IDEAS home Printed from https://ideas.repec.org/a/spr/jecstr/v12y2023i1d10.1186_s40008-023-00313-y.html
   My bibliography  Save this article

Monetary shocks and production network in the G7 countries

Author

Listed:
  • Mihaela Simionescu

    (University of Bucharest
    Romanian Academy)

  • Nicolas Schneider

    (The London School of Economics and Political Science)

Abstract

Understanding the structure and properties of production networks is essential to identify the transmission channels from monetary shocks. While growingly studied, this literature keeps displaying critical caveats from which the investigation of G-7 economies is not spared. To fill this gap, this paper applies a version of Time-Varying Parameters Bayesian Vector-Autoregressions models (TVP-VAR) and investigates the responses of production networks (upstream and downstream dynamics) to endogeneous monetary shocks on key macro-level indicators (GDP, GDP deflator, exchange rate, short-term and long-term interest rates). Two distinct time-lengths are considered: a test (i.e., 2000–2014) and a treated period (i.e., 2007–2009,”the Great Recession”). Prior, key statistical conditions are checked using a stepwise stationary testing framework including the Kwiatkowski–Phillips–Schmidt–Shin (Kapetanios et al. in J Economet 112(2):359–379, 2003—KPSS) and panel Breitung (Nonstationary panels, panel cointegration, and dynamic panels. Emerald Group Publishing Limited, London, 2001) unit root tests; followed by the Pesaran (General diagnostic tests for cross section dependence in panels, 2004) Cross-sectional Dependence (CD) test; and the Im–Pesaran–Shin (Im et al. in J Economet 115(1):53–74, 2003—IPS) test for unit root in the presence of heterogenous slope coefficients. Panel Auto-Regressive Distributed Lag Mean Group estimates (PARDL-MG) offer interesting short- and long-run monetary shocks-production networks response functions, stratified by country and sector. Findings clearly indicate that upstreamness forces dominated downstremness dynamics during the period 2000–2014, whereas the financial sector ermeges as the clear transmission channel through which monetary shocks affected the productive economy during the Great Recession. In general, we conclude that the prioduction structure influences the transmission of monetary shocks in the G-7 economies. Adequate policy implications are supplied, along with a methodological note on the forecasting potential of TVP-VAR methodologies when dealing with series exhibiting structural breaks.

