Ageing Trends in Regions and Cities - OECD

Public Governance & Territorial Development

AGEING TRENDS IN REGIONS AND CITIES

Sustainable Urban Development Policies in Ageing Societies

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TABLE OF CONTENTS

INTRODUCTION .............................................................................................................................................. 2

1. GLOBAL AGEING TRENDS ...................................................................................................................... 4

2. AGEING TRENDS IN REGIONS ................................................................................................................ 6

3. AGEING TRENDS IN METROPOLITAN AREAS .................................................................................... 8

APPENDIX 1 : METHODOLOGY TO ASSESS AGEING TRENDS IN FUNCTIONAL URBAN AREAS ............................................................................................................................................................. 15

APPENDIX 2 : CASE STUDIES ..................................................................................................................... 18

(1) TOYAMA (JAPAN) .................................................................................................................................. 19

(2) MANCHESTER (UK) ............................................................................................................................... 20

(3) LISBON (PORTUGAL) ............................................................................................................................ 21

(4) COLOGNE (GERMANY) ........................................................................................................................ 22

REFERENCES ................................................................................................................................................. 23

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FIGURES

Figure 1. Population change for four age groups, world and OECD: 1950-2100 ...................................... 4 Figure 2. Elderly share of the total population, OECD countries: 1950-2100 ........................................... 5 Figure 3. Distribution of the elderly population in predominantly urban (PU), intermediate (IN) and

predominantly rural regions (PR): 2011 (in %) .......................................................................... 6 Figure 4. Elderly dependency rate for countries, predominantly urban and predominantly rural regions,

2012 ............................................................................................................................................ 7 Figure 5. Elderly share of total population in metropolitan areas: 2001 and 2011 (in %) ......................... 8 Figure 6. Elderly share in metropolitan areas: 2001 and 2011 .................................................................. 8 Figure 7. Elderly share in metropolitan areas, accodring to urban core, hinterland: 2001 and 2011 ......... 9 Figure 8. Elderly share in metropolitan areas per country: 2001 and 2011 (in %) .................................. 10 Figure 9. Elderly share in metropolitan areas and for national average: 2011 (in %).............................. 10 Figure 10. Elderly share in metropolitan areas for urban core and hinterland, per country: 2001 and

2011 (in %) ............................................................................................................................... 11 Figure 11. Elderly and total population growth rate in metropolitan areas: Average annual growth rates,

2001-2011 (in %) ...................................................................................................................... 12 Figure 12. Elderly and total population growth rates in major metropolitan areas: Average annual

growth rates, 2001-2011 (in %) ................................................................................................ 13 Figure 13. Elderly share in metropolitan areas, according to urban core and hinterland; 2011 (in %)..... 14 Figure 14. Elderly share in Metropolitan Toyama ..................................................................................... 19 Figure 3.4. Elderly population share in Manchester City ........................................................................... 20 Figure 15. Elderly share in Metropolitan Manchester ............................................................................... 20 Figure 16. Elderly share in Metropolitan Lisbon ....................................................................................... 21 Figure 17. Elderly share in Metropolitan Cologne..................................................................................... 22

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INTRODUCTION

Objective of the brochure

This brochure “Ageing Trends in Regions and Cities” is an extract form the OECD project interim paper “Sustainable Urban Development Policies in Ageing Societies”, which was discussed in the OECD Territorial Development Policy Committee in April, 2014. This OECD project was launched, responding to a growing interest from OECD member countries, to establish a common understanding on how cities address issues related to population ageing in cooperation with national governments.

The objective of this brochure is to share the preliminary assessment of ageing trends in regions and cities as explored by this project. This preliminary assessment reveals to what extent ageing forms a spatially heterogeneous trend, varying among regions and cities, thus posing different challenges and requiring different policy approaches for respective local governments. The important feature of this preliminary assessment is that ageing trends in metropolitan areas have international comparability, which is ensured by using the OECD’s definition of Functional Urban Areas as unit of analysis (Appendix 1).

