







































AUSTRALIAN POPULATION STUDIES  2017 | Volume 1 | Issue 1 | pages 55–68 

 

© Carson, Punshon, McGrail and Kippen. Published under the Creative Commons Attribution-NonCommercial licence 3.0 
Australia (CC BY-NC 3.0 AU). Journal website: www.australianpopulationstudies.org 

 

Comparing rural and regional migration 
patterns of Australian medical general 
practitioners with other professions: 
implications for rural workforce strategies 

Dean Carson*  Charles Darwin University and Umeå University 

Katherine Punshon  Flinders University 

Matthew McGrail  Monash University 

Rebecca Kippen  Monash University  

*Corresponding author. Email: dean.carson@cdu.edu.au. Address: Pausele 95, Blåviksjön Sweden 92195 

Paper received 25 July 2017; accepted 7 October 2017; published 20 November 2017 

Abstract 

Background 

The shortage of professional workers in rural and regional Australia continues as a major policy 

challenge. There has been substantially more strategy investment for the medical general 

practitioner (GP) profession than for other professions, particularly at the start of their careers. 

Aims 

To examine differences between domestic migration patterns of GPs and other professionals to rural 

and regional zones in Australia for younger, mid-life and older workers.  

Data and methods 

Data from the Australian Bureau of Statistics (ABS) 2011 Census were used to examine five-year 

migration rates for professionals in five ABS occupational classifications: generalist medical 

practitioners (GPs); engineering professionals; legal professionals; education professionals; and other 

health professionals. Migration volumes were benchmarked for GPs and compared both for other 

professions and career stage. 

Results 

GPs were less likely than other professionals to migrate from major urban to rural zones, regional to 

rural zones, or rural to regional zones. Younger GPs had the highest rural migration rates, while mid-

life and older GPs were least likely to migrate to rural and regional zones. In contrast, increasingly 

age was associated positively with migration to rural zones for those in the other four professions. 

Conclusions 

Despite concerted policy efforts to encourage more GPs to move to rural areas, overall rural 

migration rates for GPs are lower than for other professionals, especially for older workers. Further 

investigation of the links between GP migration patterns and workforce policies needs to be 

undertaken to inform the application or otherwise of workforce strategies used by other professions. 

Keywords 

Professional migration; medical general practitioners (GPs); counter-urbanisation; rural; regional; 

workforce; gravity model. 

http://www.australianpopulationstudies.org/
mailto:dean.carson@cdu.edu.au


56 Carson D et al. Australian Population Studies 1 (1) 2017 

 

1. Introduction 

Encouraging professionals to work in rural and regional parts of Australia remains a policy challenge. 

Different professional groups have adopted diverse strategies for addressing geographic 

maldistribution and the persistent shortage of workers in rural areas (Corcoran, Faggian and McCann 

2010). The health and education professions have developed the most comprehensive strategies 

(Jenkins, Reitano and Taylor 2011). Other professions, such as engineering and the legal profession, 

lament having few if any rural workforce strategies (Campbell and Lindsay 2013; Sharma, Oczkowski 

and Hicks 2016).  

Among all the professions, medical general practitioners (GPs) appear to have attracted the most 

policy attention and resources over at least the past two decades (Walters et al. 2017). In recent 

times it has been argued that Australia has a sufficient supply of doctors for non-metropolitan areas 

as a whole, but that significant shortages persist in various kinds of ‘rural areas’, particularly those 

with smaller populations and more dispersed settlements (Walters et al. 2017). 

National analyses of need and distribution are rare for other professions. Despite differences in the 

extent of workforce strategies applied to them, there have been few comparative studies of rural 

workforce issues or migration patterns among other professions (Carson et al. 2010). A better 

understanding of the similarities and differences in migration patterns is a necessary first step in 

understanding the applicability and transferability of strategies used for professionals in other 

sectors to the GP workforce. 

Recruitment and retention of labour in rural and regional areas involves stimulating particular 

migration patterns. Researchers have attempted to track GP movements between major urban, rural 

and remote locations (Mazumdar and McRae 2015; McGrail and Humphreys 2015; Ricketts and 

Randolph 2007). However, the extent to which the observed patterns in these studies differ from 

what might be considered theoretically or comparatively ‘normal’ has not been considered. Notably, 

it is not known if the observed migration patterns are unique to GPs or apply across professions, and 

whether observed patterns are consistent with rural migration theories.  

Migration patterns change throughout the life course and as careers progress (Kley 2011). Increasing 

occupational mobility among all professions (Perales 2014) means that understanding of life course and 

life stage impacts on locational choice is paramount. A life-stage perspective is thus essential to 

understanding the spatial distribution of professional workers in Australia (McGrail and Russell 2016). 

