Sunk Cost Fallacy in Driving the Worlds Costliest

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Sunk Cost Fallacy in Driving the World’s Costliest Cars Teck-Hua Ho University of California

Sunk Cost Fallacy in Driving the World’s Costliest Cars Teck-Hua Ho University of California Berkeley Joint with I. P. L. Png and Sadat Reza National University of Singapore May, 2013 1

Key Research question Driver A Mercedes-Benz CLS Class Purchase month: February 2009 Price =

Key Research question Driver A Mercedes-Benz CLS Class Purchase month: February 2009 Price = $300, 000 Driver B Question: If both owners enjoy driving equally, would Driver B drive more as a result of higher sunk cost? US$242, 000 Mercedes-Benz CLS Class Purchase month: February 2010 Price = $322, 500 US$260, 000 2

Sunk cost fallacy ü Behavioral tendency of an economic agent to consume/produce at a

Sunk cost fallacy ü Behavioral tendency of an economic agent to consume/produce at a greater than optimal level ü Consumption: Desire not to appear wasteful ü Project investment: Do not wish to recognize losses ü To recover the sunk investment one has made (or close a mental account that carries the sunk cost of the product or project) 3

Sunk cost fallacy – Over-consumption Ø Experiment by Arkes and Blumer (1985) Ø Setting:

Sunk cost fallacy – Over-consumption Ø Experiment by Arkes and Blumer (1985) Ø Setting: ü Control: Bought a season theater ticket at full price ü Treatment: Bought a season theater ticket with unexpected discount ü Arkes and Blumer: Any difference in the attendance behaviour of the two (the number of shows attended)? Ø Result: ü Buyers in the control condition attended more shows than those in the treatment condition (4. 1 versus 3. 3 out of 5 shows) § Once the season ticket has been acquired, the actual price of the ticket paid should not affect decision to go to the show. § Unless, there is a tendency to recover the initial investment – sunk cost fallacy 4

Sunk cost fallacy – Escalation of commitment Ø Field studies by Staw and Hoang

Sunk cost fallacy – Escalation of commitment Ø Field studies by Staw and Hoang (1995) and Camerer and Weber (1999) Ø Setting: Ø National Basketball Association (NBA): Teams choose players in annual “draft”: higher rank = lower picks Ø Lower draft players are expected to perform better and guaranteed higher salaries compared to the higher draft players Ø Staw-Hoang and Camerer-Weber: Did teams deploy lower draft picks relatively (more minutes of play) because of the high salary commitment (after adjusting for performance)? Ø Result: Ø A minimal decrement in draft order increases playing time by 14 minutes in Year 2 to 2 minutes in Year 5 (Camerer and Weber, 1999). § Performance should be the key driver of how many minutes a player plays and not the draft pick order. § Escalation of commitment is another manifestation of sunk cost fallacy. 5

Positioning of research Low stakes Consumption Project Investment Arkes and Blumer (1985) Small monetary

Positioning of research Low stakes Consumption Project Investment Arkes and Blumer (1985) Small monetary involvement High stakes This study High stakes consumption, free of agency problem Staw and Hoang (1995) and Camerer and Weber (1999) Agency problem 6

Singapore car market ü Singapore car market is heavily regulated to influence demand for

Singapore car market ü Singapore car market is heavily regulated to influence demand for cars ü High tariffs make the cars in Singapore the world’s costliest o ARF (Additional Registration Fee) o COE (Certificate of Entitlement) 7

Components of car price Car price on-the-road = Open market value (OMV) + Retail

Components of car price Car price on-the-road = Open market value (OMV) + Retail mark-up + Customs duty + GST + Registration fee + Certificate of entitlement (COE) premium + Additional registration fee (ARF) 8

A popular model in our sample – Jun 2009 Car price on-the-road $ 129,

A popular model in our sample – Jun 2009 Car price on-the-road $ 129, 000 = OMV: $34, 952 + Retail mark-up: $37, 141 + Customs duty: $6, 990 + GST: $2, 936 s Registration fee: $140 + COE Premium: $11, 889 + ARF: $34, 952 Ex-policy Price (P) Policy components 9

Three sources of sunk cost Ø Ex-policy price Ø ARF Ø COE Premium 10

Three sources of sunk cost Ø Ex-policy price Ø ARF Ø COE Premium 10

Source of sunk costs: Ex-policy price Ø Value of ex-policy price declines as soon

Source of sunk costs: Ex-policy price Ø Value of ex-policy price declines as soon as the car is out on the road Ø Sunk cost is therefore the difference between the amount paid and the amount available if re-sold the very next day 11

Sunk cost of ex-policy price COE Premium ARF Ex-policy price 0 5 10 Car

Sunk cost of ex-policy price COE Premium ARF Ex-policy price 0 5 10 Car age in years 12

