Prioritising Actions for Demographic Transitions and ... filePrioritising Actions for Demographic...

Prioritising Actions for Demographic Transitions and Ageing in selected regions of Poland

GENER AL DI SCL AIMER | 2

GENERAL DISCLAIMER

This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.

Ce document et toute carte qu’il peut comprendre sont sans préjudice du statut de tout territoire, de la souveraineté s’exerçant sur ce dernier, du tracé des frontières et limites internationales, et du nom de tout territoire, ville ou région.

The views expressed in this paper do not necessarily reflect the official views of the OECD nor of the governments of its member countries nor those of the European Union.

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus” issue.

ACK NOLED GEME NT S | 3

Acknowledgements

The report is the result of combined efforts and strong co-operation between Polish Ministry of Infrastructure and Development and the OECD LEED Programme. Mr Michał Sułkowski and Mr Przemysław Herman, supervised by Mr Pawel Chorazy, Ministry of Infrastructure and Development, Poland provided data and relevant information from Polish sources. The report has been prepared by Dr Cristina Martinez of the OECD LEED Programme, which is supervised by Mr Sylvain Giguère, Head of the LEED Division and Mr Sergio Arzeni, Director of the Centre for Entrepreneurship, SMEs and Local Development. Dr Tamara Weyman (consultant) provided research assistance throughout the project and for the completion of the report.

We are grateful to the participants of the seminar "Desirable directions of public policies interventions in the context of demographic changes in Poland" hosted by the Polish Ministry of Infrastructure and Development on 14th January 2014 where the report was discussed and endorsed.

The following reports provide extended background analysis of demographic change in Poland and have contributed to this study: Martinez-Fernandez, C., et al. (2013), "Demographic Transition and an Ageing Society: Implications for Local Labour Markets in Poland", OECD Local Economic and Employment Development (LEED) Working Papers, No. 2013/08, OECD Publishing. doi: 10.1787/5k47xj1js027-en

Perek-Białas, J., C. Martinez-Fernandez and T. Weyman (2013), "Małopolska Region Demographic Transition: Working for the Future", OECD Local Economic and Employment Development (LEED) Working Papers, No. 2013/06, OECD Publishing. doi: 10.1787/5k4818gwg2jk-en

Szukalski, P., C. Martinez-Fernandez and T. Weyman (2013), "Łódzkie Region: Demographic Challenges within an Ideal Location", OECD Local Economic and Employment Development (LEED) Working Papers, No. 2013/05, OECD Publishing.doi: 10.1787/5k4818gt720p-en

Sagan, I., C. Martinez-Fernandez and T. Weyman (2013), "Pomorskie Region: Responding to Demographic Transitions Towards 2035", OECD Local Economic and Employment Development (LEED) Working Papers, No. 2013/07, OECD Publishing. doi: 10.1787/5k48189zpsmw-en

http://dx.doi.org/10.1787/5k47xj1js027-en

http://dx.doi.org/10.1787/5k4818gwg2jk-en

http://dx.doi.org/10.1787/5k4818gt720p-en

http://dx.doi.org/10.1787/5k48189zpsmw-en

CONTE NTS | 4

Contents Executive Summary ................................................................................................................................. 7

Introduction .......................................................................................................................................... 10

Demographic Change Dashboard ..................................................................................................... 10

Polish Demographic Change Dashboard ........................................................................................... 13

Regional Dashboard Profiles ............................................................................................................. 15

Dolnośląskie .................................................................................................................................. 16

Kujawsko-Pomorskie ..................................................................................................................... 19

Lubelskie ....................................................................................................................................... 22

Mazowieckie ................................................................................................................................. 25

Opolskie ........................................................................................................................................ 28

Podkarpackie ................................................................................................................................. 31

Podlaskie ....................................................................................................................................... 34

Śląskie ............................................................................................................................................ 37

Clusters of demographic transition in Polish regions ........................................................................ 40

Poland’s (Ageing) Silverprint ................................................................................................................. 45

Policies and Strategies for Regional Demographic Transition .............................................................. 57

Low population growth and fertility rates require programmes to promote family- friendly regions ................................................................................................................................. 57

Ageing societies require critical planning for age-friendly environments ........................................ 61

Workplace Age Management strategies can assure resilient ageing labour markets and economic sustainability .............................................................................................................. 63

Declining student enrolments and regional variation in tertiary education attainment require innovative approaches to education ................................................................................................. 67

Stagnation of adults participating in education requires implementation of lifelong learning programmes to sustain skills and innovation ................................................................................... 71

In conclusion – Speed of demographic transitions requires priority and sustained policy action ....... 74

References ............................................................................................................................................ 77

Annex .................................................................................................................................................... 78

Note on Contributors ............................................................................................................................ 79

CONTE NTS | 5

Figures Figure 1 Participating Polish regions ..................................................................................................... 11 Figure 2 Poland’s DCI dashboard results .............................................................................................. 13 Figure 3 Poland 2010 demographic themes dashboard ....................................................................... 15 Figure 4 Dolnośląskie DCI dashboard results ........................................................................................ 16 Figure 5 Dolnośląskie detailed dashboard results ................................................................................ 18 Figure 6 Kujawsko-Pomorskie DCI dashboard results .......................................................................... 19 Figure 7 Kujawsko-Pomorskie detailed dashboard results ................................................................... 21 Figure 8 Lubelskie DCI dashboard results ............................................................................................. 22 Figure 9 Lubelskie detailed dashboard results ..................................................................................... 24 Figure 10 Mazowieckie DCI dashboard results ..................................................................................... 25 Figure 11 Mazowieckie detailed dashboard results ............................................................................. 27 Figure 12 Opolskie DCI dashboard results ............................................................................................ 28 Figure 13 Opolskie detailed dashboard results .................................................................................... 30 Figure 14 Podkarpackie DCI dashboard results .................................................................................... 31 Figure 14 Podkarpackie detailed dashboard results ............................................................................. 33 Figure 16 Podlaskie DCI dashboard results ........................................................................................... 34 Figure 14 Podlaskie detailed dashboard results ................................................................................... 36 Figure 18 Śląskie DCI dashboard results ............................................................................................... 37 Figure 19 Śląskie detailed dashboard results ........................................................................................ 39 Figure 20 Overall 2000 DCI performance for Polish regions ................................................................. 40 Figure 21 Overall 2010 DCI performance for Polish regions ................................................................. 41 Figure 22 Overall Trend (2000-10) DCI performance for Polish regions............................................... 42 Figure 23 Dashboard regional clusters ................................................................................................. 43 Figure 24 Ageing, aged and super-aged society in Europe Map 2012 .................................................. 46 Figure 25 Ageing, aged, and super-aged society in Europe .................................................................. 47 Figure 26 Ageing, aged and super-aged society in Europe Map 2012 .................................................. 48 Figure 27 Ageing, aged, and super-aged society in Polish regions ....................................................... 49 Figure 28 Global AgeWatch Index domains and indicators .................................................................. 51 Figure 28 Global AgeWatch Index results of selected countries .......................................................... 53 Figure 29 Poland’s Ageing Silverprint ................................................................................................... 54 Figure 30 Employment (55-65) and educational attainment (60+) ...................................................... 55 Figure 31 Population growth rates (2000 & 2010) (%) ......................................................................... 58 Figure 32 Rates of natural increase (2000 & 2010) (per ,000 people) .................................................. 58 Figure 33 Fertility rates (2000 & 2010) ................................................................................................. 59 Figure 34 Youth population (2000 & 2010) (%) .................................................................................... 59 Figure 35 Youth dependency ratio (2000 & 2010) (%) ......................................................................... 59 Figure 36 Population 65 + (2000 & 2010) ............................................................................................ 61 Figure 37 Employment rate (15-64) (2000 & 2010) ............................................................................. 63 Figure 38 Population aged 55-64 (2000 & 2010) ................................................................................. 64 Figure 39 Average age of people becoming retired and office rates (2010) ....................................... 65 Figure 40 Students enrolled in education (2000 & 2010) (% of population) ....................................... 68

