IDEAS home Printed from https://ideas.repec.org/p/ags/saea17/252676.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/252676/files/SAEA%20-%20TanShaPaudel.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.252676?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roman Matkovskyy, 2016. "A comparison of pre- and post-crisis efficiency of OECD countries: evidence from a model with temporal heterogeneity in time and unobservable individual effect," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(2), pages 135-167, December.
    2. Sebastian Linde, 2023. "Hospital cost efficiency: an examination of US acute care inpatient hospitals," International Journal of Health Economics and Management, Springer, vol. 23(3), pages 325-344, September.
    3. Md Rafayet Alam & Scott Gilbert, 2017. "Monetary policy shocks and the dynamics of agricultural commodity prices: evidence from structural and factor†augmented VAR analyses," Agricultural Economics, International Association of Agricultural Economists, vol. 48(1), pages 15-27, January.
    4. Anthony N. Rezitis, 2015. "Empirical Analysis of Agricultural Commodity Prices, Crude Oil Prices and US Dollar Exchange Rates using Panel Data Econometric Methods," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 851-868.
    5. Yu, Xiaohua, 2014. "Monetary easing policy and long-run food prices: Evidence from China," Economic Modelling, Elsevier, vol. 40(C), pages 175-183.
    6. Barigozzi, Matteo & Lippi, Marco & Luciani, Matteo, 2021. "Large-dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) cointegrated factors," Journal of Econometrics, Elsevier, vol. 221(2), pages 455-482.
    7. Ouerk, Salima & Boucher, Christophe & Lubochinsky, Catherine, 2020. "Unconventional monetary policy in the Euro Area: Shadow rate and light effets," Journal of Macroeconomics, Elsevier, vol. 65(C).
    8. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    9. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    10. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    11. Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
    12. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    13. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    14. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    15. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    16. Forni, Mario & Cavicchioli, Maddalena & Lippi, Marco & Zaffaroni, Paolo, 2016. "Eigenvalue Ratio Estimators for the Number of Common Factors," CEPR Discussion Papers 11440, C.E.P.R. Discussion Papers.
    17. Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min, 2017. "Risk evaluations with robust approximate factor models," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 244-264.
    18. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.
    19. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    20. Mouloud El Hafidi & Marouane Daoui, 2019. "Chocs de la politique monétaire et croissance économique au Maroc : une approche en terme de modèles FAVAR," Post-Print hal-03311354, HAL.

    More about this item

    Keywords

    Demand and Price Analysis; Research Methods/ Statistical Methods;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:saea17:252676. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/saeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.