A lifecourse perspective on Urban - Rural migration:
The importance of the local context
Aileen Stockdale1 and Gemma Catney2
1
(Corresponding author) School of Planning, Architecture and Civil Engineering, Queen's
University Belfast, BT9 5AG
2
School of Environmental Sciences, University of Liverpool, Liverpool, L69 7ZT
Abstract
The relationship between migration and age has long been established and most recently there have
been calls for the inclusion of a lifecourse perspective to migration research. In this paper, we
explore Northern Ireland's internal migration patterns and in particular we test for the importance
of urban to rural migration at different stages of the lifecourse. Data from the Northern Ireland
Longitudinal Study (NILS) is used for the first time to analyse Urban-Rural migration patterns. The
resulting modelling demonstrates unique aspects of urban to rural migration within Northern
Ireland, which up until now have gone largely unreported.
Results from logistic regression modelling suggest that there is an age-selectivity to Urban-Rural
mobility, but not necessarily at the lifecourse stages predicted from a review of the lifecourse
migration literature. Individuals in younger age groups (at the household and family formation
stages of the lifecourse) are most likely to make an urban to rural move in Northern Ireland. Indeed
the likelihood of such a move declines with each subsequent age cohort, and specifically those aged
50-64 are 27 per cent less likely to make such a move than those in their thirties. Possible
explanations are offered linked to Northern Ireland's settlement hierarchy, rural planning policy and
family farming traditions. The findings challenge researchers to pay due attention to how migration
processes may play out differently in varying geographical, social and planning contexts and
emphasise the importance of structural factors to explain migration patterns.
Key words: Lifecourse, Urban to rural migration, Northern Ireland, Northern Ireland Longitudinal
Study (NILS)
Introduction
There is an established literature on lifecourse migration which acknowledges an increased
likelihood of moving, and moving to an urban or rural destination, at particular stages of an
individual's life (de Groot et al., 2011; Geist and McManus, 2008; Millington, 2000; Mulder, 2007).
For example, the likelihood of moving to a rural destination is generally perceived to increase around
mid-life and retirement (Bures, 1997; Hardill, 2006; Lundholm, 2010). In this paper we test the
recognised relationships between age (as a proxy for lifecourse stage) and urban to rural migration
flows in Northern Ireland and, in doing so, we highlight the (often under-acknowledged) importance
1
of local structural factors as an explanatory migration variable. Researchers need to acknowledge
that established migration trends and processes may not always ‘apply’ to all regions and localities.
Assuming that ‘one size fits all’ may overlook the potential significance of the local context and with
it the geography of migration.
Migration research has shown a growing interest in the effects of specific lifecourse factors, such as
education, employment, family and housing careers, to explain migration flows and associated
decision-making. Considerably less attention has been devoted to more structural influences such
as the connections between population movements and spatial planning (Gkartzios and Scott, 2009)
or that such influences may impact differently at varying stages of the lifecourse. The dominant
narrative has reinforced established relationships and trends and failed to capture or seek to
understand exceptions or deviations from a supposed normal relationship. ‘Geography’ is too easily
omitted from lifecourse migration studies. In this paper we seek to 'put the geography back' into
such research with specific reference to the settlement pattern and nature of the spatial economy in
Northern Ireland. We argue that these represent powerful influences on lifecourse migration
patterns and demonstrate the existence of a unique ‘Northern Ireland effect’.
The paper is structured into five parts. First, we recap briefly on the migration literature to highlight
the established relationship(s) between migration and age/ lifecourse. From this, we formulate a
research question to test using data from the Northern Ireland Longitudinal Study (NILS). The
inclusion of health card registration data in the NILS, and therefore information on changes of
address means that the dataset is a potentially invaluable data source for migration research; in the
second part of the paper we report on the NILS and explain our data analysis. Third, we present our
findings, before offering possible (Northern Ireland-specific) explanations for urban to rural
migration patterns across the lifecourse. Finally, we conclude by arguing that migration research
should give due attention to varying geographical contexts.
The relationship between migration and age/ lifecourse stage
The extent to which a person (or household) is likely to move, and their likelihood of moving to an
urban or rural environment, depends on the residential preferences of that individual (or household)
within a choice set that is determined by financial resources, restrictions (such as the distance to
work or family ties), the opportunities and constraints at the preferred destination (such as the
availability of housing and employment) and prior experience of particular residential environments
(Feijten et al., 2008). The likelihood of moving (and the choice of residential environment) also
2
varies by age or stage in the lifecourse and the age-specific migration schedule is well-known (Rossi,
1955; Fischer and Malmberg, 2001; Michielin and Mulder, 2008). ‘[D]emographic changes underlie
much of the logic of residential mobility’ (Clark and Huang, 2003: 335), with Kley and Mulder (2010:
90) demonstrating that 'migration decision-making is mainly driven by life-course events and by
perceived opportunities in several life domains'.
Numerous demographic or lifecourse triggers for migration have been reported in the literature. The
transitions from school to tertiary education and/ or employment, for example, are identified as
important among young adults (Kley and Mulder, 2010), while residential moves associated with
union formation (and dissolution), childbirth, and changes in employment are reported by de Groot
et al. (2011). In later life, too, migration is often associated with specific life events such as
retirement (Warnes, 1992a; King et al., 2000), widowhood, and increasing frailty (Chevan, 1995).
Indeed, it is recognised that migration per se ‘involves a complex interplay between age, family
status and the timing of life events’ (Geist and McManus, 2008: 302), with the anticipation or
expectation of particular lifecourse events (for example, family formation or retirement) also found
to influence migration decisions and behaviours (Kulu, 2008; Michielin and Mulder, 2008; Stockdale,
2006).
