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The Impact of Monetary Policy on Agricultural Price Index in China: A FAVAR Approach

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  • Tan, Ying
  • Sha, Wenbiao
  • Paudel, Krishna

Abstract

We use recently available Chinese data from 2005m1 to 2016m2 to examine the impact of monetary policy on agricultural price using a factor-augmented vector autoregressive (FAVAR) model proposed by Bernanke et al. (2005). Results show the superiority of a FAVAR model with three variables and three factors over other specifications. Impulse response functions show that both money supply and interest rate have no impact on agricultural price in the long-run (beyond 50 months). However, results indicate the considerable short-run impact of monetary policy on agricultural price. According to forecasting error variance decompositions, the interest rate could account more for the fluctuations in agricultural price than the money supply.

Suggested Citation

  • Tan, Ying & Sha, Wenbiao & Paudel, Krishna, 2017. "The Impact of Monetary Policy on Agricultural Price Index in China: A FAVAR Approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252676, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saea17:252676
    DOI: 10.22004/ag.econ.252676
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    1. YU Xiaohua & ZHAO Guoqing, 2009. "Chinese agricultural development in 30 years: A literature review," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 4(4), pages 633-648, December.
    2. Chambers, Robert G. & Just, Richard E., 1982. "An investigation of the effect of monetary factors on agriculture," Journal of Monetary Economics, Elsevier, vol. 9(2), pages 235-247.
    3. Jun Yang & Huanguang Qiu & Jikun Huang & Scott Rozelle, 2008. "Fighting global food price rises in the developing world: the response of China and its effect on domestic and world markets," Agricultural Economics, International Association of Agricultural Economists, vol. 39(s1), pages 453-464, November.
    4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    5. Fernald, John G. & Spiegel, Mark M. & Swanson, Eric T., 2014. "Monetary policy effectiveness in China: Evidence from a FAVAR model," Journal of International Money and Finance, Elsevier, vol. 49(PA), pages 83-103.
    6. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
    7. Jeffrey H. Dorfman & William D. Lastrapes, 1996. "The Dynamic Responses of Crop and Livestock Prices to Money-Supply Shocks: A Bayesian Analysis Using Long-Run Identifying Restrictions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(3), pages 530-541.
    8. David Orden & Paul L. Fackler, 1989. "Identifying Monetary Impacts on Agricultural Prices in VAR Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 495-502.
    9. Xu, Miao & Orden, David, 2002. "Exchange Rate Effects On Canadian/U.S. Agricultural Prices," 2002 Annual meeting, July 28-31, Long Beach, CA 19886, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Kneip, Alois & Sickles, Robin C. & Song, Wonho, 2012. "A New Panel Data Treatment For Heterogeneity In Time Trends," Econometric Theory, Cambridge University Press, vol. 28(3), pages 590-628, June.
    11. Awokuse, Titus O., 2005. "Impact of Macroeconomic Policies on Agricultural Prices," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 34(2), pages 1-12, October.
    12. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    13. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    14. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    15. Sayed H. Saghaian & Michael R. Reed & Mary A. Marchant, 2002. "Monetary Impacts and Overshooting of Agricultural Prices in an Open Economy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 90-103.
    16. Orden, David, 2002. "Exchange Rate Effects On Agricultural Trade," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 34(2), pages 1-10, August.
    17. Dae-Heum Kwon & Won W. Koo, 2009. "Interdependence of Macro and Agricultural Economics: How Sensitive is the Relationship?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1194-1200.
    18. Tweeten, Luther G., 1980. "An Economic Investigation Into Inflation Passthrough To The Farm Sector," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 5(2), pages 1-18, December.
    19. He, Qing & Leung, Pak-Ho & Chong, Terence Tai-Leung, 2013. "Factor-augmented VAR analysis of the monetary policy in China," China Economic Review, Elsevier, vol. 25(C), pages 88-104.
    20. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    21. G. Edward Schuh, 1974. "The Exchange Rate and U. S. Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 56(1), pages 1-13.
    22. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
    23. Yu, Xiaohua, 2014. "Monetary easing policy and long-run food prices: Evidence from China," Economic Modelling, Elsevier, vol. 40(C), pages 175-183.
    24. Orden, David, 1986. "Money and Agriculture: The Dynamics of Money Financial Market-Agricultural Trade Linkages," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 38(3), pages 1-15.
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    Demand and Price Analysis; Research Methods/ Statistical Methods;

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