*This brochure assessed 258 metropolitan areas in 27 OECD countries; Austria, Belgium, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Great Britain, Greece, Hungary, Ireland, Italy, Japan, Korea, Mexico, Netherlands, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, United States. These metropolitan areas cover 42.7% of the elderly population (defined as aged 65 and over) and 47.2% of the total population in the respective countries.

*Although the current assessment is based on the age threshold of 65 for defining the elderly population, it is acknowledged that other age-related elements need to be taken into account to understand the impact of ageing trends, for example, increasing longevity, active retirement age and pension eligible age, as well as skills, health and education of the individuals.

Background of the project

Ageing is a global phenomenon with great implications for sustainable urban development. Referring to wider demographic change, ageing has been framed as a key issue for the fiscal, economic and social models of societies (OECD, 1996). Sustainable urban development to pursue resilient economies and inclusive societies will be framed from a new policy context based on a changing population structure, as the ageing trend provides implications for various policy domains. However, many of the pressures on economic and social systems created by ageing will vary from one place to another. Cities are ageing, and understanding its implications are paramount to draw urgent policy responses that are needed to mitigate the challenges associated with population ageing, and to take this change as an opportunity to scrutinize established frameworks of society (OECD, 2013a; 2006).

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The uncertainties of ageing societies for securing economic growth and productivity underline the need to share policy experiences and to learn from each other in preparing for increased life expectancy and in managing longevity gains within the OECD and beyond (Garibaldi et al., 2010). The importance of developing long-term approaches to address the challenges of changing demographic structures is understood by many policy makers.

Cities have a critical role to play for sustainable urban development. Today, metropolitan areas comprise over 70% of the OECD population, and 80% of the elderly population. Recent work of the OECD provides empirical evidence for the importance of cities to guide the paths towards greener urban economies and sustainable urban forms (OECD, 2013b, 2012a). It has been discussed in previous regional studies of the OECD that cities’ possibilities to contribute to national economic performance are grounded in their agglomeration of population and industry, as well as the comprehensiveness of their policy approaches. Policy design and implementation that address ageing issues require a deep understanding of local circumstances, including the characteristics of communities, economic assets, history, and culture, given the spatially heterogeneous nature of current ageing trends. Cities’ well-versed experience of working with local communities and their profound understanding of local problems are indispensable in this respect.

The important role of cities in ageing societies was acknowledged in “the fifth OECD Roundtable of Mayors and Ministers” (4-5 December, 2013, Marseille), stating that to be attractive and competitive “cities need to take a comprehensive policy approach, integrating transport policy, housing policy, land use policy, employment policy and industry policy”. In addition it was confirmed in the Ministerial Meeting of the Territorial Development Policy Committee (5-6 December, 2013, Marseille) that “better urban policy approaches will help us to improve the quality of life for residents of all ages as well as resilience to natural disasters and climate change”.

The OECD’s project on “Sustainable Urban Development Policies in Ageing Societies (2013/14)” was launched in response to growing interest from OECD member countries that the OECD should establish a common understanding on how cities address ageing issues. This project contributes to discussion and analysis from a local government’s approach. While the emphasis of this project is on metropolitan areas, it does not exclusively consider large cities. Rather, it is about urban areas and their function for the regions and nations of which they are a part of. This project will mainly assess the following points:

• What does ageing mean today for people and for cities? What impact do ageing societies have on sustainable urban development? What are the visions of cities in ageing societies?

• What are the roles of cities to achieve those visions, including the question how cities could mitigate ageing challenges and make the best use of the opportunities that ageing provides to achieve sustainable urban development? How could national governments support cities’ efforts?

• Who are the key stakeholders to achieve visions and implement policy tools effectively?

This project takes a horizontal approach by drawing upon expertise and experience from the whole OECD, including the Directorate of Employment, Labour and Social Affairs, International Transport Forum (ITF) and Local Economic and Employment Development (LEED). It is scheduled to be finalised in November, 2014, and the launching event of the publication will be in April-May 2015 in Paris. As a part of this project, “International Roundtable for Cities in Ageing Societies” is held on 17th of October 2014 in Toyama (Japan).