CONTE NTS | 6

Figure 41 Tertiary education attainment per employment and labour force (2000, 2010) ................ 69 Figure 42 Participation of adults in education (2000 & 2010) (%) ....................................................... 72

EXECUTIVE SU MM ARY | 7

Executive Summary

Demographic change is affecting all OECD member countries and developing economies. Labour markets in particular can be impacted from both population movements and the ageing of society. The impacts of demographic change are interconnected with economic, employment and social factors that require localised solutions. The Demographic Change Dashboard (DCD) is utilised to assess the impact of demographic transition at a regional scale between 2000 and 2010 for Polish regions of Mazowieckie, Śląskie, Lubelskie, Podkarpackie, Podlaskie, Dolnośląskie, Opolskie, and Kujawsko-Pomorskie. A Polish ‘Silverprint’ was developed to assess the speed of ageing combined with the score of the Global Ageing Index.

Key findings

• Absence of population growth, low fertility rates and declining youth - All the Polish regions are experiencing low population growth, overall in 2010 Poland was experiencing 0.1% growth, Łódźkie the lowest at -0.3% with Pomorskie the highest at 0.5%. The low population growth partly results from low fertility rates that are below replacement levels, with Opolskie experiencing the lowest rate of 1.1% in 2010. As a result Polish regions are witnessing youth (0-14) decline, with Podkarpackie (-6.5%) and Podlaskie (-6.2%) being the lowest from 2000-10. Family friendly policies and strategies should be encouraged in all regions.

• Ageing societies - All Polish regions are experiencing the benefits of a healthier society with increased life expectancy , but longevity has a fundamental impact on an ageing society. All regions are experiencing ageing of their population, from 2000-10 Poland’s share of persons aged 65+ increased by 1.4%; meanwhile, Śląskie and Opolskie increased by 3.0%. The issue becomes more serious when the speed of ageing is taken into consideration, as indicated in the Silverprint. The projected transition from ‘aged society’ (share of the population over 14%) to ‘super aged society’ (share of the population over 20%) is less than two decades for all participating regions. This gives little time to adjust socio-economic impacts of ageing and therefore urgent age management policy responses are needed to adjust this changing population structure.

• Ageing workforce - The ageing society has significant impact on the sustainability and stability of economic activities. The majority of Polish regions’ elderly dependency ratio is increasing, with Śląskie and Opolskie increased by 4.6% and 4.4% respectively from 2000-10, thereby creating a potential dependency burden on workers to support social security and public health systems. All regions are experiencing an increase in the proportion of the population aged 55-64 (older working age), with Dolnośląskie and Łódźkie increasing by 5.7% and 5.2% respectively (2000-10), essentially those who are coming up to retirement. In 2010 Poland’s legislative retirement age was 65 for men and 60 for women, during that year the average age of retiring people was notably lower for men and slightly lower for women


within all regions. As a result workplace and workforce age management policies become a high priority to ensure employment continuation to retirement age and beyond.

• Declining student enrolments and stagnation of lifelong learning - Regions are witnessing a decrease in students enrolled in education as a ratio of population, this could be a consequence of the declining youth proportions among other issues. There has also been a limited improvement in the number of adults participating in education with Mazowieckie experiencing the highest participation rate followed by Pomorskie (in 2010) and therefore in a better position to implement programmes to further encourage adult education within their regions. Meanwhile, Podkarpackie, Łódzkie and Kujawsko-Pomorskie appear to be struggling to even slightly increase the adult participation rates in education. As the population ages, authorities will need to boost labour force participation rates; lifelong learning is a key process that would enable the older generations to stay within the labour force.

• Poland’s ‘silverprint’ highlighted the ageing management focal indicators that are well advanced including pension coverage, old-age poverty rate, welfare, and social connections. The indicators that require urgent policy consideration: ageing transition, health life, employment and transport. Continued policy attention is required for relative psychological/mental wellbeing, educational attainment, physical safety and civic freedom.

Policy recommendations

• Implement programmes to promote family friendly regions: Implement family–friendly support structures such as financial assistance, social infrastructure and employment flexibility. These structures should take into consideration the diversity of the family unit, regional and local context within rural/urban environments and allow flexibility changes in the family home.

• Foster critical planning for age-friendly environments: Consideration within policy formulation for an ‘age-friendly’ urban and rural environment, whereby the physical and social environment enables people to remain healthy, independent and autonomous long into their old age. Urban systems related to transport, infrastructure, pollution, housing, public spaces and services need to be adjusted to the needs of the elderly population. Specific services will need to be increased such as in health and disease prevention, early investment in healthy lifestyles and active communities, which incorporate new approaches to the development of infrastructure and the provision of services, and that will reduce medical costs in later life.

• Design initiatives to stimulate workforce age management: private and public sectors need to foster a new work continuum, ranging from full-time to part-time within employment options for companies, governments and other sectors to extend the length, variety of and engagement in working-life; leading to longer employment and increased productivity for people across all sectors. Governments can encourage companies to implement age management practices, such as flexible working hours; opportunities for older workers to update their skills and better health and/or safety programmes to


encourage older workers to stay within the working environment. Increasing research investment into the effects of ageing on employment structures within the economic activities would assist in formulating age management policies specific to regional and local social-economic context.

