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3412.0.55.003 - Information Paper: Review of Interstate Migration Method, Mar 2014  
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 27/03/2014   
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INFORMATION PAPER; REVIEW OF INTERSTATE MIGRATION METHOD, MARCH 2014

1. Introduction

2. Rebasing and Re-derivation of Interstate Migration

3. Review of Interstate Migration Method

4. Scenarios Analysed

5. Scenario Outcomes

6. Future Directions

7. Previous Interstate Migration Methods Used

8. Further Information

Attachment 1. ERP and Components of Change, 2006 to 2011


SUMMARY

Within Australia there is no direct quarterly measure of interstate migration, unlike that of natural increase and net overseas migration. Instead, quarterly estimates of interstate migration are modelled using Medicare change of address data and Department of Defence data in the case of military personnel. This model is reviewed and updated every five years using data from the latest Census of Population and Housing.

Changes to the model, including the updated expansion factors in this paper, have been applied to interstate migration estimates from 30 September 2011 onwards. These estimates were released on the 27 March 2014 in Australian Demographic Statistics, September Quarter 2013 (cat. no. 3101.0) and include the revision of preliminary estimates already published. The method described in this paper will be used for the intercensal period 2011 to 2016 until data from the 2016 Census of Population and Housing has been finalised.

The outcome of this current review is similar to the previous model used to estimate interstate migration from 2006 to 2011. It includes updated expansion factors based on data from the 2011 Census and Medicare data. Expansion factors are used to account for an under-coverage in the Medicare data on change of address for males and females in particular age groups. The new model includes the following characteristics:

  • Medicare data lagged by three months (both for calculating expansion factors and for estimating progressive quarters of interstate migration);
  • smoothed inputs used to produce expansion factors (i.e. Census, Medicare & multiple movers data were smoothed);
  • capping applied to expansion factors; and
  • expansion factors applied to males aged 19 to 32 years and females aged 19 to 25 (this differs to the age range used in 2006-2011 method).
These are explained in more detail below.

1. INTRODUCTION

In accordance with legislative requirements, the ABS provides quarterly estimates of the population of Australia and each of the states and territories. These population estimates, known as the estimated resident population (ERP), are published each quarter in Australian Demographic Statistics (cat. no. 3101.0).

The Census of Population and Housing provides the benchmark for population estimates once every five years. Post-censal ERP is then calculated forward each quarter by using the quarterly estimates of each of the three components of population change: natural increase (the excess of births over deaths); net overseas migration; and net interstate migration. Statistics of births and deaths are based on birth and death registrations, while overseas migration is calculated using data collected from passenger cards, visas and passport information for those persons travelling into and out of Australia. Data on interstate migration, however, are not directly estimated. Instead, post-censal estimates of net interstate migration are modelled using administrative by-product data. This document describes the most recent review of the method used to produce quarterly post-censal estimates of interstate migration.

Currently, the data used by the ABS is information on change of address advised to Medicare Australia and to the Department of Defence in the case of the military personnel. Every five years, after data from the latest Census has been finalised, these modelled estimates are then reviewed against, and potentially replaced by, the interstate migration estimates that are calculated from the Census (i.e. rebased to the Census). This is known as the re-derivation of interstate migration and is explained later in this paper.

Strength of Medicare data as an indicator

The ABS has evaluated a range of potential sources of administrative data for estimating interstate migration on a quarterly basis. Medicare Australia data supplying change of address information was found to be the most effective source currently available. For more information, refer to the Information Paper: Evaluation of Administrative Data Sources for Use in Quarterly Estimation of Interstate Migration (cat. no. 3127.0.55.001).

Medicare card holders are required to register any change of address when they make claims, or when their cards are replaced. However, it is known that some people, particularly younger people, do not register changes of address with Medicare, or do so long after the fact. Comparison of Medicare change of address with census data on the address of respondents one year prior to the Census suggests that the level of under-reporting in Medicare is fairly constant over time. In addition, this under-reporting seems to be similar for interstate arrivals and interstate departures, as well as for age and sex across each state and territory.

Defence force adjustments

Medicare theoretically covers all Australian usual residents as well as those non-Australian residents granted temporary Medicare registration. However, there are a range of Australian usual residents who do not access the Medicare system, primarily due to access to alternative health services. One such group is the military. As such, estimates of interstate migration produced from the interstate migration model are adjusted to compensate for defence force movements not covered by Medicare. These adjustments are estimated using counts of defence force personnel by age, sex and state/territory, obtained from the Department of Defence, with 70% of any change in quarterly defence force numbers assumed to be due to interstate migration not otherwise covered by the model.

