Monitoring and Visualising Sub-national Migration Trends in the United Kingdom
Urban policy makers and service providers need to understand the magnitude and dynamics of population migration to and from towns and cities since both the internal and international components are increasingly important in driving urban demographic development. In this chapter, an information system is outlined with a simple interface that allows migration data alongside data for natural change for selected districts or city regions to be tabulated and visualised so that time series trends and spatial patterns can be identified and compared. The data suggest that, during the 2000s, the major cities in the UK collectively experienced significant population growth, a large increase in net international migration and a decline in the relatively longstanding process of counterurbanisation.
In both the developed and less developed worlds, cities are growing rapidly and smart methods are increasingly required to manage complexity, increase efficiency, reduce expenditure and improve quality of life. Whilst emerging technologies (ultra-low power sensors, wireless networks and web and mobile-based applications) have begun to reshape urban environments and smart cities are fast becoming a reality (Batty 2012; Department for Business Innovation and Skills 2013; Centre for Cities 2014), basic understanding of the demographic evolution of towns and cities is imperative if local authorities are to provide housing, infrastructure and services that accord with demand. This involves understanding the complexity of flows into and out of metropolitan areas as well as the spatial demographic dynamics taking place within cities and their hinterlands.
Mid-year population estimates for local authority districts in the United Kingdom (UK) are generated by the national statistical agencies. Together with population projections, they are used directly by local authorities for planning and policy making but they also underpin the annual allocation of financial resources from central government to local authorities following the Lyons enquiry (Lyons 2007). Demographic change (in both urban and rural areas of the UK), as in other parts of the world, is driven by the changes in the components of growth: the balance between births and deaths and between in-migration and out-migration. It is important to monitor patterns and trends in each of these components to establish, quantify and understand the processes that have occurred in the relatively recent past (e.g. urbanisation, suburbanisation) and that are currently taking place (e.g. counterurbanisation, reurbanisation) as well as to provide a basis for projecting what might happen in the future.
In this chapter we report on the construction of a system for monitoring population change, natural change, internal migration and international migration over time from the beginning of the twenty-first century for a hierarchical system of spatial units that includes local authority districts, city regions and NUTS1 regions in each of the countries that constitute the UK. Details of the time series data sets estimated for a consistent set of spatial units are outlined in the next section. An information system has been built to support the quick and easy retrieval of estimated data based on user specification of a spatial unit and time period. The system interface is based on the concept of a demographic dashboard for illustrating the time series trends in different demographic components for a selected city by the user, but in this case the data are assembled manually and the user observes time-series rather than real-timeindicators. Thereafter, there are two sections which provide analyses of time-series trends and spatial patterns which are, at the moment, not automated as part of the information system. First, key trends occurring in flows between metropolitan and non-metropolitan areas across the UK are presented together with relationships between internal and international migration. Second, London’s migration characteristics are examined using conventional mapping methods before directional flows between city regions are visualised using circular plots. Some conclusions are included in the final section with proposals for further improvements and extensions to the system.
2 Demographic Data and Spatial Units
In addition to the estimated inter-censal mid-year to mid-year time-series matrices of internal migration flows, vectors of mid-year populations, annual births and deaths and international immigrants and emigrants have been assembled from official sources and adjusted where necessary, enabling a full accounting of the population change from one mid-year period to the next from 2000–01 to 2010–11 for sets of spatial units with consistent boundaries throughout the period. Considerable time and effort has been invested in building this unique set of data for the UK for monitoring and analysis of changing spatial patterns and processes. The following sections explain the user interface and identify, for the first time, some of the trends and relationships that characterize migration in the UK in the 2000s. Although estimates have been produced for populations by five-year age group and sex, we have confined our analysis to aggregate statistics in this chapter.
3 Structure and Exemplification of the Monitoring Tool
One example of the development of creating, modelling and communicating aspects of the smart city is the ‘city dashboard’, a service that collects various types of near-live publically available data from different external websites and makes them available through a web interface that enhances public awareness. One example of this is that created for London and other cities in the UK (Roumpani et al. 2013). The concept of a dashboard underpins the interface of the information system that we have constructed which in our case is based on ‘historical’ data estimated externally and assembled manually in Microsoft Excel with each of the time-series data sets for every component being assembled in the same workbook. The interface is a spreadsheet with VLOOKUP functions to retrieve values for each of the variables for the spatial unit (LAD) selected by the user from a dropdown list.
It is apparent from the international migration graph that the time-series trends have been much less stable over time, with a significant increase in immigration taking place between 2002–03 and 2004–05 without a corresponding change in emigration. The demographic trajectory of the Leeds population has therefore been impacted by the net immigration rising from 5,422 to 8,028 to 12,961 over the three years concerned with serious implications for the provision of services such as housing and schools.
