Abstract
This paper quantifies the Chinese consumers’ boycott of Japanese cars that immediately followed the anti-Japanese demonstrations in September 2012. We decompose the total boycott effect into two effects: the transfer effect, which refers to consumers switching from Japanese to non-Japanese brands, and the cancellation effect, which captures decline in sales due to consumers exiting the market. We find that the cancellation effect accounts for more than 90% of the total decline in Japanese car sales, implying a small substitution effect in the automobile market, even though brands of all other countries have benefited. This paper provides evidence of both negative and positive impacts of political conflicts for different market participants and includes analysis with welfare implications.
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Notes
Proxy boycotts can also occur in domestic politics. For example, Cuadras-Morató and Raya (2016) study the boycotts of Catalan sparkling wine in Spain.
Our data also cover the period of the “Senkaku Event” in 2010 that arisen from disputes over the Senkaku Islands, known as Diaoyu Islands in China. However, we find no evidence of negative impact resulted from the 2010 “Senkaku Event” in the Chinese automobile market.
We computed the size of Japanese imported cars as a percentage of “Made in China” Japanese cars using data from UN Comtrade (HS code 8703) and our data and find that imported cars account for less than 10% of Japanese car sales in China.
Studies of the automobile industry are abundant in the economics literature. See, for example, Bandeen (1957), Sheahan (1960), Hess (1977), Berkovec (1985), Bresnahan (1987), Cooper and Haltiwanger (1993), Ries (1993), Berry et al. (1995) and Park (2003), covering a variety of topics. In addition, Depner and Bathelt (2005), Deng and Ma (2010), Luong (2013) and Hu et al. (2014) provide analyses of various aspects of the Chinese automobile industry.
CAAM also reports the sales of Jiaocha cars, which are designed for both cargo and passenger purposes. This type of car is specially designed for the Chinese market, especially in the rural areas. Since they are not general passenger cars, and there is no foreign-brand cars in this category, we exclude them from our sample.
See Heilmann (2016) for more details of the boycotts of Japanese products.
The basic fixed effect regression with common trend is
$$\begin{aligned}Y_{it}=\alpha _{i}+\lambda _{t}+{\hat{\rho }} D_{it}+\varepsilon _{it},\end{aligned}$$while the regression with unique trends is
$$\begin{aligned} Y_{it}=\alpha _{i}+\bar{\lambda _{t}}+ {\tilde{\lambda }}_t D_{it} + {\tilde{\rho }} D_{it}+\varepsilon _{it}, \end{aligned}$$where \(\alpha _{i}\) and \(\lambda _{t}\) indicate the group fixed effect and the time fixed effect and \(D_{it}\) is a dummy variable that equals 1 for the treatment group after policy and 0 otherwise. In the second regression, \(\bar{\lambda _{t}}\) denotes the collection of trends of the non-treatment groups while \(\lambda _t D_{it}\) is the unique trend of the treatment group. With the common trend regression, \({\hat{\rho }}\) gives the estimate of ATE. However, if the unique trend model is the true model, then \({\hat{\rho }}\) would be overestimated because its value is equal to \({\tilde{\lambda }}_t + {\tilde{\rho }}\) from the regression with unique trend.
Please see “Appendix A” for additional detail.
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Acknowledgements
This paper was presented at the Chinese Economists Society 2015 North America Conference, the 2016 CEC Workshop, and seminars at Fudan University and Peking University. We thank conference and seminar participants, especially Le Wang, Zhao Chen, Wei Huang, Lixing Li, Yongqian Li, Pinghan Liang, Tianyang Xi, Yiqing Xu, and Shilin Zheng for their helpful comments.
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Zhou acknowledges financial support from the National Natural Science Foundation of China (Grant Number: 71803064) and the Fundamental Research Funds for the Central Universities of Jinan University (Grant Numbers: 12JNYH002, 12JNKY001, and 15JNQM001).
Appendices
Appendices
1.1 Appendix A
To further separate \({\mathsf {CE}}\) and \({\mathsf {TE}}\) and express them as percentages of total changes in sales, we need information on the substitutability between sales of Japanese cars and other cars. Let \(\delta \) denote the marginal rate of substitution (MRS), which is conditional on the information set \(\varLambda _{t}\); we then have
which may be rewritten into a discrete form asFootnote 11
The MRS, as conventionally defined, measures the substitutability between sales of Japanese versus other cars, based on the information set. We envisioned the information set to contain not only observable market conditions, but also unobservable attitudes of the Chinese customers towards foreign countries especially Japan. There are three main assumptions for the set up of \(\delta \) in Eq. (8). First, consumer preferences are stable. It is especially important that consumers’ attitudes towards Japan are stable, which is arguably true because of the long unhappy history between the two countries. This is also why Eq. (8) does not have a time dimension. Second, non-Japanese and Japanese cars, especially those of similar sizes, are close substitutes, if not perfect substitutes, in the sense that a family may purchase only one car at a time. As a result, the utility function of consumers is a linear combination of consumptions of all cars with a consumer buying the car that gives the highest utility. Last, although price information is unavailable in our data, the prices of new cars in China are stable and can be anticipated almost perfectly. This can be the case because the used car market in China is underdeveloped and most consumers choose to buy new cars from dealership or flagship stores.
1.2 Appendix B
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Luo, Z., Zhou, Y. Decomposing the effects of consumer boycotts: evidence from the anti-Japanese demonstration in China. Empir Econ 58, 2615–2634 (2020). https://doi.org/10.1007/s00181-019-01650-3
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DOI: https://doi.org/10.1007/s00181-019-01650-3