The Italian value chain in the pandemic: the input–output impact of Covid-19 lockdown
Tóm tắt
This paper investigates the role of the domestic value chain in transmitting the economic impact of Covid-19 lockdown measures. By employing techniques of complex networks analysis and input–output traditional tools, the study identifies those sectors that are key in the complex structure of the Italian supply chain and provides different rankings of the most ‘systemically important’ industries involved in the Covid-19 lockdown. The results suggest that by stopping the production process of many key sectors, the lockdown has led to a drop in input and output that, in turn, has generated a lock of about 52% of total circulating value added, 30% of which has been locked within indirect value chains. Further, by adding sectoral physical proximity indexes to the scenarios analysis, the method developed here provides a tool to guide governments in designing safe and efficient reopening policies.
Tài liệu tham khảo
Acemoglu, D., Carvalho, V., Ozdaglar, A., & Tahbez-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977–2016. https://doi.org/10.3982/ECTA9623.
Barbieri, T., Basso G., & Scicchitano S. (2020). Italian workers at risk during the Covid-19 epidemic, INAPP working paper, 46.
Baqaee, D. R., & Farhi, E. (2020a). Nonlinear production networks with an application to the Covid-19 crisis. Mimeo. Cambridge: UCLA and Harvard.
Baqaee, D. R., & Farhi, E. (2020b). Supply and demand in disaggregated keynesian economies with an application to the Covid-19 crisis. Mimeo. Cambridge: UCLA and Harvard.
Bank of Italy. (2020). Economic Bulletin N° 2, 17 April 2020. https://www.bancaditalia.it/pubblicazioni/bollettino-economico/2020-2/
Barrot, J.-N., Grassi, B., & Sauvagnat, J. (2020). Sectoral effects of social distancing. Covid Economics, 3, 85–102.
Bonadio, B., Huo, Z., Levchenko, A.A., Nitya, P.-N. (2020). Global supply chains in the pandemic. CEPR DP14766.
Bootsma, M. C. J., & Ferguson, N. M. (2007). The effect of public health measures on the 1918 influenza pandemic in US cities. Proceedings of the National Academy of Sciences, 104(18), 7588–7593.
Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer Networks, 30, 107–117. https://doi.org/10.1016/S0169-7552(98)00110-X.
Caracciolo, G., Cingano, F., Ercolani, V., Ferrero, G., Hassan, F., Papetti, A., Tommasino, P. (2020). Covid-19 and economic analysis: A review of the debate. Banca D’Italia, Literature Review Issue no. 2. https://www.bancaditalia.it/media/notizie/2020/Covid-literature-newsletter-n2.pdf. Accessed 30 Apr 2020.
Carvalho, V. M. (2014). From micro to macro via production networks. Journal of Economic Perspectives, 28(4), 23–48. https://doi.org/10.1257/jep.28.4.23.
Cerina, F., Zhu, Z., Chessa, A., & Riccaboni, M. (2015). World input–output network. PLoS ONE, 10(7), e0134025. https://doi.org/10.1371/journal.pone.0134025.
Dietzenbacher, E., & Lahr, M. L. (2013). Expanding extractions. Economic Systems Research, 25, 341–360. https://doi.org/10.1080/09535314.2013.774266.
Fana, M., Tolan, S., Torrejón, S., Urzi Brancati, C., & Fernández-Macías, E. (2020). The COVID confinement measures and EU labour markets. Brussels: Publications Office of the European Union.
Garbellini, N., & Wirkierman, A. L. (2014). Blocks and circularity in labour requirements: An interplay between clusters and subsystems in the EU. Structural Change and Economic Dynamics, Elsevier, 28(C), 60–74.
Giammetti, R., Russo, A., & Gallegati, M. (2020). Key sectors in input–output production networks: An application to Brexit. World Economy, 43, 840–870. https://doi.org/10.1111/twec.12920.
Giammetti, R. (2020). Tariffs, domestic import substitution and trade diversion in input–output production networks: An exercise on Brexit. Economic Systems Research. https://doi.org/10.1080/09535314.2020.1738347.
Hatchett, R. J., Mecher, C. E., & Lipsitch, M. (2007). Public health interventions and epidemic intensity during the 1918 influenza pandemic. Proceedings of the National Academy of Sciences of the United States of America, 104(18), 75827.
Markel, H., Lipman, H. B., Navarro, J. A., Sloan, A., Michalsen, J. R., Minna Stern, A., et al. (2007). Nonpharmaceutical interventions implemented by US cities during the 1918–1919 influenza pandemic. Journal of the American Medical Association, 298(6), 644–654.
Miller, R. E., & Blair, P. D. (2009). Input–output analysis; foundations and extensions (2nd ed.). Cambridge: Cambridge University Press.
Miller, R. E., & Lahr, M. L. (2001). A taxonomy of extractions. In M. L. Lahr & R. E. Miller (Eds.), Regional science perspectives in economic analysis (pp. 407–441). Amsterdam: Elsevier Science.
OECD. (2020). Evaluating the initial impact of covid-19 containment measures on economic activity. OECD technical report, April 2020. https://www.read.oecd-ilibrary.org/view/?ref=126_126496-evgsi2gmqj&title=Evaluating_the_initial_impact_of_COVID-19_containment_measures_on_economic_activity. Accessed 14 Apr 2020.
Palomino, J. C., Rodríguez, J. G., & Sebastian, R. (2020). Wage inequality and poverty effects of lockdown and social distancing in Europe. Covid Economics, 25, 186–229.
Wren-Lewis, S. (2020). The economic effects of a pandemic. In R. Baldwin & B. Weder di Mauro (Eds.), Economics in the time of COVID-19 (pp. 109–112). Oxford: CEPR Press.