• Promote innovative programmes to support education: implementing and promoting innovative programmes such as distance education and open universities to provide opportunities for students to continue their education where vocational facilities are not available should be a priority. Investment in research is needed to ascertain the causes of regional variation in tertiary education attainment and to establish appropriate policy response relevant to the regional and local context.

• Encourage a culture of lifelong learning: Develop programmes to foster lifelong learning focusing on increasing skill levels of young and older workers and instil the culture within society of lifelong learning values. Firm initiatives and employee incentives are required to initiate interest in skills and training development and the benefits of long-life learning approaches.

INT ROD UCT IO N | 10

Introduction

Anticipating demographic changes is a key strategic response of Poland regional policy. Effects of demographic change are not uniform but intertwined with economic, employment and social factors that require localised analysis and targeted strategies and policies for labour markets.

A recent OECD report (Martinez-Fernandez et al, 2013) analysed the implications of the demographic transition for labour markets in three Polish regions (Małopolskie, Łódźkie and Pomorskie) revealing the need for a territorial analysis for policy preparation, development and implementation where national and local policy efforts are co-ordinated. During this study a Demographic Change Dashboard (DCD) was developed.

This report is divided into three parts; the analysis of the dashboard on national and regional levels; Poland’s (ageing) silver-print; and priorities for policies and strategies for regional demographic transition.

Demographic Change Dashboard

The ‘Demographic Change Dashboard’ is a dynamic tool used for strategic analysis and policy prioritisation of actions at local level. The DCD was tested in the analysis of demographic change in Małopolskie, Łódźkie and Pomorskie (Martinez-Fernandez et al, 2013) and the analysis is now extended in this report to the regions of Mazowieckie, Śląskie, Lubelskie, Podkarpackie, Podlaskie, Dolnośląskie, Opolskie, and Kujawsko-Pomorskie (see figure 1).


Figure 1 Participating Polish regions

Source: d-maps.com

To illustrate the performance of the regional areas analysed, a dashboard is used, presenting a set of indicators in a simple pie chart based on three principles:

1. The size of a segment reflects the relative importance of the issue described by the indicator.

2. Colour codes signal relative performance, with green meaning “good” and red meaning “bad”.

3. A central circle, the Policy Performance Index (PPI), summarises the information from the component indicators – in this case, it is called the Demographic Change Index (DCI).

Pomorskie

Kujawsko-Pomorskie

Mazowieckie

Podlaskie

ŁódźkieLubelskie

Podkarpackie

Małopolskie

Śląskie

Opolskie

Dolnośląskie

SłupskGdańsk

Grudziądz

Bydgoszcz

Włocławek

Warszawa

Łódź

Radom

KrakówKatowice

CzęstochowaOpole

Wrocław

Wałbrzych

JeleniaGóra

Rzeszów

Lublin

Białystok

Suwałki

RUSSIALITHUANIA

BELARUS

UKRAINE

SLOVAKIA

CZECHREPUBLIC

GERMANY


The dashboard Therefore shades of green indicate good (positive) performance, while shades of red indicate a bad (negative) performance, overall there are nine performance categories: excellent (dark green), very good, good, fair (light green), average (yellow), bad (light red/pink), very bad, serious, and critical (dark red). The dashboard has 5 key themes:

1. Demographic change index (DCI) (overall summary performance index). 2. Demography (population growth; age cohorts (0-14, 15-64, and 65+); life expectancy;

rates of natural increase; fertility rates; and infant mortality) 3. Economy (primary income of households; GDP per capita; youth, elderly and economic

dependency ratios) 4. Labour (employment rates (15-64, 15-24, 55-64 age cohorts); and unemployment rates

(15-24, 55-64 age cohorts) 5. Skills and Education (students enrolled in education (percentage of population);

students enrolled in tertiary education (percentage of students); tertiary education attainment (percentage of employment and labour force); and participation of adults in education (by gender).

For comparison purposes, the EU-27 and OECD are included in the analysis. The dashboard highlights strategic areas where policy dialogue and response is needed for each analysed region and where further examination is needed at the regional/local level. Table 1 below shows the themes and indicators included in the dashboard and the reference code for each of the indicators.

Table 1 Dashboard themes and indicators

Theme / Indicators Codes Demography

Population growth rates PopGR Population 0-14 (%) PopYR Population 15-64 (%) PopWR Population 55-64 (%) PopOWR Population 65+ (%) PopER Life expectancy (at less than a year) LifeE Life expectancy – males LifeEM Life expectancy – females LifeEF Rate of Natural increase (per 1 000 people per year) RNI Fertility rate Fert Infant mortality rate (deaths per 1 000 live births) InMort

Economy Income of household (balance of primary income, net (uses)) (Euro per inhabitant) PrIn Gross domestic product (GDP) at current market prices (Euro per inhabitant) GDPcap Youth dependency ratio (%) (youth – 0-19) (dependency 20-64) YDR Elderly dependency ratio (%) (elderly – 65+) (dependency 20-64) EDR Economic dependency ratio (%) (Number of pensioners (old age and disability) plus number of unemployed compared to number of working)) (dependency 20-64)

EcDR

Labour Employment rate (15-64) EmpR Employment rate (15-24) EmpYR Employment rate (55-64) EmpOR


Unemployment rate (15+) UempR Theme / Indicators Codes

Unemployment rate (15-24) UempYR Unemployment rate (55-64) UempOR

Skills and education Students enrolled in education as per population (%) STenED Students enrolled in tertiary education as per total students (%) STenTED Tertiary education attainment (% total employment (15+)) TerEdAtEm Tertiary education attainment (% of labour force) TerEdLF Participation of adults in education (%) PaADEd Participation of male adults in education (%) PaAdEdM Participation of female adults in education (%) PaAdEdF

Polish Demographic Change Dashboard According to the dashboard, Poland in 2000 was struggling with its demographic change in comparison with the OECD and EU-27, with an overall DCI performance rated as ‘bad’; in all themes the performance levels rated between ‘bad’ and ‘very bad’ for skills and education (see figure 2). However, by 2010 Poland was performing stronger overall with DCI rating as ‘fair’ and within two of the themes (labour and economy), while demography and skills and education rated as ‘average’.

