A minimum-disruption approach to input–output disaster analysis

ABSTRACT

The frequency of disasters has been increasing over the past decades, fuelled by natural phenomena and climate-related events. Policymakers require robust methodologies to assess supply-chain impacts of disasters. Input–output-based disaster approaches are able to assess such impacts; however, they rely on some assumptions, such as the fixed production-recipe assumption for industries or the possibility of negative final demand. This study presents an improved disaster analysis approach, called minimum disruption, in order to assess more realistically the impacts of a disaster on essential and non-essential sectors. In particular, we propose a priority-weighted approach for incorporating decision-makers’ priorities for transitioning economies to post-disaster equilibrium. We showcase the new approach by modelling the actual occurrences during Venezuela’s economic crises.

KEYWORDS:

• minimum disruption
• input–output disaster analysis
• priority-weighted approach
• input substitution

JEL:

• D57

ACKNOWLEDGEMENTS

The authors thank Sebastian Juraszek for expertly managing the advanced computation requirements, Charlotte Jarabak for assistance with collecting data, and Jacob Fry and Takako Wakiyama for processing data feeds.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1 This method has been applied to floods in Germany (Schulte in den Bäumen et al., 2015) to severe space weather events (Schulte in den Bäumen et al., 2014), and to damage from a tropical cyclone (Lenzen et al., 2018).

2 Their equations (12), (13), (22) and (23).

3 Negative final demand can be interpreted as indicating that the disaster necessitates assistance from outside the economy under consideration. However, this assumption becomes problematic in studies where the global economy is examined. Dietzenbacher et al. (2019) write, ‘It would assume importing from Mars’ (see Appendix A1.1 in the supplemental data online).

4 In Schulte in den Bäumen et al. (2014), intermediate sectors that receive only marginal inputs from a damaged sector are assumed to be able to substitute for the reduced input, or slightly alter their production recipe otherwise, so they can keep producing at pre-disaster levels. The distinction between marginal and significant inputs is controlled by manually setting a threshold (see Appendix A1.2 in the supplemental data online).

5 Condition ii is Oosterhaven and Bouwmeester’s equation (2). For Condition iv, see Oosterhaven & Bouwmeester (2016, p. 587), but no distinction is made for subsidies and decreases in inventories. Instead of our condition i, Oosterhaven and Bouwmeester’s model specific scenarios in equations (7) and (8). Conditions iii and v do not appear in Oosterhaven & Bouwmeester (2016).

6 According to Baptista (1997), oil rent results from the remuneration paid out of ownership of non-produced means of production, therefore, this rent is not the result of the productive effort of the productive factors that participate in any capitalist society to generate the product.

7 Several studies have suggested the causes for this ‘curse of natural resources’, such as the Dutch disease, lack of human capital accumulation, corruption, rent-seeking and deficiencies in institutions (Aganani & Iza, 2011).

8 According to Monaldi (2015), along the last oil price boom, which ended in mid-2014, some oil exporter’s countries were more prudent than in the past, saving and investing more of the windfall and taking advantage of the price environment to increase oil production. Venezuela was not one of them.

9 Chávez’s government (1999–2012) used the income from high oil prices to dramatically boost domestic consumption largely sustained by cheap imports, while accumulating a profuse foreign debt without generating any significant in productive reinvestment (for further details, see Monaldi, 2015; and Bull & Rosales, 2020).

10 Regional groupings necessarily require compromises. For example, many ‘Former Eastern Bloc’ countries are now European Union members; however, their per capita income lies significantly below that of earlier European Union member states. On the other hand, non-European Union members, such as Switzerland and the UK, fit into the ‘EU+’ group because of their similar per capita income.

Additional information

Funding

This work was financially supported by the Australian Research Council through its Discovery Project [grant numbers DP0985522, DP130101293, DP190102277, DP200103005 and DP200102585], as well as by its Large Infrastructure, Equipment and Facilities (LIEF) grant [grant number LE160100066, Linkage Project LP200100311], ARC Research Hub [grant number IH190100009] and National eResearch Collaboration Tools and Resources project (NeCTAR) through its Industrial Ecology Virtual Laboratory VR201. NeCTAR are Australian government projects conducted as part of the Super Science initiative and financed by the Education Investment Fund.