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1. GLOBAL AGEING TRENDS

This part will assess the long term ageing trend by countries. The assessment by country provides useful insight to understand the context of ageing trends in individual regions and cities in different countries.

Ageing is a global phenomenon with its greatest increase in the course of the next 50 years (Figure1). The second half of the 21st century will see a “new equilibrium” within the demographic structure (UN, 2012). In particular, advanced-age groups (60 years old or over) made up the smallest part of the population until late 2040’s all around the world. This trend will be inverted in the latter half of the 21st century, when advanced-age groups will surpass all younger population groups. While this inversion in terms of numbers will occur later in time on the global level, the advanced-age population within the OECD region already outnumbered the youngest population groups (0-19 years old) in 2010 and is expected to surpass all other population groups by 2020.

Figure 1. Population change for four age groups, world and OECD: 1950-2100

Source: OECD calculations. Based on United Nations Population Division (2010), World Population Prospects: The 2010 Revision online, http://esa.un.org/unpd/wpp/unpp/panel_indicators.htm.

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The share of elderly age group will increase significantly as a consequence of the rising number of elderly people and stagnating or decreasing numbers of younger age groups. Figure 2 shows that between 1950 and 2010, the population share of the elderly, increased from 7.8% to 19.0% for the OECD on average. This elderly share is projected to increase to 23.7% by 2025, surpassing 30% during the course of the 21st century and reaching 36.1% by 2100. While these shares will continue to vary by 2100, the differences among countries will be much smaller than in 2010.

Figure 2. Elderly share of the total population, OECD countries: 1950-2100

Source: OECD calculations. Based on United Nations Population Division (2010), World Population Prospects: The 2010 Revision online, http://esa.un.org/unpd/wpp/unpp/panel_indicators.htm.

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2. AGEING TRENDS IN REGIONS

This part will assess regional ageing trends in countries. It shows how the ageing trend differs across regions, in particular by regions in urban context compared to regions in rural.

OECD countries experience unequally distributed patterns of ageing that reveal regions with different

level of elderly shares, as well as with different elderly growth rates. When looking at small regions within OECD countries (Territorial Level 3), regional differences of ageing trends are observed between different types of regions. In 2011, 44% of the elderly population in OECD countries resided in predominantly urban regions (PU) 1, 30% in intermediate (IN) and 25% in predominantly rural regions (PR) (Figure 3).

Figure 3. Distribution of the elderly population in predominantly urban (PU), intermediate (IN) and predominantly rural regions (PR): 2011 (in %)

Source: OECD Regions at a Glance (OECD, 2013)

1. TL3 regions are classified as: Predominantly Urban (PU), if the share of population living in rural local units is

below 15%; Intermediate (IN), if the share of population living in rural local units is between 15% and 50%; Predominantly Rural (PR), if the share of population living in rural local units is higher than 50% (OECD, 2010).

0% 20% 40% 60% 80% 100%

BelgiumNetherlands

GermanyUnited Kingdom

United StatesCanada

KoreaTurkeyOECDJapan

ItalyAustralia

SpainPortugal

IrelandPoland

SwitzerlandFinland

New ZealandDenmark

FranceGreeceAustriaSweden

HungarySlovak RepublicCzech Republic

EstoniaNorwayIceland

LuxembourgSlovenia

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The ratio of the elderly to the working age population (the elderly dependency rate) is steadily growing in OECD countries. The elderly dependency rate gives an indication of the balance between the economically active and the retired population. In 2012, this ratio was around 23% in OECD countries, with substantial differences between countries. Differences among regions within the same countries were also large.

