Car fleet modelling: Data processing and discrete choice model estimation YU SHEN MASTER’S THESIS SUPERVISOR:EMMA FREJINGER KTH ROYAL INSTITUTE OF TECHNOLOGY STOCKHOLM,SWEDEN JUNE,2011 TSC-MT 11-017 谨以此文献给我的父母和妻子 Abstract This thesis deals with the modelling of the choice of new car based on the registra- tion data of the whole Sweden car fleet for 2005 to 2010. It is divided into two parts. In the first part, to obtain the observations of new car choices for the discrete choice modelling, a subset based on the first registration date of each car is extracted. Then, a descriptive analysis based on the new car choice data is presented to find the variances of the attributes for the modelling. Specifically, two major issues are paid attention to. One is the change of market share of each car make in these years and the other is the incremental demand of diesel and hybrid fuel cars. The second part of the thesis deals with the discrete choice modelling. In order to designate the alternatives, another dataset showing the new car supply in Sweden is in- troduced. In the supply data, the alternatives are shown in the car version level, whereas the registration data only contain the names of car models. Additionally, the supply data also have some attributes that are unavailable in the registration, e.g. price. Thus, this thesis presents various matching methods to match the supply and the registration to define the alternatives for the modelling and also to obtain a higher precision of each attribute than that in matching with model names only. Finally, we choose to match the data by the same model name with the same maximum power, which is defined as the “model-engine” level. Therefore, based on these model-engine level alternatives, 18 MNL models are estimated from 2005 to 2010, with 3 different ownerships, namely private owned, company owned and company owned but leasing to its employee which is named as “leasing users”. The results show the slump of the brand constants of Saab among these years in private owners and leasing users due to the close-down crisis when the coefficient of Volvo is fixed to zero. By contrast, the brand value of Kia for private owners and the value of VW for leasing users go up. Meanwhile, this thesis analyses a shift of car buyers’ attitude to the alternative fuel car from negative in 2006 to positive in 2007 when a “clean car” compensation policy is implemented from Jan. 2007 to Jul. 2009. And in 2010, the coefficient of the alternative fuel remains positive. These results indicate that this policy was quite successful. 3 4 Acknowledgements First, I want to thank my dear parents, Zhencheng Shen and Honggang Du, and my beloved wife, Jing Wu. Without their fully helps, I can hardly finish my master study in Sweden. Second, I am deeply grateful to my supervisor, Dr. Emma Frejinger. Without her suggestion, I cannot even imagine that I would have an opportunity to take part in this project. During these months, the discussions and meetings of this thesis with Emma indeed help me a lot in both professional knowledges and scientific writings. And I also appreciate Visiting Professor Staffan Algers and Dr. Muriel Beser Hugosson for their kindly helps to this thesis. Then, I want to appreciate all the colleges in Division of Transport and Location Analysis, especially Shiva Habibi, Qian Wang, Dr. Tom Petersen and Tongzhou Bai, for their enthusiastic help to my work in different ways. Meanwhile, I would like to thank all the teachers and classmates in Transport Systems programme for their helps in these two years, e.g. Professor Lars-Goran¨ Mattsson, Professor Haris Koutsopoulos, Dr. Joel Franklin, and also my classmates Yu Liu, Shuang Zhang, etc, just to name but a few. Finally, I want to thank those who read this thesis. Your readings and comments make my work valuable. Tack sa˚ mycket! 5 6 Contents Abstract 3 Acknowledgements 5 Contents 9 List of figures 12 List of tables 14 1 Introduction and literature review 15 1.1 Background . 15 1.2 Literature review . 15 1.2.1 Discrete choice modelling . 16 1.2.2 Modelling methodology . 17 1.3 Thesis structure . 18 1.4 Scope and limitations . 19 2 Data storage and processing 25 2.1 Introduction . 25 2.2 Data storage and migration . 