However, it is not only the likelihood of moving that varies by age or lifecourse stage but, linked to
this, so too do migrant motivations and, accordingly, the direction of migration from and to urban
and rural areas. In relation to migrant motivations, Millington (2000: 521) asserts that ‘… the power
of labour market stimuli is found to decline with migrant age whilst the relative importance of
amenity and housing effects shows a corresponding increase’. This helps to explain the dominant
direction of migration between urban and rural areas over the lifecourse and, accordingly, the
dominant migration processes operating in urban and rural areas. Young adult out-migration
commonly characterises rural areas (Stockdale, 2002) and corresponds to young adult in-migration
to urban centres possessing tertiary education and/ or employment opportunities. Actual or
anticipated changes during early adulthood in employment, marriage/cohabitation, and starting a
family further enhance the likelihood of moving between urban areas, within a specific urban area
(for example, from a city centre location to the suburbs) or from urban to rural areas (Clark and
Huang, 2003; Kulu, 2008; van Ham et al., 2001). With age, and subsequent stages of the lifecourse,
employment considerations (most likely to focus on an urban environment) become less influential
as a factor in the choice of residential environment. This is likely to be most pronounced at or
around retirement and, as such, older age cohorts may be most likely to move from urban centres
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towards more rural destinations. The counterurbanisation trend of the last forty years would seem
to bear testimony to this, characterised as it has been by middle-aged or older age groups (Dean et
al., 1984; Rees, 2003; Hardill, 2006).
At this age or stage of the lifecourse, labour market stimuli which dominate at earlier lifecourse
stages (and younger ages) are likely to be less important and reduce the need to live close to the
workplace and therefore near to or within urban employment centres. Similarly, this stage will also
often correspond to an ‘empty nest’ stage, when any children will have reached adulthood and
personal independence from their parents. According to Bures (2009: 846) there is an ‘increased
risk of long-distance mobility as the age of the youngest child at home increases’ and Wulff et al.
(2010) calculate that empty nest status confers a 13 per cent point mobility premium compared with
couples that still have children living at home. This mid-life transition can often prompt a change of
address and lead to the realisation of an aspiration for ‘a place in the country’ (Hardill, 2006).
Moreover, traditional retirement migration has favoured amenity (coastal and rural) destinations
(Warnes, 1992a) with Bures (1997) and Stockdale (2006) finding that the pre-retirement aged cohort
(those in their fifties and early sixties), in the US and UK respectively, shared the residential
preferences of the post-retirement age cohort for less populous and amenity-rich areas. This raises
the prospect of a retirement transition (Hayward et al., 1994) lifecourse stage (commonly defined as
aged 50-64 years) when the expectation of retirement acts as a catalyst for change, including a
change in residential preferences. Informed by the counterurbanisation and retirement migration
literature, one might expect retirement transition migrants to display a greater likelihood of moving
to a rural destination compared to those at earlier stages (or younger ages) of the lifecourse.
Research in Sweden, for example, has demonstrated that migration by the over 55s is orientated
towards rural areas (Lundholm, 2010).
Inevitably, the relationships between migration and age/ lifecourse stage are much more complex
than to be reducible to pattern norms. Human behaviour in response to recognised migration
triggers is often less predictable and may display geographical variations influenced by local cultures
and contexts, and the state of the national and local employment and housing markets. In other
words, structural factors will influence migration patterns. First, and an example of the complex
interactions between lifecourse events and traditional migration flows, while the general ‘pull’
towards urban centres may be thought to dominate among young adults, primarily for employment
considerations, Kulu (2008) and Lindgren (2003), in their Austrian and Swedish studies respectively,
demonstrate that first conception significantly increases the likelihood of moving to a rural or small
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town destination, and that the likelihood of leaving large cities for rural areas increases with the
birth of a second and third child. It is not only at the empty-nest, retirement transition or postretirement lifecourse stages that a rural destination is more likely: an increase in family size among
young adults, for some, may trigger migrations that lead to a more pleasant residential environment
in the countryside in which to bring up children.
Second, although the literature points to clear relationships between migration and lifecourse
events, and in turn a relationship between lifecourse events and preferred residential environments,
one important enabling factor should not be overlooked – that of housing. Changes in the
household composition, often brought on by lifecourse events, may raise the need to adapt the
housing situation to the new needs of the individual or household (Feijten and Mulder, 2002).
Mulder and Lauster (2010: 434) recognise ‘[h]ousing serves as the context for family events and
families serve as the context for housing events’. Indeed it is often difficult to disentangle family
events from housing events and from related migration events. Lifecourse events such as leaving
the parental home, marriage or cohabitation (and dissolution of a union), childbirth, empty nest,
retirement, the onset of ill health and widowhood all are likely to possess important housing
dimensions. Examples reported in the literature include: high local house prices may delay the
likelihood of leaving the parental home (Mulder and Clark, 2000); starting a family is commonly
associated with a move into an owner-occupied or single family home (Feijten and Mulder, 2002);
and union dissolution may lead to a move out of home ownership by at least one of the partners
(Feijten, 2005; Feijten and von Ham, 2010). Access to housing and the nature of the housing market
at the location of origin and preferred destination are therefore likely to be important determinants
in the likelihood of moving and the choice of residential environment. Linked to this is the
important role of parents in providing resources to help adult children achieve better housing (Smits
and Michielin, 2010). Direct and indirect financial transfers by parents to their adult children are
noted as important in helping young adults attain home ownership in the Netherlands by Helderman
and Mulder (2007), with Mulder (2007) calling for more research into the importance of family to
residential choice. Such financial gifts are likely to be most important during a period of rising
property prices. The home-owning parents of young adults are likely to possess considerable
housing equity at the same time as their housing costs have declined: they may already own their
home outright or possess only a small mortgage.
Third, family and/or housing norms will be important. In Italy, for example, Barban and DallaZuanna (2010) note that it is common for newly-weds to live less than 1 km from the parental home
5
of the husband, wife or both. This characteristic, according to Finch (1989), distinguishes southern
Europe from other countries. However, in the Netherlands too Helderman and Mulder (2007)
report that people often live in close proximity to their parents and ‘if people live closer to
homeowning parents, the probability that they are also homeowners is greater’ (p.234). Such
intergenerational transmission of home-ownership may be affected by other parental characteristics
(for example, socioeconomic status) or children aspiring to attain the same housing tenure as their
parents.
Fourth, all these relationships and influences operate within a national, regional, local and individual
economic context. Clark and Huang (2003) demonstrate lifecourse and mobility relationship
differences between the London housing market and the rest of the United Kingdom: ‘Although the
dynamics underlying preference to move are more or less the same across housing markets, local
contextual effects are thus important in determining the observed mobility’ (p.335). Similarly,
Feijten and Mulder (2002) acknowledge the important role of macro and micro economics.