Source of sunk costs: ARF Ø Owners can purchase a new car by paying

Source of sunk costs: ARF Ø Owners can purchase a new car by paying ARF at a preferential rate (PARF) if they dispose the car within 10 years Ø If disposed within the first 5 years, a new car can be purchased by paying 25% of ARF (current policy) Ø From the 6 th year onward, the preferential rate increases by 5% per year (current policy) Ø Therefore, 25% of ARF is sunk cost 13

Sunk cost of ARF COE Premium ARF Ex-policy price 0 5 10 Car age

Sunk cost of ARF COE Premium ARF Ex-policy price 0 5 10 Car age in years 14

Source of sunk costs: COE premium Ø COE is valid for 10 years Ø

Source of sunk costs: COE premium Ø COE is valid for 10 years Ø If vehicle is disposed within 2 years of purchase, only 80% is refundable Ø After 2 years the COE premium is depreciated on a monthly basis until the end of the 10 th year. Ø Therefore, 20% of COE premium is sunk cost 15

Sunk costs of COE Premium ARF Ex-policy price 0 2 5 10 Car age

Sunk costs of COE Premium ARF Ex-policy price 0 2 5 10 Car age in years 16

Panel dataset of car usage Ø Proprietary field data from a car dealer in

Panel dataset of car usage Ø Proprietary field data from a car dealer in Singapore • Jan 2001 – Dec 2011 • 33, 457 observations on 6, 474 cars • Engine capacity – 15 different sizes • LTA registration date • Servicing date • Cumulative mileage Ø Other information (from Land Transport Authority, Dept of Statistics) • OMV • ARF rates • COE quota and premium - monthly • CPI Fuel - monthly • Car population per km - monthly 17

Key empirical regularity Noticeable phenomenon: Usage declines with time and price 2600 2400 2200

Key empirical regularity Noticeable phenomenon: Usage declines with time and price 2600 2400 2200 2003: $174, 578 2004: $161, 173 2000 2005: $151, 607 2006: $145, 347 1800 1600 1400 6 12 18 24 30 36 Vertical axis: average usage per month in km, horizontal axis: age of car in months (the most popular model in the sample) 18

Hypothesis 1: Novelty effect (H 1. ) Ø Driver’s may drive more right after

Hypothesis 1: Novelty effect (H 1. ) Ø Driver’s may drive more right after purchase of the car Ø Novelty effect can be assumed to have non-negative contribution to utility of driving Ø The effect diminishes over time

Hypothesis 2: Increasing gasoline cost (H 2. ) Gasoline Cost 2001 -2011 160 CPI

Hypothesis 2: Increasing gasoline cost (H 2. ) Gasoline Cost 2001 -2011 160 CPI Fuel Octane 98 140 120 100 80 60 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11

Hypothesis 3: Increasing congestion due to more cars on the road (H 3. )

Hypothesis 3: Increasing congestion due to more cars on the road (H 3. ) Number of cars in Singapore 2001 -2011 1000000 Number of cars 900000 800000 700000 600000 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11

Hypothesis 4: Reduction in sunk cost (H 4. ) Ø Decreasing prices resulted in

Hypothesis 4: Reduction in sunk cost (H 4. ) Ø Decreasing prices resulted in decreasing sunk cost Ø Average ARF and COE Quota Premium also declined 22

Hypothesis 4: Reduction in sunk cost (H 4. ) Ø Decreasing prices resulted in

Hypothesis 4: Reduction in sunk cost (H 4. ) Ø Decreasing prices resulted in decreasing sunk cost Ø Average ARF and COE Quota Premium also declined 200000 180000 160000 140000 Retail price 120000 ARF 100000 COE premium 80000 Policy-related sunk cost 60000 40000 20000 0 Jun-01 Jun-02 Jun-03 Jun-04 Jun-05 Jun-06 Jun-07 Jun-08 23

Hypothesis 5: Reduction in price – selection effect (H 5. ) Ø Average price

Hypothesis 5: Reduction in price – selection effect (H 5. ) Ø Average price of two most popular models in our sample: Year of Purchase Model A Model C 2003 $174, 578 $212, 140 2007 $145, 347 $171, 920 24

Model of driving behavior Ø Assumptions : ü Individual buys a car ü Plans

Model of driving behavior Ø Assumptions : ü Individual buys a car ü Plans to use for 120 months ü Scrap value at the end of the 120 th month – 50% of ARF 25

Model of driving behavior • Usage value Gasoline cost Congestion cost Depreciation cost 26

Model of driving behavior • Usage value Gasoline cost Congestion cost Depreciation cost 26

Model of driving behavior • Usage value Gasoline cost Congestion cost Depreciation cost 27

Model of driving behavior • Usage value Gasoline cost Congestion cost Depreciation cost 27

Model of driving behavior Usage value = Novelty effect Gasoline cost = Congestion cost

Model of driving behavior Usage value = Novelty effect Gasoline cost = Congestion cost = 28

Optimal usage – standard model • 29

Optimal usage – standard model • 29

Incorporating sunk-cost fallacy Psychological Sunk Cost • 30

Incorporating sunk-cost fallacy Psychological Sunk Cost • 30

Optimal usage with sunk costs • H 1. H 2. H 3. H 4.