Figure 2 Poland’s DCI dashboard results

Notes: D (Demography); E (Economy); L (Labour); and SE (Skills and Education). Notes see appendix 1. Source: OECD calculations based on OECDstats, EuroStats and Poland CSO

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Excellent Good Average Very bad Critical

Very Good Fair Bad Serious


As revealed in figure 3, the detailed dashboard results for 2010, highlights the strengths and weaknesses within the demographic change index (figure 3):

Demography was rated as ‘average’:

• Strengths: Population growth was in the positive (only just) but was an improvement from 2000, the working age population was comparably higher than the EU27 and OECD average and had increased since 2000, infant mortality rates had decreased by 3.1 from 2000 (to 2010).

• Weaknesses: Decrease in youth population by 4.7% since 2000 (to 2010); increase in older working age (55-64) by 3.3% since 2000 and fertility rates below replacement levels.

Economy was rated as ‘fair’:

• Strengths: Youth dependency ratios had dropped by 14.4% since 2000, economic dependency ratio has also dropped from 71.1 % (2000) to 63.1% although still quite high and elderly dependency ratios has remain stable at 24.4%.

• Weaknesses: compared to the EU27 the GDP per capita is low, along with primary household income.

Labour was rated as ‘fair’:

• Strengths: increase in employment rates by 4.2%, decrease in unemployment rates by 6.7% since 2000.

• Weaknesses: Compared to the OECD average and EU27 youth employment is low at 24.1%

Skills and education was rated as ‘average’:

• Strengths: Slight increase in students enrolled in tertiary education (per total students) (6.4% 2000-10) and increases in tertiary education attainment (both employment and labour force) indicates an up-skilling of the economic active population (13.8% and 10.4% respectively).

• Weaknesses: Decline in students enrolled in education (per population) (-2.5% 2000-10)indicates a slowing of youth population and adult participation in education has remained practically the same which indicates a lack of lifelong learning culture.


Figure 3 Poland 2010 demographic themes dashboard

Note: see appendix 1 Source: OECD calculations based on OECDstats, EuroStats and Poland CSO

Although Poland has significantly progressed since 2000, an overall commitment to the continued overall improvement within all regions with concerted focus on encouraging population growth, increase fertility rates, youth support, age management and resources in skills and education will provides the backbone to a strong economy that is inclusive of all regions.

However, as revealed in the recent OECD (2013) analysis of Małopolskie, Łódźkie and Pomorskie each region can experience differing issues associated with their socio-economic situations and therefore designing of actions and strategies needs to be based on individual regional assessments. The following section presents the regional dashboard profiles for the extended regions in this report.

Regional Dashboard Profiles The regional dashboards illustrate the overall DCI (centre circle) and theme results (surround boxes) for 2000, 2010 and 2000-10 (trend) with the coded colour: red (bad), yellow (average) and green (good) shading. Under each box are the scores calculated by the dashboard in a bar graph highlighting the changes in the theme in related to the overall DCI score for the corresponding year. Further detailed analysis was completed on each theme to find which focal indicators provide opportunities and threats to the demographic transition in the regions. Dashboard scores are calculated as relative to the regions involved in the analysis.

Excellent Good Average Very bad Critical

Very Good Fair Bad Serious

http://www.paiz.gov.pl/polish_regions/voivodships/malopolskie


Dolnośląskie Dolnośląskie is located on the south-western Poland bordering the countries of Germany and Czech Republic and the voivodships of Lubuskie, Wielkopolskie, and Opolskie. The demographic change dashboard, illustrated in figure 4, revealed an improvement in all the demographic themes from 2000 to 2010 – Demography, Economy, and Labour had the most notable performance improvement illustrated by the colour change from red shades (bad) to yellow (average) with overall DCI score from 27.8 (out of 100) in 2000 to 54 in 2010 (as shown in the bar graphs in figure 4). However, Skills and Education had remained in the ‘bad’ performing trend indicating that the improvements were not as significant compared to the other regions. The trend analysis (2000-10) revealed a mostly overall improvement (green shading) which is a positive development but the region is still a long way from an ideal demographic and socio-economic environment. The labour category had a significant performance improvement compared with the other regions from serious (score 13.2) to average (52.5) resulting in a very good trend performance rating (score 81.9) (Figure 4).

Figure 4 Dolnośląskie DCI dashboard results

Note: D – Demography; E – Economy; L – Labour; SE – Skills and education Source: OECD calculations based on OECDstats, EuroStats and Poland CSO

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Detailed dashboard analysis (2000, 2010, and 2000-10) (figure 5) revealed the following opportunities (green shading) and threats (red and yellow shading), which highlight areas for future improvement:

• OPPORTUNITIES – In 2010 population of the working age (PopWR) had increased from 69.4% (2000) to 72.5% (2010: rated as excellent); Infant mortality (InMort: rated as fair) declined by 3.4 deaths per 1000 births (2000-10) and life expectancies female (LifeEF) was at 80.6 years an increase on average 3.0 since 2000. Unemployment rates (UEmpR) was 11.3 (2010: rated as fair) and had decreased significantly since 2000. Student enrolment in tertiary education (as per total students) (STenTED) had increased by 8.9% (2000-10), along with tertiary education attainment (percentage of employment and labour force)(TerEdAtEm and TerEdAtLF) reflecting an up skilling of the workforce in the region. Youth dependency ratios (YDR) was 30.4% (2010: rated as Excellent) declined by 14.5% since 2000 and elderly dependency ratio was 24.9% (2010: rated as good) also declined by 19.1%.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.3: rated as very bad) below replacement level and thus negative rate of natural increase (RNI -0.1 per 1 000 people: rated as average). Youth population (PopYR: 0-14) had declined from 18.4% (2000) to 14.0% (2010: rated as critical). At the same time there was an increase the older working population (PopOWR: 55-64) from 8.5% (2000) to 14.2% (2010) (critical). Youth employment rates (EmpYR: bad) was under-performing along high unemployment for older workers (UEmpOR), nevertheless these indicators have improved since 2000. Student enrolment in education (as per population) had declined by 3.1% (2000-10) and participation of adults in education, although was rated as averaged overall/males and bad for females the trend from 2000-10 has remained stagnated. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Dolnośląskie was 10 400 Euro, 4 600 Euro per capita below which had a performance rating of very bad, although the region still achieved the second highest GDP per capita compared to the participating regions and had a notable improvement since 2000.