Economic growth (or decline) in a country will influence the nature of its housing market, its housing
stock and the average price of owner-occupied homes. Such growth (or decline) will also contribute
to spatial variations within the country. At the micro level, the individual's or household's economic
resources will either restrict or facilitate the realisation of residential aspirations and, accordingly,
affect lifecourse migration.
Fifth, the local geography, and in particular its settlement pattern and the nature of its spatial
economy, is likely to also affect migration patterns. Few migration studies directly acknowledge this
potential planning role. Recent exceptions include Shucksmith (2011) who reports on the role of
planners and planning as agents in the process of spatial exclusion. For example, since the 1940s
planning in England and Wales has given the greatest priority to urban containment: ‘… a planned
scarcity of [rural] housing duly emerged’ (Newby, 1985: 220). This has directly shaped the housing
market, especially the rural housing market, and accordingly has been a powerful influence on
migration between urban and rural areas. These important connections have also been recently
reported in Ireland. ‘[R]esidential mobility reflects not only a range of consumer motivations but
also results in diverse processes of settlement change underpinned by local planning policies and
housing markets’ (Gkartzios and Scott, 2010: 80). What is absent from these studies is how
planning, including the settlement pattern and spatial economy of an area, may impact differently
on residential decision-making and associated migration patterns at varying stages of the lifecourse.
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This brief overview of the migration literature suggests that residential decision-making and
preferences are, at least in part, variable at different ages and accordingly at different stages of the
lifecourse, and that the relationship between migration and lifecourse stages is influenced by the
interaction of numerous factors. These factors, and their interactions, will not be identical or of
similar relative importance through time or over space. In other words, the recognised relationship
between migration and lifecourse stages ignores the geography of migration. The key question
addressed in this paper is: ‘does the likelihood of making an urban to rural move within Northern
Ireland vary by stage in the lifecourse?’ In addition, and in contrast to other studies, we seek to
explain the observed, and possibly unexpected, relationship between migration and lifecourse
stages with reference to unique interactions (at least unique within a UK context) between the
Northern Ireland housing market, urban settlement hierarchy, local rural planning context and, in
relation to young adults specifically, the role of parental resources. Collectively, these factors
introduce an increased complexity to the recognised relationship between lifecourse stage,
migration and choice of destination and demonstrate the importance of geographies of migration.
Data and methods
The Northern Ireland Longitudinal Study (NILS) is a large-scale dataset comprising a representative
sample of approximately 28 per cent of the Northern Ireland population (equating to c. 500,000
people). The NILS is a record linkage study created by combining statistical and administrative data
sources within Northern Ireland. Data included are the 2001 Census returns, demographic and
migration events and vital events (births, deaths and marriages). An individual is included in the NILS
if their birth date is one of the 104 anonymous selected dates. NILS data are accessed in a safe
setting in the Northern Ireland Statistics and Research Agency (NISRA) headquarters. A more
detailed description of the data is provided by O’Reilly et al. (2011).
The inclusion of data from health card registrations means that the NILS presents a unique resource
for migration research. If a NILS member registers a change of address with their health practitioner
(commonly a GP), the new address will be linked into the NILS, at six-monthly downloads (i.e., for up
to two changes of address a year). This is available to researchers at Super Output Area Level
(average population just under 2000). The NILS therefore provides longitudinal migration data for
NILS members, enriching the number of possible migration events reported and therefore our
understanding of the patterns and processes of migration in Northern Ireland. While the 2001
Census of Population provides ‘full’ population coverage, migration data are derived only from the
7
one year migration question (previous address one year prior to enumeration), and hence are more
limited.
Our project-specific NILS dataset includes migration information for NILS members from 2001-2008,
with up to 12 possible moves (one in 2001 and 2008, given the date of downloads, two in all other
years). The full range of demographic and socio-economic Census variables are available for the NILS
members, however it should be noted that these indicators are only available from the Census, and
therefore the characteristics of a mover in 2008 will only be linked to their status in 2001.
For our urban/rural area classification we followed the 2005 ‘Statistical classification and delineation
of settlements’ published by NISRA (2005). The classification scheme comprises eight bands
according to types of settlement; A: Belfast Metropolitan Area, B: Derry Urban Area, C: Large Town,
D: Medium Town, E: Small Town, F: Intermediate Settlement, G: Village, and H: Small Village, Hamlet
and Open Countryside. A simpler scheme which merges bands A-E as Urban and F-H as Rural is also
specified, representing a commonly agreed division between urban and rural as being among
settlements between 3,000 and 5,000 people. This scheme presents some 65 per cent of the
population as urban dwellers, and approximately 35 per cent as rural residents (NISRA, 2005). This
broad Urban-Rural classification was used in the present analysis. We acknowledge that it misses
some of the finer features of the settlement hierarchy of Northern Ireland, but a more detailed
scheme would have resulted in a complex range of possible outcomes difficult to handle in a
regression framework and confusing to interpret. The Urban-Rural division is available at Super
Output Area (SOA) level, and this was linked to the NILS data, whereby each area was coded as
either Urban or Rural, for all possible origins and destinations.
Logistic regression was employed as it allows us to test the likelihood of making an urban to rural
move. As stated above, each individual could make up to a maximum of twelve moves in the given
time period, although in reality most move counts were four or below. Moves could be from an
urban SOA origin to a rural SOA destination, rural to urban, or rural to rural and urban to urban
(including internal SOA moves in the latter two cases). Exploring each possible move combination
was not possible given the range of scenarios available. Rather, the logistic model predicted the
likelihood of a move outcome from the 2001 origin for any subsequent destination; this was the first
move for the individual, and could take place at any point in the timeframe. For example, the
likelihood of moving to a rural area for urban dwellers was determined as the odds of any individual
who resided in an urban-classified SOA in 2001 moving to a rural area at any point in the period, as
8
opposed to another urban area or within the same urban area. This model is the main focus of our
analysis, although an identical model for rural to urban moves and for the likelihood of moving at all
is also reported below. In the case of urban to rural moves, only urban dwellers (in 2001) were
included in the model, likewise only rural dwellers (in 2001) were included in the model of rural to
urban moves. The likelihood of moving (regardless of origin or destination type) model included the
whole NILS sample. Of course, this procedure fails to capture the intensity of moves, particularly for
the highly mobile: it is only one (the first) move during the time period which is analysed. It also
ignores return moves: while an urban to rural move may take place, the now rural dweller may have
returned to an urban area in that timeframe. However, our modelling procedure does allow us to
gain an insight into the possible nature of rural migration; further extensions could be considered in
future work.