This paper addresses some of the gaps in knowledge about professional migration in Australia by 

comparing migration patterns between GPs and other professionals across career stages. The paper 

limits its discussion to migration within Australia, recognising that drivers of international migration are 

likely to be substantially different. The findings are interrogated in relation to leading rural migration 

theories. By using GPs as a benchmark, the research also allows for some insights into how useful 

workforce strategies for the general medical practitioner profession may be for other professions.  

2. Rural migration theory 

Rural migration theory suggests a number of potential drivers of domestic migration from urban to 

rural areas. These can be divided broadly into economic and lifestyle drivers which may include, for 



Australian Population Studies 1 (1) 2017 Carson D et al. 57 

 

example, the prospect of cheaper housing, higher pay and a ‘better’ or different lifestyle. A 

substantial focus of the economic literature has been on so-called ‘escalator migration’ in which 

younger workers are attracted to rural areas by the promise of rapid career development (Smith and 

Sage 2014). It is increasingly recognised, however, that economic motivations may apply also at 

other stages of life (Martel, Carson and Taylor 2013). Likewise, while ‘lifestyle’ dominates in 

discussions of push–pull factors for older worker migration to rural areas (Han 2016; Argent et al. 

2014), lifestyle motives may apply also to younger workers. Nevertheless, a life stage framework 

which postulates that there are substantial opportunities for rural migration for younger and older 

workers, in particular, is a useful foundation for examining professional migration patterns. 

Strategies aimed at drawing GPs to rural areas have considered both economic and lifestyle factors. 

More recently, they have focused additionally on improved career pathways and career development 

(for an overview of strategies in Australia in the past 20 years, see Walters et al. 2017). Economic 

inducements in the form of financial incentives may include additional service payments and support 

for housing and continuing education costs. These tend to be governed by the degree of ‘rurality’ of 

the practice location and increase accordingly. Lifestyle strategies may include support for partners 

and children to assist the family unit to embed more fully in the community.  

There is some evidence of the effectiveness of career development strategies for GPs, such as 

providing opportunities for postgraduate vocational training in rural areas, mixed evidence of the 

effectiveness of financial incentive programs and little known about the effectiveness of lifestyle 

related strategies (Verma at al. 2016). Nevertheless, the importance of ‘life stage’ is implicit in the 

suite of strategies developed for GPs in Australia. Most rural workforce strategies focus on 

encouraging graduate doctors to select rural clinical training early in their career with the hope that 

some will ‘step down’ from the larger regional training centres to smaller rural practices in 

subsequent years (Farmer et al. 2015; Mullan, Chen and Steinmetz 2013). 

In addition to rural-based education, substantial effort has been invested in encouraging people of 

‘rural origin’ or ‘rural background’ (meaning they spent part or all of their childhood in rural areas) 

to, firstly, undertake medicine and, secondly, specialise in rural relevant medicine, predominantly 

as GPs (Sureshkumar et al. 2017). The principal outcome of rural workforce strategies for GPs has 

been to create a ‘rural specialisation’ which is selected very early in a doctor’s career. Meanwhile, 

rural strategies targeting older GPs have focused largely on retention with little consideration 

given as to how lifestyle or amenity migration may also be stimulated for GPs whose family 

responsibilities, for example, are no longer so tightly tied to larger regional or major urban centres. 

Other health professions have also been keen to adopt some of the strategies used to encourage 

spatial redistribution of the GP workforce, with particular attention to early career oriented 

strategies (Hay et al. 2017).  

The education profession also has a long history of rural-focused workforce strategies which include 

rural practicum placements and career advancement incentives for periods of rural service (Kelly and  

Fogarty 2015). In other professions, rural workforce strategies have tended to be less systematically 

employed. However, there are now increasing calls for lessons from the health and education sectors 

to be learned in professions such as the legal profession (Browne 2016) and engineering (Sharma, 

Oczkowski and Hicks 2016). 



58 Carson D et al. Australian Population Studies 1 (1) 2017 

 

Rural workforce strategies may well be transferable between professions because of the universality 

of some of the rural migration theories considered above. However, structural differences in 

professions may mean that strategies which are effective for one profession may be less so for 

others (Perales and Vidal 2013). Clearly, arguments could be made that each profession will have its 

own enablers of, and constraints to, rural migration. However, empirical evidence of migration 

patterns between professions is yet to be published. Along with differing demands for particular 

professions, factors such as age of entry into the workforce, gender balance within occupations and 

options for career pathways may provide varying opportunities for, and barriers to, rural migration at 

different life stages. This paper provides some insights into how such opportunities may be grown 

and barriers lowered.  