Figure 5 Dolnośląskie detailed dashboard results

Source: OECD calculations based on OECDstats, EuroStats and Poland CSO

Dolnośląskie 2000 Dolnośląskie 2010 Dolnośląskie 2000-2010





Kujawsko-Pomorskie Kujawsko-Pomorskie located on the north-central Poland bordering the voivodships of Pomorskie, Warmińsko-Mazurskie, Mazowieckie, Łódzkie, Wielkopolskie and Zachodniopomorskie. The demographic change dashboard in figure 6, revealed an improvement in the majority of the dashboard themes – Demography, Economy, and Labour illustrated by the colour change red shades (bad) (2000) to yellow (average) and light green (fair) in 2010 with an overall DCI score from 28.8 (out of 100) in 2000 to 48.6 in 2010. Although Skills and Education had remained in the ‘very bad’ performance rating and the trend analysis (2000-10) was rated as ‘serious’. It should also be noted that the overall trend improvements was average (yellow shading in the 2000-10). Similar to Dolnośląskie the labour category had a significant performance improvement compared with the other regions from serious (score 19.4) to average (52.7) resulting in a very good trend performance rating (score 71.6) (Figure 6).

Figure 6 Kujawsko-Pomorskie DCI dashboard results


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Detailed dashboard analysis (2000, 2010, and 2000-10) (figure 7) revealed the following opportunities (green shading) and weaknesses (red and yellow shading), which highlight areas for future improvement:

• OPPORTUNITIES - Population of the working age (PopWR) had increased from 68.2% (2000) to 71.8 % (2010: rating as good). Infant mortality (InMort) declining by 2.9 deaths per 1000 births and the rate of natural increase (RNI) in the positive at 1.0 (per 1 000 people: rated as fair). Unemployment has declined by 7.6%, with notable improvements in youth unemployment, declining by 12.6% (2000-10) combined with an overall trend of employment rate increase, although the actual rate in 2010 was below the EU27 and OECD average and the Polish region of Mazowieckie. Currently the youth and economic dependency ratios are declining (-14.8 and -13.6% respectively) and the elderly dependency was stable.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.4: rated as bad) below replacement level as a result there had been a decline in youth population (PopYR: 0-14) from 20.5% (2000) to 15.7% (2010: rated as very bad). At the same time there was an increase the older working population (PopOWR: 55-64) from 8.4% (2000) to 13.0% (2010: rated as serious). Life expectancies in 2010 (75.7) which is 4 years less than the EU27 and OECD average, with minimal improvement since 2000 (2.2 years) with the gap between genders remaining at (8.5 years). Compared to the other Polish regions youth employment rates (EmpYR: very bad) was under-performing. The region was under-performing in all aspects of skills and education compared to the other polish regions. Student enrolment in education (as per population) had declined by 2.5% (STenEd 2000-10). Participation of adults in education was rated as very bad overall and for each gender with the stagnation trend from 2000-10. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Kujawsko-Pomorskie was 7 700 Euro, 7 300 Euro per capita below, which had a performance rating of serious.


Figure 7 Kujawsko-Pomorskie detailed dashboard results


Kujawsko-Pomorskie 2000-2010Kujawsko-Pomorskie 2010Kujawsko-Pomorskie 2000





Lubelskie Lubelskie located on the eastern Poland bordering the voivodships of Podlaskie, Mazowieckie, Świętokrzyskie, and Podkarpackie and the countries of Belarus and Ukraine. The demographic change dashboard revealed a small improvement in all the dashboard themes – Demography, Economy, Labour and Skills and Education illustrated by the colour change from red and yellow shades (2000) to yellow (average) and light green (fair) in 2010 and an overall DCI score of 39.5 (out of 100) to 52.3 (Figure 8). The trend (2000-10) dashboard highlighted that the improvements were not as significant compared to the other Polish regions as indicated by the red shading.

Figure 8 Lubelskie DCI dashboard results



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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 65.7% (2000) to 70.1 % (2010) and Infant mortality (InMort) declined by 3.3 deaths per 1000 births although the rate of natural increase (RNI) was still in the negative at -0.2 (per 1 000 people: rated as average). The life expectancy for females in 2010 was 81 years, an increase of 2.6 years since 2000. Unemployment had declined by 3.7 %, with notable improvements in youth unemployment, declining by 8.9% (2000-10). The youth ratio declined by 16.1% along with minor adjustments to the elderly and economic dependency ratios (-0.6 and 0.8% respectively). Importantly the region experienced an improvement in tertiary education attainment per employment and labour force of 11.4 and 10.1%.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.4: rated as bad) below replacement level as a result there had been a decline in youth population (PopYR: 0-14) from 20.8% (2000) to 15.5% (2010: rated as critical). At the same time the older working population (PopOWR: 55-64) increased from 8.7% (2000) to 12.4% (2010: rated as very bad). Life expectancies was 76.1 in 2010 (75.7) with minimal improvement since 2000 (2.5 years) with the gap between genders remaining at (9.7 years). Compared to the other Polish regions youth employment rates (EmpYR: critical) was under-performing declining by 8.9% at the same time the overall employment rate declined by 3.7% reflecting the red shading the trend dashboard (2000-10). The region was struggling in the majority skills and education indicators compared to the other polish regions. Student enrolment in education (as per population) has declined by 2.9% (STenEd 2000-10), this could be the result of the declining youth population within the region. Participation of adults in education was rated as average with minimal improvement since 2000. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Lubelskie was 6 200 Euro, 8 800 Euro per capita below, which had a performance rating of serious.


Figure 9 Lubelskie detailed dashboard results


Lubelskie 2000 Lubelskie 2000-2010Lubelskie 2010

Lubelskie 2000 Lubelskie 2010 Lubelskie 2000-2010




Mazowieckie Mazowieckie located on the east-central Poland bordering the voivodships of Warmińsko-Mazurskie, Podlaskie, Lubelskie, Świętokrzyskie, Łódzkie and Kujawsko-Pomorskie with Warsaw being the nation’s capital city. The demographic change dashboard revealed improvements in all the dashboard themes – Demography, Economy, Labour and Skills and Education illustrated by the colour change from yellow (average) and light green (fair) (2000) to the overall shading of green ranging from fair to very good in 2010 and an overall DCI score of 51.5 (out of 100) to 73.8. Mazowieckie region was the best performing region in 2000 and 2010 and is comparable with the EU27 and OECD average. The trend (2000-10) dashboard highlighted greater improvements in economy and skills/education (Figure 10).