We controlled for the ‘standard’ demographic and socio-economic factors known to affect migration
propensity, namely age, sex, marital status, and health status, and proxies for income which included
housing tenure and car ownership. These variables were derived from the 2001 Census, and are on
an individual level basis. Ideally, a person’s National Statistics Socio-economic Classification (NS-SEC)
would have been included as a further proxy for ‘social status’, however the individual level
classifications do not classify the very young and very old (under 15 and over 75), who are grouped
as ‘unclassified’; this means that the inclusion of individual-level NS-SEC leads to a loss of
information on these age groups in our model. In other studies, this information could be sacrificed
in order to include this important control. Given that the focus of the study here is to test if the
likelihood of making an urban to rural move differs by age/ lifecourse stage, this was not possible.
Rather than losing this control altogether, the NS-SEC of the household reference person (HRP) has
been included instead. Given that many individuals move as part of a wider household, and that for
single person households the mover will be the HRP, this approach provides a ‘next best’ guess at
the social status of the mover. A similar problem of unclassified individuals occurs for education,
and this is not controlled for in the models. Those living in communal establishments were excluded
in the modelling.
Individuals were banded into one of seven possible age groups: 0-15, 16-29, 30-39, 40-49, 50-64, 6574 and 75+. The very youngest age group comprises children who will mainly move with their
parents. The 16-29 year olds are those who are legally able to work and includes those in
traditionally the most transient period of the lifecourse, where mobility may be related to leaving
the parental home, study, marriage/cohabitation, and/or new forms of employment. By 30 much of
9
this behaviour will have settled down, and the 30-39 year olds form the third age group, followed by
those in their 40s. Following the wider literature (Stockdale, 2006) the pre-retirement age group has
been defined as 50-64 year olds. Those aged 65-74 are grouped separately to those in their mid-70s
and older. In our models, it is the individual’s age in 2001 that is used to assign them to one of our
seven age bands. We have not, therefore, aged the individual to approximate their age (and
reassign age bands) at the time of the move. To do so would have generated a somewhat
cumbersome logistic regression model.
Findings
The numbers moving from urban to rural and rural to urban areas, alongside the numbers moving at
all are shown in Table 1. Of the 451,948 individuals in our NILS sample, approximately one third (c.
160,000 individuals) moved over the period 2001-2008; 25 per cent of the total population in the
sample were movers who originated in an urban area in 2001 (112,807 individuals). Of this 25 per
cent, just under 20 per cent moved from an urban to a rural locale in the time period, while the
remaining 80 per cent who moved ended up in another urban area, or moved within the same urban
SOA. Only around 10 per cent of the total population in the sample originated in a rural area and
moved in the period (equating to 46,291 individuals), of which around 30 per cent moved to an
urban area between 2001 and 2008.
Total Sample: 451,948 (100%)
Mover Sample: 159,098 (35%)
Origin
Urban
Rural
Total
Non-Mover Sample: 292,850 (65%)
Destination
Rural
20,789 (18%)
32,868 (71%)
53,657
Urban
92,018 (82%)
13,423 (29%)
105,441
Total
112,807
46,291
159,098
Table 1 Move types, by counts and percentages.
Source: Northern Ireland Longitudinal Study.
Table 2 presents the odds ratios for the three models described earlier. The first model (Model 1:
Move) includes all individuals in the sample (451,948) and predicts the likelihood of moving at all.
The remaining two models take only those who moved to assess the likelihood of moving to a rural
area rather than within the same or to another urban area, for those who originated in an urban
area (Model 2: Destination Rural), and the odds of moving to an urban area rather than within or
between rural areas, for individuals originating in a rural area (Model 3: Destination Urban). The
10
socio-economic and demographic covariates described above are included in all three models, but
the odds ratios for age are presented separately in Table 3.
Setting aside age for the time being and focusing on Table 2, the characteristics of movers from an
urban to a rural area (Model 2: Destination Rural) are broadly in line with the known attributes of
movers. Females show a marginal increase in the likelihood of making such a move compared to
males (although note this effect is not statistically significant for urban to rural moves). Those who
are married are more likely to move to rural areas than individuals who are separated, widowed or
divorced, who are in turn more likely than single people to move to rural areas. Compared to
married individuals, those separated, widowed or divorced are more likely to move than not (Model
1: Move), and, along with single people, are more likely to move from rural to urban areas than
within rural areas (Model 3: Destination Urban). In line with the migration literature, private renters
have the highest odds of moving in all three models. For Model 2 (Destination Rural), social renters
have a large and significant (Odds Ratio (OR) 0.76 (95% Confidence Intervals (CI) 0.72, 0.80))
decreased likelihood of moving from urban to rural areas when compared to owner-occupiers, who
act as the reference category. This is most likely explained by the lower availability of social housing
in rural as compared to urban areas; in Northern Ireland social or public sector housing is largely
concentrated within urban centres (Department for Social Development, 2010). Unsurprisingly, car
access has a positive effect on the likelihood of moving from urban to rural locales (Model 2),
although interestingly the reverse is the case for moves in general (Model 1). Those without access
to cars are more likely to move from rural to urban areas than to another rural locale (Model 3). As
discussed above, it was necessary to include as a control the National Statistics Socio-economic
Classification (NS-SEC) of the household reference person rather than on an individual basis.
