The Geography of Personal and Household Incomes

Data from the Census of Australia

Ian Manning, National Institute of Economic and Industry Research and
charter member, Brotherhood of St Laurence

Paper for the Australian Social Policy Conference, Social Policy Research Centre,
University of New South Wales

11 September 2019

 

Download the full paper (pdf)

Download the presentation (zip/pptx)

 

“Data is not information, information is not knowledge, knowledge is not understanding and understanding is not wisdom.”  (Clifford Stoll)

 

For two decades the National Institute of Economic and Industry Research has prepared a State of the Regions report for the Australian Local Government Association. Each annual report includes measures of inter-regional income inequalities based on National Accounts data. This paper first reviews the National Accounts indicators and then considers alternative indicators based on Census data, including the geographic patterns they reveal. The comparisons were made for each of the 544 LGAs listed in the Census but for purposes of exposition the results were aggregated to 67 regions.

The 2016 Census required respondents aged 15 and over to tick a box to denote their weekly income. The Census form included the comment: ‘information from this question provides an indication of living standards in different areas’. The Census income data are published as personal income and equivalised household income. The geographic patterns revealed in the Census data were described in the State of the Regions report for 2019-20 and are here further analysed, concentrating on the proportion of households, by region, reporting incomes in the bottom and top deciles of equivalised income.

The geographic distributions of income documented from the Census indeed throw light on living standards, but there are no conclusions, only further questions, such as the following.

  • In what kinds of region do low personal incomes generate low equivalised incomes?
  • Why is Sydney so income-segregated?
  • What are the effects of fly-in fly-out and indigenous residence on living standards in remote areas?

National populations are a natural focus for studies of inequality, since national governments preside over taxation and public expenditure policies which directly affect the distribution of income and wealth. In Australia the national distribution of income, wealth and consumption expenditure, both between individuals and households, has been assiduously documented in a series of sample surveys, beginning with the ABS survey of income distribution for the Poverty Inquiry in 1973 and continued since, particularly in the ABS surveys of income and household expenditure and in the University of Melbourne HILDA survey. The surveys have been analysed in a search for trends, with the results somewhat dependent on the indicators of inequality chosen. The most definite results have included the association between income and employment (employed people generally receive higher incomes than not-employed), income and industry of employment (some industries pay better than others), income and gender (men tend to have higher individual incomes than women) and income and age (both young and old have lower incomes than the middle aged) (Productivity Commission 2018). The national distribution maps down to the regional level, so that regions where unemployment rates are low are expected to have high regional incomes, and likewise regions with middle-aged populations and regions where employment is concentrated in high-income industries. (One might add regions with masculine populations, but fortunately the sex ratio does not vary much between regions except as a consequence of age distribution.)

Though regional inequality of income can confidently be predicted from the national sample surveys, they cannot be proven from this source; neither can it be shown that regional inequality is greater or less than indicated by the factors identified at national level due to the influence of regional factors. The problem is simple: national sample surveys do not yield results which are statistically significant at the regional level.  Two main sets of indicators are in use to identify rich and poor regions. One set derives from administrative sources and is summarised in Gross Regional Product, the other set derives from the Census. This paper describes and assesses the available measures, limiting itself to recent estimates (the financial year 2018-19 and Census 2016). It does not attempt to quantify trends, but does attempt to identify the reasons why particular regions are currently rich or poor.

 

 

Electricity generation by SOR regions

Australia generated around 247,109 GWh of electricity in the 2019 financial year, which included 196,723 GWh from fossil fuels and 50,386 GWh from renewable sources. In 2019 renewable energy made up 20.4 per cent of total generation, while in 2018 the proportion of renewable generation was 18.7 per cent.

The following chart presents Australian annual electricity generation (GWh) for each of the SOR regions for the 2019 financial year. It shows the supply of electricity by each major fuel type within the region rather than electricity consumption (or electricity demand). The supply of electricity captures metered generation from grid sources from the National Electricity Market and South-West Interconnected System. Supply to smaller networks, off-grid and behind the fence industrial loads have been estimated and included where possible.

For more details, please refer to the State of Regions 2019-2020 report.

Distribution of household income: A 2016 snapshot

It is estimated that in 2016, 5.7 per cent of the population lived in households with very low incomes after allowance for household size. We identify poor households as those with incomes below the 10th percentile. Judged by the proportion of households with incomes at this level, the poorest regions were either remote or urban. Two remote regions matched this profile: NT Lingiari and SA Far North and West. Other remote and resource-based regions reported proportions around the national average. Among metropolitan regions, Sydney Mid-West stood out as particularly disadvantaged. The only other metropolitan region remotely like it was Adelaide North. There were no equivalents in the other metropolitan areas. No ex-urban or lifestyle regions stood out. However, the proportion of poor households was above the national average in several rural regions. Insofar as high income supports a high standard of living, the most prosperous regions were the ACT, Darwin, the Sydney metropolitan core, the central regions of Melbourne, Perth and Brisbane, and the WA Pilbara Kimberley.

Note: Equivalised income applies to households living in private dwellings which reported their incomes. Between 2011 and 2016 the household consumption price index as recorded in the National Accounts rose by approximately 6 per cent, hence after adjustment for inflation overall median income rose by approximately 9 per cent or 1.6 per cent a year.

For more details, please refer to the State of Regions 2019-2020 report.

Exports to China by State (1996-2017)

Data originally published in State of Regions 2018.

A social geography of the Mornington Peninsula

This article was prepared for the George Hicks Foundation as part of a background paper for a meeting of philanthropists interested in work on the Mornington Peninsula. An evaluation of the costs and benefits of providing educational assistance to disadvantaged families living on the Peninsula is provided in a separate posting.

