ 69 $ 59 $ 51 $ 44 -1.50% fare growth per year Average Fare $ 87 $ 80 $ 72 $ 66 $ 59 -0.94% fare growth per year
Business Traffic Price Elasticity 50.0 49.5 49.0 48.5 48.0 0.50 Price Elasticity GDP growth 50.0 68.5 93.9 128.6 176.3 3.2% GDP growth Non-GDP growth 50.0 56.3 63.5 71.5 80.6 1.2% Trade, Service Grow Total Demand 50.0 76.4 116.8 178.6 272.9 4.3% Net Growth
Pleasure Traffic Price Elasticity 88.9 111.5 139.9 175.5 220.1 1.50 Price Elasticity GDP growth 88.9 121.8 166.9 228.7 313.4 3.2% GDP growth Non-GDP growth 88.9 91.6 94.4 97.2 100.2 0.3% Trade, Service Grow Total Demand 88.9 157.4 278.9 493.9 874.8 5.9% Net Growth Market Elasticity 1.14 1.17 1.20 1.23 1.26
Total Demand 139 234 396 672 1148 5.4% Total RPK Growth Growth 5.4% 5.4% 5.5% 5.5%
Business Share 36% 33% 30% 27% 24% -0.3% Decline/yr
Load Factor 60% 63% 66% 70% 73% 0.50% Gain/yr ASK 100 160 258 417 677 4.9% ASK Growth $/seat $ 52.32 $ 50.23 $ 48.00 $45.66 $43.27 -0.4% Gain/yr
Business Share of Traffic Declines SlowlyWhat set of assumptions fits all the available data?
Conclusion: Data is a NuisanceContinually 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.”
Post 9/11 Forecast Build-Up
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add fear
add cost & hassle
add GDP
add confidence
traffic level
New TrendOld Trend
William Swan:
Data Troll
Story Teller
Economist