3. Data and methods 

This research utilises the Modified Monash Model (MMM) developed for use in GP retention policies 

in Australia (Hudson and May 2015). This model distinguishes four types of geographical zone: major 

urban; regional; rural; and remote. For the purposes of our research the zones are defined at the 

national level (Figure 1) with no distinction made between moves within or between the states and 

territories.  

 

Figure 1: Major urban, regional, rural and remote zones based on SA3s. 

Source: ABS SA3 shapefile with concordance to zones by authors. 

The MMM as one of many systems for classifying urban, regional, rural and remote areas in 

Australia. It closely relates to the Australian Statistical Geography Standard – Remoteness Areas 

(ASGS-RA) classification, but provides a more nuanced distinction within the two ‘regional’ categories 

based on population size rather than remoteness. The MMM is selected and used in this research 

because of its immediate relevance to GP workforce distribution strategies.  



Australian Population Studies 1 (1) 2017 Carson D et al. 59 

 

In this paper, the ‘major urban’ zone consists of all major cities (MMM category 1, which is nearly 

identical to ASGS-RA 1). MMM distinguishes between ‘regional’ centres with more than 50,000 

residents (MM category 2), and more sparsely populated ‘rural’ areas with under 50,000 residents 

(MM categories 3–5). The MM also incorporates ‘remote’ and ‘very remote’ locations (MM categories 

6–7), which are nearly identical to ASGS-RA 4 and 5 and include small populations that are isolated 

from larger urban centres.  

The substantial differences in human geography between rural and remote locations (Taylor 2016) 

mean that modelling patterns of migration to the latter requires separate attention. Migration to 

remote and very remote locations consequently is not considered in this paper. Likewise, the 

substantial impact of recent overseas immigrants on the geographic distribution of health and other 

professionals in Australia warrants separate attention (Golebiowska et al. 2016; Negin et al. 2013; 

Terry, Woodroffe and Ogden 2013). Hence, professionals who had arrived in Australia within the past 

five years were also excluded from this study.  

Data drawn from the ABS 2011 Census (Australian Bureau of Statistics 2011) included:  

• occupation – separately identifying ‘generalist medical practitioners’ (GPs), other health 

professionals, education professionals, engineering professionals and legal professionals 

• age – divided into ‘younger’ (less than 40 years), ‘middle’ (40–54 years) and ‘older’ (55 years and 

over) as broad proxies for career stage 

• place of residence on Census night 2011 

• place of residence five years’ prior to Census night.  

Place of residence was defined at Statistical Area Level 3 (SA3), which is a classification intended to 

represent regional agglomerations identified for district-level activities like health, education or 

natural resource management (Peters et al. 2016). SA3 units were then categorised as major urban, 

regional, rural and remote zones. ‘Migrants’ were identified as individuals who had a residential 

address in one zone on Census night 2011 and in a different zone five years’ earlier. Observed 

migration matrices were constructed separately for each profession, and for younger aged, middle 

aged and older aged populations in each profession.  

A gravity model (see Anderson 2011) was used to estimate the proportion of migrants from one zone 

who would be expected to move to another zone, given the size of the professional group and the 

initial geographic distribution. The gravity model approach accounts for the substantial differences in 

job availability in different zones for different professions. The gravity model assumed that the 

distance between zones was identical, and that there were no intervening factors which would 

influence migration between any two zones (such as differences in income).  

Following Shen’s approach (Shen 2016), 

𝑀𝑖𝑗 = 𝑃𝑖 𝑃𝑗  

𝑀𝑖𝑗  is the expected migration between zone 𝑖 and zone 𝑗, and 𝑃𝑖 and 𝑃𝑗 are the 2011 population of 

professionals in the respective zones. An estimated migration matrix was constructed using this 

equation for each profession and each career stage within each profession. An attractiveness error 

(AE) was then calculated: 



60 Carson D et al. Australian Population Studies 1 (1) 2017 

 

𝐴𝐸 =
𝑂𝑖𝑗 − 𝑀𝑖𝑗

𝑂𝑖𝑗
 

where 𝑂𝑖𝑗 is the observed migration and, as above, 𝑀𝑖𝑗 is the expected migration. While the error 

values for a single professional group do not reflect the ‘normality’ of its observed migration patterns 

well (Simini et al. 2012), comparison of error values between professional groups highlights 

differences in migration patterns. The error differential (ED) for each profession was calculated as 

𝐸𝐷𝑝 = 𝐴𝐸𝑝 − 𝐴𝐸𝑔𝑝 

where 𝑔𝑝 is GPs and 𝑝 is the comparison professional group. Professional groups with positive EDs 

were more attracted (in the technical sense of more likely to migrate) than GPs to the focus zone, 

whereas those with negative EDs were less attracted than GPs to the focus zone.  

