Demographic Analysis Of Wollongong City And Its Suburbs

Population and Household Demographics

Wollongong City is in the Illawarra area of New South Wales. This region is almost 80 kilometer south of Sydney.  The city community profiles helps in providing a demographic analysis of Wollongong and its suburb regions. The population of the region as per the Estimated Resident Population (ERP) is 213,841and the nearby land area is around 68,384 (Pang, Lin and Jiang 2015). The population destiny for the area is around 3.13 people per hectare. The city offers magnificent natural environment that ranges from untouched rainforest to dramatic sea cliffs and sandy beaches.  All age group of people are found in the country.  Large percentage of the area in the city includes outlying towns, rural localities and suburbs.

 The people in the area are mostly of average age of about 35 to 40 years. Population of Aboriginals and Torres Strait Islander includes 2.6% of total population. 30% of population in the region is couples with children. Older couples without children include 11% of the total population (Wilkins 2015).  Almost 20% of the people in the region are qualified and holds a degree in University.  Average household income of the people on a weekly basis is around $ 1,335. The mortgage weekly repayment on the average basis includes $ 449 (Finlay and Price 2015).  Unemployment rate is usually low at Wollongong and participation of labor forces is high. Couples with children are more of the dominant population of Wollongong. Male population is higher than female population in the area. Majority of population in the area speaks languages other than English at their homes.

Dwelling type in The Wollongong region is as crucial determinant to know the role and functions of the residential. Huge concentration related to higher density dwellings is more likely to attract smaller households and young adults.  In Wollongong, almost 31% of the dwelling is of medium or high density. The dwelling types of the individual are mostly private in form.  The tenure type of dwelling is maximum mortgaged while fully owned is very less. The housing structure or separate house is more and people dwelling over there often opt for renting.  Separate, larger or detached dwellings are more likely to attract the perspectives families. The residential built form of the area often showcases the market opportunities as well as its planning policies.  Denser forms of housing are built around the employment centered and public transport nodes. In the year 2016, separate houses are around 67.3% (Bolton et al. 2018). Medium density is generally higher than tan the high density type of dwelling.  Occupied private dwellings in the area are maximum. The total number of dwellings in the region is estimated to grow up to 95,149 in the year 2026.  The average household size is decreasing from the rate of 2.54 to 2.51 by the end of 2026. The number of household during this period has increased at an alarming rate and the average number of individuals. The dwelling occupancy rate has risen up to 95.89%. It is expected that new dwelling will also increased at a rapid pace for the year 2016.

Dwelling Types and Occupancy Rates

Household income is one of the main elements to determine the socio-economic status of a particular region. The people with need of assistance or disability are a vital indicator of the level of ability so that they can efficiently participate in the economy and society of Australia.  Most of the population in the region has a weekly population of around $650-$799. During the year 2016, it was ascertained that larger proportion of individuals needs assistance with high household incomes. Such as people earning income that ranges up to $2, 500 each week and more.  Higher proportion in low income households consisting of earning that is less than $650 each week.  In Wollongong City, 10.7% of the overall population earned an overall income of around $1,750 or more each week for the year 2016 (Rowley et al. 2107).  The household income level of the people are usually not comparable over time and due to influences related to economic changes like inflation and wage level fluctuations.  Through income quartiles the relative income earning capabilities can be easily compared over time. Through the analysis of income distribution for the people it is evaluated that a greater proportion of individuals in the households has highest income quartile. Moreover, greater proportion is seen in the lowest income quartile.  The most vital change in the Wollongong City is seen between the year 20016 and 2011.  People needing assistance that was seen in the medium lowest quartile was increased by 651 individuals (Milner et al. 2015).

The Gini coefficient is the measure for inequality and is used to calculate the income distribution of households or individual within an economy. Gini coefficient lies between zero and unity. The higher is the level of Gini coefficient, more uneven will be the distribution of income. The Gini coefficient for Wollongong region in Australia is expected to be 0.337.The Gini coeffiecient is highly sensitive to high values. Since the last twenty years, the income of the average household has increased by 60%. While the income of the other quintile has also increased by 74%.