Figure 4. Elderly dependency rate for countries, predominantly urban and predominantly rural regions, 2012

Source: OECD Regions at a Glance, OECD(2013)

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3. AGEING TRENDS IN METROPOLITAN AREAS

Metropolitan areas show diverse trends of ageing, implying a distinct impact on sustainable urban development. This part will assess the ageing trends in metropolitan areas with a population above 0.5 million. This data on population ageing in metropolitan areas was collected and processed for 2001 and 2011 by the project on “Sustainable Urban Development Policies in Ageing Societies”, applying the OECD’s “functional urban area” (Appendix 1). OECD metropolitan areas comprise densely inhabited “urban cores” and “hinterlands” whose labour markets are highly integrated with the urban cores.

The share of the elderly population accounted on average for 12.3% of the total population in 2001, and increased to 14.0% in 2011 (Figure 5) in all OECD metropolitan areas. The number of the elderly population in OECD metropolitan areas increased by 22.7% from 2001 to 2011(Figure 6). The growing ratio is more pronounced in the urban core 21.7%, compared to that in the hinterland of 26.3%.

Figure 5. Elderly share of total population in metropolitan areas: 2001 and 2011 (in %)

Source: OECD calculations. For the statistical sources, see Appendix 1.

Figure 6. Elderly population in metropolitan areas, according to core and hinterland: 2001 and 2011


12.3% 14.0%0

20

40

60

80

100

2001 2011

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Ageing occurs unequally according to urban core and hinterland. Figure 7 shows that although increasing both in urban cores and hinterlands, the elderly population ratio is higher in hinterlands. On average 16.1% of the population residing in urban hinterlands was aged 65 and over in 2011. Compared to a share of 14.7% in cores, urban hinterlands had a 1.4% higher elderly share than the average for OECD metropolitan areas.

Figure 7. Elderly share in metropolitan areas, according to urban core, hinterland: 2001 and 2011 (in %)


14.85% 13.42% 15.49%14.71% 13.89% 15.02%

16.1% 14.47%16.71%

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All metropolitan areas (258) Large metropolitan areas (80) Small metropolitan areas (178)

2011 (in %)

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13.15% 12.01% 13.67%

13.31%12.62% 13.57%

13.8%

12.29%

14.36%

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All metropolitan areas (258) Large metropolitan areas (80) Small metropolitan areas (178)

2001 (in %)

Total Core Hinterland

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Considerable differences of elderly shares persist between countries. Figure 8 shows that almost all OECD metropolitan areas registered increase in their share of the elderly population between 2001 and 2011 when grouping metropolitan areas by country.

Figure 8. Elderly share in metropolitan areas per country: 2001 and 2011 (in %)


OECD metropolitan areas tend to be younger than their respective country average. OECD metropolitan areas registered a 4.4% lower elderly share than the national average, at 14.8% compared to 19.1% in 2011(Figure 9).

Figure 9. Elderly share in metropolitan areas and for national average: 2011 (in %)


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In 2001, five out of 27 countries (Germany, Great Britain, Japan, Korea and Mexico) have higher elderly shares in urban hinterlands (Figure 10). A decade later, in 2011, however, the number of countries with higher elderly shares in urban hinterlands was twelve out of 28 countries.

Figure 10. Elderly share in metropolitan areas for urban core and hinterland, per country: 2001 and 2011 (in %)


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Figure 11 displays the distribution of metropolitan areas according to the average annual growth rates for the total and elderly population for 2001-2011. Japanese and Korean metropolitan areas feature the total population growth rates range from -1% to 1%, whereas the elderly population growth rates vary from 2% to 4%. The majority of European metropolitan areas show a wider range of population growth. It varies from -1% to 2% for the total and from -1% to 4% for the elderly population. Metropolitan areas from Chile, Mexico and the United States show the largest dispersion, ranging from -1% to 4% for the total population and from -1% to 6% for the elderly population. Figure 12 and 13 complement the information on average annual growth rates of elderly and total population in selected metropolitan areas.

Figure 11. Elderly and total population growth rates in metropolitan areas: Average annual growth rates, 2001-2011 (in %)

Source: OECD calculations. For the statistical source, see Appendix 1.