While there are no tests of statistical significance of these differences, given that census (whole of 

population) data are used, a value of +/- 5 per cent was assumed to have some practical importance. 

The gravity model accounted for differences in the geographical structure of each professional group. 

The most significant example was the relative lack of GPs in the younger age groups in the rural 

zones when compared with other professional groups. This was largely a result of the concentration 

of postgraduate training in the regional and major urban zones. 

Census data have previously been used to analyse the geography of the GP workforce in Australia  

and other professions (Johnston and Wilkinson 2001; Joyce and Wolfe 2005). The use of Census data 

for this purpose can be problematic because of the requirement for professional self-identification, 

aggregation of data at the SA3 level and the potential disconnect between place of residence (which 

is used in migration analysis) and place of work. Nevertheless, the Census remains the only data set 

in Australia which allows for direct comparisons between professions. 

4. Results 

GPs (10%) were less likely to be living in the rural zone in 2011 than other health professionals (15%) 

and education professionals (16%), but similarly likely to be living in a rural zone as engineering and 

legal professionals (Table 1). While overall migration rates were similar among the five  professional 

groups examined, GPs were more likely to migrate to a different zone at younger ages, and legal 

professionals were less likely to migrate to another zone at younger ages. 

Table 1: Zone of residence (2011) and inter-zonal migration rates (2006–2011) by professional group 

 GPs 
(n = 36,914) 

Other health 
(n = 35,1731) 

Education 
(n = 418,474) 

Engineering 
(n = 262,544) 

Legal 
(n = 149,019) 

Zone of residence      

Reside: major urban zone  74%  66%  65%  74%  74% 

Reside: regional zone  15%  17%  17%  13%  13% 

Reside: rural zone  10%  15%  16%  11%  11% 

Reside: remote zone  1%  2%  2%  2%  2% 

Migration rates      

Overall migration between 
zones 

 11%  9%  8%  10%  8% 

Migration: early career   19%  14%  14%  14%  11% 

Migration: mid-career   8%  6%  6%  6%  7% 

Migration: late-career   4%  5%  4%  4%  6% 

Source: ABS 2011 Census. 



Australian Population Studies 1 (1) 2017 Carson D et al. 61 

 

Table 2: Patterns of migration into the rural zone, 2006–2011 

 Percentage of migrants who moved to the rural 

zone (observed value on top line; expected on 

second line) 

Standardised differences in observed 

and expected migration (‘Error 

Differential’, compared to GPs) 

  
GPs 

Other 
Health 

EDU ENG Legal 
Other 
health 

EDU ENG Legal 

All migrants 
21% 

(21) 

28% 

(25) 

30% 

(26) 

24% 

(22) 

27% 

(23) 
8% 12% 7% 14% 

Migrants: 
from major 
urban 

33% 

(38) 

41% 

(44) 

45% 

(46) 

40% 

(41) 

43% 

(42) 
8% 14% 12% 17% 

Migrants: 
from regional  

17% 

(11) 

31% 

(18) 

37% 

(19) 

23% 

(12) 

26% 

(12) 
8% 15% 13% 20% 

Migrants: 
from remote  

24% 

(10) 

26% 

(15) 

25% 

(16) 

19% 

(11) 

24% 

(11) 
-18% -23% -18% -4% 

Migrants: 
early career 

20% 

(16) 

25% 

(22) 

30% 

(24) 

23% 

(20) 

24% 

(19) 
-10% -4% -11% -4% 

Migrants: 
mid-career 

23% 

(22) 

31% 

(26) 

29% 

(26) 

28% 

(24) 

28% 

(24) 
13% 6% 11% 13% 

Migrants: 
late-career  

25% 

(25) 

37% 

(28) 

33% 

(28) 

32% 

(26) 

36% 

(26) 
25% 18% 20% 27% 

Source: Authors’ construction based on gravity model analysis of ABS 2011 Census data. Notes: EDU = Education; ENG = 
Engineering. 

Table 2 shows the percentage of migrants of various types who moved to the rural zone, and the 

error differential for each non-GP professional group compared to GPs. While the gravity model 

showed that all professions had a higher than expected rate of migration to the rural zone, the rural 

zone was substantially more attractive for all other professionals than for GPs (only 21 per cent of 

GPs overall moved to the rural zone), and particularly attractive for education (30%) and other health 

professionals (28%).   

