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CHAPTER 8 INTERNET CONNECTIVITY BY COMBINED GEOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICS.

In chapters 3 through 6 of this paper, Internet connectivity has been analysed from regional and socio-economic perspectives. In chapter 7, Internet connectivity for Indigenous people has been investigated. Higher income, presence of school going children in families and geographic location (with regard to remoteness) emerged as factors having relatively strong take-up of the Internet in cross-tabular outputs and Chapter 8 combines key outputs of this analysis. This chapter analyses Internet connectivity, disaggregated by remoteness area, by selected income ranges and household characteristics. The analysis by income is extended further to indigenous and non-indigenous people.

Table 14: Access to Any Internet and Broadband Connection , by Remoteness and Weekly Equivalised Household Income
	Nil, negative or between $1 and $399		Between $400 and $1,299		$1,300 or more
	Any Internet	BB connection	Any Internet	BB connection	Any Internet	BB connection
	%	%	%	%	%	%
Major Cities	42	26	72	48	87	66
Inner Regional	39	19	67	37	82	52
Outer Regional	37	15	64	32	79	46
Remote	35	14	63	33	79	50
Very Remote	19	10	59	33	79	50

Table 15: Access to Internet by Indigenous Status , by Remoteness by Weekly Equivalised Household Income
		Nil, Negative or Between $1 and $399		Between $400 and $1,299		$1,300 or More
		Any internet	BB Connection	Any internet	BB Connection	Any internet	BB Connection
		%	%	%	%	%	%
Non-Indigenous
	Major Cities	42	26	72	49	87	66
	Inner Regional	40	20	68	37	82	52
	Outer Regional	38	16	65	32	79	46
	Remote	38	15	65	33	79	50
	Very Remote	37	21	65	37	80	50
Indigenous
	Major Cities	36	22	64	43	80	59
	Inner Regional	34	19	60	33	74	46
	Outer Regional	26	13	50	27	69	42
	Remote	15	8	44	25	65	42
	Very Remote	6	3	29	16	62	39

The results suggest that for the overall population income has a strong relationship with Internet connectivity which is more sensitive to income than geographic spread. For a selected income range (such as equivalised household income of between $400 and $ 1,299 per week) there is a difference of 16 percentage points in Broadband connectivity rates for outer regional (even lower than very remote) Australia and major cities. However, the difference in Broadband connectivity rates between the lower income range (between $1 and $399 as well as nil or negative income) and the higher income range ($1,300 or more) is 40 percentage points in both major cities and very remote Australia.

In relation to the Indigenous population, the analysis reveals that in addition to income, remoteness has a strong influence on connectivity. For example, the lowest income group has only 3% Broadband connectivity in very remote Australia compared with 22% in major cities.

Analysed with regard to family composition (see Table 16), couple families with children under 15 have the highest Broadband connectivity in all areas, ranging from 34% in very remote Australia, and 64% in major cities. There is also considerable difference within remoteness areas between couple families with and without children under 15. Compared across regions, connectivity rates for one parent families, with or without children under 15, are similar to couple families without children under 15, and are considerably lower than couple families with children (differences ranging from 15 percentage points for Outer Regional Australia to 24 points for very remote Australia. Connectivity for one parent families with or without children under 15 is particularly low (10% and 15% respectively) in very remote Australia, perhaps reflecting a combination of low income and regional disadvantage for these families.

The above analysis brings out the complex relationship between Internet connectivity and relevant regional and socio-economic variables. Readers may have obtained enough information from this analysis, however those who wish to consider analysis undertaken in even greater details (and complexity) can consider Chapter 9 which tests relationships between such variables using regression analysis.

With the likelihood of collinearity between explanatory variables such as remoteness and income, cross-tabular analysis has its limitations. Multivariate regression analysis becomes a useful analytical tool for examining more complex situations.

Table 16: Access to the Internet and Broadband Connection, by Remoteness and Family Composition
	Couple family with no children under 15		Couple family with children under 15		One parent family with no children under 15		One parent family with children under 15		Other family
	Any Internet	BB connection	Any Internet	BB connection	Any Internet	BB connection	Any Internet	BB connection	Any Internet	BB connection
	%	%	%	%	%	%	%	%	%	%
Major Cities	65	43	86	64	65	43	65	42	64	45
Inner Regional	59	30	82	49	57	30	59	32	44	24
Outer Regional	56	26	78	41	50	26	52	26	39	21
Remote	59	29	78	43	44	24	44	23	33	17
Very Remote	55	31	54	34	25	15	18	10	17	8