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Figure 12. Elderly and total population growth rates in major metropolitan areas: Average annual growth rates, 2001-2011 (in %)

Source: OECD calculations. For the statistical sources, see Appendix 1,

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Brussels

Prague

Brno

Berlin

Munich

Cologne

Frankfurt

Aachen

Tallinn

Madrid

Helsinki

ParisAthens

Dublin

Rome

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Oslo

Lisbon

StockholmWien

London

Manchester

Copenhagen

Sendai

Toyama

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Osaka

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Daejeon

Santiago

MonterreyMexico City Puebla

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Chicago

New York

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Figure 13. Elderly share in major metropolitan areas, for urban core and hinterland; 2011 (in %)


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APPENDIX 1 : METHODOLOGY TO ASSESS AGEING TRENDS IN FUNCTIONAL URBAN AREAS

The project “Sustainable Urban Development Policies in Ageing Societies (2013/14)” has developed a population by age dataset based on Functional Urban Areas (FUA) to assess the demographic structures and the spatial population dynamics in metropolitan areas. The definition and the methodology to define functional urban areas can be found in the report Redefining “Urban” (OECD, 2012b): www.oecd.org/regional/redefiningurbananewwaytomeasuremetropolitanareas.htm.

Functional Urban Areas

Redefining “Urban” identifies functional urban areas for 29 OECD member countries. 5 out of 34 OECD member countries (Australia, Iceland, Israel, New Zealand and Turkey) are not covered by the FUA assessment, for lack of comparable data. Despite its recognised effects on the economy, on quality of life and on the environment, urban development is still poorly monitored. Moreover, statistically robust comparisons of cities across countries are lacking. This knowledge gap is mostly due to the absence of an international agreement on what to measure, i.e. what is “‘urban” and what is the real area of a city’s labour market (its functional area). The methodology identifies urban areas as functional economic units, characterised by densely inhabited “urban cores” and “hinterlands” whose labour markets are highly integrated with the urban cores.

Step 1. Identifying core municipalities through gridded population data: high-density clusters are defined as aggregations of contiguous high-density 1 km square grid cells. High-density cells have a population density of at least 1 500 inhabitants per km2 in Europe, Japan, Korea and Mexico. A lower threshold of 1 000 inhabitants per km2 is used for Australia and the United States, where several metropolitan areas are less compact. Smaller clusters (with fewer than 50 000 people in Europe, Canada and the United States and 100 000 in Japan, Korea and Mexico) are dropped. If the percentage of a municipality’s population living within the urban cluster is higher than 50%, the municipality is considered densely inhabited.

Step 2. Connecting non-contiguous cores belonging to the same functional area: not all OECD urban areas are characterized by contiguity of built-up development. Many develop in a polycentric way, with densely inhabited cores that are physically separated, but economically integrated. An important innovation of this work is the identification of urban areas with a polycentric structure. This is done by looking at the relationships among the urban cores, using information from the commuting data. Two urban cores are considered integrated, and thus part of the same polycentric metropolitan area, if more than 15% of the residence population of any of the cores commutes to work in the other core.

Step 3. The identification of the urban hinterlands: the hinterland can be defined as the “worker catchment area” of the urban labour market that is outside the densely inhabited core. The size of the hinterland, relative to the size of the core, gives a clear indication of the influence of cities on surrounding areas. All municipalities that send to the core a percentage of their workers above a given threshold are assigned to each core as hinterland municipalities. After extensive sensitivity analysis, the threshold has

http://www.oecd.org/regional/redefiningurbananewwaytomeasuremetropolitanareas.htm

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been fixed at 15% of the residents of the municipalities. The multiple cores within a polycentric metropolitan area are considered as a single destination.

This methodology makes it possible to compare functional urban areas of similar size across countries. A classification of urban areas into four types according to population size is proposed:

• small urban areas, with a population below 200 000 people (and above 50 000);

• medium-sized urban areas, with a population between 200 000 and 500 000;

• metropolitan areas, with a population between 500 000 and 1.5 million;

• large metropolitan areas, with a population of 1.5 million or more.

Source : OECD (2012b), Redefining Urban: A New Way to Measure Metropolitan Areas, OECD Publishing, Paris.