Only 33 per cent of GPs migrated from the major urban zone to the rural zone, compared to at least 

40 per cent of all other professionals and 45 per cent of education professionals. GPs were also 

substantially less likely than other professionals to move from the regional zone to the rural zone, 

once the gravity model accounted for differences in starting distributions. Legal professionals were 

20 per cent more likely than GPs to migrate from the regional to rural zone. In contrast, GPs in 

remote zones were more likely than other professionals to move to the rural zone.  

Table 3 (next page) shows that the regional zone was substantially more attractive to GP migrants 

than to all other professional groups except ‘other health’. GPs were far more likely than other 

professionals to migrate from the major urban zone to the regional zone. However, GPs were less 

likely than other professionals to migrate from the rural zone to the regional zone. 



62 Carson D et al. Australian Population Studies 1 (1) 2017 

 

Table 3: Patterns of migration into the regional zone, 2006–2011 

 Percentage of migrants who moved to the 

regional zone (observed value on top line; 

expected on second line) 

Standardised differences in observed 

and expected migration (‘Error 

Differential’, compared to GPs) 

  
GPs 

Other 
health 

EDU ENG Legal 
Other 
health 

EDU ENG Legal 

All migrants 
36% 
(30) 

33% 
(28) 

28% 
(27) 

29% 
(27) 

30% 
(28) 

-1% -11% -11% -7% 

Migrants: 
from major 
urban 

61% 
(58) 

49% 
(51) 

40% 
(48) 

45% 
(51) 

47% 
(52) 

-9% -25% -18% -17% 

Migrants: 
from rural  

31% 
(17) 

41% 
(20) 

39% 
(20) 

35% 
(15) 

38% 
(15) 

3% 2% 11% 14% 

Migrants: 
from remote  

14% 
(15) 

24% 
(18) 

22% 
(17) 

18% 
(14) 

19% 
(13) 

33% 27% 30% 34% 

Migrants: 
early career 

40% 
(34) 

33% 
(30) 

27% 
(27) 

28% 
(28) 

31% 
(30) 

-5% -15% -16% -12% 

Migrants: 
mid-career 

29% 
(30) 

34% 
(28) 

32% 
(27) 

31% 
(27) 

32% 
(27) 

20% 16% 15% 17% 

Migrants: 
late-career  

30% 
(27) 

32% 
(26) 

28% 
(26) 

33% 
(26) 

27% 
(25) 

7% 0% 11% -3% 

Source: Authors’ construction based on gravity model analysis of ABS 2011 Census data. Notes: EDU = Education; ENG = 
Engineering. 

 

Figure 2: Stylised view of migration to rural and regional zones by various professional groups 

Source: Authors’ construction based on gravity model analysis of ABS 2011 Census data. Note: The width of the arrow 
represents the relative likelihood of the move.  

Figure 2 summarises the flows of the various 

professions between zones. Figure 3 (next 

page) provides a visual comparison of 

relative migration rates to both rural and 

regional zones for each profession for each 

age group. Non-GP professions are 

benchmarked against GPs using the error 

differentials in Tables 2 and 3. The figure 

shows the relatively low likelihood of rural 

migration at younger ages for all professions, 

and the relatively high likelihood of rural 

migration (compared to regional migration) 

at older ages (40 years or above) for all 

professions except GPs.  



Australian Population Studies 1 (1) 2017 Carson D et al. 63 

 

 

 

 

Figure 3: Relative levels of migration into rural and regional zones by profession and broad age group 

Source: Authors’ construction based on gravity model analysis of ABS 2011 Census data. 

Younger GPs were more likely to move to a rural zone than younger engineering and other health 

professionals, despite a lower observed rural migration rate due to fewer rural job opportunities. GPs 

in the middle and older age groups migrated to rural zones less frequently than other professionals. 

Education professionals in these age groups also were relatively unlikely to migrate to the rural zone 

compared to those in the remaining three professions. Younger GPs were substantially more 

attracted to the regional zone than other professional groups. GPs aged 40–54 years were 

substantially less attracted than their peers in other professions to regional practice in their middle 

years. Regional migration patterns for individual professions were relatively stable in the latter years 



64 Carson D et al. Australian Population Studies 1 (1) 2017 

 

(55 years plus) with other health and engineering professionals being more attracted and legal 

professionals being less attracted to regional living than GPs. 