Residents in households headed by those in more professional occupations are more likely to move
to rural areas than those in lower NS-SEC, likely a result of higher average house prices in rural areas
and a greater willingness to commute further distances for a more well paid employment position
(although note the lack of significance for some NS-SEC categories). The largest relative difference
from the reference category in Model 2 is for full-time students (OR 1.60 (CI 1.36, 1.88)). The finding
that full-time students are more likely to move to rural areas is in sharp contrast to the expected
norm whereby further and higher education institutions are commonly located in urban areas. It
might be perceived as a consequence of edge of town university campuses, for example the
Coleraine and Jordanstown campuses of the University of Ulster. However, neither campus is
classified as rural in our dataset. Instead, the finding is explained by understanding the nature of our
data. Because the full-time student classification is based on the individual’s status in 2001 whereas
11
the move modelled may have taken place at any time during the period 2001-08 it is likely that the
finding includes graduates who have returned to a rural parental home address following
completion of their studies. As shown by Model 3, compared to those with a household head in the
most professional group, individuals in all other occupational categories (except full-time students)
are less likely to move from rural to urban areas than within or between other rural locales. With
the exception of the ‘top end’ of the rural housing market (accessible to higher earners), the urban
property market has been traditionally more expensive. It may therefore be difficult for lower
earners to make the transition into an urban property market. This is exacerbated by the fact that
the period under study (2001-2008) corresponds to rapidly rising house prices within Northern
Ireland. Given their greater economic resources, those in the very highest occupational
classifications are, for the most part, most likely to move compared to those in other professions
(Model 1). Somewhat surprisingly, those with a Limiting-Long Term Illness (LLTI) are marginally
more likely to move than those without a LLTI (It may be that their illness necessitates a move to a
more suitable property or to be nearer family support).
Sex
Male (ref.)
Female
Marital status
Married (ref.)
Single
Separated/Widowed/Divorced
Tenure
Owner-occupier
Private renter
Social renter
Car ownership
Access 2+ (ref.)
Access 1
No access
HRP NS-SEC
Professional (h/l) (ref.)
Intermediate
Own account workers
Lower supervisory
Routine
Not working
FT students
Unclassified
Odds ratios (95% confidence intervals)
Model 1: Move
Model 2:
Destination Rural
Model 3:
Destination Urban
1.00
1.12 (1.10, 1.13)
1.00
1.02 (0.99, 1.06)
1.00
1.08 (1.04, 1.13)
1.00
0.94 (0.92, 0.96)
1.32 (1.29, 1.36)
1.00
0.70 (0.66, 0.73)
0.94 (0.89, 1.00)
1.00
1.87 (1.75, 1.99)
1.75 (1.62, 1.90)
1.00
2.55 (2.48, 2.61)
1.32 (1.29, 1.34)
1.00
1.39 (1.32, 1.46)
0.76 (0.72, 0.80)
1.00
1.18 (1.11, 1.26)
1.05 (0.97, 1.13)
1.00
1.08 (1.06, 1.10)
1.22 (1.19, 1.25)
1.00
0.66 (0.64, 0.69)
0.35 (0.33, 0.37)
1.00
1.05 (1.00, 1.10)
1.10 (1.01, 1.20)
1.00
1.08 (1.05, 1.10)
0.95 (0.93, 0.97)
1.01 (0.98 ,1.03)
0.98 (0.96, 1.00)
0.97 (0.94, 1.00)
0.94 (0.85, 1.04)
0.90 (0.85, 0.94)
1.00
1.06 (1.00, 1.12)
1.20 (1.14, 1.27)
0.97 (0.92, 1.03)
0.98 (0.94, 1.02)
0.92 (0.85, 1.00)
1.60 (1.36, 1.88)
1.15 (0.97, 1.35)
1.00
0.92 (0.85, 1.00)
0.62 (0.58, 0.66)
0.73 (0.68, 0.79)
0.63 (0.59, 0.67)
0.56 (0.50, 0.62)
1.08 (0.78, 1.51)
0.55 (0.46, 0.66)
12
Health status
No LLTI (ref.)
With LLTI
1.00
1.03 (1.01, 1.05)
1.00
1.02 (0.97, 1.07)
1.00
1.12 (1.05, 1.20)
Table 2 Logistic regression odds ratios for likelihood of (1) migrating (Model 1: Move); (2) migrating
from an urban to rural area (Model 2: Destination Rural); (3) migrating from a rural to urban area
(Model 3: Destination Urban).
Source: Northern Ireland Longitudinal Study.
Notes: HRP NSSEC is National Statistics Socio-economic Classification (NS-SEC) of the household
reference person (HRP); Professional (h/l) are those in higher and lower managerial and professional
occupations; FT Students is full-time students; LLTI is limiting long-term illness.
Having established trends broadly in line with our expectations we now turn our attention to
variations in the likelihood of moving from urban to rural locales by age. For context, Table 3 shows
the odds ratios for all move types. The coefficients for age are part of the model outputs presented
in Table 2; that is, the models presented in Table 3 also include as covariates sex, marital status,
tenure, car ownership, HRP NS-SEC and health status. Those aged 30-39 act as the reference
category (selected given that it is the first age group where migration patterns have ‘settled’ from
initial high mobility at the new household formation/education/employment stage of the lifecourse).
Concentrating on Model 2 (Destination rural), it is clear that those in the youngest age groups are
more likely than the older groups to move from urban to rural areas; individuals in the 0-15, 16-29,
and 30-39 age groups were most likely to make such a move, while those in older age groups (40-49,
50-64, 65-74, 75+) were less likely. Compared to 30-39 year olds, those at a possible retirement
transition lifecourse stage (age group 50-64) are considerably less likely to migrate in this way (OR
0.73 (CI 0.68, 0.77)). There is, therefore, a rather convincing ‘downward’ gradient with an increase in
age corresponding to a decrease in the likelihood of making an urban to rural move: there is a steady
decline in the odds of migrating to rural areas from children to the very old. Those at or immediately
above the state pension age of 65 (young-old) are the least likely (OR 0.58 (CI 0.52, 0.64)) to make an
urban to rural move in Northern Ireland. The group with the highest odds of moving in this direction
are children aged 0-15, of which most moves will take place with their parents (i.e., those in the next
three older age categories for whom the likelihood of migrating is also high, with an odds ratio of
one or above). Individuals in their forties are less likely to make this kind of move than those in their
thirties, and this decrease in likelihood with increasing age can be seen along the age ranges to the
over 75 year olds.
13
Age group
0-15
16-29
30-39 (ref.)
40-49
50-64
65-74
75+
Odds ratios (95% confidence intervals)
Model 1: Move
Model 2: Destination
Rural
0.89 (0.86, 0.91)
1.25 (1.18, 1.33)
1.42 (1.39, 1.46)
1.06 (1.00, 1.12)
1.00
1.00
0.52 (0.51, 0.54)
0.78 (0.73, 0.83)
0.36 (0.35, 0.37)
0.73 (0.68, 0.77)
0.28 (0.27, 0.29)
0.58 (0.52, 0.64)
0.40 (0.38, 0.42)
0.66 (0.56, 0.78)
Model 3: Destination
Urban
0.77 (0.71, 0.84)
1.33 (1.24, 1.43)
1.00
0.99 (0.91, 1.07)
0.90 (0.82, 0.98)
0.99 (0.88, 1.12)
1.58 (1.31, 1.90)
Table 3 Logistic regression odds ratios for likelihood of (1) migrating (Model 1: Move); (2) migrating
from an urban to rural area (Model 2: Destination Rural); (3) migrating from a rural to urban area
(Model 3: Destination Urban) by age.
