Transitioning Regional Economies


Measuring adaptive capacity — a single metric



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37.2.3 Measuring adaptive capacity — a single metric


It is not possible to predict with confidence how a regional community will respond or adapt to any particular disruptive event, so we cannot identify regions most at risk of failing to adjust on this basis. But as noted above, resilience outcomes are influenced by the adaptive capacity of communities. The Commission’s approach to developing an index to rank regions most at risk of failing to adjust (as required by the terms of reference for this study) is to develop a measure of the relative adaptive capacity of regional communities.

There are significant challenges associated with developing a single metric of adaptive capacity. As noted above, adaptive capacity is influenced by a complex set of factors (both social and economic). Reducing these factors into a single metric will, to some extent, disguise the unique characteristics of regions. Obtaining data on a consistent basis for each region is also challenging, and the analysis in this study is necessarily limited by this. The metric is also likely to be highly sensitive to the variables included in the analysis. This highlights the importance of sensitivity testing and cautious interpretation of the results.

There is also no agreed method for how best to combine the large set of factors that are thought to affect adaptive capacity into a single metric. A number of approaches could be used (OECD and JRC 2008), and the choice is largely based on judgment. The Commission has chosen to use Principal Component Analysis (PCA), a technique that has previously been used by the ABS and others to construct indexes of socioeconomic disadvantage, vulnerability, resilience and adaptive capacity (box 2.7).

PCA enables the construction of a single index by summarising the data on factors that are thought to influence adaptive capacity, and presenting them in terms of the elements that explain the most variation. These elements are called principal components. Principal components can then be used to create indexes and rank regions.




Box 2.7 Indexes based on principal component analysis

The ABS SocioEconomic Indexes for Areas (SEIFA) consist of four indexes that measure different aspects of relative socioeconomic advantage and disadvantage.

The Australian Bureau of Agricultural and Resource Economics — Bureau of Rural Sciences (2010) developed an Index of Community Vulnerability for the MurrayDarling Basin Authority to compare the vulnerability of communities across the Basin. This was based on the five capitals framework (box 2.6).

Baum, Mitchell and Flanagan (2013) from the Centre of Full Employment and Equity at the University of Newcastle created an Employment Vulnerability Index to rank regions according to risk of job loss.

Dinh et al. (2016) from the University of Canberra created an index of potential community economic resilience at a small regional level. They grouped factors under the five capitals, and also included levels of economic diversity and accessibility to service centres.

Nelson et al. (2009a) created an index of adaptive capacity for Australian farms based on the five capitals framework.








The factors that have been included in the metric are those identified as important for adaptive capacity, based on those mentioned in the economic literature and by study participants (table 2.1). Most of the variables chosen can be gathered into five groups based on the capitals framework. Some variables do not fit logically into the five capitals framework and have been included separately, including an indicator of economic diversity, which is in line with other studies in this area (Dinh et al. 2016; Lawton et al. 2014; Nelson et al. 2009b). Data that would best capture some important factors are unavailable, so in some cases, surrogate variables have been used. For example, mining employment has been used in place of the value of discovered and undiscovered minerals.

PCA was conducted on all variables, and the resulting principal components were aggregated into an overall index (appendix E). The contributions of each factor and each group of related factors were then examined to identify which played the largest part in each region’s overall index score.




Table 2.1 Indicators of adaptive capacity

Type of indicator

Indicators included in metric

Human capital

Proportion of people aged 15–64 who have completed year 12 or higher

Proportion of people aged 15–24 fully engaged in work or study

Proportion of employed people in high to mediumskilled occupations (loosely corresponding with a Certificate III or IV qualification or above)

Proportion of the labour force who are employed

Proportion of people aged 15–64 who were working or looking for work

Ratio of longterm Newstart Allowance recipients to population aged 15–64

Proportion of people aged 15–64

Proportion of people who identify as Indigenous

Ratio of patent applicants to population

Ratio of trademark applicants to population

Business entry and exit rates

Ratio of Disability Support Pension recipients to population aged 15–64

Estimated proportion of people aged 15+ who selfassessed their health as better than fair

Estimated proportion of people aged 18+ with high or very high psychological distress

Estimated proportion of people aged 18+ with at least one of four health risk factors (current smoker, high risk alcohol consumption, obese, no or low exercise in the previous week)


Financial capital

Proportion of households with equivalised household income greater than $1250 a week

Ratio of total investment income to population

Ratio of government income support recipients to population

Weighted average of median house and unit sale prices

Proportion of households who live in an owneroccupied dwelling with or without a mortgage

Estimated proportion of households that are in the bottom 40 per cent of the distribution of equivalised household income and are paying more than 30 per cent on mortgage or rent



Physical capital

Remoteness, based on Accessibility/Remoteness Index of Australia

Proportion of households that access internet from the dwelling

Ratio of mean value of nonresidential building approvals over 2014–16 to population

Estimated proportion of people aged 18+ who do not find it difficult getting to places needed with transport



Natural capital

Proportion of employed people working in agriculture industry

Proportion of employed people working in mining industry

Proportion of land as national parks or nature reserves


Social capital

Proportion of people who volunteered

Estimated proportion of people aged 18+ who are able to get support in times of crisis from persons outside the household

Estimated proportion of people aged 18+ or their partner who provide support to other relatives living outside the household

Estimated proportion of people aged 18+ who felt very safe or safe walking alone in local area after dark

Estimated proportion of people aged 18+ who felt they had experienced discrimination or unfair treatment in the past 12 months

Estimated proportion of people aged 18+ who do not disagree with acceptance of other cultures

Estimated proportion of people who are homeless


Other

Herfindahl index of industry diversity

Proportional change in population aged 15–64 over five years

Proportion of people who travel to work in a different region










The analysis was conducted for FERs (box 2.2), which the Commission constructed based on Statistical Area Level 2 (SA2) regions drawn from the ABS Australian Statistical Geography Standard.