5. Discussion 

GPs were substantially less likely than other professionals to migrate to rural locations in the 2006–

2011 period (Table 2), despite being slightly more mobile overall (Table 1). However, they were generally 

more likely to migrate to locations in the regional zone than professionals in the other groups (Table 3). 

The migration patterns of professionals in engineering, other health, education and the legal 

profession were broadly similar with migration to the rural zone increasing with age and relatively 

stable levels of migration to the regional zone. This was in contrast to GP migration patterns, which 

demonstrated only a small increase in rural migration after age 40 and a decrease in regional 

migration relative to their younger years.  

Migration rates for GPs in the middle (45–54) and older (55 plus) age groups were much lower than 

those of their peers in other professional groups. Significantly, there was substantially lower GP 

migration from regional to rural areas than for other professionals. The greatest diversity of migration 

patterns between professions was in major urban to regional zones and remote to rural zones. GPs 

and other health professionals were substantially more likely than other professionals to engage in 

the former; GPs and legal professionals were substantially more likely to engage in the latter. 

There is some evidence of younger GPs being more likely to engage in migration for rapid career 

advancement to the regional zone, which may be driven in part by more recent policies supporting 

Rural Pathway training for GPs in such areas (McGrail, Russell and Campbell 2016). However, it is of 

great concern that the high migration to the regional zone evidenced for GPs in the under 40 age 

group does not appear to lead to substantial ‘step down’ or migration of GPs to the rural zone in the 

older age groups. By way of contrast, there was great similarity in the rates of migration to rural and 

regional areas in the older age groups for all other professions.  

This research makes a case for ‘GP exceptionalism’ (GPs having distinctive migration patterns 

compared to other professions) when it comes to professional migration to regional and rural 

Australia. While exceptionalism cannot be ascribed to specific workforce strategies with the methods 

used in this study, some insights may be offered.  

• The focus of GP workforce training and development strategies on early career location decisions 

does appear to make a difference to rates of migration to both rural and regional zones.  

• The similar focus of the education profession on rural exposure and incentives for early career 

rural service might also have impacted the high levels of rural migration for neophyte teachers 

but is not apparent in levels of regional migration.  

• The lack of attention to rural pathways for older GPs is likely also reflected in the data, with 

barriers to the sorts of occupational changes required in different zones (particularly rural) 

possibly a factor.  

In this regard, the ‘rural specialisation’ strategy adopted by the GP profession may be counter-

productive when trying to attract more experienced workers. Other professions may be well served 

by considering how to balance the benefits of early specialisation on early career location decisions 

with strategies that facilitate rural migration in mid or later career stages. 



Australian Population Studies 1 (1) 2017 Carson D et al. 65 

 

The other crucial aspect of GP exceptionalism is the lack of movement from regional to rural areas. 

This may be a reflection of the increasing focus of ‘rural’ medical education programs in ‘regional’ 

areas. Other professions may pay particular attention to this issue, and ensure that rural exposure 

occurs in those areas where workforce growth is most needed. For GPs, at least, it is apparent that 

‘regional’ is not ‘rural’.  

6. Conclusions 

Despite concerted policy efforts to encourage GPs to move to rural areas, overall rural migration 

rates remain low when compared with other professions. The literature suggests that strategies 

which involve the exposure of medical students and GPs to rural training environments are more 

effective in determining ultimate work location than economic or lifestyle strategies promoting 

financial incentives or rural lifestyle advantages. However, most of these exposure strategies are 

targeted at younger GPs and typically involve exposure to regional rather than rural areas.  

The data reveal that younger GPs are more likely than professionals in equivalent age groups to work 

in rural locations, but are particularly more likely to locate to regional zones. A substantial challenge 

for the GP profession is to stimulate increased rural migration for experienced practitioners in the 

middle and older age groups, and to stimulate migration from regional to rural areas. That these two 

types of migration flow are more common in other professions suggests that those professions may 

receive additional benefit from strategies targeting younger workers. Likewise, GP workforce policy 

may well benefit from an improved understanding of the drivers of migration in other professions. 

There must be some caution taken, however, when considering the potential of ‘exposure’ type 

strategies used by other professions. There is a possibility that the counterpoint to strategies for 

early career ‘lock in’ to regional and rural practice may be a ‘lock out’ for older workers.  

Our research explored the impacts on a simple gravity model of the workforce age distribution for 

five professions: generalist medical practitioners; education professionals; legal professionals; 

engineering professionals; and other health professionals. There is potential to expand the model 

considerably to examine economic (e.g. income, housing costs, financial incentives) and lifestyle 

factors (e.g. working hours, leisure opportunities, quality of spousal/partner employment) which 

might provide for more insights into the causes of GP exceptionalism. This work should be done 

within the theoretical frameworks outlined in this paper. While life stage influences on migration 

patterns have been clearly established, evidence for ‘escalator’, ‘step’ and ‘amenity’ migration 

drivers is yet to be investigated. More work is required also to analyse out-migration and the net 

effects of in- and out-migration on workforce distribution. 

