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Illuminating the Effects of the US-China Tariff War on China's Economy

Author

Listed:
  • Davin Chor
  • Bingjing Li

Abstract

How much has the US-China tariff war impacted economic outcomes in China? We address this question using high-frequency night lights data, together with measures of the trade exposure of fine grid locations constructed from Chinese firms' geo-coordinates. Exploiting within-grid variation over time and controlling extensively for grid-specific contemporaneous trends, we find that each 1 percentage point increase in exposure to the US tariffs was associated with a 0.59% reduction in night-time luminosity. We combine these with structural elasticities that relate night lights to economic outcomes, motivated by the statistical framework of Henderson et al. (2012). The negative impact of the tariff war was highly skewed across locations: While grids with negligible direct exposure to the US tariffs accounted for up to 70% of China's population, we infer that the 2.5% of the population in grids with the largest US tariff shocks saw a 2.52% (1.62%) decrease in income per capita (manufacturing employment) relative to unaffected grids. By contrast, we do not find significant effects from China's retaliatory tariffs.

Suggested Citation

  • Davin Chor & Bingjing Li, 2021. "Illuminating the Effects of the US-China Tariff War on China's Economy," NBER Working Papers 29349, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29349
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    Cited by:

    1. Cai, Yifei & Mignon, Valérie & Saadaoui, Jamel, 2022. "Not all political relation shocks are alike: Assessing the impacts of US–China tensions on the oil market," Energy Economics, Elsevier, vol. 114(C).
    2. Shapiro, Daniel & Oh, Chang Hoon & Zhang, Peng, 2023. "Nighttime lights data and their implications for IB research," Journal of International Management, Elsevier, vol. 29(5).
    3. Chih‐Hai Yang & Kazunobu Hayakawa, 2023. "The Substitution Effect of US‐China Trade War on Taiwanese Trade," The Developing Economies, Institute of Developing Economies, vol. 61(4), pages 324-341, December.
    4. Chen, Yu-Lun & Mo, Wan-Shin & Qin, Rong-Ling & Yang, J. Jimmy, 2023. "Return spillover across China's financial markets," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    5. Hayakawa,Kazunobu, 2022. "The trade impact of U.S.-China conflict in Southeast Asia," IDE Discussion Papers 873, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    6. Ding, Guanzu & Guo, Guangyuan & Wu, Caiyun & Yu, Jiawen, 2022. "China-US trade friction and welfare: The role of regional trade agreements," Economic Modelling, Elsevier, vol. 113(C).
    7. Lei Wang & Thomas Stephen Ramsey, 2023. "Will falling domestic labor compensation share really be improved when global trade slowdown?," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.

    More about this item

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • F10 - International Economics - - Trade - - - General
    • F13 - International Economics - - Trade - - - Trade Policy; International Trade Organizations
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F16 - International Economics - - Trade - - - Trade and Labor Market Interactions

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