IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v116y2022ics0264999322002383.html
   My bibliography  Save this article

Price connectedness and input–output linkages: Evidence from China

Author

Listed:
  • Jia, Yanyan
  • Fang, Yi
  • Jing, Zhongbo
  • Lin, Faqin

Abstract

In contrast to the aggregate level, prices at the industry level are flexible. Meanwhile, the majority of the studies on price connectedness through production networks have focused on the supply side and direct transmission, with less attention on the demand side and indirect transmission of price. Thus, this study constructs a network model and analyzes the spillover effect of price at the industry level by using China's supply-side producer price index and demand-side consumer price index from 2007 to 2019. The results show that the spillover effect from the supply-side price to the demand-side price is larger than vice versa. As for the other findings, direct input–output linkages between industries increase the intensity of price spillovers, while the aggregate effect of indirect price transmission has a greater influence on price connectedness than the effect of direct price transmission.

Suggested Citation

  • Jia, Yanyan & Fang, Yi & Jing, Zhongbo & Lin, Faqin, 2022. "Price connectedness and input–output linkages: Evidence from China," Economic Modelling, Elsevier, vol. 116(C).
    • Handle: RePEc:eee:ecmode:v:116:y:2022:i:c:s0264999322002383
    DOI: 10.1016/j.econmod.2022.105997
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999322002383
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2022.105997?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter J. Klenow & Oleksiy Kryvtsov, 2008. "State-Dependent or Time-Dependent Pricing: Does it Matter for Recent U.S. Inflation?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(3), pages 863-904.
    2. Raphael A. Auer & Andrei A. Levchenko & Philip Sauré, 2019. "International Inflation Spillovers through Input Linkages," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 507-521, July.
    3. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    4. Enghin Atalay, 2017. "How Important Are Sectoral Shocks?," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(4), pages 254-280, October.
    5. 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.
    6. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    7. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    8. Daron Acemoglu & Pablo D. Azar, 2020. "Endogenous Production Networks," Econometrica, Econometric Society, vol. 88(1), pages 33-82, January.
    9. Szafranek, Karol, 2021. "Evidence on time-varying inflation synchronization," Economic Modelling, Elsevier, vol. 94(C), pages 1-13.
    10. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
    11. Hafedh Bouakez & Emanuela Cardia & Francisco J. Ruge-Murcia, 2009. "The Transmission Of Monetary Policy In A Multisector Economy," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1243-1266, November.
    12. 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.
    13. Colclough, William G. & Lange, Mark D., 1982. "Empirical evidence of causality from consumer to wholesale prices," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 379-384, August.
    14. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    15. Vasco M. Carvalho & Alireza Tahbaz-Salehi, 2019. "Production Networks: A Primer," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 635-663, August.
    16. Nguyen, Linh Xuan Diep & Mateut, Simona & Chevapatrakul, Thanaset, 2020. "Business-linkage volatility spillovers between US industries," Journal of Banking & Finance, Elsevier, vol. 111(C).
    17. Tiwari, Aviral Kumar, 2012. "An empirical investigation of causality between producers' price and consumers' price indices in Australia in frequency domain," Economic Modelling, Elsevier, vol. 29(5), pages 1571-1578.
    18. Messner, Jakob W. & Pinson, Pierre, 2019. "Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1485-1498.
    19. Jochen Meyer & Stephan von Cramon‐Taubadel, 2004. "Asymmetric Price Transmission: A Survey," Journal of Agricultural Economics, Wiley Blackwell, vol. 55(3), pages 581-611, November.
    20. Emi Nakamura & Jón Steinsson, 2008. "Five Facts about Prices: A Reevaluation of Menu Cost Models," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(4), pages 1415-1464.
    21. Lucas, Robert E., 1977. "Understanding business cycles," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 5(1), pages 7-29, January.
