Uncovering substitution patterns in new car sales using a cross nested logit model
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1 Uncovering substitution patterns in new car sales using a cross nested logit model Swiss Transportation Research Conference Anna Fernández Antoĺın Matthieu de Lapparent Michel Bierlaire May 19, 2016 A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
2 Outline Outline 1 State of the art 2 Case study 3 Results 4 Conclusions and future work A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
3 Outline Research question Real research question Can we model more flexible substitution patterns using Choice Probability Generation Functions (CPGF) based models? A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
4 Outline Research question Real research question Can we model more flexible substitution patterns using Choice Probability Generation Functions (CPGF) based models? But before... Start by a Cross-Nested Logit Add on the car-type ownership literature A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
5 Outline Car-type models Why are they interesting? For car manufacturers: valuation of car attributes For governments, forecasts of: Tax revenues Energy consumption Emission levels Can be used for policy measures This is preliminary work. Comments and suggestions are more than welcome! A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
6 State of the art Identifying a vehicle type Make-model-engine 2 An alternative: Volvo XC Over 00 alternatives Sampling of alternatives needed Market and fuel type 3 An alternative: Small petrol car Between 15 and 30 alternatives No sampling of alternatives needed 2 Birkeland, M. E. & Jordal-Jorgensen, J. (2001) Energy efficiency of passenger cars. Paper presented at the European Transport Conference 2001, PTRC, Cambridge, UK. 3 Page, M., Whelan, G.,& Daly, A. (2000) Modelling the factors which influence new car purchasing. Paper presented at the European Transport Conference 2000, PTRC, Cambridge, UK. A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
7 Case study Data: France 2014 Decision makers 40,000 observations 20,000 contain no NAs A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
8 Case study Data: France 2014 Decision makers 40,000 observations 20,000 contain no NAs Attributes Reported fuel consumption [l/0km] Engine power [bhp] Price after discounts and government schemes [e] Reported range (EV) [km] A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
9 Case study Data: France 2014 Decision makers 40,000 observations 20,000 contain no NAs Attributes Reported fuel consumption [l/0km] Engine power [bhp] Price after discounts and government schemes [e] Reported range (EV) [km] Socioeconomic variables Income Number of adults/children in the household Residential location (agglomerations vs. rural areas) Education level (university vs. no university) A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
10 Case study Choice-set definition Choice set Car type = market segment + fuel type A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
11 Case study Choice-set definition Choice set Car type = market segment + fuel type Market segment Full Luxury Medium Multi-purpose vehicle (MPV) Off-road Small Fuel type Hybrid Diesel Petrol Electric A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
12 Case study Cross-nesting structure full luxury medium MPV offroad small hybrid diesel petrol electric A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
13 Case study Attributes of non-chosen alternatives What are the attributes of an off-road diesel car that I didn t choose? 1 Draw vectors of attributes from the empirical distribution. 2 Define the unchosen alternatives for each respondent. 3 Estimate the parameters of the model with this dataset. 4 Iterate. A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
14 Results Parameter estimation: CNL Scale parametes (µ small = µ hybrid = µ electric = 1) Alpha market segment A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, 2016 / 12
15 Results Substitution patterns Market shares before and after a 50% increase in price of alternative 5 (diesel offroad) Alternative Observed Logit CNL How does the market share for alternative 12 increase when the market share of alternative 5 decreases? Logit: = 0 = 61% CNL: = 0 = 79% A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
16 Conclusions and future work Conclusions and Future work Conclusions Most results are in line with our expectations and the literature. Results seem stable with only draws. Substitution patterns seem more intuitive with the CNL. Future work Endogeneity of price and fuel consumption CPGF-based models A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
17 Thank you for your attention! Questions? A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
18 Nesting structure 1 Market segment full luxury medium MPV offroad hybrid small A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
19 Nesting structure 2 Fuel type diesel electric petrol A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
20 Parameter estimation: CNL Attributes of the car Income A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
21 Parameter estimation: CNL Socioeconomics Dummy variables A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
22 Parameter estimation: Logit Attributes of the car Income A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
23 Parameter estimation: Logit Socioeconomics Dummy variables A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
24 Model specification (1/2) Parameter ASC full ASC luxury ASC medium ASC MPV ASC offroad ASC petrol ASC electric β income inc full income 000 β inc luxury 0 income β inc medium 0 0 income β inc MPV income β inc offroad income β inc hybrid income β nbr adults small nbr. adults 0 0 β nbr chilren small nbr. child. 0 0 β nbr cars lux 0 nbr. cars β nbr cars hybrid nbr. cars 0 β university β town rural EV β town rural hybrid town rural 0 price β 1 0 price 2 0 price 3 0 price 4 0 price 5 0 price 6 0 price 7 0 price 8 0 price inc income income income income income income income income cons1 pd 0 cons2 pd 0 cons3 pd 0 cons4 pd 0 cons5 pd 0 cons6 pd 0 cons7 pd 0 cons8 pp 0 β conso inc max income power income income income income income income income βmax power 1 max power 2 max power 3 max power 4 max power 5 max power 6 max power 7 max power 8 β range EV A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
25 Model specification (2/2) Parameter ASC full ASC luxury ASC medium ASC MPV ASC offroad ASC petrol ASC electric β inc full β income inc luxury β inc medium 0 income β inc MPV 0 0 income β inc offroad income β inc hybrid income β nbr adults small nbr. adults 0 0 β nbr chilren small nbr. child. 0 0 β nbr cars lux nbr. cars β nbr cars hybrid nbr. cars 0 β university β town rural EV town rural β town rural hybrid town rural 0 price β 9 0 price 0 price 11 0 price 12 0 price 13 0 price 14 0 price inc income income income income income income cons9 pp 0 cons pp 0 cons11 pp 0 cons12 pp 0 cons13 pp 0 cons14 pp 0 price 15 0 income β conso inc max income power income income income income income βmax power 9 max power max power 11 max power 12 max power 13 max power 14 β range EV max power 15 range EV 0 A. Fernández Antoĺın (TRANSP-OR EPFL) Car-type choice May 19, / 12
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