Download here

Opportunities to create pathways to assist disadvantaged children in the Mornington Peninsula, Victoria

This article was prepared for the George Hicks Foundation as part of a background paper for a meeting of philanthropists interested in work on the Mornington Peninsula. A more detailed social geography of the Peninsula is provided in a separate posting.

 

Download here

The importance of manufacturing and industry policy

During the decade to 1995 Australia reduced import tariffs on manufactured goods and, therefore, exposed many of its hitherto-protected manufacturing industries to overseas competition. At the same time, it implemented a series of targeted and highly cost-effective industry policies that assisted a wide range of Australian manufacturing businesses to become internationally cost-competitive, gaining export markets at the same time as they met import competition. With the obvious success of the previous government’s industry policies, the stated intentions of the Coalition government elected in 1996 were to leave the existing structure largely unaltered and continue with the general government–industry partnership model. However, the first national budget of the new government for 1996–1997 revealed a different intention. There was a significant change in philosophy away from targeting firms and industries and towards an neutral approach in line with the ideals of the Washington Consensus. The Commonwealth government moved from targeted to generalised industry assistance and, hence, moved from cost-effective to ineffective policies. During the mineral boom it was possible to pretend that this did not matter; Australian prosperity would be guaranteed by mineral exports. The time of reckoning now approaches. Mineral prices have slumped and manufacturing has been decimated. The Washington Consensus has already been discredited within the world economic development community; the time is long past that it should likewise have been discredited in Australia.

 

Download here

Incubus of overseas debt

This paper considers the role of overseas debt in financial crises, including the Asian financial crisis, and the experience of other debt-afflicted countries since 1997. Recent trends in Australian overseas debt are compared with the equivalent trends in Asian countries in the years leading up to the Asian financial crisis, and the performance of economies recovering from debt-induced collapse is considered. Australia does not fare well in this comparison. Indonesia, for instance, with a fraction of the living standards of Australia, showed sustained discipline to hold growth in living standards in check for the benefit of debt reduction, whereas Australia chose to maximise growth in consumption expenditure, totally disregarding the growth in foreign debt that this produced. Australia currently has most of the symptoms of impending debt-induced collapse, and insists on pursuing policies that are likely to lead to collapse and maintains a mindset that will seriously hinder recovery from collapse.

 

Download here

Review of EDD weather standards for Victorian gas forecasting

 

The Effective Degree Day (EDD) index was developed to capture the combined impact of temperature, wind and sunshine on Victorian gas demand. edd long term trend

Gas consumption due to short term weather variations is often removed prior to forecasting gas demand. This is partly achieved by developing weather standards that represent conditions under temperatures, for example, that are neither warmer nor cooler than expected. 

Weather standards for Victorian gas forecasting are typically developed using the Effective Degree Day index.

The Australian Energy Market Operator (AEMO), and previously VENCorp, have reviewed the EDD index and EDD standards every two to three years since 2000 with the latest completed in 2012.

The 2016 NIEIR Review of EDD Standards for Victorian Gas Forecasting report follows on from these reviews with a particular focus on the development of new weather standards for annual gas consumption and peak day to inform the Gas Access Arrangement Review (GAAR) over the 2018 to 2022 period.

 

This report covers:

  • background to weather normalisation and how the EDD index is formulated;
  • the development of new annual EDD standards under alternative methodologies;
  • the development of new 1-in-2 and 1-in-20 peak day EDD standards under alternative methodologies;
  • The impact of climate change on annual and peak day weather standards;
  • The correction applied to temperature to account for the change in location of the official Melbourne weather station from the CBD to Olympic Park in 2015 and;
  • monthly standards are also estimated for gas consumption and peak day.

 

Download the NIEIR Review of EDD weather standards for Victorian gas forecasting report:

Full Report    (26 pages | PDF | 1,328 kb)

Tables   (XLSX | 87 kb)

The Experience of Australia and Kazakhstan in the Mineral Price Boom of 2006-2014 by Dr Ian Manning

Both Australia and Kazakhstan are large in physical area but relatively small in population. Both have extensive mineral deposits complemented by relatively fragile manufacturing sectors. Thanks to high prices for energy minerals and iron ore, the terms of trade of both countries were highly favourable from 2006 to 2014. Australia is well endowed with coal, iron ore and natural gas, all of which fetched high prices during the boom years; Kazakhstan has a similar endowment with the addition of oil. In Australia, the central and state governments have surrendered control over national investment strategy to the private sector and are also, with the exception of the petroleum sector, have foregone the capacity to exact additional revenue from the mining sector during times of high mineral prices. From 2009 high profitability in the sector triggered considerable investment in capacity expansion. Australia’s exchange rate is market-determined and followed the terms of trade, in the short term facilitating mining investment but in the long-term exacting a high cost: its manufacturing and other non-mining trade-exposed industries suffered loss of competitiveness, with a resulting lack of investment and industry closures. The Australian banks also borrowed overseas, and now that the boom has ended the Australian banking system finds itself with high levels of short-term overseas borrowing and very low levels of foreign exchange reserves.  By contrast, Kazakhstan’s market-oriented reforms over the past three decades did not surrender broad state control of the pattern of investment. Its government responded to the high mineral prices by concentrating on the oil industry, using negotiated agreements to finance developmental investment and build up an Oil Fund. This allowed control of the exchange rate to give its manufacturing industries the opportunity to upgrade their competitiveness. Royalties on other minerals were maintained at rates which discouraged exploration. The author is much more familiar with the Australian history than with that in Kazakhstan (the two countries are seldom compared) and will seek views as to whether his interpretation of Kazakhstani history is correct. The initial conclusion is that Kazakhstan managed the mineral price boom much more effectively than Australia.

Australia Kazakhstan paper