Optimal usage with sunk costs • H 1. H 2. H 3. H 4. ( confounded by H 5. ) 31

Diminishing effect of sunk-cost fallacy Car Usage (km/month) Optimal usage with sunk cost S

Diminishing effect of sunk-cost fallacy Car Usage (km/month) Optimal usage with sunk cost S 2 Optimal usage with sunk cost S 1 < S 2 Optimal usage without sunk cost fallacy Assumptions: 10 years ü Constant gasoline prices over time ü Constant level of congestion over time ü Zero novelty effect Time 32

Selection effect and identification of sunk-cost fallacy • 33

Selection effect and identification of sunk-cost fallacy • 33

Sunk cost definition 34

Sunk cost definition 34

Estimating sunk-cost fallacy • 35

Estimating sunk-cost fallacy • 35

Target usage • 36

Target usage • 36

Alternative specifications for robustness check Ø The following specifications are estimated : Specification a:

Alternative specifications for robustness check Ø The following specifications are estimated : Specification a: Conventional model (without sunk cost) Specification b: Main specification (previous slide) Specification c: Allowing marginal benefit to be dependent on price Specification d: Alternative definition of sunk cost Specification e: Main specification – smaller cars only Specification f: Main specification – larger cars only Specification g: Main specification – heterogeneous distribution of target usage for smaller and larger cars 37

Robustness check specifications ü Marginal benefit dependent on price (specification c): Usage value =

Robustness check specifications ü Marginal benefit dependent on price (specification c): Usage value = ü Alternative definition of sunk cost (specification d): Sunk cost, ü Separate estimation for small and large cars (specifications e, f) • Target usage drawn from distributions with corresponding sample average as mean ü Heterogeneous target usage (specification g): • Target usage drawn from two distributions with means corresponding to small and large cars 38

Estimates: With and Without Sunk Cost 39

Estimates: With and Without Sunk Cost 39

Estimates: Controlling for Self-selection 40

Estimates: Controlling for Self-selection 40

Estimates: Alternative Specification of Sunk Cost 41

Estimates: Alternative Specification of Sunk Cost 41

Estimates: Small versus Large Cars 42

Estimates: Small versus Large Cars 42

Estimates: Allowing for Different Means of Target Usage for Different Engine Sizes 43

Estimates: Allowing for Different Means of Target Usage for Different Engine Sizes 43

Results ü Significant improvement in log-likelihood with specifications including sunk-cost ü Sunk-cost effect is

Results ü Significant improvement in log-likelihood with specifications including sunk-cost ü Sunk-cost effect is significant in all specifications ü Elasticity wrt sunk-cost is similar (statistically not different) in all specifications ü Novelty effect is generally positive and significant ü Effect of gasoline cost is not significant (plausible since the sample is of premium cars) ü Congestion cost is generally positive and significant 44

Policy effect ü COE premium increased by $22, 491 from February 2009 to February

Policy effect ü COE premium increased by $22, 491 from February 2009 to February 2010 ü Specification b: Estimated increase in sunk cost $4, 500 and increase in average monthly usage is 147 km (8. 8% increase) ü Specification d: Estimated increase in average monthly usage due to increase in sunk cost is 164 km (9. 9%) 45

Policy/Managerial implications ü Policy: - Making cars expensive has countervailing effect - Better to

Policy/Managerial implications ü Policy: - Making cars expensive has countervailing effect - Better to directly price congestion ü Managerial: - Countervailing argument against ‘razor/razorblade strategy’ - Underpricing the razor would reduce consumption of razor blade? 46

Back to the question that we posed in the beginning…. Driver A Mercedes-Benz CLS

Back to the question that we posed in the beginning…. Driver A Mercedes-Benz CLS Class Purchase month: February 2009 Estimated price=$300, 000 • Owner of the second car pays $22, 500 more for the same model, due to increase in the COE premium. Driver B • Structural estimation suggests that Driver B will drive 147 -164 km per month more than Driver A US$242, 000 Mercedes-Benz CLS Class Purchase month: February 2010 Estimated price=$322, 500 US$260, 000 47

Conclusion Ø Developed a behavioral model of car usage that incorporated mental accounting for

Conclusion Ø Developed a behavioral model of car usage that incorporated mental accounting for sunk cost, where the standard model is a special case. Ø Tested the model on a proprietary data set of 6, 474 cars in Singapore, the world’s most expensive car market Ø Found compelling evidence of sunk cost fallacy in car usage in Singapore 48