Figure 10 Mazowieckie DCI dashboard results



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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 67.8% (2000) to 70.4% (2010), infant mortality (InMort) declined by 2.7 deaths per 1000 births and the rate of natural increase (RNI) increased by 2.2 (per 1 000 people: rated as average). The life expectancy for females in 2010 was 81.2 years, an increase of 2.5 years since 2000. Employment rates were 64.4% in 2010, with increases in youth and older-aged worker employment (1.2 and 1.8% respectively). Unemployment had declined by 5.9%, with notable improvements in youth unemployment, declining by 12.9% (2000-10) reflecting good economic conditions within the region. The youth dependency ratio declined by 11.9% along with minor decrease in economic dependency ratio (4.9%). The region has the highest household income (balance of primary income) and gross domestic product per capita. Students enrolled in tertiary education (per total students) increased from 28.0 (2000) to 33.4% (2010), with increases in tertiary education attainment in employment and labour force by 20.7 and 14.3% respectively (2000-10) and the highest rate of adult participation in education compared with the other polish regions. Importantly the region experienced an improvement in tertiary education attainment.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.5: rated as average) below replacement level as a result there had been a decline in youth population (PopYR: 0-14) from 18.5% (2000) to 15.1% (2010: rated as serious). At the same time there was an increase the older working population (PopOWR: 55-64) from 9.0% (2000) to 12.9% (2010: rated as very serious). Mazowieckie life expectancies gender gap was 8.6 years suggesting further initiatives for men health programmes. Compared to the other Polish regions youth employment rates (EmpYR: critical) only increased by 1.2% (2000-10). Population growth within the region also decline from 0.9% in 2000 t0 0.3%, it should be noted however, all the regions in Poland and the EU27/OECD averages were struggling with population growth.


Figure 11 Mazowieckie detailed dashboard results


Mazowieckie 2000 Mazowieckie 2010 Mazowieckie 2000-2010





Opolskie Opolskie located in the southern Poland bordering the country of Czech Republic and the voivodships of Dolnośląskie, Wielkopolskie, Łódzkie and Śląskie. The demographic change dashboard revealed slight improvements in all the dashboard themes – Economy, Labour and Skills and Education illustrated by the colour change from red and yellow shading (2000) to the overall shading of yellow (average), light green (fair) and light red (bad) 2010 and an overall DCI score of 36.8 (out of 100) to 49.7 (figure 12). The trend (2000-10) dashboard highlighted that the Opolskie region was struggling to improve their performance compared to the other Polish regions especially within economy and demography (figure 12).

Figure 12 Opolskie DCI dashboard results



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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 69.2% (2000) to 72.2% (2010). Infant mortality (InMort) declined by 0.8 deaths per 1000 births and life expectancy improving by 2.6 years (2000-10). Employment was 58.5% an increase on 2.6% since 2000 and unemployment declined by 5.0% to 9.6% in 2010 with notable improvements in youth unemployment, declining by 10.0% (2000-10). In 2010 the youth and economic dependency ratios declined (-15.9 and -2.6% respectively) while the elderly dependency increased slightly to 26.4%.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.1: rated as critical) below replacement level and the rate of natural increase declined by 0.7 (to be -0.7 in 2010) as a result there had been a decline in youth population (PopYR: 0-14) from 19.5% (2000) to 13.6% (2010: rated as critical). At the same time there was an increase the older working population (PopOWR: 55-64) from 9.6% (2000) to 12.5% (2010: rated as very bad) and the over 65s also increased from 11.3% (2000) to 14.3% in 2010. Opolskie was also struggling with the life expectancy gap between genders remaining at (7.9 years) suggesting further initiatives for men health programmes. Compared to the other Polish regions youth and older worker employment rates (EmpYR: very bad) were under-performing. The region was under-performing in all aspects of skills and education compared to the other polish regions. Student enrolment in education (as per population) had declined by 3.0% (STenEd 2000-10). Participation of adults in education was rated bad overall (only 4.8% in 2010) and 4.1 and 5.5% respectively for male and female although the trend reveals that the rate has improve by 1.6% overall. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Opolskie was 7 300 Euro, 7 700 Euro per capita below, which had a performance rating of serious.


Figure 13 Opolskie detailed dashboard results


Opolskie 2000 Opolskie 2010 Opolskie 2000-2010





Podkarpackie Podkarpackie located in the south-eastern Poland bordering the country of Ukraine and Slovakia and the voivodships of Lubelskie, Małopolskie and Świętokrzyskie. The demographic change dashboard revealed slight improvements in all the dashboard themes – Economy, Labour and Skills and Education illustrated by the colour change from red shading (2000) to the overall shading of yellow (average), lighter red for skills and education (very bad) 2010 with an overall DCI score of 36.8 (out of 100) to 48.8 (figure 14). The trend (2000-10) dashboard highlighted that the Podkarpackie region was struggling to improve their performance compared to the other Polish regions in all dashboard themes (figure 15).

Figure 14 Podkarpackie DCI dashboard results



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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 65.6% (2000) to 70.8% (2010). Health standards seems to be improving in the region with infant mortality (InMort) declining by 2.0 deaths per 1000 births, rate of natural increase is 1.8 (although had declined by -0.8) and life expectancy improving by 2.9 years (2000-10) to 77.9. Employment of the older-aged workers had increased by 1.6% to 39.7% in 2010, while unemployment in the same age category in 2019 was only 4.8%, and the overall unemployment had decreased by 2.8% (2000-10). In 2010 youth and economic dependency ratios declined (-18.6 and -1.3% respectively) while the elderly dependency increased slightly to 25.4%.

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.3: rated as very bad) below replacement level and the rate of natural increase declined by 0.8, as a result there had been a decline in youth population (PopYR: 0-14) from 22.6% (2000) to 16.1% (2010: rated as very bad). At the same time the older working population (PopOWR: 55-64) increased from 8.2% (2000) to 11.4% (2010: rated as bad). Compared to the other Polish regions youth employment rates (EmpYR: very bad) (20.0% 2010) with a youth unemployment rate of 11.7%. The region was under-performing in all aspects of skills and education compared to the other polish regions. Student enrolment in education (as per population) had declined by 2.9% (STenEd 2000-10), this could be the result of the declining youth population within the region. Students enrolled in tertiary education (per total students) was 16.2% (2010: rated as very bad) and tertiary education attainment per employment and labour forces was categorised as average compared to the other Polish regions). Participation of adults in education was rated serious overall (only 3.4% in 2010) and 3.2 and 3.6% respectively for male and female and the trend indicated little improvement. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Podkarpackie was 6 200 Euro, 8 800 Euro per capita below, which had a performance rating of critical.


