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The relative price of investment goods, the price level, and the "slope puzzle"

Author

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  • Sen Zhang

    (China Economics and Management Academy, Central University of Finance and Economics, Beijing, China)

  • Yangyang Ji

    (China Economics and Management Academy, Central University of Finance and Economics, Beijing, China)

  • Tianye Lin

    (China Economics and Management Academy, Central University of Finance and Economics, Beijing, China)

Abstract

The application of Blanchard and Quah's (1989) method to Chinese data always obtains counterintuitive responses of output and the price level to demand and supply shocks, referred to in the literature as the "slope puzzle." Empirical findings of this paper reveal that the low-frequency movement in the price level causes this puzzle, which arises from the relative price of investment goods, and the friction in China's financial market drives this movement.

Suggested Citation

  • Sen Zhang & Yangyang Ji & Tianye Lin, 2019. "The relative price of investment goods, the price level, and the "slope puzzle"," CEMA Working Papers 609, China Economics and Management Academy, Central University of Finance and Economics.
    • Handle: RePEc:cuf:wpaper:609
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    References listed on IDEAS

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    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    3. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    4. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    5. Cho, Dongchul, 2012. "Aggregate demand gap based on a simple structural VAR model," Economics Letters, Elsevier, vol. 114(2), pages 228-234.
    6. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    7. Chun Chang & Kaiji Chen & Daniel F. Waggoner & Tao Zha, 2016. "Trends and Cycles in China's Macroeconomy," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 1-84.
    8. Carlstrom, Charles T & Fuerst, Timothy S, 1997. "Agency Costs, Net Worth, and Business Fluctuations: A Computable General Equilibrium Analysis," American Economic Review, American Economic Association, vol. 87(5), pages 893-910, December.
    9. Cover, James Peery & Enders, Walter & Hueng, C. James, 2006. "Using the Aggregate Demand-Aggregate Supply Model to Identify Structural Demand-Side and Supply-Side Shocks: Results Using a Bivariate VAR," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(3), pages 777-790, April.
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    Cited by:

    1. Wan, Cihang & Ji, Yangyang & Luo, Youliang & Zhang, Tianyu, 2022. "AS-AD Curves: An Analysis Using the BQ and OLS Methods," MPRA Paper 113437, University Library of Munich, Germany.

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