Multi-Scale Assessment of the Economic Impacts of Flooding: Evidence from Firm to Macro-Level Analysis in the Chinese Manufacturing Sector

Abstract

We present an empirical study to systemically estimate flooding impacts, linking across scales from individual firms through to the macro levels in China. To this end, we combine a detailed firm-level econometric analysis of 399,356 firms with a macroeconomic input-output model to estimate flood impacts on China’s manufacturing sector over the period 2003–2010. We find that large flooding events on average reduce firm outputs (measured by labor productivity) by about 28.3% per year. Using an input-output analysis, we estimate the potential macroeconomic impact to be a 12.3% annual loss in total output, which amounts to 15,416 RMB billion. Impacts can propagate from manufacturing firms, which are the focus of our empirical analysis, through to other economic sectors that may not actually be located in floodplains but can still be affected by economic disruptions. Lagged flood effects over the following two years are estimated to be a further 5.4% at the firm level and their associated potential effects are at a 2.3% loss in total output or 2,486 RMB billion at the macro-level. These results indicate that the scale of economic impacts from flooding is much larger than microanalyses of direct damage indicate, thus justifying greater action, at a policy level and by individual firms, to manage flood risk.

A Framework To Estimate Loss And Damage (L&D) To Floods In a Changing Climate, Using Capital-Based Approach

“…Unlike CGE, SAM is linear in structure, provides overestimated impacts, and does not respond to price change (Okuyama, 2008). On the other hand, econometric models which are statistically rigorous and provide stochastic estimates are also used in assessing impacts of floods (Zhang, 2016;Hu et al, 2019). (Motschmann et al, 2020) also assessed the L&D in mountains due to glacier retreat, due to climate change, by considering three dimensions-social impacts of ice loss by perception based survey; glacial hazards by its likelihood, flood extent and magnitude; and variability of water availability by a water balance model.…”

Conversion strategy builds supply chain resilience during the COVID-19 pandemic: A typology and research directions

“…Through interconnected supply chains, trade, and lifeline networks, disaster risks can spread, causing systemic risks [ [3] , [4] , [5] , [6] ]. Supply chain disruptions in the manufacturing sector due to natural hazards have been explored in countries, including China [ 7 ], Japan [ 5 ], Thailand [ 8 ]. Studies are looking at supply chains from the resilience perspective in the context of the COVID-19 pandemic, for instance, in the automotive and airline industries [ 9 ], the fashion industry [ 10 ], additive manufacturing [ 11 ], and others.…”

Downstream Consequences of Ribb River Damming, Lake Tana Basin, Ethiopia

“…According to the international disaster database report, cited by Hu et al (2019), on average, 85 million people were affected per year between 2007 and 2016, with an annual economic loss of 36.7 billion US dollars. It is believed that flood disasters cannot be avoided; however, the associated impacts can be reduced by awareness and preparedness.…”