Intercensal Difference - change to terminology

The terms 'intercensal discrepancy' and 'intercensal error' have been updated to include the new terms 'preliminary intercensal difference' and 'final intercensal difference' respectively. This is being done in response to the term 'intercensal error' often being misinterpreted, with the word 'error' being too commonly considered to be a synonym for 'mistake'. As a result, the ABS will use the terms 'preliminary intercensal difference' and 'final intercensal difference' in the 2016 rebasing cycle.

For further information see the Glossary in Australian Demographic Statistics (cat. no. 3101.0). 2. REBASING AND RE-DERIVATION OF INTERSTATE MIGRATION

Due to the non-compulsory and non-universal nature of the available (indirect) data sources, post-censal quarterly estimates of interstate migration have long been considered the weakest component of population change. For this reason, the model for generating post-censal estimates of interstate migration is largely superseded when new census information becomes available (i.e. rebased to the Census).

Part of the process of rebasing ERP for states and territories is the re-derivation of interstate migration for the intercensal period. To estimate interstate movements, the overall approach is to minimise the final intercensal difference for the states and territories using information from the census question on usual residence one year ago and the Medicare based estimate. For a state or territory where this census information does not reduce the final intercensal difference the Medicare based estimate is used.

For example, during rebasing of interstate migration estimates to the 2011 Census as seen in Table 1, for New South Wales, Victoria, South Australia, Western Australia and the Northern Territory the Medicare based estimate was used in the re-derivation as it reduced final intercensal difference more than the Census based estimate. Whereas for Queensland, Tasmania and the Australian Capital Territory the Census based estimate was used in the re-derivation.

The net total interstate flows however, must always sum to zero, as for each arrival in one state or territory there should always be a corresponding departure from another. Therefore, a zero-sum adjustment (or proration) is made to scale interstate migration levels for each state and territory so the total will sum to zero at the Australia level as seen in Table 1.

When the final intercensal difference is finalised, the difference between the original interstate migration estimates and the rebased estimates is apportioned across all quarters, movement categories, ages and sexes in the intercensal period in order to minimise quarterly change.


TABLE 1. REBASING INTERSTATE MIGRATION ESTIMATES — 2006-11
PROCESS FOR
PRELIMINARY INTERCENSAL DIFFERENCE

PROCESS FOR
FINAL INTERCENSAL DIFFERENCE

Medicare based estimate
Census based estimate
Preliminary
Intercensal Difference
Re-derivation
Zero-sum
adjustment
Final Intercensal
Difference
net gain/loss
net gain/loss
no.
net gain/loss
net gain/loss
no.
NSW
92,930
81,638
41,182
92,930
88,741
45,440
Vic.
-1,858
-5,928
21,475
-1,858
-4,785
24,447
Qld
-85,246
-66,527
23,902
-66,527
-70,404
9,115
SA
18,410
12,022
2,283
18,410
17,334
3,376
WA
-22,946
-17,612
-5,931
-22,946
-24,494
-4,360
Tas.
-365
-1,403
-1,252
-1,403
-1,956
256
NT
1,195
1,410
-1,753
1,195
456
-1,002
ACT
-2,120
-3,342
-1,639
-3,342
-4,184
438
OT(a)
..
-258
-615
-663
-708
-58
Aust.
0
0
77,652
15,796
0
77,652

.. not applicable
(a) Other Territories.

3. REVIEW OF INTERSTATE MIGRATION METHOD

The ABS has reviewed the interstate migration model using finalised data from the 2011 Census of Population and Housing. The outcome of this current review is similar to the previous model used to estimate interstate migration from 2006 to 2011. This review has focussed on a set of expansion factors applied to Medicare data, which adjust Medicare numbers to account for under-coverage of moves for men and women of certain age groups in the population. The defence force adjustment applied to interstate migration estimates was not reviewed.

Calculating expansion factors for Medicare data

Expansion factors applied to Medicare data are based on the estimated proportion of the population who moved interstate. To calculate this proportion, Medicare data for the period October 2010 to September 2011 was compared with 2011 Census data on persons' usual residence one year ago as seen in the graph below. The period of Medicare data chosen reflected the assumption that there is a lag in the registration of change of address through Medicare.