Ageing trends assessment in Functional Urban Areas

In the interim paper of “Sustainable Urban Development Policies in Ageing Societies (2013/14)”, population by age data (5 year age bands) has been collected for 27 OECD countries that have defined FUAs as “large metropolitan area” with a population of 1.5 million or more and “metropolitan area” with a population between 500,000 and 1.5 million.

The years collected are listed in the table below. The population data by age has been collected for two points in time and refers to either the 2000-2010 period, or to the 2001-2011 period, with the exception of Italy whose population by age data was available for 2002 instead of 2001, and in Korea for 2005 instead of 2000. The rational to choose these two points in time was to provide an overview of the demographic change within the most recent decade for which census data exists.

The geographic units for which population by age data has been collected are defined by the methodology to identify functional urban areas. For all European countries, the definition uses municipalities (LAU2 in Eurostat terminology). In non-European countries, the selected building block is generally the smallest administrative unit for which national commuting data are available.

Urban cores

Hinterland

London

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Population in functional urban areas, assessed year and data source

Country Source Years

Australia (No FUA defined) - Austria Statistics Austria 2001-11 Belgium Statistics Belgium 2001-11 Canada - - Chile INE Demographic Census 2002, Population projections 2012 2002-2012 Czech Republic Czech Statistical Office 2001-11 Denmark Statistics Denmark - Estonia Statistics Estonia, Population database 2001-11 Finland Statistics Finland 2001-11 France INSEE, Demographic Census 1999-2010 Germany Regionaldatenbank Deutschland 2001-11 Great Britain Office for National Statistics 2001-11 Greece National Statistical Service of Greece 2001-11 Hungary Hungarian Central Statistical Office 2001-11 Iceland (No FUA defined) - Ireland Central Statistics Office of Ireland 2001-11 Israel (No FUA defined) - Italy ISTAT, Demography in Figures 2002-11 Japan Statistical Office, Population and Households data 2000-10 Korea Korea National Statistical Office 2005-10 Luxemburg - - Mexico INEGI, Demographic Census 2000-10 Netherlands Statistics Netherlands 2001-11 New Zealand (No FUA defined) - Norway Statistics Norway 2001-11 Poland Central Statistical Office of Poland 2001-11 Portugal INE, Demographic Census 2001-11 Slovak Republic Statistical Office of the Slovak Republic 2001-11 Slovenia Statistical Office of the Republic of Slovenia 2001-11 Spain INE, Demographic Census 2001-11 Sweden Statistics Sweden 2001-11 Switzerland Swiss Federal Statistics Office 2001-11 Turkey (No FUA defined) - United States U.S. Census Bureau 2000-10

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APPENDIX 2 : CASE STUDIES

The OECD project on “Sustainable Urban Development Policies in Ageing Societies” assesses ageing trends and policy practices at the city level for case studies. This appendix briefly shows how the ageing trend is spatially diverse in 4 case study cities, Toyama (Japan), Manchester (UK), Lisbon (Portugal) and Cologne (Germany). The case study cities provide evidences that the geographically diverse ageing trend poses different challenges from place to place for cities, thus requiring cities to take policy reactions which consider spatial heterogeneity as their core policy agenda.

Case study assesses policies for administrative local governments, however, because the ageing trend is influenced beyond the border of cities, this project analyses each city’s ageing trend in connection to the population trend in its surrounding metropolitan areas, namely functional urban area.

In the course of the project, other cities will be also join as case study cities, including Yokohama (Japan), Helsinki (Finland), Brno (Czech Republic), Daejeon (Korea), Calgary (Canada) and Chicago (USA).

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(1) Toyama (Japan)

In Toyama City, the elderly population grows due to increases in longevity and the ageing of the baby boomer generation. The elderly population was at 115,961 in 2010, and is expected to increase to 125,079 by 2025 and 129,302 in 2045. The population in Toyama City has peaked in 2010 with 419,263 and has been decreasing since. It is estimated to be at 321,641 in 2045,a 23% decrease from 2010. As Toyama experiences a positive migration inflow, high mortality and low fertility rates are the main drivers of the projected population decrease. As a result the elderly population ratio will increase from 24.0% (2011) to 32% (2025) and finally to 40% by 2040.