The index measures the extent to which regions are ‘different’ to others. An index score is computed for each region, with higher (lower) scores indicating higher (lower) adaptive capacity relative to other regions. Regions are then ranked according to their score to identify those most at risk of failing to adjust.

It is important to note that the index developed by the Commission measures relative, rather than absolute, adaptive capacity — regions ranked lowly by the index do not necessarily have low adaptive capacity, rather they only have lower adaptive capacity relative to other Australian regions.

38.Using the single metric of relative adaptive capacity


The index can be used as a starting point for identifying regions that might be at risk of failing to adjust on the basis of their relative adaptive capacity. However, it does not identify whether regions will be successful in transitioning to a more sustainable economic base following a disruption. As discussed earlier, a region’s outcomes depend on its circumstances as well as its adaptive capacity and prospects for development (box 2.3). The index does not account for the circumstances and opportunities that regions face or how these might change in response to an economic disruption.

Thus, the actual ability of a community to adjust depends on the precise challenge it faces, and the actions of people within communities as they seek to take advantage of opportunities available to them. Study participants pointed to a number of opportunities for transition and development, including through diversification into other activities, such as agriculture, renewable energy or tourism, or by better utilising existing infrastructure assets and building on industry specialisation (box 2.8). However, many of these proposals would require taxpayer funding and so should be subject to rigorous, transparent cost–benefit analysis. As always, there are limited resources and proposals should be compared so that the ones with the largest net benefits are chosen.

The development opportunities and prospects for regional communities depend on the particular attributes of a region, including its geographical location and proximity to other communities and markets, its endowments of natural resources and attractions, and the skills of the local population. Prospects also relate to external factors such as advances in technology and changes in consumer preferences for the goods and services provided by regional economies.


Box 2.8 Participants’ views on opportunities for change

Regional Development Australia Pilbara (sub. 6, pp. 15–16):

The Pilbara has very substantial renewable energy potential, primarily in solar and wind energy. Solar power potential is based on the high number of sunlight hours in the region …

A particular niche market opportunity exists in luxury tourism, which is the leading growth sector in tourism. … The Pilbara has several sights that could be considered for luxury tourism development, including the Dampier peninsula.

Linda Nadge (sub. 1, p. 3):

My idea is to grow Broken Hill by basing a space industry here.

Cairns Regional Council and Advance Cairns (sub. 13, pp. 40–41):

Given large expanding markets in Asia, cattle exports are predicted to grow. Technological improvements, including better stock, better infrastructure and investment in properties is underpinning ability to expand supply … Cape York is likely to prove a major area for increased production.

There are strong prospects for expanding [agricultural] production beyond current limits around the Tablelands … A number of industries in the area, including sugar, only need more water to expand.

Illawarra Business Chamber (sub. 15, p. 5):

The fastest growing sector over the next 20 years in the Illawarra is expected to be health care, driven primarily by an ageing population … Education and training is also expected to grow strongly.

The Illawarra’s proximity to Sydney and Canberra also provide substantial opportunities for tourism growth in the region … For the region to benefit from these growth areas and opportunities, we need improved transport connectivity to and from the region.

Upper Spencer Gulf Common Purpose Group (sub. 20, p. 1):

There is considerable potential to build on these comparative strengths and reposition the economy as a hub for renewable energy generation and testing; defence; intermodal transport and logistics; valueadding and innovation in agriculture; event and marinebased tourism; advanced manufacturing to support the mining and energy sectors; and as centres for delivery of government services and higher education/research.

Tasmanian Government Minister for State Growth (sub. 21, p. 2):

We have also been working to facilitate the growth of emerging and high growth industries, such as aged care and [National Disability Insurance Scheme] linked programs, agriculture, transport and tourism.

Western Australian Local Government Association (sub. 22, pp. 13–14):

Mining will remain an important part of the WA economy, and there remains considerable and ongoing opportunities to supply raw materials to Asia. However, there are also opportunities for WA to build on its knowledge and expertise in resources production to become a major supplier of mining technology and services.

Beyond commodities, there are also significant opportunities for WA to supply consumer goods and services to the [Asia] region … which is demanding more ‘luxury’ goods such as premium food and wine products and services as their incomes increase.

Queensland Government (sub. 26, pp. 16, 27):

There is also a role of cultural tourism in transitioning regional economies to reflect Tourism Australia’s finding that half (51%) of all International visitors to Australia are cultural and heritage visitors.

The tourism industry is a potential bright spot for the Mackay region, with the Whitsundays being a major tourist attraction. The lower AUD is expected to encourage more Australians to travel domestically and attract more tourism from overseas.








How successful regional communities are in adjusting to change depends on whether they are able to take advantage of available opportunities. Regional communities are best placed to drive change, and in this context, local leadership and entrepreneurship have a strong role to play. Governments are not best placed to pick which industries or projects are likely to succeed in the future. As noted by the Western Australian Local Government Association:

It is important that the policy focus is not around ‘picking winners’, but instead about creating an environment that will improve the efficiency and competitiveness of the economy in general. (sub. 22, p. 2)

Thus, in assessing the scope for economic and social development in regions, it is necessary to look beyond the single metric and adopt a broader framework that takes into account a region’s circumstances, strengths, opportunities and existing arrangements.


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