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Analyzing the prices of the most expensive sheet iron all over the world: Modeling, prediction and regime change

Author

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  • Fu-Tie Song

    (ECUST)

  • Wei-Xing Zhou

    (ECUST)

Abstract
The private car license plates issued in Shanghai are bestowed the title of "the most expensive sheet iron all over the world", more expensive than gold. A citizen has to bid in an monthly auction to obtain a license plate for his new private car. We perform statistical analysis to investigate the influence of the minimal price $P_{\min}$ of the bidding winners, the quota $N_{\rm{quota}}$ of private car license plates, the number $N_{\rm{bidder}}$ of bidders, as well as two external shocks including the legality debate of the auction in 2004 and the auction regime reform in January 2008 on the average price $P_{\rm{mean}}$ of all bidding winners. It is found that the legality debate of the auction had marginal transient impact on the average price in a short time period. In contrast, the change of the auction rules has significant permanent influence on the average price, which reduces the price by about 3020 yuan Renminbi. It means that the average price exhibits nonlinear behaviors with a regime change. The evolution of the average price is independent of the number $N_{\rm{bidder}}$ of bidders in both regimes. In the early regime before January 2008, the average price $P_{\rm{mean}}$ was influenced only by the minimal price $P_{\min}$ in the preceding month with a positive correlation. In the current regime since January 2008, the average price is positively correlated with the minimal price and the quota in the preceding month and negatively correlated with the quota in the same month. We test the predictive power of the two models using 2-year and 3-year moving windows and find that the latter outperforms the former. It seems that the auction market becomes more efficient after the auction reform since the prediction error increases.

Suggested Citation

  • Fu-Tie Song & Wei-Xing Zhou, 2010. "Analyzing the prices of the most expensive sheet iron all over the world: Modeling, prediction and regime change," Papers 1001.3176, arXiv.org.
    • Handle: RePEc:arx:papers:1001.3176
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    References listed on IDEAS

    as
    1. Xie, Dong-Fan & Gao, Zi-You & Zhao, Xiao-Mei & Li, Ke-Ping, 2009. "Characteristics of mixed traffic flow with non-motorized vehicles and motorized vehicles at an unsignalized intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(10), pages 2041-2050.
    2. Tang, T.Q. & Huang, H.J. & Gao, Z.Y. & Wong, S.C., 2007. "Interactions of waves in the speed-gradient traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 481-489.
    3. Zhou, Wei-Xing & Sornette, Didier, 2004. "Antibubble and prediction of China's stock market and real-estate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(1), pages 243-268.
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    Cited by:

    1. Singfat Chu, 2014. "Mitigating supply and price volatilities in Singapore’s vehicle quota system," Transportation, Springer, vol. 41(5), pages 1119-1134, September.
    2. Chu, Singfat, 2012. "Allocation flexibility and price efficiency within Singapore’s Vehicle Quota System," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1541-1550.
    3. Yang, Xiaofang & Jin, Wen & Jiang, Hai & Xie, Qianyan & Shen, Wei & Han, Weijian, 2017. "Car ownership policies in China: Preferences of residents and influence on the choice of electric cars," Transport Policy, Elsevier, vol. 58(C), pages 62-71.
    4. Yu, De-Ping & Li, Zhi-Chun, 2023. "Income distribution, implementation sequence, and equity in auto ownership rationing," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 59-89.
    5. Suwei Feng & Qiang Li, 2018. "Evaluating the car ownership control policy in Shanghai: a structural vector auto-regression approach," Transportation, Springer, vol. 45(1), pages 205-232, January.

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