Expansion factors, as shown in the equation below, were estimated for each state and territory, by sex, single year of age and movement category (arrivals/departures). Analysis showed that for all states and territories expansion factors were, on average, greater than 1 (i.e. suggesting 'undercoverage' in Medicare data) for males aged 19-32 years and females aged 19-25 years. These age ranges were chosen as they decreased the final intercensal difference the most when compared to any other range. Expansion factors are applied universally for all states and territories to Medicare data with these age-sex characteristics. For all other age groups, it is assumed that Medicare data provides a full coverage (i.e. an expansion factor of 1 was used). The equation used to calculate the expansion factors was:



Multiple movers and census data

Some people will move more than once during a given time period, including some who move to one location, then return to their original location. However, the Census asks for each person's address one year ago without reference to multiple moves which could have occurred over the one year period.

Medicare data does include some information on multiple/return movements as it is captured each quarter. During the 2006 review the proportion of multiple movements was used as a proximate to adjust data from the 2006 Census.

The proportion of multiple movers identified using Medicare data was calculated by dividing all quarterly movements by the number of final annual movements for each state or territory, by sex, single year of age and movement category (arrivals/departures). Those calculations showed that 7% of all movements were multiple movements. Those who had moved twice represented 6% of all movements whereas those who moved more than twice only represented 1% of all movements.

For the 2011 review of the interstate migration method, an assumption was made that the proportion of multiple movements would not have changed significantly from those calculated during the 2006 review. Therefore, the same proportions of multiple movements have been applied to adjust data from the 2011 Census. This will be reassessed for the 2016 review.

The use of census data on address one year ago does introduce some potential problems because a relatively short (and therefore potentially more volatile and less representative) time period is used to estimate expansion factors. Smoothing used in generating the expansion factors, as seen in the many scenarios analysed, helps to address these problems.
4. SCENARIOS ANALYSED

A number of scenarios were developed (several of which are included in this paper) using Medicare data and data from the 2011 Census. The complete process of estimating interstate migration for the intercensal period (2006 to 2011) and final rebasing was replicated for each scenario. These scenarios vary in their use of expansion factors, lagging, smoothing and other adjustments, and were each used to estimate June 2011 ERP by state/territory. The extent to which each scenario matched final June 2011 ERP, or in other words reduced final intercensal difference, was used as an indication of its accuracy in modelling interstate migration (refer to Scenario outcomes below). The plausibility of assumptions in each scenario was also taken into account.

Some of the scenarios used in the interstate migration review are summarised in the following table with their components described in more detail further in this paper.

TABLE 2. INTERSTATE MIGRATION REVIEW, Scenarios analysed
SCENARIO

INPUT DATA(a)

EXPANSION FACTORS

Census data adjusted(b)Medicare laggedAll inputs
smoothed
or raw
Factors
smoothed
or raw
Factors
Capped

S1....RawNo factors applied..
S2....RawRaw..
S3Age adjusted..RawRaw..
S4Age adjustedLaggedRawRaw..
S5Age adjustedLaggedSmoothedRaw..
S6..LaggedSmoothedRaw..
S7Age adjustedLaggedSmoothedRawCapped
S8 (c)..LaggedSmoothedRawCapped
S9..LaggedSmoothedSmoothedCapped
S10..LaggedRawSmoothedCapped

.. not applicable
(a) Input data includes Census, Medicare and multiple movers.
(b) Census data adjusted for age at move.
(c) Scenario 8 is the preferred model chosen for the 2011-16 expansion factors.

Lagging of Medicare data

Analysis has shown that registration of changes of address through Medicare generally occurs some time after the actual move. The interstate migration models for both 2001-2006 and 2006-2011 assumed an average registration lag of three months (one quarter), so Medicare information for a particular quarter was used to estimate interstate migration for the previous quarter. It is not possible to lag this data further (i.e. to assume a delay in registration of more than three months) as this would impact on the production and publication of population estimates which are released within 6 months after the reference period.

The first scenario considered (S1) assumes that Medicare changes of address perfectly capture all interstate movements (i.e. no under coverage), and that there is no delay between persons moving address and registering a change with Medicare (i.e. no lagging). These assumptions are known to be false, but are used to provide a baseline for later scenarios.