One of the key features of demographic development in the UK during the 2000s has been the extent of net immigration from the rest of the world, an issue that has led to much political debate and public discussion, not least in terms of its implications for the labour market and for the provision of services. Figure 4b captures the time series trend in the total number of immigrants into the UK during the decade, rising from around half a million in 2001–02 to 666,000 in 2004–05 and remaining at over 600,000 per year for the rest of the decade. Around one half of this migration has been into the city region cores, with London attracting one third of a total immigration (over 6 million) to the UK throughout the period, whilst contributing only 28 % of the total flow of migrants (3.7 million) leaving the country.
Top and bottom positions in the population change league table, 2001–2011
Sheffield Coast and Country
Aberdeen Coast and Country
Belfast Coast and Country
Liverpool Coast and Country
Manchester Coast and Country
Glasgow Coast and Country
4 Trends in and Relationships Between Demographic Components
The graph in Fig. 5b depicts only migration from the core areas of city regions, again indexed to 2001–02. In this case, we observe that whilst core to core movements have been increasing, regardless of whether London Core is included or excluded in the analysis, it is longer-distance movement from the cores to the coast and country (C & C) areas of the city regions that has declined significantly. Flows out of cores to neighbouring rest or near regions have only shown marginal decline.
These estimates of net migration for the decade as a whole provide a useful summary of the extent of internal net losses and external net gains in migration but they conceal fluctuations that may have occurred during the time period from year to year as well as processes of internal migration within London Core. In the next section, we retain our focus in the first instance on London and examine patterns of net and gross migration using conventional mapping techniques but then demonstrate a new method of mapping directional flows using data for city regions.
5 Visualising Internal Migration Flow Patterns
Within London, a process of deconcentration is taking place resulting in net losses in inner London and net gains in outer London as migrants reveal their preference for more suburban residential environments in the outer boroughs or fewer opportunities to find suitable accommodation in the inner areas where house prices have risen disproportionately during the decade. However, inner London boroughs are gaining migrants in net terms from the rest of the UK whilst outer London boroughs are losing migrants in significant quantities to the rest of the UK. These patterns align with the concept of London as an ‘escalator’ region (Fielding 1992). Inner London is an important destination for employment and educational opportunities and therefore, like other cities, attracts large numbers of migrants in higher education or early career life stages, whereas migrants departing London from the outer boroughs tend to be older and motivated to leave for housing and other reasons. Comparison between the two years indicates how more inner London boroughs were experiencing net in-migration from the rest of the UK by the end of the period. The pattern of international balances shown in map e shows net gains across the board in 2001–02 which are particularly high in the north (Haringey, Barnet, Enfield, Waltham Forest and Redbridge) but also in the west (Ealing) and in the east (Newham and Tower Hamlets). A similar pattern is evident for 2010–11 (map f) with the exception of Kensington and Chelsea, whose balance has turned positive.
Both the maps in Fig. 9 shows gross out-migration flows of over 500 individuals originating from London Core and moving to other LADs in the UK, overlaid on top of choropleth maps showing the rates of in-migration from London into each of the destination LADs. The rates are computed as the number of in-migrants per 1000 resident population in each LAD. At the beginning of the period, outflow destinations are predominant in the south and east of England. By 2010–11, the pattern has changed, with far fewer migrants moving from London to the Midlands and the North of England as well as moving shorter distances to the East, South West and rest of the South East. The number of LADs that receive over 500 migrants from London fell from 155 in 2001–02 to 134 in 2010–11. This decline is driven primarily by a fall in the number of LADs that received between 500 and 1000 migrants (the black lines in Fig. 9), which fell from 69 in 2001–02 to 51 in 2010–11. While London has maintained a substantial influence as a distributor of migrants around the UK, this influence in terms of out-migration rates appears to have declined over the 2000s, and as the maps illustrate, the highest in-migration rates are more spatially confined to LADs close to London in the South East by the end of the time series.
Figure 10 shows the larger gross flows between each of the 13 city regions and reveals that inter-regional flows are not entirely dominated by London although London does have major links with all the other city regions in England. There are also relatively strong migration flows between those city regions that are adjacent to one another—between Sheffield and Birmingham, Manchester and Leeds, Sheffield and Leeds and Liverpool and Manchester. The numbers around the perimeter of the plot are gross flows in 10,000s and only gross flows over 7,380 are shown on the plot so as not to obscure the image with a lot of smaller links. Consequently, the city regions in Scotland and Northern Ireland appear relatively isolated apart from the link in both directions between Glasgow and Edinburgh.
The second circular plot (Fig. 11) illustrates the flows of net migration in excess of 280 individuals between each of the component parts of the city regions, where the numbers around the perimeter are net flows measured in 1000s. In this instance, the plot is dominated by the net flows from London Core to London Rest although this pattern is replicated for other provincial city regions.