Figure 15 Podkarpackie detailed dashboard results


Podkarpackie 2000 Podkarpackie 2010 Podkarpackie 2000-2010





Podlaskie Podlaskie located in the north-eastern Poland bordering the country of Lithuania and Belarus and the voivodships of Lubelskie, Mazowieckie and Warmińsko-Mazurskie. The demographic change dashboard revealed slight improvements in all the dashboard themes – Demography, Economy, Labour and Skills and Education illustrated by the colour change from red and yellow shading (2000) to the overall shading of yellow (average), light green (fair) 2010 with an overall DCI score of 39.2 (out of 100) to 50.7 (figure 16). The trend (2000-10) dashboard highlighted that the Podlaskie region is struggling to improve their performance compared to the other Polish regions in all dashboard themes (figure 14).

Figure 16 Podlaskie DCI dashboard results



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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 65.3% (2000)

to 70.2% (2010) Infant mortality (InMort) declined by 2.8 deaths per 1000 births, and life expectancy improved by 2.7 years (2000-10) to 77.3 (2010) and high life expectancy for females (82 years in 2010). Employment rate was 59.2% (2010) while unemployment declined by 5.5% to 10.2% along with youth unemployment (- 6.5%). In 2010 youth and economic dependency ratios declined (-17.4 and -0.4% respectively). The region had reasonable tertiary education attainment per employment and workforce (26.3 and 21.9% respectively in 2010).

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.4: rated as very bad) below replacement level and the rate of natural increase declined by 0.1, as a result there had been a decline in youth population (PopYR: 0-14) from 21.3% (2000) to 15.1% (2010: rated as very bad). At the same time the older working population (PopOWR: 55-64) increased from 8.7% (2000) to 11.2% (2010: rated as bad). Youth employment rates (EmpYR: serious) was 23.7% in 2010 and the region was under-performing in majority of aspects of skills and education compared to the other polish regions. Student enrolment in education (as per population) had declined by 3.3% (STenEd 2000-10), this could be the result of the declining youth population within the region. Students enrolled in tertiary education (per total students) was 20.7% (2010: rated as average) and participation of adults in education was rated bad overall (only 5.2% in 2010) and 4.4 and 6.0% respectively for male and female. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Podlaskie was 6 700 Euro, 8 300 Euro per capita below, which had a performance rating of serious.


Figure 17 Podlaskie detailed dashboard results


Podlaskie 2000 Podlaskie 2010 Podlaskie 2000-2010





Śląskie Śląskie located in the southern Poland bordering the countries of Slovakia and Czech Republic and the voivodships of Łódzkie, Świętokrzyskie, Małopolskie and Opolskie. The demographic change dashboard revealed improvements in all the dashboard themes – Demography, Economy, Labour and Skills and Education illustrated by the colour change from red shading (2000) to the overall shading of yellow (average), light green (fair) 2010 with an overall DCI score of 25.7 (out of 100) to 51.6 (figure 18). The trend (2000-10) dashboard highlighted that the Śląskie region was improving (green shading) their performance compared to the other Polish regions in the majority of dashboard themes, except economy (rated as bad 2000-10) (figure 18).

Figure 18 Śląskie DCI dashboard results


Detailed dashboard results (2000, 2010, and 2000-10) (figure 19) revealed the following opportunities (green shading) and weaknesses (red and yellow shading), which highlight areas for future improvement:

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• OPPORTUNITIES - Population of the working age (PopWR) had increased from 67.1% (2000)

to 71.9% (2010) providing and infant mortality (InMort) declined by 4.4 deaths per 1000 births. Unemployment rates declined by 9.8% to 9.1% in 2010 along with youth unemployment (declined by 10.1%). In 2010 youth and economic dependency ratios declined (-13.0 and -16.1% respectively) and a relative low elderly dependency ratio of 26.1% (2010). The region had reasonable tertiary education attainment per employment and workforce (28.3 and 21.6% respectively in 2010).

• THREATS - In 2010 the region was experiencing a low fertility rate (Fert 1.3: rated as very bad) below replacement level as a result there had been a decline in youth population (PopYR: 0-14) from 18.3% (2000) to 13.9% (2010: rated as critical). At the same time the older working population (PopOWR: 55-64) increased from 10.0% (2000) to 14.2% (2010: rated as serious). Youth employment rates (EmpYR: very bad) was 25.5% in 2010. The region was under-performing in majority of aspects of skills and education compared to the other polish regions. Student enrolment in education (as per population) had declined by 3.1% (STenEd 2000-10), this could be the result of the declining youth population within the region. Participation of adults in education was rated average overall (only 5.6% in 2010) and 5.0 and 6.2% respectively for male and female however the trend indicated improvement. Compared with Mazowieckie which had the highest GDP per capita (GDPcap) (15 000 Euro) in 2010 while Śląskie was 9 800 Euro5 200 Euro per capita below, which had a performance rating of very bad.


Figure 19 Śląskie detailed dashboard results


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Clusters of demographic transition in Polish regions

The demographic dashboard analysis shows than in 2000, the participating Polish regions were struggling with their demographic challenges. Figure 20 illustrates the DCI overall performance for each region, rating between ‘average’ for Mazowieckie to ‘very bad’ for the four more central regions of Kujawsko-Pomorskie, Łódzkie, Śląskie and Dolnośląskie. According to the dashboard results Mazowieckie, and Małopolskie were performing better than the whole of Poland, while Śląskie appears as the under-performing region in 2000.

Figure 20 Overall 2000 DCI performance for Polish regions


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In 2010, there was a significant improvement in the overall DCI index for all Polish regions. Figure 21 illustrates the overall DCI performance for each region rating between ‘good’ (Mazowieckie), ‘fair’ (Pomorskie, Małopolskie, and Dolnośląskie) and ‘average’ for the remaining regions. According to the dashboard results Mazowieckie in 2010 is not only out performing Poland but also the EU-27 and OECD. The regions of Małopolskie and Pomorskie were out performing Poland, while Podkarpackie, Kujawsko-Pomorskie and Opolskie were the lowest performing regions in 2010.

Figure 21 Overall 2010 DCI performance for Polish regions


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Figure 22 illustrates the overall trend (2000-10) DCI index for all Polish regions, whereby notable performance (fair) improvements were experienced by Dolnośląskie, Łódzkie, Mazowieckie, Pomorskie, and Śląskie, ‘average’ (Kujawsko-Pomorskie) and ‘bad’ for the remaining regions. According to the dashboard results Dolnośląskie and Mazowieckie) were the best improvers from 2000, while the regions of Podlaskie and Opolskie were the regions that improved the least since 2000.

Figure 22 Overall Trend (2000-10) DCI performance for Polish regions


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The demographic change dashboard results illustrate three different performing regional clusters whereby policy focus varies (Figure 22):

• Central corridor (Kujawsko-Pomorskie, Łódzkie, Opolskie and Śląskie): average performing regions in 2010, and although indicating good improvement trends, nevertheless they show an overall weak performance.

