A map of the results of the index is shown in figure 4.2. Regional communities that are likely to have the lowest relative adaptive capacity (about 17 per cent of all regions24) are predominantly located outside of greater capital city regions and concentrated in outer regional and remote/very remote areas of Australia. These regions are generally located across the inner parts of Australia (South Australia and the Northern Territory) and across much of Tasmania.25
Figure 4.2 Relative adaptive capacity of Australia’s regionsa
a Regions are defined using functional economic regions. ‘Not estimated’ regions were excluded from the analysis due to insufficient data. Least (most) adaptive regions are defined as those below (above) one standard deviation of the mean index value of adaptive capacity across all regions.
Source: Productivity Commission estimates.
Many of the regional areas with above average adaptive capacity are located in areas in Victoria, New South Wales and Western Australia. All metropolitan cities have at least above average adaptive capacity.
In total, 90 per cent of regions in Victoria have at least above average adaptive capacity. This contrasts starkly with South Australia, the Northern Territory, Tasmania and Queensland, where between 17 per cent and 33 per cent of their regions have at least above average adaptive capacity. Just over half of the regions in New South Wales and Western Australia have at least above average adaptive capacity.
64.Index of relative adaptive capacity and population
Although maps are useful to illustrate the geographical spread of the adaptive capacity of regions, they do not convey the number of regions, or the number of people, within the least adaptive category of regions.
The proportion of regions, by number, that are remote and very remote is higher among the least adaptive category when compared with all regions (figure 4.3). Nearly half of the regions in the least adaptive category are remote or very remote. In contrast, no major cities are in the least adaptive category.26 Similarly, the share of the population living in the least adaptive regions in remote and very remote areas is higher than the share of the population living in remote and very remote areas overall.
Although very remote regions cover large areas of Australia, they are sparsely populated compared with major cities and smaller urban and regional areas. Indeed, most Australians live in capital cities (section 3.4), with levels of population in regions declining as remoteness increases.
Because the outer regional and remote regions are sparsely populated, there are few people living in the least adaptive regions (figure 4.3). In contrast, although major capital cities are few in number, the population living in major cities is large.
In total, about 659 000 Australians live in the least adaptive regions, representing 3 per cent of the total population. In contrast, there are nearly 16 million people who live in the most adaptive regions (66 per cent of the population) (figure 4.3). The most adaptive regions are concentrated in major cities. This does not mean there are not pockets in cities where adaptability is low — as discussed in chapter 3, some areas within cities are characterised by high concentrations of people with low skills and are vulnerable to, for example, declining manufacturing employment. However, these subregions are located within major city areas that are typically associated with diverse industry structures, more highly educated and skilled workers, and have good access to services and infrastructure (all factors that positively contribute to the adaptive capacity of the city as a whole).
Figure 4.3 Regions and population by relative adaptive capacity and remoteness
Source: Productivity Commission estimates.
The proportion of regions in the least adaptive category increases with the degree of remoteness. About 659 000 people (or 3 per cent of the population) live in the least adaptive regions. In contrast, nearly 16 million people (66 per cent of the population) live in the most adaptive regions, which are concentrated in major cities.
65.Factors affecting regional rankings of adaptive capacity
There is no simple explanation for why the adaptive capacity of communities varies so markedly. Although the index value for each region is driven by the many factors included in the index, peoplerelated factors (including education, skills, employment and incomes) appear to have a strong influence, particularly for communities in urban areas. For communities in remote areas, these and other factors associated with remoteness, such as accessibility to services and infrastructure, have the strongest influence.
Overall, communities in cities and inner regional areas have the highest capacity to adapt, largely due to their connectivity with other regions and markets, and the diverse skills and higher education levels of their workforce. Where inner regional areas have more limited adaptive capacity, this is frequently attributable to general social and economic disadvantage.
Remote areas with low relative adaptive capacity are typically those with limited access to resources that underpin economic and social wellbeing. Access to infrastructure and services is more limited in these areas and people within these communities have lower levels of education and fewer employment opportunities.
Youth engagement in work or study is particularly low in remote and very remote communities (regardless of adaptive capacity) — 47 per cent on average compared with 65 per cent for all other types of regions. Low youth engagement can mean greater risk of unemployment and cycles of low pay and employment. Youth engaged in work or study may reflect both opportunities as well as people’s intrinsic motivation to pursue these opportunities (DIRD 2015a).
Another story emerges when examining the main sources of economic activity in the regions that have been found to have the lowest adaptive capacity (figure 4.4). For inner regional areas with the lowest adaptive capacity, government services are the main source of employment. As remoteness increases for the least adaptive regions, agricultural employment begins to play a more prominent role. In inner regional and outer regional areas with the lowest adaptive capacity, the government services that are the main source of employment are health care and social assistance.27 In remote and very remote regions with low adaptive capacity, both health care and social assistance and public administration and safety are the main government services people are employed in. (The reasons why some agricultural regions have low adaptive capacity are discussed later.)
Figure 4.4 Main source of employment for the least adaptive regions by class of remoteness
Source: Productivity Commission estimates.
The main factors shaping the index value of relative adaptive capacity for each region relate to:
peoplerelated factors (including educational achievement, employment rates, skill levels, personal incomes and community cohesion)
the degree of remoteness and accessibility of infrastructure and services.
There is considerable interest (as reflected in the terms of reference for this study) in considering whether regions affected by the resources investment boom are likely to be at risk of failing to adjust.
Those functional economic regions that have a relatively high share of employment in mining have below average adaptive capacity, as assessed using the relative adaptive capacity index. They include larger population centres in the Pilbara, such as Karratha and Port Hedland, as well as Mackay and Mudgee.