The ageing trend is spatially heterogeneous. Among the 65 districts, the elderly population ratio varies from 21.1% (Fuchu District) to 38.8% (Hosoiri District). Toyama district, which has 76.6% of Toyama City’s population, is the only district that experiences a population increase, due to its central location in the city. Its elderly share has been increasing, from 18.8% in 2000 to 26.6% in 2013, and the number of elderly increased by 68.3%. Toyama City considers this to be mainly due to a natural increase; however, the city assumes that the city’s compact city policy has been contributing to the increase of elderly citizens in the central area of the city.

Toyama City considers ageing and population decline to pose fundamental challenges to the city’s sustainable development, thus compact city strategies are effectively implemented to overcome such issues. Toyama City assesses their challenges in three areas. First, the city forecasts that its tax revenue will decrease (e.g. income tax) and that pressure on medical-nursing expenditures will have a negative impact on urban “resilience”. Secondly, the city is concerned about the mobility loss of citizens. The city estimates that there will be 1.2 times more people without access to a car in 2030 due to population ageing. Consequently, this trend will deteriorate access to jobs and public services. Third, Toyama City has experienced a “doughnut phenomenon”, which increases residential and public facility development in suburbs. This causes the decline of economic resilience in urban central, because economic activities are shifting from the centre to the periphery.

Figure 14. Elderly share in Metropolitan Toyama

Source: OECD calculations based on statistics provided by Toyama City

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(2) Manchester (UK)

Over the course of the last two centuries, Manchester was marked by a trajectory of tremendous industrial growth and subsequent decline, during which the Mancunian population increased from 88,577 in 1801 to 751,292 in 1931, followed by a decrease to 391,819 in 2001.For 2001-2011, Manchester City registered a positive population growth rate of more than 2.5% per annum mainly due to in-migration of higher education students and younger workers, increasing the total population to 503,000 in 2011. Driven by natural losses and out-migration the elderly population decreased by 0.9% per year amounting to 47,544 in 2011 within the city boundaries. With 9.5% of the total population aged 65 and over, Manchester City shows the lowest elderly share in the Greater Manchester region and remains far below the national average of 20.3% for 2012. Even though the elderly population is projected to increase twice as fast as the total population until 2020, it will only do so at a moderate annual growth rate of 1.2%, increasing the elderly share from 9.5% to 10%.

The elderly population is distributed unevenly across the 32 wards of Manchester City. Long-standing communities of elderly tend to concentrate at the edges of the city, such as in Moston ward in the north-east (15.7% elderly share in 2011) and Brooklands in the south-west (14.3%). The inner city, such as Hulme or City Centre, features the lowest elderly share. These areas are marked by high shares of ethnic diversity and university students, and show a high proportion of private rented housing. Even though Manchester City registered a net out-migration of elderly people most senior residents tend to settle in neighbouring municipalities of Greater Manchester, notably Stockport, Trafford and Tameside.

The City Council framed ageing especially as a challenge of social inclusiveness. Due to out-migration of those elderly who can afford to live in suburbs, Manchester faces an elderly population as a small and dispersed minority in a young and booming city. The Council assumes that low and dispersed numbers of elderly are an indicator of “weak areas” featuring low levels of community capacity and social capital. In this context, the “Valuing Older People” programme was introduced since 2003 to improve the quality of life for elderly. Increasing health care and social service expenditure is also conceived as a significant challenge in Manchester, in face of the recession and further budget cuts in the near future.

Figure 15. Elderly share in Metropolitan Manchester

Source: OECD calculations based on statistics provided by Manchester City

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(3) Lisbon (Portugal)

Lisbon City has experienced a sharp population decline, from approximately 810,000 (1981) to 550,000 (2011) inhabitants. The elderly share reached from 14.6 % in 1960 to 24 % in 2011, which is 5% higher compared to the national value of 19%. Considering current population forecasts this trend is bound to continue with an additional population decrease of approximately 1.6% p.a. over the next 15 years and an increase in the elderly share by approximately 4.5%.

