Appendix Three – Resilience
Appendix 3 – Resilience
Appendix 3.1
Over 14,000 respondents to the World Economic Forum’s Executive Opinion Surveylxi were asked to rate their government’s risk management effectiveness:
How would you assess your national government’s overall risk management effectiveness of monitoring, preparing for, responding to and mitigating against major global risks (e.g. financial crisis, natural disasters, climate change, pandemics, etc.)? (1 = Not effective in managing major global risks; 7 = Effective in managing major global risks)
Table 4lxii provides the average results for each country, ranked from highest (best) to lowest (worst). Singapore and many innovation-driven economies (Stage 3 in the Forum’s Global Competitiveness Index) are ranked higher than factor-driven (Stage 1) economies (for definitions of stages, see below). The table also gives the survey sample size and the margin of error for each country, its ISO code, and development stage. Countries marked in light blue were used for the preliminary analysis presented in the Special Report section; the selection criterion was the available sample size from the Global Risks Perception Survey (see Table 5).
Meanwhile, respondents to the Global Risks Perception Survey were asked, per risk, about their country of expertise’s ability to adapt and or recover from its impact:
“What would be your country’s capability to adapt and/or recover from the national impact of this global risk?”
Table 5 ranks the countries from the highest to lowest according to their adaptability/ recoverability score. As with the Executive Opinion Survey risk-management question results, Singapore again and many Stage 3, innovation-driven economies are ranked higher than Stage 1, factor-driven economies. Additional details about the survey sample size for each country and its economic development stage are also provided in the table. Analysing the countries in table 5 in terms of their economic development stage presents an interesting way to group countries and tests whether this is the best method to do so.lxiii In the Global Competitiveness Report 2012-2013, the economic development stages are as defined below:
- Economies in the first stage are mainly factor-driven and compete based on their factor endowments – primarily low-skilled labour and natural resources.
- Transition from stage 1 to stage 2.
- Economies in the second stage have moved into an efficiency-driven stage of development, when they must begin to develop more efficient production processes and increase product quality because wages have risen and they cannot increase prices.
- Transition from stage 2 to stage 3.
- Economies in stage 3 have moved into the innovation-driven stage, wages will have risen by so much that they are able to sustain those higher wages and the associated standard of living only if their businesses are able to compete with new and/or unique products, services, models and processes.
Countries highlighted in blue were used for the preliminary analysis presented in the Special Report section. The selection criterion was the sufficiency of the country sample size to guarantee a margin of error smaller than 0.5 units (equal to a 95% confidence interval of less than one unit). 66 countries were not included below as the sample size was smaller than 5.lxiv
Appendix 3.2
As presented in the Special Report section, a country system is assessed using five components of resilience: robustness, redundancy, resourcefulness, response and recovery. Each component is further defined by key attributes, and for each of these attributes, potential qualitativelxv and quantitative indicators have been identified (see Table 6lxvi).
Table 7 shows the questions identified in the Executive Opinion Survey that are potential variables for the Country Resilience framework described in the Special Report section of this report.
Appendix 3.3
As explained in the Special Report, 10 countries were identified that had a margin of error of less than 0.5: Brazil, China, Germany, India, Italy, Japan, Russia, Switzerland, United Kingdom and United States. Statistical analysislxvii was conducted to identify paired differences between groups for the 10 countries, regionslxviii and economic development stages.lxix
Generally, respondents from Stage 3, innovation-driven economies had greater confidence that their country will be able to adapt and/or recover from the impact of a global risk. Respondents from Stage 1, factor-driven economies, were more pessimistic. Most interestingly, in the societal category, we found the only risk that had no statistically significant difference, mismanagement of population ageing, and the only risk where Stage 2, efficiency-driven economies were more optimistic than Stage 3 economies was rising religious fanaticism.
Following similar patterns, North Americans generally had greater confidence, while Sub-Saharan Africans had less. Statistically significant differences between countries were found for all risks, other than the two risks hard landing of an emerging economy and species overexploitation. Depending on the category and sometimes the risk, different countries were seen to have comparatively higher ability to adapt and/or recover from the impact of the risks. For the economic and environmental categories, it was Switzerland; for the geopolitical, it was China; for the technological, it was the United States; and for the societal category, there was no one particular country.
Across 50 global risks, where there are statistically significant differences (56% of the risks for age and 44% of the risks for gender), respondents under 40 years of age and female respondents rate their country as having less ability to adapt and/or recover from the impact of the risk. The majority of risks that had no statistically significant differences were from the geopolitical and technological category for gender and the environmental category for age. The largest differences in opinion were found on the unsustainable population growth and water supply crises.
With regards to perceptions of experts versus non-experts, unlike with likelihood and impact, for this group statistically significant differences were found only in the societal and technological category. Self-identified societal experts were more pessimistic about our recovery from societal risks, while self-identified technological experts were more optimistic about our recovery from technological risks.