Suggested Citation

  • Mihaela Simionescu & Nicolas Schneider, 2023. "Monetary shocks and production network in the G7 countries," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-32, December.
    • Handle: RePEc:spr:jecstr:v:12:y:2023:i:1:d:10.1186_s40008-023-00313-y
    DOI: 10.1186/s40008-023-00313-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40008-023-00313-y
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s40008-023-00313-y?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ronald E. Miller & Umed Temurshoev, 2017. "Output Upstreamness and Input Downstreamness of Industries/Countries in World Production," International Regional Science Review, , vol. 40(5), pages 443-475, September.
    2. Pesaran, M.H. & Shin, Y., 1995. "An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis," Cambridge Working Papers in Economics 9514, Faculty of Economics, University of Cambridge.
    3. Heathcote, Jonathan & Perri, Fabrizio, 2002. "Financial autarky and international business cycles," Journal of Monetary Economics, Elsevier, vol. 49(3), pages 601-627, April.
    4. Emmanuel Dhyne & Ayumu Ken Kikkawa & Magne Mogstad & Felix Tintelnot, 2021. "Trade and Domestic Production Networks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(2), pages 643-668.
    5. 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.
    6. Carlos Carvalho & Jae Won Lee & Woong Yong Park, 2021. "Sectoral Price Facts in a Sticky-Price Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 216-256, January.
    7. Jörg Breitung & Samarjit Das, 2005. "Panel unit root tests under cross‐sectional dependence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 414-433, November.
    8. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    9. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    10. Jean-Noël Barrot & Julien Sauvagnat, 2016. "Input Specificity and the Propagation of Idiosyncratic Shocks in Production Networks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1543-1592.
    11. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    12. Basile Grassi & Julien Sauvagnat, 2019. "Production networks and economic policy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 35(4), pages 638-677.
    13. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    14. Xavier Gabaix, 2011. "The Granular Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 79(3), pages 733-772, May.
    15. 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.
    16. Emmanuel Dhyne & Ayumu Ken Kikkawa & Magne Mogstad & Felix Tintelnot, 2021. "Trade and Domestic Production Networks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(2), pages 643-668.
    17. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1148-1171, October.
    18. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
    19. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    20. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, September.
    21. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    22. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    23. Ghassibe, Mishel, 2021. "Monetary policy and production networks: an empirical investigation," Journal of Monetary Economics, Elsevier, vol. 119(C), pages 21-39.
    24. Vasco Carvalho, 2007. "Aggregate fluctuations and the network structure of intersectoral trade," Economics Working Papers 1206, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2010.
    25. Cushman, David O. & Michael, Nils, 2011. "Nonlinear trends in real exchange rates: A panel unit root test approach," Journal of International Money and Finance, Elsevier, vol. 30(8), pages 1619-1637.
    26. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    27. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    28. Caraiani, Petre & Dutescu, Adriana & Hoinaru, Răzvan & Stănilă, Georgiana Oana, 2020. "Production network structure and the impact of the monetary policy shocks: Evidence from the OECD," Economics Letters, Elsevier, vol. 193(C).
    29. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LLC, vol. 12(1), pages 61-71, March.
    30. Liddle, Brantley, 2015. "What Are the Carbon Emissions Elasticities for Income and Population? Bridging STIRPAT and EKC via robust heterogeneous panel estimates," MPRA Paper 61304, University Library of Munich, Germany.
    31. 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.
    32. McNerney, James & Fath, Brian D. & Silverberg, Gerald, 2013. "Network structure of inter-industry flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6427-6441.
    33. 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.
    34. Bekiros, Stelios, 2014. "Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area," Economic Modelling, Elsevier, vol. 38(C), pages 619-626.
    35. Rafael E. De Hoyos & Vasilis Sarafidis, 2006. "Testing for cross-sectional dependence in panel-data models," Stata Journal, StataCorp LLC, vol. 6(4), pages 482-496, December.
    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. Mihaela Simionescu & Nicolas Schneider & Beata Gavurova, 2024. "A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus," Journal of Applied Economics, Taylor & Francis Journals, vol. 27(1), pages 2395114-239, December.
    2. Schneider, Nicolas & Strielkowski, Wadim, 2023. "Modelling the unit root properties of electricity data—A general note on time-domain applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    3. Frank Smets & Joris Tielens & Jan Van Hove, 2018. "Pipeline Pressures and Sectoral Inflation Dynamics," Working Paper Research 351, National Bank of Belgium.
    4. 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.
    5. 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.
    6. Ghassibe, Mishel, 2021. "Monetary policy and production networks: an empirical investigation," Journal of Monetary Economics, Elsevier, vol. 119(C), pages 21-39.
    7. repec:zbw:bofrdp:2018_003 is not listed on IDEAS
    8. Pasten, Ernesto & Schoenle, Raphael & Weber, Michael, 2017. "Price rigidities and the granular origins of aggregate fluctuations," Working Paper Series 2102, European Central Bank.
    9. Belaïd, Fateh & Zrelli, Maha Harbaoui, 2019. "Renewable and non-renewable electricity consumption, environmental degradation and economic development: Evidence from Mediterranean countries," Energy Policy, Elsevier, vol. 133(C).
    10. Nicolas Schneider & Avik Sinha, 2023. "Better clean or efficient? Panel regressions," Climatic Change, Springer, vol. 176(8), pages 1-24, August.
    11. 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.
    12. Jae Won Lee & Seunghyeon Lee, 2025. "Monetary Non-Neutrality in a Multisector Economy: The Role of Risk-Sharing," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 55, January.
    13. Tiba, Sofien & Belaid, Fateh, 2020. "The pollution concern in the era of globalization: Do the contribution of foreign direct investment and trade openness matter?," Energy Economics, Elsevier, vol. 92(C).
    14. Acar, Pinar & Berk, Istemi, 2022. "Power infrastructure quality and industrial performance: A panel data analysis on OECD manufacturing sectors," Energy, Elsevier, vol. 239(PC).
    15. Saqib, Najia & Ozturk, Ilhan & Sharif, Arshian & Cichoń, Dariusz, 2024. "Enhancing sustainable energy: Mineral exports, financial development, and foreign investment can build a greener future?," Resources Policy, Elsevier, vol. 97(C).
    16. Ernest Liu & Aleh Tsyvinski, 2021. "Dynamical Structure and Spectral Properties of Input-Output Networks," Working Papers 2021-13, Princeton University. Economics Department..
    17. Emmanuel Dhyne & Ayumu Ken Kikkawa & Glenn Magerman, 2022. "Imperfect Competition in Firm-to-Firm Trade," Journal of the European Economic Association, European Economic Association, vol. 20(5), pages 1933-1970.
    18. Längle, Katharina & Xu, Ankai & Tian, Ruijie, 2021. "Assessing the supply chain effect of natural disasters: Evidence from Chinese manufacturers," WTO Staff Working Papers ERSD-2021-13, World Trade Organization (WTO), Economic Research and Statistics Division.
    19. Trofimov, Ivan D., 2020. "Is There a J-Curve Effect in the Services Trade in Canada? A Panel Data Analysis," MPRA Paper 106704, University Library of Munich, Germany.
    20. Chen, Sihao, 2025. "International production networks and the propagation of financial shocks," Journal of International Economics, Elsevier, vol. 153(C).
    21. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization Institute Working Papers 153, Federal Reserve Bank of Dallas.

    More about this item

    Keywords

    Production network; Monetary policy shocks; Panel ARDL model; Bayesian VAR model;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:spr:jecstr:v:12:y:2023:i:1:d:10.1186_s40008-023-00313-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.