Comparison of the outcomes of most scenarios tested indicated that the use of lagging reduced final intercensal difference particularly at the overall level as seen in the sum of absolutes in Table 3. Later scenarios tested alternative methods of applying expansion factors (smoothing input data and/or smoothing the factors produced), adjusting census data for the age at move, as well as the impact of imposing an upper limit (or 'cap') on the factors.

Smoothing

It is likely that much of the variability in data from one single-year age group to the next was due to volatility in the data, so smoothing was incorporated in some form in many of the scenarios analysed. Two options for smoothing were used in the production of some expansion factors. Firstly, for each state/territory, sex and movement category, all of the input data used to calculate expansion factors were smoothed across single years of age, using a three-term moving average as applied in scenarios S5 to S9. The second option was to smooth the actual output (or expansion factors), again using a three-term moving average as applied in scenarios S9 to S10.

Overall, the second option (smoothing of expansion factors) produced only small improvements in the estimated levels of final intercensal difference; in some cases, results were worsened when the factors were smoothed. Greater improvements (represented by smaller intercensal discrepancies) were gained by smoothing the inputs of Medicare, Census and multiple movement data used to produce the expansion factors. For most states and territories, the best results were found in those scenarios from which expansion factors were created using smoothed input data.

Capping expansion factors

In this interstate migration model, expansion factors calculated as being greater than 2 (i.e. less than 50% coverage estimated for Medicare data) are capped at 2. The rationale for 'capping' expansion factors is that this would reduce the influence of outlying extreme results, such as unusually low registrations for particular age/sex groups.

For this review, analysis of the various scenarios and subsequent expansion factors showed once again that capping produced improvements in most cases. Scenario S8 (the preferred model) is an improvement on scenario S6 by using capping which has decreased final intercensal difference.

The only outlying groups of interstate movers for which capping was applied during this review occurred for males of various ages between 20 to 26 arriving to or departing to the Northern Territory or the Australian Capital Territory and for females aged 19 arriving to the Australian Capital Territory.

Census data adjustment - age at move

The age of interstate migrants taken from census information on a person's usual residence one year ago is the age at census night - not the age at move. Therefore this adjustment assumes half of the population were one year younger at date of move than at date of the Census. It was calculated by pairing each consecutive single year of age and dividing by two as seen in the equation below:


While this adjustment did show improvements in some scenarios, it was not chosen as it had less impact on the actual final intercensal difference than the preferred scenario.
5. SCENARIO OUTCOMES

Table 3 below shows the actual final intercensal difference (both in terms of persons and as a percentage of final 30 June 2011 ERP) for 2006-11. For each scenario the complete process of estimating interstate migration for the intercensal period (2006 to 2011) and final rebasing has been replicated. This is necessary to show the final intercensal difference produced under each scenario tested. The following table summarises these outcomes for each scenario.


TABLE 3. FINAL INTERCENSAL DIFFERENCE, Actual and Scenario examples — 2006 to 2011
NSW
Vic.
Qld
SA
WA
Tas.
NT
ACT
Sum (a)

PERSONS (No.)
Actual

Scenario
outcome(b)
45,440
24,447
9,115
3,376
-4,360
256
-1,002
438
..
S1
49,028
23,125
9,762
3,892
-8,095
665
-1,179
512
..
S2
43,613
22,758
9,972
3,516
-3,606
471
361
624
..
S3
42,155
23,307
10,433
3,930
-3,724
533
345
730
..
S4
42,949
23,876
9,357
3,811
-3,250
379
94
495
..
S5
43,350
23,867
9,083
3,757
-3,358
340
242
432
..
..
S6
44,396
23,332
8,663
3,193
-2,968
279
478
341
..
S7
43,444
23,910
9,134
3,772
-3,360
347
33
433
..
S8 (c)
46,647
23,269
8,279
2,603
-3,448
225
-105
245
..
S9
44,371
23,673
8,799
3,200
-3,011
299
21
360
..
S10
44,409
23,761
8,767
3,177
-2,969
295
-82
354
..