Source: Northern Ireland Longitudinal Study.
In order to assess how unique this urban to rural migration pattern by age may be within the wider
internal migration system in Northern Ireland, we now turn our attention to models for the
likelihood of moving to an urban area (for those who made a move and who originated in rural
areas) and the odds of moving at all (for the whole population in the NILS sample) in Table 3. The
likelihood of moving (Model 1: Move) shows no surprises and is similar to many migration schedules
produced elsewhere (see Rogers et al., 1978), with a typical peak in migration among those in their
late teens and twenties, associated with leaving the parental home, higher education, joining the
labour force, and for marriage or cohabitation. After this, migration likelihood falls steadily (and is
lowest for those in the 50-64 and 65-74 age groups) until a rise in the oldest age group.
Odds of migrating to urban areas for originally rural dwellers (Model 3: Destination Urban) tend to
follow this migration pattern up to and including the 30-39 year olds, but then rather than
decreasing in older years, the likelihood of moving to urban areas remains steady for those aged 4049, then dips slightly for the pre-retirement age group (50-64 years), before rising in the older age
groups (65 and above). However, the results for age groups 40-49 and 65-74 for this model are not
statistically significant. It should be remembered that the populations in question differ for these
three types of move and so they cannot be compared directly, however it is interesting to note that
it seems that for rural dwellers it is urban areas which attract most migrants in the older age groups
(perhaps moving to be closer to required services and facilities, and involving no doubt those moving
into largely urban-based pensioner-type housing and care homes).
14
The findings point to several age-related migration trends, some of which were expected given the
relationships identified from the general migration and lifecourse literature while others were more
surprising. First, as expected, we found evidence to support that the likelihood of moving declines
with increasing age. Migration theory acknowledges that young adults are most mobile. Second,
the likelihood of making a rural to urban move shows two peaks across the lifecourse: among young
adults and at post-retirement age (especially among the over 75s). Again, such a pattern was largely
expected. In contrast, the likelihood of making an urban to rural move declines with increasing age.
This too was largely expected, however, the ‘peaks’ among young adults (up to and including those
in their thirties) is perhaps contrary to the literature on young adult mobility, whereby moves
associated with higher education, first employment, and household formation are generally thought
to display an urban bias. We also anticipated the existence of a (slight) increased likelihood of an
urban to rural move among those aged 50-64 and therefore at a retirement transition stage or at the
retirement stage of their lifecourse. The literature suggests that migration undertaken at these
lifecourse stages has been an important driver of the counterurbanisation phenomenon evident in
other areas. Little evidence is obtained to support this among Northern Ireland’s internal migrants
during the period 2001-08. Focusing specifically on the 50-64 and 65-74 age cohorts Table 3
demonstrates that, it is these ages which are consistently amongst the least likely to make a move
(of any type) and, notably, are least likely to make a rural to urban move specifically. The latter,
however, is not mirrored by a corresponding greater likelihood to make an urban to rural move
which the counterurbanisation and lifecourse migration literature might have led us to expect.
A ‘Northern Ireland effect’ to explain lifecourse migration patterns
While most of the patterns shown in Table 3 accord with the migration literature, one stands out as
being largely unexpected – it is those in younger age groups that are more likely than older age
groups to move from urban to rural areas. Accordingly, in Northern Ireland it is those at the union
and family formation lifecourse stages which display the greater likelihood of participating in an
urban to rural migration flow. There are several possible explanations for this pattern which reflect
a ‘Northern Ireland effect’ rooted in its unique geography. This geography includes its settlement
hierarchy, rural planning policy, family farming traditions and, most recently, its economic
performance and the subsequent impact this has had on the regional housing market.
First, Northern Ireland possesses a distinctive settlement hierarchy for a country/ region with a
population of less than 2 million. Belfast, the largest city, had a population of just under 280,000 at
the time of the 2001 Census, with the Greater Belfast Metropolitan Area (which includes a number
15
of smaller settlements and district towns) possessing a population of just less than 600,000.
Derry/Londonderry, Northern Ireland’s second city, had a population of approximately 90,000.
Below that the country’s settlement hierarchy is characterised by a further 24 district towns
(including some within the Greater Belfast Metropolitan Area) whose populations (in 2001) ranged
from approximately 5000 (Ballycastle) to 30,000 (Ballymena and Newry). Each district town includes
a sizeable rural hinterland within a discrete district council area. For a country where one can drive
either north to south or east to west in approximately two hours, this represents a somewhat
unique settlement hierarchy, where longer distance commutes and other necessary day-to-day
mobility may preclude one’s need to move home. The key settlements (the district towns) represent
important centres for employment and service provision (at least, until recently when there is more
instability due to government centralisation policies, funding cuts and the economic downturn).
Since at least the mid-1970s, successive regional development strategies have focused on the
growth of district towns (Department of Housing, Local Government and Planning, 1975;
Department for Regional Development, 2001). All possess, to varying degrees, public sector services
(and associated employment opportunities) in health, education and local government. Notably
Northern Ireland's dependency on public sector employment is the highest in the UK. District towns,
therefore, 'represent loci of employment and commuting to these areas is evidently very much a
part of living in a rural area' (Moss et al., 2004: 126). Further evidence from the Moss et al. (2004)
study suggests that in the absence of local employment opportunities and in order to compensate
for lower wage rates in rural labour markets, males, in particular, move out into the wider regional
labour market and commute to district towns and larger urban centres. What this means in practice
is that those working in Belfast, for example, will include daily commuters from as far afield as
Londonderry, Newry and Enniskillen. Similarly, with the dispersed concentration of employment
(and services) in each of the district towns even a rural residence is likely to be only a short commute
to a choice of urban centres. Therefore, in contrast to the literature (Millington, 2000) which
emphasises the importance of labour market stimuli for younger age migration (and economically
active lifecourse stage migration) this does not necessarily hold true in Northern Ireland where its
settlement hierarchy is such that there is a reduced need to move at the onset of a new lifecourse
stage. Indeed, within Northern Ireland, on average, only 5-6 per cent of the population change
address per year (Shuttleworth and Barr, 2009b) and the median distance moved is only 3.58
kilometres (Shuttleworth and Barr, 2009a).