As occupational mobility increases there will be demand for knowledge about how the processes for 

career development and career transition impact the identification and take up of employment 

opportunities and choice of residential location. Analysis of these processes within and across 

vocations can provide insights beyond those which arise from the interrogation of a single 

profession. While this research has investigated migration patterns across a range of professions at 

the national level, further investigation is required to identify causative factors and to consider the 

position of more detailed geographies.  

 



66 Carson D et al. Australian Population Studies 1 (1) 2017 

 

Key messages 

• While encouraging major urban to rural migration is a shared ambition of many professions, 

diverse strategies may be required because of pre-existing differences in migration patterns. 

• There is evidence of the impact of GP training strategies with increased early career migration 

into regional areas. However, migration to rural and remote areas for those in other professions 

is highest in the later career stages. 

• Despite more than two decades of concerted policy efforts to influence GP migration patterns, 

overall rates of rural and regional migration are lower for this profession than for other 

professions. 

• Theories about the drivers of migration at different career stages, including escalator migration, 

step migration and amenity migration, may provide insights into effective strategies to influence 

migration patterns.  

References 

Anderson J (2011) The gravity model. Annual Review of Economics 3(1): 133–160.  

Argent N, Tonts M, Jones R and Holmes J (2014) The amenity principle, internal migration, and rural 

development in Australia. Annals of the Association of American Geographers 104(2): 305–318.  

Australian Bureau of Statistics (2011). TableBuilder, Census of Population and Housing, accessed February 

2017, http://www.abs.gov.au/websitedbs/censushome.nsf/home/tablebuilder. 

Browne K V (2016) Rural lawyers and legal education: ruralising and indigenising Australian legal curricula. 

International Conference on Education and e-Learning (EeL): Proceedings. Singapore: Global 

Science and Technology Forum; 50–59. 

Campbell S and Lindsay K (2013) Lawyers of the future: creating aspirations, forging connections and 

facilitating professional links in rural and regional contexts, Occasional papers series, 

International Journal of Rural Law and Policy 2013(2): 1–10.  

Carson D, Coe K, Zander K and Garnett S (2010) Does the type of job matter? Recruitment to Australia's 

Northern Territory. Employee Relations 32(2): 121–137.  

Corcoran J, Faggian A and McCann P (2010) Human capital in remote and rural Australia: the role of 

graduate migration. Growth and Change 41(2): 192–220.  

Farmer J, Kenny A, McKinstry C and Huysmans R (2015) A scoping review of the association between rural 

medical education and rural practice location. Human Resources for Health 13: 27.  

Golebiowska K, Carter T, Boyle A and Taylor A (2016) International migration and the changing nature of 

settlements at the edge. In Taylor A, Carson D B, Ensign P C, Rasmussen R, Huskey L and Saxinger G 

(eds) Settlements at the Edge: Remote Human Settlements in Developed Nations. Cheltenham, 

UK: Edward Elgar Publishing. 

Han Y (2016) Up and down flows of migration in national-space hierarchy over time. Journal of Korean 

Society of Rural Planning 22(1): 49–56.  

Hay M, Mercer A M, Lichtwark I, Tran S, Hodgson WC, Aretz H T, Armstrong E G and Gorman D (2017) 

Selecting for a sustainable workforce to meet the future healthcare needs of rural communities in 

Australia. Advances in Health Sciences Education 22(2): 533–551.  

Hudson J and May J (2015) What influences doctors to work in rural locations? Medical Journal of 

Australia 202(1): 5. 

Jenkins K, Reitano P and Taylor N (2011) Teachers in the bush: supports, challenges and professional 

learning. Education in Rural Australia 21(2): 71.  

Johnston G and Wilkinson D (2001) Increasingly inequitable distribution of general practitioners in 

Australia, 1986–96. Australian and New Zealand Journal of Public Health 25(1): 66–70.  

http://www.abs.gov.au/websitedbs/censushome.nsf/home/tablebuilder


Australian Population Studies 1 (1) 2017 Carson D et al. 67 

 

Joyce C and Wolfe R (2005) Geographic distribution of the Australian primary health workforce in 1996 

and 2001. Australian and New Zealand Journal of Public Health 29(2): 129–135.  