    22. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    23. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    24. Alan Greenspan, 2004. "Risk and Uncertainty in Monetary Policy," American Economic Review, American Economic Association, vol. 94(2), pages 33-40, May.
    25. Chambers, Marcus J & Bailey, Roy E, 1996. "A Theory of Commodity Price Fluctuations," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 924-957, October.
    26. Tiwari, Aviral Kumar & Suresh K.G., & Arouri, Mohamed & Teulon, Frédéric, 2014. "Causality between consumer price and producer price: Evidence from Mexico," Economic Modelling, Elsevier, vol. 36(C), pages 432-440.
    27. Barauskaite, Kristina & Nguyen, Anh D.M., 2021. "Global intersectoral production network and aggregate fluctuations," Economic Modelling, Elsevier, vol. 102(C).
    28. Ivo da Rocha Lima Filho, Roberto, 2019. "Does PPI lead CPI IN Brazil?," International Journal of Production Economics, Elsevier, vol. 214(C), pages 73-79.
    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. Ernesto Pasten & Raphael S. Schoenle & Michael Weber & Michael Weber, 2017. "Price Rigidities and the Granular Origins of Aggregate Fluctuations," CESifo Working Paper Series 6619, CESifo.
    2. Ernesto Pasten & Raphael Schoenle & Michael Weber, 2017. "Price Rigidity and the Origins of Aggregate Fluctuations," NBER Working Papers 23750, National Bureau of Economic Research, Inc.
    3. repec:zbw:bofrdp:2018_003 is not listed on IDEAS
    4. Pasten, Ernesto & Schoenle, Raphael & Weber, Michael, 2017. "Price rigidities and the granular origins of aggregate fluctuations," Working Paper Series 2102, European Central Bank.
    5. Frank Smets & Joris Tielens & Jan Van Hove, 2018. "Pipeline Pressures and Sectoral Inflation Dynamics," Working Paper Research 351, National Bank of Belgium.
    6. N. Melisa Bilgin & Kamil Yilmaz, 2018. "Producer Price Inflation Connectedness and Input-Output Networks," Koç University-TUSIAD Economic Research Forum Working Papers 1813, Koc University-TUSIAD Economic Research Forum.
    7. Emi Nakamura & Jón Steinsson, 2010. "Monetary Non-neutrality in a Multisector Menu Cost Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 961-1013.
    8. Dong, Feng & Wen, Yi, 2019. "Long and Plosser meet Bewley and Lucas," Journal of Monetary Economics, Elsevier, vol. 102(C), pages 70-92.
    9. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    10. Erik Frohm & Vanessa Gunnella, 2021. "Spillovers in global production networks," Review of International Economics, Wiley Blackwell, vol. 29(3), pages 663-680, August.
    11. Mundt, Philipp, 2021. "The formation of input–output architecture: Evidence from the European Union," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 89-104.
    12. Jennifer La'O & Alireza Tahbaz‐Salehi, 2022. "Optimal Monetary Policy in Production Networks," Econometrica, Econometric Society, vol. 90(3), pages 1295-1336, May.
    13. Ghassibe, Mishel, 2021. "Monetary policy and production networks: an empirical investigation," Journal of Monetary Economics, Elsevier, vol. 119(C), pages 21-39.
    14. Shutao Cao & Wei Dong, 2019. "Production Networks and the Propagation of Commodity Price Shocks," 2019 Meeting Papers 612, Society for Economic Dynamics.
    15. Seyit Kerimkhulle & Natalia Obrosova & Alexander Shananin & Gulmira Azieva, 2022. "The Nonlinear Model of Intersectoral Linkages of Kazakhstan for Macroeconomic Decision-Making Processes in Sustainable Supply Chain Management," Sustainability, MDPI, vol. 14(21), pages 1-21, November.
    16. Buchen, Teresa, 2014. "News Media, Common Information, and Sectoral Comovement," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100391, Verein für Socialpolitik / German Economic Association.
    17. Pasten, Ernesto & Schoenle, Raphael & Weber, Michael, 2020. "The propagation of monetary policy shocks in a heterogeneous production economy," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 1-22.
    18. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," Energy Economics, Elsevier, vol. 128(C).
    19. Carlos Carvalho & Niels Arne Dam & Jae Won Lee, 2020. "The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 162-179, March.
    20. Váry, Miklós, 2021. "The long-run real effects of monetary shocks: Lessons from a hybrid post-Keynesian-DSGE-agent-based menu cost model," Economic Modelling, Elsevier, vol. 105(C).
    21. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.

    More about this item

    Keywords

    Price connectedness; Supply-side price; Demand-side price; Direct transmission; Indirect transmission;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:eee:ecmode:v:116:y:2022:i:c:s0264999322002383. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.