25 2.3 Software and processing . 26 I Descriptive analysis 29 3 Descriptive analysis of vehicle ownership 31 3.1 Introduction . 31 3.2 Car ownership analysis . 32 3.2.1 Car ownership share by make . 32 3.2.2 Car ownership by vintage . 34 7 8 CONTENTS 4 Descriptive analysis of new car registries 39 4.1 Introduction . 39 4.1.1 Extraction of new car data . 39 4.1.2 Model name generation for 2005 to 2007 . 41 4.2 Market analysis of choices . 43 4.2.1 Issues of defining price . 43 4.2.2 Market analysis in Sweden new car market . 44 4.2.3 Comparative analysis of the new car market in other countries . 47 4.3 Analysis of fuel type choices . 50 5 Descriptive analysis of car attributes 53 5.1 Introduction . 53 5.2 Share of fuel types in supply . 55 5.3 Distribution of the attribute values . 55 5.4 Technology attributes . 58 II Disaggregated analysis 61 6 Data matching 63 6.1 Description . 63 6.2 Methodology of matching . 65 6.2.1 Standardisation of model name . 65 6.3 Results and drawbacks of model level . 66 6.4 Matching in a more detailed level . 68 6.4.1 A level between model and version . 68 6.4.2 Matching with power or weight . 69 6.4.3 Results of matching by power . 76 6.4.4 Conclusion about matching with power and weight . 77 7 New car choice modelling 79 7.1 Introduction and methodology . 79 7.1.1 Analysis of new car choice sets . 79 7.1.2 Estimation tool - BIOGEME . 80 7.2 Model estimation . 81 7.3 Estimation results . 83 7.3.1 Sampling from private owned car data . 83 CONTENTS 9 7.3.2 Parameter analysis for private owner choices . 84 7.3.3 Parameter analysis for company owner choices . 88 7.3.4 Parameter analysis of the choices of company cars for leasing . 91 7.4 Analysis across various years . 95 7.4.1 The impact of “clean car” compensation . 95 7.4.2 The brand value decline of Saab . 97 8 Conclusion and discussion 99 8.1 Summary of results . 99 8.2 Comparison results in literatures . 100 8.3 Future works . 101 List of appendices 107 A List of car makes and models 107 B List of numerical attributes 111 C Estimated parameters comparison 115 10 CONTENTS List of Figures 3.2.1 Total market share of different brands . 35 3.2.2 Ownership by vintage of 1984 to 2004 . 36 4.1.1 Different numbers of new car registration . 40 4.1.2 Comparison of monthly sales . 41 4.1.3 Procedures of finding model names before 2008 . 42 4.2.1 Shares of car make by origin area in 2007 . 45 4.2.2 Shares of car make by origin area in 2010 . 45 4.3.1 Share of various fuel types of new registered cars . 51 4.3.2 Share of various fuel types in Bil Sweden . 51 5.2.1 Share of various fuel types in supply . 55 5.3.1 Histogram and density of price . 57 5.3.2 Histogram and density of log price . 57 5.3.3 Histogram and density of power . 57 5.3.4 Histogram and density of displacement . 57 5.3.5 Histogram and density of weight . 58 5.3.6 Histogram and density of acceleration . 58 6.3.1 CV of price, model level 2007 . 67 6.3.2 CV of price, model level 2008 . 67 6.3.3 CV of price, model level 2009 . 68 6.3.4 CV of price, model level 2010 . 68 6.4.1 CV of price, model-engine level 2007 . 71 6.4.2 CV of price, model-engine level 2008 . 71 6.4.3 CV of price, model-engine level 2009 . 71 6.4.4 CV of price, model-engine level 2010 . 71 6.4.5 CV of price, matching by power and gear 2007 . 72 6.4.6 CV of price, matching by power and gear 2008 . 72 11 12 LIST OF FIGURES 6.4.7 CV of price, matching by power and gear 2009 . 72 6.4.8 CV of price, matching by power and gear 2010 . 72 6.4.9 CV of price, model-weight level 2007 . 74 6.4.10CVof price, model-weight level 2008 . 74 6.4.11CVof price, model-weight level 2009 . 74 6.4.12CVof price, model-weight level 2010 . 74 7.4.1 Change of MWTP of alternative fuel . 96 List of Tables 1.4.1 Summary of literatures . 21 3.1.1 Fuel types and codes . 32 3.2.1 Rank of car ownership shares by make . 33 4.1.1 Different numbers of new car registration . 39 4.1.2 Numbers and shares of new cars deregistration in 2008 . 43 4.2.1 Numbers and shares of new registries by vintage . 44 4.2.2 Market Shares of Top 15 Brands in New Car Market . 44 4.2.3 Top 20 models and sales in Sweden new car market . 46 4.2.4 Top 10 brands of new car registries in Germany . 48 4.2.5 Passenger cars share by origin in China in 1st half of 2010 .