Transitioning Regional Economies



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115.E.7 FER adaptive capacity results for 2011


The analysis was conducted for FERs using 2011 data. For indicators where 2011 data were not available, data were used from the closest available year.

Although the results are displayed here for completeness, index results for each region at different time periods cannot be used to assess change, for a number of reasons.




Figure E.10 Many people in the least adaptive SA2s live in major cities

this figure contains two charts. the first chart shows stacked column charts of all sa2 regions and the least adaptive sa2 regions, coloured according to their remoteness level. the second chart shows stacked column charts of the population in all sa2 regions and the least adaptive sa2 regions, coloured by remoteness. the charts show that many people in the least adaptive sa2 regions live in major cities.



Source: Productivity Commission estimates.






First, the indexes are relative measures of adaptive capacity. They do not show whether a region has high or low adaptive capacity, only whether they have higher or lower adaptive capacity than other regions. Therefore, all else equal, a decrease in a region’s index ranking could mean that the region’s adaptive capacity has actually declined, or that other regions that used to have lower adaptive capacity have improved.

Second, changes in index scores could be due to changes in the value of indicators or changes in the weights on indicators in PCAs across years. An indicator of adaptive capacity for a region might have improved over time, but if the weight on the indicator has decreased, then it might still have the same contribution to the index.

Third, there are issues with obtaining consistent data on indicators over time. Not all indicators are available for each year, and some values of the indicators used are the same for both 2011 and 2016 indexes. Changes in rankings might be partly due to indexes not being able to take into account data for the correct year. Even where data are available, the definitions of indicators can change over time, which can add further difficulty when making comparisons.

As a result, no clear conclusions can be made about how a region’s adaptive capacity has changed over time.



For the adaptive capacity index for 2011, weights of each indicator are presented in table E.19 and the contributions of each capital domain are presented in table E.20. Comparing the contributions of each capital domain to the FER index for 2016 and 2011 (tables E.10 and E.20), human capital indicators contribute over 50 per cent of the index in both years (though the weights on individual indicators differ). Human and financial capital indicators make a slightly larger contribution to the 2011 index than the 2016 index, whereas natural and social capital indicators make a slightly smaller contribution.


Table E.19 Single PCA for FERs, 2011 — weights of indicators in index

Ordered from largest to smallest in absolute value

Indicator

Weight in index




Indicator

Weight in index

skill1to3

0.110




patents

0.039

selfhealth

0.104




herfinneg

0.034

comprisk

0.100




youtheng

0.034

govtpyts

0.085




indig

0.033

dsp

0.084




wkagechange

0.029

emptolf

0.083




psychdistress

0.028

yr12plus

0.082




bsnsentryrate

0.028

ltnewstart

0.080




accesstransport

0.019

participation

0.071




ownhome

0.018

getsupport

0.070




trademarks

0.017

highinc

0.069




safeatnight

0.017

invinc

0.065




bsnsexitrate

0.016

internet

0.062




volunt

0.016

buildappvalpp

0.058




homeless

0.008

wkage

0.053




agind

0.008

propprice

0.051




miningind

0.007

housingstress

0.049




remoteness

0.004

nature

0.048




interflows

0.003

culturalacceptance

0.044




providesupport

0.001

discriminated

0.041













Source: Productivity Commission estimates.









Table E.20 Single PCA for FERs, 2011 — contributions of each capital domain

Ordered from largest to smallest contribution

Capital domain

Contribution to index (%)

Human

54.33

Financial

19.08

Social

11.17

Physical

8.07

Other

3.78

Natural

3.57




Source: Productivity Commission estimates.






A map of the adaptive capacity of FERs in 2011 is presented in figure E.11. The most adaptive regions include most greater capital city regions, as well as some major mining regions (Karratha, Port Hedland – Newman, and Goldfields regions of Western Australia). The boom in mining activity boosted incomes and employment in these mining regions, which positively contributed to these regions’ human and financial capital and their adaptive capacity index score for 2011 (which was during the height of the mining boom). Despite being in more remote parts of Australia, these regions also had relatively high levels of physical capital due to the construction during the mining boom years. The least adaptive regions are in inner regional to remote areas, and are characterised by low levels of human and financial capital (such as poor education and skill levels and low incomes).


Figure E.11 Single PCA — relative adaptive capacity of FERs, 2011

this figure shows a map of the relative adaptive capacity of regions in 2011, 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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