Transitioning Regional Economies



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113.E.5 Results discussion


This section provides a brief overview of the results from the Commission’s preferred index of adaptive capacity, using the single PCA approach. A more detailed discussion can be found in chapter 4. In addition, appendix B contains a list of regions by their ranking and category of adaptive capacity.

The least adaptive regions tend to be concentrated in more remote regions of Australia, while the most adaptive regions tend to be in major cities (figure E.4). This is further illustrated in figure E.8. There are no major city regions within the least adaptive or below average categories. In terms of population sizes, a relatively larger share of people in the least adaptive regions are living in regional or remote areas, compared with the share of people in those areas among the whole of Australia (figure E.8). However, in terms of the whole population, the number of people living within the least adaptive regions is small, due to the relatively sparse populations in these areas when compared with the populations in major cities (figure E.8).




Figure E.8 Regions and population by relative adaptive capacity and remoteness

this figure contains three charts. the first chart of the top panel shows stacked column charts of all regions and the least adaptive regions, coloured according to their remoteness level. the second chart of the top panel shows stacked column charts of the population in all regions and the least adaptive regions, coloured by remoteness. together, the charts illustrate that remote and outer regional areas feature strongly in the least adaptive category. the final chart in the bottom panel shows percentages of the whole population within each adaptive capacity category. it illustrates that very few people live in the least adaptive regions and most people live in the most adaptive regions.



Source: Productivity Commission estimates.








114.E.6 SA2 adaptive capacity results for 2016


Creating the index of adaptive capacity at the FER level has the potential to hide differences in indicators between the SA2s that make up the FERs. Therefore the index was also created at the SA2 level, using the single PCA approach. A total of 2070 SA2 regions were included in the calculation of the index. 126 were excluded due to missing data.

The indicators that were included in the analysis were the same as for the FER analysis, but at the SA2 level. There are a few exceptions — the measures of industry diversity and interregional flows are at the FER level for the SA2 analysis. These variables are more appropriate to consider at a larger level of geography than SA2s because people live, work and consume services across multiple SA2s (particularly in urban areas).



Weights of each indicator in the SA2level index are presented in table E.17 and the contributions of each capital domain are presented in table E.18.


Table E.17 Single PCA for SA2 regions, 2016 — weights of indicators in index

Ordered from largest to smallest in absolute value

Indicator

Weight in index




Indicator

Weight in index

safeatnight

0.103




accesstransport

0.048

invinc

0.097




trademarks

0.042

providesupport

0.091




bsnsexitrate

0.042

ownhome

0.090




bsnsentryrate

0.039

volunt

0.086




buildappvalpp

0.038

nature

0.082




psychdistress

0.035

indig

0.080




yr12plus

0.034

skill1to3

0.077




remoteness

0.033

youtheng

0.077




agind

0.030

selfhealth

0.075




internet

0.029

homeless

0.071




highinc

0.026

propprice

0.071




dsp

0.026

wkage

0.068




miningind

0.024

housingstress

0.064




interflows

0.023

comprisk

0.060




wkagechange

0.019

ltnewstart

0.057




govtpyts

0.017

getsupport

0.053




herfinneg

0.009

emptolf

0.053




discriminated

0.009

culturalacceptance

0.051




participation

0.005

patents

0.049













Source: Productivity Commission estimates.









Table E.18 Single PCA for SA2 regions, 2016 — contributions of each capital domain

Ordered from largest to smallest contribution

Capital domain

Contribution to index (%)

Human

41.30

Social

23.43

Financial

18.38

Physical

7.47

Natural

6.86

Other

2.55




Source: Productivity Commission estimates.






Human capital factors have the largest contribution to the index at 41 per cent (table E.18). However, this is smaller than the contribution of human capital to the single PCA index for FERs (50 per cent). Social capital factors make a larger contribution to the index for SA2 regions than FERs (23 per cent compared with 17 per cent). The contributions of financial, physical, natural and other factors to the SA2 index are similar to that of FERs.

After grouping SA2 regions into categories according to their index scores, 309 were classified as least adaptive, 740 as below average, 710 as above average and 311 as most adaptive. However, similar to the FER results, region’s index scores are sensitive to changes in the sample of regions and indicators included in the analysis.

Figure E.9 presents a map of SA2 regions by their relative adaptive capacity, according to each region’s index score. A comparison of figures E.4 and E.9 shows that large remote and regional areas tend to have relatively low adaptive capacity at both the FER and SA2 level. However, there are pockets of lower adaptive capacity within major cities that are not obvious at the aggregate FER level.

For the single PCA index for SA2 regions, the share of people in more remote regions within the least adaptive category is larger than the national share of people in more remote regions (figure E.10). However, most people within the least adaptive category of SA2s live in major cities. These people were masked in the FER results, because they reside within a FER that had relatively high adaptive capacity overall.




Figure E.9 Single PCA — relative adaptive capacity of SA2 regions, 2016

this figure shows a map of the adaptive capacity of sa2 regions, as per the commission’s index using the single pca approach. regions are coloured according to their adaptive capacity category. further information can be found in the text surrounding the figure.



Source: Productivity Commission estimates.







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