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Dispersion in macroeconomic volatility between the core and periphery of the international trade network

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  • Chakrabarti, Anindya S.

Abstract

At the country level, macroeconomic volatility tends to correlate with trade openness although the direction of correlation is not stable across samples. Higher openness allows for greater diversification opportunities, but provides lesser immunity from outside shocks. Here I consider trade network as a composite of all pairwise trade linkages to emphasize that different linkages contribute differently to the transmission or mitigation of shocks, and show that volatility is inversely related to centrality, a summary measure of strength of the linkages specific to a country. I study a dynamic multi-country, multi-sector model subject to idiosyncratic liquidity shocks, and characterize volatility as an explicit function of centrality, diversification and the Herfindahl of the trade network in equilibrium. With sufficient skewness in the trade linkages across countries, similar shocks generate substantially different levels of repercussions across the network. The conventional effect of diversification holds true that countries with better diversified trade portfolio fluctuate less. Centrality directly contributes to higher resilience to exogenous shocks, thus reducing volatility. Combined effect of these two mechanisms dominates the opposite effect that a more central country is also more exposed to shocks, which increases volatility. The model calibrated to the EU generates and closely replicates the negative relationship between centrality and volatility. The theoretical model is then extended to capture preference shocks and sparseness of the trade networks.

Suggested Citation

  • Chakrabarti, Anindya S., 2018. "Dispersion in macroeconomic volatility between the core and periphery of the international trade network," Journal of Economic Dynamics and Control, Elsevier, vol. 88(C), pages 31-50.
  • Handle: RePEc:eee:dyncon:v:88:y:2018:i:c:p:31-50
    DOI: 10.1016/j.jedc.2018.01.019
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    Cited by:

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    2. 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.
    3. Yu, Miao & Hu, Xiaolu & Zhong, Angel, 2024. "Network centrality, information diffusion and asset pricing," International Review of Financial Analysis, Elsevier, vol. 93(C).
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    5. Ashish Kumar & Anindya S. Chakrabarti & Anirban Chakraborti & Tushar Nandi, 2020. "Distress propagation on production networks: Coarse-graining and modularity of linkages," Papers 2004.14485, arXiv.org.
    6. Hempfing, Alexander & Mundt, Philipp, 2022. "Tie formation in global production chains," BERG Working Paper Series 181, Bamberg University, Bamberg Economic Research Group.

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    More about this item

    Keywords

    Macroeconomic volatility; Centrality measure; Diffusion process; Network; Markov chain;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • F62 - International Economics - - Economic Impacts of Globalization - - - Macroeconomic Impacts

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