PERCENTAGE OF FINAL 30 JUNE 2011 ERP (%)

Actual
0.63
0.44
0.20
0.21
-0.19
0.05
-0.43
0.12
2.27
Scenario
outcome(b)
S1
0.68
0.42
0.22
0.24
-0.34
0.13
-0.51
0.14
2.68
S2
0.60
0.41
0.22
0.21
-0.15
0.09
0.16
0.17
2.02
S3
0.58
0.42
0.23
0.24
-0.16
0.10
0.15
0.20
2.09
S4
0.59
0.43
0.21
0.23
-0.14
0.07
0.04
0.13
1.86
S5
0.60
0.43
0.20
0.23
-0.14
0.07
0.10
0.12
1.89
S6
0.62
0.42
0.19
0.19
-0.13
0.05
0.21
0.09
1.90
S7
0.60
0.43
0.20
0.23
-0.14
0.07
0.01
0.12
1.81
S8 (c)
0.65
0.42
0.18
0.16
-0.15
0.04
-0.05
0.07
1.71
S9
0.61
0.43
0.20
0.20
-0.13
0.06
0.01
0.10
1.73
S10
0.62
0.43
0.20
0.19
-0.13
0.06
-0.04
0.10
1.75

(a) Sum of absolute values. Excludes Other Territories.
(b) Estimated intercensal discrepancy produced under each scenario.
(c) Scenario 8 is the preferred model chosen for the 2011-16 expansion factors.

Assessing Model/Scenario quality

The alternative interstate migration models (scenarios) were assessed using two main criteria.
  • Models were assessed on the basis of the resulting final intercensal difference for each state and territory for June 2011 (refer to Rebasing and re-derivation of interstate migration above). In part, the aim was to reduce the overall final intercensal difference (i.e. reduce the sum of absolute percentage values). Each model had been applied over the 2006 to 2011 intercensal period so final intercensal difference could be compared as seen in Table 3. Final intercensal difference is the remaining unattributable difference between the ERP counts at 30 June 2011 after all components of population change have been finalised and the final ERP at 30 June 2011 based on the 2011 Census. Refer to Attachment 1 for ERP and components of change for 2006 to 2011.
  • Models also had to make intuitive sense. This second criteria was included to avoid problems associated with selecting non-intuitive models which could coincidentally produce lower intercensal differences. Similarly, it was important that any relationships assumed by the model finally proposed were considered to be sustainable over the next intercensal period from 2011 to 2016.

For this review all states and territories have shared the same model. Although a model could be designed for an individual state or territory to reduce their own final intercensal difference, it needs to be remembered that all states and territories need to be considered at the same time so that the overall final intercensal difference is collectively improved.


Preferred model

Results from scenarios 1-10 indicated that the preferred interstate model should contain the following characteristics:

  • Lagging of Medicare input data by three months (both for calculating expansion factors and for estimating progressive quarters of interstate migration);
  • Smoothing of input data (Census, Medicare and multiple movers) used to produce expansion factors;
  • Capping applied to expansion factors;
  • Expansion factors applied to males aged 19 to 32 years and females aged 19 to 25.

This preferred model was reflected in scenario eight (S8) and provided the best overall results. It also happens to be the same model as was used in the previous review apart from a slight change to the age ranges.

Although the various scenarios display little variation to each other as seen in Table 3, the preferred scenario (S8) was able to reduce the overall final intercensal difference while also reducing it for the majority of states and territories. In addition, S8 was able to improve on the final intercensal difference at the Australia level by reducing the sum of absolute percentage values from 2.27 (actual) to 1.71 (S8).

The ABS will apply this model to produce interstate migration estimates each quarter for the current intercensal period (i.e. September quarter 2011 to June quarter 2016) and onwards until once again a review is undertaken after data from the 2016 Census of Population and Housing has been finalised. A defence force adjustment will continue to be applied to estimates produced by this model to compensate for movements of defence force personnel not covered by Medicare.

6. FUTURE DIRECTIONS

With the completion of this review, the ABS will investigate the feasibility of producing expansion factors at the capital city and balance of state level. If successful, the quality and usefulness of any new expansion factors at the sub-state level will first be examined in the context of improving the measurement of intrastate migration and the measurement of sub-state ERP. 7. PREVIOUS INTERSTATE MIGRATION METHODS USED

For information on the method used for estimating interstate migration for the intercensal period 2001 to 2006 is detailed in Demography Working Paper: 2004/1, Review of Interstate Migration Method, May 2004. For the method used in estimating interstate migration for the most recent intercensal period 2006 to 2011 see: Information Paper: Review of Interstate Migration Method, March 2009.


