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Sectoral shocks, production linkages, and business cycles in China11We sincerely thank the associate editor, Kang Shi, and two anonymous referees for their invaluable suggestions and comments. Their contributions have been truly significant to this project. Any remaining errors are ours

Author

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  • Jiang, Lunan
  • Kim, Young Sik
  • Zhang, Lin

Abstract

This paper develops a dynamic multisector model to examine the contribution of sectoral productivity shocks and input-output linkages to the dynamics of the Chinese economy. Our baseline simulations replicate the volatility and comovement in the data fairly well. More importantly, we show that the idiosyncratic components of sectoral productivity shocks together with the production linkages are the primary drivers of volatility and comovement, while the common components of sectoral productivity shocks mainly result in resource reallocation across sectors through substitution effects. The sensitivity analysis highlights the importance of elasticity-of-substitution parameters. Finally, the share of state-owned enterprises in each sector is shown to have significant impact on the aggregate volatility.

Suggested Citation

  • Jiang, Lunan & Kim, Young Sik & Zhang, Lin, 2024. "Sectoral shocks, production linkages, and business cycles in China11We sincerely thank the associate editor, Kang Shi, and two anonymous referees for their invaluable suggestions and comments. Their c," China Economic Review, Elsevier, vol. 87(C).
  • Handle: RePEc:eee:chieco:v:87:y:2024:i:c:s1043951x24001007
    DOI: 10.1016/j.chieco.2024.102211
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    References listed on IDEAS

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    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2017. "Microeconomic Origins of Macroeconomic Tail Risks," American Economic Review, American Economic Association, vol. 107(1), pages 54-108, January.
    3. Enghin Atalay, 2017. "How Important Are Sectoral Shocks?," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 254-280, October.
    4. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
    5. Huffman, Gregory W. & Wynne, Mark A., 1999. "The role of intratemporal adjustment costs in a multisector economy," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 317-350, April.
    6. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    7. Daron Acemoglu & Ufuk Akcigit & William Kerr, 2016. "Networks and the Macroeconomy: An Empirical Exploration," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 273-335.
    8. Mario Forni & Lucrezia Reichlin, 1998. "Let's Get Real: A Factor Analytical Approach to Disaggregated Business Cycle Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 453-473.
    9. David Rezza Baqaee & Emmanuel Farhi, 2019. "The Macroeconomic Impact of Microeconomic Shocks: Beyond Hulten's Theorem," Econometrica, Econometric Society, vol. 87(4), pages 1155-1203, July.
    10. Daoju Peng & Kang Shi & Juanyi Xu & Yue Zhou, 2020. "SOE and Chinese Real Business Cycle," Annals of Economics and Finance, Society for AEF, vol. 21(2), pages 415-469, November.
    11. Liu, Zheng & Spiegel, Mark M. & Zhang, Jingyi, 2021. "Optimal capital account liberalization in China," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 1041-1061.
    12. Dupor, Bill, 1999. "Aggregation and irrelevance in multi-sector models," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 391-409, April.
    13. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
    14. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    15. Miranda-Pinto, Jorge & Young, Eric R., 2019. "Comparing dynamic multisector models," Economics Letters, Elsevier, vol. 181(C), pages 28-32.
    16. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
    17. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    18. Horvath, Michael, 2000. "Sectoral shocks and aggregate fluctuations," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 69-106, February.
    19. Michael Horvath, 1998. "Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(4), pages 781-808, October.
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    More about this item

    Keywords

    Dynamic multisector model; Input-output; Aggregate fluctuation; Sector interaction; State-owned enterprises; Chinese economy;
    All these keywords.

    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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