A second possible explanation (in addition to graduates returning to the parental home) for the fact
that the likelihood of moving to a rural location declines with age (or rather is greater among those
16
in their twenties and thirties; ages which correspond to the household and family formation stages
of the lifecourse) can be offered via rural planning policy alongside a strong tradition of small scale
family farming (Jack et al., 2009). While an urban containment and protection of the countryside
approach to rural planning in England has 'acted as a crucial arena for class formation and social
exclusion ... operating generally in the interests of the privileged and against poorer, marginalised
groups' (Shucksmith, 2011: 609), in Ireland (North and South) a very different and relaxed rural
planning approach has been evident (Gallent et al., 2003; Gkartzios and Scott, 2010). In Northern
Ireland specifically, this more liberal approach (see Sterrett, 2003; Scott and Murray, 2009), relative
to other parts of the United Kingdom, has arguably privileged those from family farming
backgrounds and led to a distinctive rural housing feature comprising single detached properties
often of bungalow style, and commonly referred to as ‘one-off housing in the countryside’. Such
housing is also common in the Republic of Ireland (Gkartzios and Scott, 2009). In Northern Ireland,
89 per cent of (6756) planning applications for single dwellings in the countryside were approved
during the year 2002-03 (Department of Environment, 2004) and Sterrett (2003) estimates that 2000
single houses are built each year in the open countryside of Northern Ireland which may account for
as much as 40 per cent of all private sector residential development taking place outside the Belfast
City region.
The ease with which planning permission for one-off housing in the countryside was obtained allied
with a strong family farming tradition (Magee, 2002) to farm small holdings (Jack et al., 2009) has
meant that a (new build) rural house was often the least expensive mode of entry onto the property
ladder for young adults from a family farming background. Indeed, according to Sterrett (2003:139)
'... in rural culture the offering of a site to a newly married couple has long been regarded as almost
an obligation'. Given the broad definition of urban/rural (NISRA, 2005) used in our analysis it is likely
that one of the partners at this household formation stage of the lifecourse will have moved from an
urban settlement and hence this helps to explain the greater likelihood of an urban to rural move.
This represents a form of parental contribution to help adult children achieve owner-occupation
unique to Northern Ireland. The availability of such sites has meant that young adults (at the
household formation stage of the lifecourse) have not needed to move away from rural areas for
housing needs towards more urban centres (in contrast to other regions/ areas of the UK and
Ireland). It has been possible to live in the countryside and commute to the nearest (or other)
district town for employment. Although Gkartzios and Scott (2010: 76) acknowledge that '[s]elfbuilding is a common activity in rural areas and a common pathway to home ownership in Ireland'
they do not make an explicit connection to family farming. Important also, in Northern Ireland, is
17
that this practice is not necessarily restricted to one adult child – instead, a number from the one
family may build on the family farm unit reinforcing Northern Ireland's dispersed settlement
character. Furthermore, the new build is frequently constructed with future lifecourse stages in
mind (for example, family formation) thus reducing a need to move at the onset of subsequent
lifecourse stages. The long-term intention, at least initially, is to live in close proximity to the
parental home. In this respect similarities can be drawn with the observations of Helderman and
Mulder (2007) and Barban and Dalla-Zuanna (2010) in the Netherlands and Italy respectively.
It is important to acknowledge that a more restrictive countryside planning policy in Northern
Ireland has recently been introduced (Department of Environment, 2010), one whereby planning
permission will only be granted to build one new house on a farm unit within any ten year period.
This new policy has already led to a 53 per cent reduction in the number of planning applications
submitted for one-off housing in the countryside, in 2010-11 compared to 2002-03, (Department of
Environment, 2012).
Third, the wider economic context in which migration decisions were being made during the period
of study (2001-08) also deserves comment. This context helps to reinforce the potential role of a
parental gift in the form of a building site as an explanation for the Urban-Rural lifecourse migration
patterns evident from Table 3. The period 2001-07 corresponds to an unprecedented period of
economic prosperity and rapid growth in the residential property market. Northern Ireland was
frequently referred to as the UK regional hotspot for house prices (University of Ulster, 2005). Land
prices rose dramatically (Jack et al., 2009) and house prices soared, rising by 20 and 37 per cent
respectively during 2005 and 2006 (according to the University of Ulster's House Price Index for 2005
and 2006). Such increases made Northern Ireland a particularly difficult housing market for first time
buyers (commonly those at the union and family formation stages of the lifecourse). The parental
'gift' of a building site therefore greatly helped adult children attain home ownership at a time when
many were simply out-priced in a rapidly rising regional property market. Any associated housing
mortgage by the young couple was limited to self-build costs as opposed to the hugely inflated
house purchase prices at that time. Those at the household formation lifecourse stage building on
family-owned land was not, however, an explicit temporal response to the rapidly rising house prices
in the region. One-off house building in the Northern Irish countryside has been a strong feature for
some time, albeit the magnitude of which may have intensified during this period of economic
prosperity.
18
Fourth, there are also a number of data limitations which need to be considered when interpreting
our findings. As highlighted in the data and methods section, data on changes of address based on
health card registrations rely on an individual informing their health practitioner that they have
moved home. Work using the NILS by Shuttleworth et al. (2012) has highlighted the demographic
and social variations in late and non-reporting of address changes by individuals to health
professionals; most commonly by males, the healthy and owner-occupiers, those in urban areas and
those in deprived areas. We have noted that the covariates included in the model are derived only
from 2001 Census returns, and that we have not been able to account for some potentially
important factors due to either the nature of the study (individual level NS-SEC and education
status) or other potentially important socio-economic, demographic or perhaps cultural factors
which are not included in the Census. We do not know, for example, anything about the motivations
for migration, or barriers which prevent mobility, and how these may affect age groups
differentially. We model only the first move of any individual; however their age (and socioeconomic characteristics) are as at Census enumeration (2001). For some individuals, they may have
moved to an older age category by the time they change address. Our modelling procedure has not
allowed the full extent of migration to be captured; multiple migration events or return moves are
not accounted for. The fact that migration (at least after the young adult lifecourse stage) tends to
be undertaken by households, rather than individuals, may mean that our models under- or overestimate the amount of migration to rural areas, for different age groups. Some of these data and
methodological issues will be more important than others, but may nonetheless have an impact on
the results and their interpretation.