8. FURTHER INFORMATION

For further information on the interstate migration method, contact Amy Donnelly in Hobart (03) 6222 5984, or email your comments to the attention of Amy Donnelly at demography@abs.gov.au. The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.

ATTACHMENT 1: ERP AND COMPONENTS OF CHANGE, 2006 to 2011

Tables A1 and A2 below show how the demographic balancing equation is calculated between the 2006 and 2011 Censuses. Two tables have been presented to be able to clearly show data for all states and territories. Each table contains preliminary net interstate migration (unrebased) and final net interstate migration (rebased). They show how each contribute to ERP and help generate a preliminary intercensal difference or a final intercensal difference. For example, preliminary net interstate migration, which has used modelled Medicare data for quarterly interstate migration estimates, will contribute to the preliminary intercensal difference. Final intercensal difference is the remaining unattributable difference between the two different ERP counts at 30 June 2011. The first count is the final ERP at 30 June 2011 based on the 2011 Census and the second count is after all components of population change (including interstate migration) have been finalised.

TABLE A1. ERP AND COMPONENTS OF CHANGE — Selected States, 2006 to 2011 ('000)
NSW
Vic.
Qld
SA
Aust.(a)
'000
'000
'000
'000
'000

With preliminary net interstate migration
ERP, 30 June 2006
6,742.7
5,061.3
4,008.0
1,552.5
20,451.0
+ final natural increase
253.4
178.1
177.6
36.1
780.3
+ final NOM(b)
356.5
318.0
229.8
71.7
1,186.4
+ preliminary NIM(c)
-92.9
1.9
85.2
-18.4
0.0
=unrebased ERP, 30 June 2011
7,259.7
5,559.3
4,500.7
1,641.9
22,417.7
Final rebased ERP, 30 June 2011
7,218.5
5,537.8
4,476.8
1,639.6
22,340.0
Preliminary intercensal difference
41.2
21.5
23.9
2.3
77.7

With final net interstate migration
ERP, 30 June 2006
6,742.7
5,061.3
4,008.0
1,552.5
20,451.0
+ final natural increase
253.4
178.1
177.6
36.1
780.3
+ final NOM(b)
356.5
318.0
229.8
71.7
1,186.4
+ final NIM(c)
-88.7
4.8
70.5
-17.3
0.0
= ERP, 30 June 2011 (with components finalised)
7,264.0
5,562.3
4,485.9
1,643.0
22,417.7
Final rebased ERP, 30 June 2011
7,218.5
5,537.8
4,476.8
1,639.6
22,340.0
Final intercensal difference
45.4
24.4
9.1
3.4
77.7

(a) Includes Other Territories.
(b) NOM - Net overseas migration.
(c) NIM - Net interstate migration.


TABLE A2. ERP AND COMPONENTS OF CHANGE — Selected States and Territories, 2006 to 2011 ('000)
WA
Tas.
NT
ACT
Aust.(a)
'000
'000
'000
'000
'000

With preliminary net interstate migration
ERP, 30 June 2006
2,050.6
489.3
209.1
335.2
20,451.0
+ final natural increase
91.8
12.5
14.5
16.2
780.3
+ final NOM(b)
182.2
8.1
7.2
12.9
1,186.4
+ preliminary NIM(c)
22.9
0.4
-1.2
2.1
0.0
=unrebased ERP, 30 June 2011
2,347.5
510.2
229.5
366.3
22,417.7
Final rebased ERP, 30 June 2011
2,353.4
511.5
231.3
368.0
22,340.0
Preliminary intercensal difference
-5.9
-1.3
-1.8
-1.6
77.7

With final net interstate migration
ERP, 30 June 2006
2,050.6
489.3
209.1
335.2
20,451.0
+ final natural increase
91.8
12.5
14.5
16.2
780.3
+ final NOM(b)
182.2
8.1
7.2
12.9
1,186.4
+ final NIM(c)
24.5
1.9
-0.4
4.2
0.0
= ERP, 30 June 2011 (with components finalised)
2,349.0
511.7
230.3
368.4
22,417.7
Final rebased ERP, 30 June 2011
2,353.4
511.5
231.3
368.0
20,340.0
Final intercensal difference
-4.4
0.3
-1.0
0.4
77.7

(a) Includes Other Territories.
(b) NOM - Net overseas migration.
(c) NIM - Net interstate migration.


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