As noted by James Cook University (sub. 24, p. 5), classifying regions based on common characteristics potentially enables inferences in datapoor areas, however there is a risk that incomplete or incorrect data could lead to ‘wrong’ typologies. The unique attributes of regions means that seemingly similar towns or regions may experience very different development paths due to small differences. This is apparent in the experiences in Nhulunbuy (in the Northern Territory) and Weipa (in Queensland) (chapter 3).
That said, some common factors have been identified which have a negative impact on the adaptive capacity of mining regions. These relate primarily to natural assets, and the characteristics of the communities in the region as well as concentration of employers and activities.
Regions with mines that have high cost structures (and that are therefore only economically viable during periods of relatively high commodity prices) face challenges from cyclical downturns. For example, in the Kimberley region of Western Australia, three mines that accounted for 30 per cent of gross regional product when iron ore prices were at their peak are now in care and maintenance (chapter 3).
Natural assets present both opportunities and risks for mining regions. Mining provides opportunities for employment within these communities. Some of the towns in these regions may not exist were it not for the mineral endowments in the area. Indeed, some towns were developed solely to service the mining industry, and a number of these have since been abandoned.
The new towns built to service the mining industry in the 1960s and 1970s were located immediately adjacent to the major resources (e.g. Tom Price and Mt Tom Price, Newman and Mt Whaleback, Leinster and Leinster Nickel Operations) and the port facilities (e.g. Dampier and Dampier Port, Wickham and Cape Lambert). Some towns that were located near resources that have become exhausted have subsequently been removed entirely — such as Goldsworthy and Shay Gap. (Chamber of Minerals and Energy of WA, sub. 28, p. 18).
However, a lack of diversity can present a challenge as it leaves the communities exposed to disruptions that could negatively impact the value of mining activity and lead to the collapse of economic activity that was once feasible in the region. This is reflected in the estimation of the metric — as the share of mining employment increased, it had a more negative contribution to the index.28
Another characteristic that has a negative contribution to the metric for most mining regions is social capital. Indicators such as rates of volunteering, selfassessed feelings of safety at night and discrimination are worse across most mining regions.
There are some differences in people–related factors across mining regions. For instance, Karratha and Port Hedland are characterised by having relatively high human capital (in particular, high education, employment and participation, and trade skills), which are all associated with higher adaptive capacity. The Western Australian Department of Regional Development (sub. 27, p. 5) noted that improved social and community infrastructure in the Pilbara, particularly Port Hedland and Karratha, ‘is encouraging people to stay in town, educate their children locally and plan a future in the region’. Other mining regions have lower human capital, which reduces their adaptive capacity.
Although Karratha and Port Hedland have higher human capital outcomes, their adaptive capacity is lowered, partly because they have relatively low financial capital. Despite having high household incomes, these regions tend to have low investment incomes and low home ownership.
Although mining regions are exposed to commodity cycles, and most were assessed as having relatively low adaptive capacity, many have proven to be sustainable in the longer term where there are secure resources that can be mined economically. As noted in chapter 3, regions (such as the Pilbara) that have a comparative advantage in markets for minerals and commodities have benefited from significant investments in new projects and expansions during the investment boom. This will likely provide an economic and employment base in these regions for decades to come, largely irrespective of commodity market cycles. As noted earlier, employment in many mining regions is higher than before the commencement of the mining boom.
67.The adaptive capacity across agricultural regions is very diverse
In total there are 22 regions with a relatively high share of employment in agriculture. As discussed in chapter 3, these agricultural regions have diverse characteristics. They are located from across Western Australia through to the East coast. While some are located in inner regional areas (for example Warrnambool), many lie in outer regional and remote/very remote areas.
The adaptive capacity scores across agricultural regions are diverse. Three agricultural regions are in the lowest adaptive capacity group, with the remainder roughly evenly split between having below average or above average adaptive capacity.
Many factors contribute to the diversity of adaptiveness across agricultural regions.
Most of the agricultural regions with above average adaptive capacity (five of the nine) are located in Western Australia. As noted in chapter 3, agricultural regions in Western Australia (especially in the Wheat Belt) recently performed better than other agricultural regions, on measures such as income growth. And financial capital is one of the key indicators where there is a noticeable difference between those agricultural regions with relatively low or high adaptive capacity. Agricultural regions with the highest adaptive capacity tend to have higher rates of home ownership and less housing stress. They also have higher household incomes, investment incomes and relatively few recipients of government pensions and allowances.
As noted in chapter 3, there has been an ongoing agglomeration in agricultural areas towards regional centres that are better serviced and connected. These factors are important for adaptability. For instance, those agricultural regions that have relatively low adaptive capacity are typically associated with being in remote areas and having poor access to transport.
People–related factors also differ between those agricultural regions with relatively low adaptive capacity and those with above average capacity. Although as noted above, these factors are important across all regions.
Finally, social capital is important. The loss of key leadership skills and the ongoing challenges agricultural regions face as community leaders leave a region was noted in chapter 3. Agricultural regions with higher adaptive capacity typically display higher volunteering rates and better perceptions regarding being safe at night. The role that volunteering plays in supporting communities respond to challenges was noted by the Rotary Club of Traralgon Central Inc. (sub. DR50, p. 1):
Volunteer organisations cover a wide range of social, physical, spiritual and mental (educational) fields. Whilst not at the top of the list in economic terms, a significant part of the response to human stresses and challenges is met by the aggregated support and effort of volunteers, providing a positive effect in supporting families.
Similarly, Volunteering Australia (sub. DR61, p. 2) stated that volunteering is crucial in ‘building strong and resilient communities, by encouraging economic participation, mitigating isolation and loneliness, and increasing social inclusion, community participation and cohesion’.