In the Wollongong region, 25.9% of the total households has mortgage that makes high loan repayments of  around $2,600 and ore for each month in the year 2016 (Beer et al. 2015). In the Wollongong area, level of equity, length of occupancy and mortgage repayments is related in a direct manner to the house prices. In the mortgage belt areas, the households are expected to pay a higher proportion of their income as compared to well-built areas. Moreover, the first-hand purchaser or buyer of such areas should have high mortgages than all the developed areas. The mortgage payment levels are indirectly comparable due to inflation. After analyzing the monthly housing repayments of household in the Wollongong regions in comparison with the Regional NSW the results are finally evaluated.

Household Income and Wealth Distribution

Overall, 20% were paying very low repayments whereas 25.9% of households were giving high mortgage repayments. The major differences between Wollongong NAD Regional NSW were:

• High percentage of people between $ 3,000 to $3,999, which is 11% more as compared to 6.2%.
• High percentage of individuals of $ 2,600 to $2,999, which is 9.5% compared to 6.1% (Brown and Gray 2015)

 In Wollongong area, the medium highest group was the largest quartile and comprises of at least 29% 0f the overall households with mortgages. Wollongong City’s family structure and household is a crucial demographic indicator. This helps in revealing the demand level for all facilities and services that is mostly related to the household types. In Wollongong city, 63.8% of the total population reported that need for assistance that was fully owned their home. 13.9% rented privately while the other 16.4% were included in the social housing for the year 2015 (Powdthavee, Lekfuangfu and Wooden 2015).

Pattern for Household expenditure for mortgage and rent in NSW, Wollongong:

References:

Beer, A., Bentley, R., Baker, E., Mason, K., Mallett, S., Kavanagh, A. and LaMontagne, T., 2016. Neoliberalism, economic restructuring and policy change: Precarious housing and precarious employment in Australia. Urban studies, 53(8), pp.1542-1558.

Bolton, P.E., Rollins, L.A., Brazill-Boast, J., Maute, K.L., Legge, S., Austin, J.J. and Griffith, S.C., 2018. Genetic diversity through time and space: diversity and demographic history from natural history specimens and serially sampled contemporary populations of the threatened Gouldian finch (Erythrura gouldiae). Conservation Genetics, pp.1-18.

Brown, S. and Gray, D., 2016. Household finances and well-being in Australia: An empirical analysis of comparison effects. Journal of Economic Psychology, 53, pp.17-36.

Da Luz, F.Q., Sainsbury, A., Mannan, H., Touyz, S., Mitchison, D. and Hay, P., 2017. Prevalence of obesity and comorbid eating disorder behaviors in South Australia from 1995 to 2015. International Journal of Obesity, 41(7), p.1148.

Finlay, R. and Price, F., 2015. Household saving in Australia. The BE Journal of Macroeconomics, 15(2), pp.677-704.

Milner, A., Niedhammer, I., Chastang, J.F., Spittal, M.J. and LaMontagne, A.D., 2016. Validity of a job-exposure matrix for psychosocial job stressors: results from the Household Income and Labour Dynamics in Australia Survey. PloS one, 11(4), p.e0152980.

Pang, Z., Lin, B. and Jiang, J., 2015. The papers listed below have been accepted for publication in future issues of Australian & New Zealand Journal of Statistics. Aust. NZJ Stat, 57(1), p.167.

Powdthavee, N., Lekfuangfu, W.N. and Wooden, M., 2015. What’s the good of education on our overall quality of life? A simultaneous equation model of education and life satisfaction for Australia. Journal of behavioral and experimental economics, 54, pp.10-21.

Rowley, S., Leishman, C., Baker, E., Bentley, R. and Lester, L., 2017. Modelling housing need in Australia to 2025 (No. 287). AHURI Final Report.

Wilkins, R., 2015. Measuring income inequality in Australia. Australian Economic Review, 48(1), pp.93-102.

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