Within Lisbon City, the ageing population is distributed heterogeneously across 24 freguesias, which are the lowest tier of local governments in Portugal. While increasing average age is observed in the majority of freguesias, the opposite is the case in the 11 freguesias, mainly in the historic city centre. Here the elderly share dropped from 2001 and 2011 to approximately 20%. It is not clear if this is caused by an influx of younger people paired with a decrease in the elderly population, or by an overall population decline that is accelerated in the elderly age group.

One of the main areas of challenges faced by Lisbon is to attract young families to live in the city and therewith compensate for an increasing share of elderly people, as well as to retain a sustainable population level. Closely related to this challenge is the creation of economic growth and employment opportunities to leverage the city’s economic pull factors, while at the same time engaging the elderly in the labour force and to capitalize on their skills and knowledge.

Figure 16. Elderly share in Metropolitan Lisbon

Source: OECD calculations based on statistics provided by Lisbon City

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(4) Cologne (Germany)

Between 2000 and 2012, Cologne’s population has increased by 57,800 people to 1,026,700. This increase can be linked to a birth surplus since 2006 as well as a significant increase in the city’s net migration. Cologne’s positive migration balance is characterized by a substantial in-migration of younger generations, with approximately 50% of the city’s in-migrants between the age of 18 and 30. According to current population forecasts, Cologne City will continue to grow until 2020 to reach a total population of about 1.06 million before it will decline by approximately 15,000 inhabitants to 1.05 million in 2040. The decrease in population growth from the year 2020 onward will be driven by a slowing of the high migration rates and the expected overall decline in the age cohort 18-30 across Germany.

The elderly share accounted for 19.6% of the total population in 2011. According to the city’s population forecast, the elderly population will increase by approximately 20,000 until 2040, which will amount to approximately 21% of Cologne’s total population. Until 2040 Cologne will experience a significant increase of its 80+ age cohorts which will account for almost 7% of the total population. However, by 2040 Cologne will be approximately 6 years younger than the country average, with 43.9 years as compared to 49.3 respectively. The highest elderly shares are registered in peripheral districts, such as Chorweiler in the south-west and Porz in the north-east. In contrast, the inner city and neighbouring districts in the east and west are marked by a high proportion of younger population groups.

Due to increasing elderly shares, especially of the highly aged, the demand for housing, both for new types of housing as well as publicly funded housing is expected to increase. The existent housing stock and future development need furthermore to be adapted to meet barrier-free design standards. Linked to appropriate, affordable and accessible housing is the provision of accessible means of public transport, requiring both accessible design, as well as proximity. Taking into account the desire of elderly in Cologne to age in place, providing services in a customised, flexible and home-based manner poses another key challenge. A long-term concern stems from current and projected shortages in skilled labour, ageing of the work force and an increasing number of elderly looking for job opportunities.

Figure 17. Elderly share in Metropolitan Cologne

Source: OECD calculations based on statistics provided by Cologne City

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REFERENCES

Garribaldi, Pietro; Joaquim Oliveira Martins and Jan van Ours (2010), Ageing, Health and Productivity. The Economics of Increased Life Expectancy, Oxford. OECD (1996), Ageing in OECD countries. A Critical Policy Challenge, Paris.

OECD (2006), Live Longer, Work Longer. Ageing and Employment Policies, Paris

OECD (2010), OECD Regional Typology, http://www.oecd.org/gov/regional-policy/42392595.pdf.

OECD (2012a), Compact City Policies: A Comparative Assessment, Paris.

OECD (2012b), Redefining “Urban”: A New Way to Measure Metropolitan Areas Paris

OECD, (2013a), Pensions at a Glance, Paris.

OECD (2013b), Green Growth in Cities, Paris.

UN (2012), Population Ageing and Development, New York.

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Ageing Trends in Regions and Cities - OECD

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