We might also ask, are the same age-related migration patterns evident at other spatial scales? The
definition of urban and rural that we have adopted is, of course, somewhat coarse, and will
inevitably miss some of the detail of the settlement hierarchy of Northern Ireland. For example,
prior research suggests that ‘rurality’ and accordingly gradations of rural are important when
investigating migration to rural areas (Bures, 1997; Stockdale, 2006). The broad Urban-Rural
classification (NISRA, 2005) used here does not distinguish between degrees of rurality – it is based
solely on population size. Likewise, might the findings be repeated if we substituted urban to rural
migration for a coarser scale, such as migration between and within Belfast versus the rest of
Northern Ireland? While this would provide an interesting avenue for further research, a higher
geographical scale such as a major city and other regions risks masking the age-related migration
patterns which we have found here and which were a focus of our research in this paper. Moreover,
it potentially undermines the importance of Northern Ireland’s unique settlement hierarchy and the
19
structural factors at play (as detailed above). There is a danger that this would simply ‘smooth out’
the geographies of migration which we have been able to capture through our urban to rural
migration analysis. One might also consider using distance of move rather than analysing migration
between origin and destination types. We have not used this for two main reasons; firstly, the type
of environment moved to (town or rural destination) is ignored, which is obviously central to our
investigation. Secondly, in Northern Ireland the distance between an area classified as urban and
that classified as rural can often be very small. If we were to focus on, say, long- and short-distance
moves (or even a finer-grained classification of distances moved), we could miss the transition
between these two settlement types (urban and rural) for moves which are short in physical
distance. The finer grain analysis offered by our urban to rural migration findings enable us to
identify explanatory structural factors which otherwise have gone unreported.
Conclusion
While our findings support many of the age-related migration patterns evident from the migration
and lifecourse literature, they also highlight some unexpected patterns. Most surprising is, first, the
identification of the greater odds of participating in an urban to rural flow among those in their
twenties, thirties and children relative to older age groups, and second, the apparent lack of
evidence to support an increased likelihood of making an urban to rural move by those at the midlife and retirement stages of the lifecourse. The involvement of young adults (at the household
formation lifecourse stage) in urban to rural migration has led us to consider ‘unique’ features of
Northern Ireland’s geography and planning context as possible explanations. These include the
peculiarities of Northern Ireland's settlement hierarchy, rural planning policy and family farming
tradition, alongside a strong tradition of rural ‘self-build’ homes (intended for life) by those at the
household formation stage of their lives. The relationships between migration and age displayed in
Table 3 are likely the collective outcome of these influences, rather than being explained by any one
contributory factor.
If we assume that the data limitations associated with the use of NILS are no more problematic than
in other regions of the UK and Ireland, then collectively our findings and their possible explanations
demonstrate the need to pay due regard to the geographies of migration (as demonstrated here
through a ‘Northern Ireland effect’). The relationship between migration and age (or lifecourse
stage) may not always play out in accordance with our expectations (as informed by the migration or
lifecourse literature). Local circumstances will often explain such discrepancies. But even when the
relationship between migration and age is as expected, the explanation may lie once more in local
20
circumstances as opposed to any set of ‘one size fits all’ reasons. The local geography of an area,
including its settlement hierarchy, its culture of migration (in terms of migration direction and
decision-making) and local structures (for example, rural planning policy) need to be considered.
Collectively and individually they represent powerful influences on internal migration flows, as has
been shown in the case of Northern Ireland.
Our findings are significant for other reasons too. First, they have relevance to the study of
counterurbanisation. Traditionally, counterurbanisation has been associated with mid-life and older
age groups with many studies concentrating on their migration flows, decision-making processes
and consequences. Our analysis suggests that such cohorts may represent only a small component
of urban to rural migration flows, and that traditional counterurbanisation research may have failed
to capture the full range of migrants involved. The evidence from Northern Ireland is that younger
age groups (and those at earlier lifecourse stages) also participate in counterurban migration flows.
Second, the findings provide a positive outlook for rural demographic ageing. Not only are young
families settling in rural areas, but importantly adult children and their families through their close
residential proximity to the parental home offer a potential source of future family support for
ageing parents. Third, our findings demonstrate the significant role of planning in shaping
residential mobility patterns. Most recently Shucksmith (2011) has reported on planners as agents
of rural gentrification, nevertheless, the relationships between planning and population change/
migration patterns would appear to warrant greater empirical study. A particular opportunity for
such research in Northern Ireland has been presented by the recent revision to rural planning policy.
Will this supposedly more restrictive policy to one-off housing in the Northern Ireland countryside
lead to very different (age-related) migration patterns emerging in the future? Linked to this, there
is also a question to be asked about the occupants of one-off housing. Many are as described above
(adult children of farm families at the household formation stage of the lifecourse), however, it
would be naïve not to at least acknowledge – especially during a time of high land and property
prices – that some farm families will have sold building sites as a useful source of extra income
(Finnerty et al., 2003) and perhaps also homes built by family members. Surprisingly, to date, there
has been no research on this issue undertaken in Northern Ireland.
Acknowledgements
The analysis undertaken in the preparation of this paper was a specific component of a larger project
funded by the ESRC (RES-062-23-1358). A much earlier draft of this paper was presented at the
2012 British-Irish Population Geography Conference (sponsored by the RGS-IBG) in Belfast and the
authors are grateful for the constructive comments received from delegates. The help provided by
21
the staff of the Northern Ireland Longitudinal Study (NILS) and the NILS Research Support Unit is
acknowledged. The NILS is funded by the Health and Social Care Research and Development Division
of the Public Health Agency (HSC R&D Division) and NISRA. The NILS-RSU is funded by the ESRC and
the Northern Ireland Government. The authors alone are responsible for the interpretation of the
data and any views or opinions presented are solely those of the authors and do not necessarily
represent those of NISRA/NILS.
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