Kelly N and Fogarty R (2015) An integrated approach to attracting and retaining teachers in rural and 

remote parts of Australia. Journal of Economic and Social Policy 17(2): 1.  

Kley S (2011) Explaining the stages of migration within a life-course framework. European Sociological 

Review 27(4): 469–486.  

Martel C, Carson D and Taylor A (2013) Changing patterns of migration to Australia’s Northern Territory: 

evidence of new forms of escalator migration to frontier regions? Migration Letters 10(1): 101–113. 

Mazumdar S and McRae I (2015) Doctors on the move: national estimates of geographical mobility among 

general practitioners in Australia. Australian Family Physician 44(10): 747–751.  

McGrail M and Humphreys J (2015) Geographical mobility of general practitioners in rural Australia. 

Medical Journal of Australia 203(2): 92–97.  

McGrail M and Russell D (2016) Australia’s rural medical workforce: supply from its medical schools 

against career stage, gender and rural-origin. Australian Journal of Rural Health First published 21 

November (early view): 1–8.  

McGrail M, Russell D and Campbell D (2016) Vocational training of general practitioners in rural locations 

is critical for the Australian rural medical workforce. Medical Journal of Australia 205(5): 216–221.  

Mullan F, Chen C and Steinmetz E (2013) The geography of graduate medical education: imbalances signal 

need for new distribution policies. Health Affairs 32(11): 1914–1921.  

Negin J, Rozea A, Cloyd B and Martiniuk A L (2013) Foreign-born health workers in Australia: an analysis of 

census data. Human Resources for Health 11: 69.  

Perales F (2014) How wrong were we? Dependent interviewing, self-reports and measurement error in 

occupational mobility in panel surveys. Longitudinal and Life Course Studies 5(3): 299–316. 

Perales F and Vidal S (2013) Occupational characteristics, occupational sex segregation, and family 

migration decisions. Population, Space and Place 19(5): 487–504.  

Peters P, Taylor A, Carson D and Brokensha H (2016) Sources of data for settlement level analysis in 

sparsely populated areas. In Taylor A, Carson D, Ensign P, Huskey L, Rasmussen R and Saxinger G 

(eds.) Settlements at the Edge: Remote Human Settlements in Developed Nations. Cheltenham, 

UK: Edward Elgar Publishing; 153–177. 

Rees P, Bell M, Kupiszewski M, Kupiszewska D, Ueffing P, Bernard A, Charles-Edwards E and Stillwell J 

(2017) The impact of internal migration on population redistribution: an international 

comparison. Population, Space and Place 23(6; e2036). 

Ricketts T and Randolph R (2007) Urban‐rural flows of physicians. The Journal of Rural Health 23(4): 

277–285.  

Sharma K, Oczkowski E and Hicks J (2016) Skill shortages in regional New South Wales: the case of the 

Riverina. Economic Papers: A Journal of Applied Economics and Policy 36(1): 3–16.  

Shen J (2016) Error analysis of regional migration modeling. Annals of the Association of American 

Geographers 106(6): 1253–1267.  

Simini F, Gonzalez M, Maritan A and Barabasi A (2012) A universal model for mobility and migration 

patterns. Nature 484(7392): 96–100.  

Smith D and Sage J (2014) The regional migration of young adults in England and Wales (2002–2008): a 

‘conveyor-belt’ of population redistribution? Children's Geographies 12(1): 102–117.  

Sureshkumar P, Roberts C, Clark T, Jones M, Hale R and Grant M (2017) Factors related to doctors’ choice 

of rural pathway in general practice specialty training. Australian Journal of Rural Health 25(3): 

148–154.  



68 Carson D et al. Australian Population Studies 1 (1) 2017 

 

Taylor A (2016) Introduction. In Taylor A, Carson D, Ensign P, Rasmussen R, Huskey L and Saxinger G (eds) 

Settlements at the Edge: Remote Human Settlements in Developed Nations. Cheltenham, UK: 

Edward Elgar Publishing; 3–24. 

Terry D, Le Q, Woodroffe J and Ogden K (2013) The baby, the bath water and the future of IMGs. 

International Journal of Innovative Interdisciplinary Research 2(1): 51–62.  

Verma P, Ford J A, Stuart A, Howe A, Everington S and Steel N (2016) A systematic review of strategies to 

recruit and retain primary care doctors. BMC Health Services Research 16(126). 

Walters L, McGrail M, Carson D, Russell D, O'Sullivan B, Strasser R, Hays R and Kamien M (2017) Where to 

next for rural general practice policy and research in Australia? Medical Journal of Australia 

207(2): 56–58.  

 