If we compare the plots between the beginning and end of the decade,2 although changes have taken place, there is remarkable stability of directional origin-destination migration patterns over time. The proportion of intra-versus inter-city region migration is fairly stable across the time series, hovering around 63 % of total. Collectively, it is the city region core to core moves that have increased at a faster rate than any other kind of move, while moves from core to coast and country have declined and moves to the core from all other types of area have increased.
Whilst urban planners must understand the complexities of demographic change within cities, we contend that it is also important that policy makers and service providers have an equally good understanding of the relationship between cities and their migration ‘hinterlands’, be they within the same country or overseas. This is equally true of other interaction phenomena such as commuting, tourism or trade flows, but migration is a particularly important component of demographic change because of the relative permanence associated with changing place of usual residence and the implications for housing and the labour market as well as the provision of welfare, education and health services. We also believe that grouping like areas together is a beneficial approach for illustrating sub-national patterns and helping to understand the underlying processes.
During the 2000s, the UK as a whole has experienced population growth more rapid (7 %) than for a number of decades and much of this growth has come about in the cities. Collectively, the city region cores have grown by 10 %, due in many cases to the increased levels of immigration rather than internal migration, although the overall magnitude of the latter is far greater. Net international immigration has reached unprecedented levels and captured the attention of politicians and journalists as well as urban planners concerned with the implications for service and infrastructure provision. Concern has also been expressed over the shortcomings associated with the collection and measurement of international migration data, prompting the National Statistician in 2006 to set up an Inter-Departmental Task Force on Migration Statistics (National Statistics 2006), leading to recommendations for an ONS programme on ‘Improving Migration and Population Statistics (IMPS)’. In 2008, a Parliamentary Committee reviewed complaints from local authorities about the inadequacy of official population statistics and its report (House of Commons Treasury Committee 2008) resulted in a cross-government programme to deliver the Task Force recommendations by 2012. In other words, the primary consideration given by central government to improving the measurement of migration is indicative of the importance that is attached to this dimension of urban and regional development.
The information system that we have constructed provides access to a valuable new collection of both internal and international migration estimates and natural change components over time which allows users to explore and compare trends and patterns for selected districts or their wider city regions or NUTS1 regions. At the moment, we make use of the lookup functions of Excel to perform the queries that generate the dashboard of indicators for selected areas but the creation of graphics, maps and circular plots presented as part of the subsequent analyses of the data are not automated or linked to the spreadsheet. Although this platform satisfies the basic demands for handling the data, it would be beneficial to move to a database system with a web interface for access and analysis, akin to the Web-based Interface to Census Interaction Data (WICID)3 used by the UK Data Service-Census Support to provide users with access to migration and commuting flow data from the last five successive censuses (Stillwell and Duke-Williams 2003; Dennett et al. 2010). This transition would seem imperative because estimates have also been made of inter-district migration flows for each year for five-year age groups for males and females and a spreadsheet is less suitable for handling a much larger number of cell counts. It would also facilitate linkage with the software for creating circular plots and necessitate the adoption of web mapping tools. We envisage using a bundle of open source software (postgres, R and QGIS) with some scripts to automate the SQL queries and support a series of options that take the multi-scale origin-destination flow matrices, plus the boundary files and populations at risk, and create the charts and maps required for analysis from pick lists.
Aside from these technical or computational developments, the next steps in terms of data acquisition and estimation include: (i) adjustment of the time-series estimates for each of the inter-censal years so that they are consistent with the flows due to be released from the 2011 Census; (ii) updating the time-series estimates for the years following the 2011 Census so that more contemporary dynamics can be monitored and analysed; (iii) extending the time series beyond the immediate past by estimating future trends in different components or incorporating future projections generated by the national statistical agencies; and (iv) the addition of some key socio-economic time-series indicators such as employment, house prices, GDP and deprivation so that relationships between demographic and socio-economic development can be investigated.
Finally, there is the challenge of estimating the inter-censal time series of annual migration flows taking place within districts. In London this has been partly achieved since data are available on flows between boroughs but, both in London and elsewhere, planners and policy makers would find it extremely useful to know something about annual flows taking place between smaller spatial units on an annual basis. Although the current census provides flows of migrants between small sub-district areas such as wards and super output areas, annual estimates would rely on using data collected from administrative sources which, as yet, are not available on a national level across the UK. It is to be hoped that current and future work by the national statistical agencies on the use of administrative data as an alternative to the traditional census (ONS 2014b), will be fruitful in this respect, particularly if the traditional population census is replaced in due course by an alternative approach in which small area migration statistics are no longer collected.
The first author is grateful for funding to support his involvement in this research from the Economic and Social Research Council under project ES/J02337X/1 (UK Data Service Census Support Service). We are grateful for the editorial comments provided by Joe Ferreira.
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