• Eastern Border corridor (Podlaskie, Lubelskie and Podkarpackie): average performing regions in 2010 along with bad performance trends, these regions all border with Eastern countries.

• Scattered stronger axis (Mazowieckie, Pomorskie, Małopolskie and Dolnoślqskie): with fair to good performances in 2010 and associated positive trends from 2000-10 (except Małopolskie).

Figure 23 Dashboard regional clusters

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The importance of identifying demographic change regional clusters so that policies could be differentiated as per typology of corridor as its shows different speeds of demographic transition. As a result priority and sustained policy action can be identified for each region.

POLAN D’ S ( A GEIN G) S ILVE RPRINT | 45

Poland’s (Ageing) Silverprint

This section discusses measures of ageing, the speed of ageing transitions and the ‘silverprint’ of Poland which is defined by the speed of ageing combined with the score of the Global Ageing Index1 subcategories:

Domain 1: Income security

The income security domain assesses people's access to a sufficient amount of income, and the capacity to use it independently, in order to meet basic needs in older age.

Domain 2: Health status

The three indicators used for the health domain provide information about physical and psychological wellbeing.

Domain 3: Employment and education

The two indicators in this domain look at different aspects of the empowerment of older people.

Domain 4: Enabling environment

This domain uses data from Gallup World View to assess older people's perception of social connectedness, safety, civic freedom and access to public transport - issues older people have singled out as particularly important.

The participating regions will be discussed in this section in relation to the speed of ageing.

The speed of ageing transitions is a significant factor for regional policy

Although all OECD countries are ageing, not all countries are ‘ageing’ at the same pace; some countries can be characterised as ‘ageing’ when their share of population aged over 65 is over 7% and less than 14%, or ‘aged’ societies when their share of population aged over 65 greater than 14% and less than 20% or ‘super-aged’ society when the share of the population aged over 65 is over 20% (Lee, 2013).

In Europe the ageing of the population is very significant in the majority of the territory (see figure 24 below) in 2012 the ageing of Europe is well advanced. In fact both Germany and Italy are in the ‘super-aged category’. The majority of the European countries are within the ‘Aged Society’, and

1 Global Ageing Index - contains four key domains developed by HelpAge International supported by (supported by international organisations such as the World Bank, the World Health Organisation (WHO), the International Labour Organisation (ILO) and the United Nations Educational, Scientific and Cultural Organisation (UNESCO) (HelpAge International, 2013).

POLAND’S (AGEING) SILVERPRINT | 46

‘Ageing society’ (including Poland), while Azerbaijan is the only country in Europe in 2012 that has population aged over 65 less than 7%.

Figure 24 Ageing, aged and super-aged society in Europe Map 2012

Share of population over 65 Source: OECD calculations derived from EuroStats The ageing process and speed of transition since 1950 and projected to 2050 varies considerable among European countries2 (see figure 25). As illustrated in the graph there are potential six cluster of ageing countries, Early to Current (2000-2010), mid future (2020-2030) and long-term (2040+). As already stated Germany and Italy are already within the ‘Super-Aged society’ since 2000. But it is the speed of transition from ‘aged society’ to ‘super-aged society’ which is more critical for policy design. Poland reached the ‘ageing society’ category in 1970 and is projected to stay within that category for 50 years (to approximately 2020) when the country will then be categorised as an ‘aged society’. However, the transition from ‘aged society’ to ‘super-aged society’ in Poland is projected to only take a decade (approximately 2030), a rapid transition that will likely cause socio-economic

2 To gain insight of the transition speed of ageing, statistics were sourced from the United Nations, Department of Economic and Social Affairs (Population Division, Population Estimates and Projections Section) using the ‘medium variant’ to conduct the statistical analysis. As a result the data varies slightly with the EuroStats.

Super Aged Society (over 20%)

Aged Soceity (Over 14%)

Ageing Society (Over 7%)

Young Society (Less than 7%)

No Data

Poland (see figure 26)


stress for the nation if policy action is not implemented. Other countries that will experience this rapid transition include Turkey, Malta, Netherlands, and Serbia.

Figure 25 Ageing, aged, and super-aged society in Europe

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

AzerbaijanTurkey

AlbaniaArmeniaMoldova

BelarusUkraineCyprus

SlovakiaIcelandIreland

Macedonia, FYRMontenegro

RomaniaLithuania

LuxembourgNorwayPolandSerbia

Bosnia and HerzegovinaCzech Republic

GeorgiaEstonia

HungaryLatviaSpain

SwitzerlandBelgium

DenmarkUnited Kingdom

AustriaMalta

NetherlandsBulgariaFinlandGreeceCroatia

PortugalSlovenia

FranceSweden

ItalyGermany

Year

Young society Ageing society Aged society Super-aged society

Note: share of population 65+ (%)

Note by Turkey: The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus” issue. Note by all the European Union member states of the OECD and the European Union: The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the government of the Republic of Cyprus.


Source: statistics3 derived from United Nations, Department of Economic and Social Affairs (Population Division, Population Estimates and Projections Section), World Population Prospects: The 2012 Revision. For the participating Polish regions, ageing of the population is an important process within the demographic transition of societies, there appears to be a split between the ‘ageing’ and ‘aged societies’ (figure 26). Pomorskie, Kujawsko-Pomorskie, Dolnośląskie, Małopolskie and Podkarpackie are within the ‘ageing’ phase, while Podlaskie, Mazowieckie, Łódzkie, Lubelskie, Opolskie and Śląskie are in the more advanced ‘aged’ society phase and as a result will require more urgent age management policy response depending on the speed of transition.

Figure 26 Ageing, aged and super-aged society in Europe Map 2012

3 http://esa.un.org/unpd/wpp/unpp/panel_population.htm

Pomorskie

Kujawsko-Pomorskie

Mazowieckie

Podlaskie

ŁódzkieLubelskie


Śląskie

Opolskie

Dolnośląskie

RUSSIALITHUANIA

BELARUS

UKRAINE

SLOVAKIA

CZECHREPUBLIC

GERMANY

Aged Soceity (Over 14%)

Ageing Society (Over 7%)

* Warsaw


Share of population over 65 Source: OECD calculations derived from EuroStats

The speed of transition from aged to super-aged societies varies across Poland, figure 27 illustrates three clusters of transition: Less than 10 years, 10 to 15 years, and 15+. Kujawasko-Pomorskie and Dolnośląskie will experience a very quick transition to a super-aged society requiring a urgent policy response, followed by Śląskie, Pomorskie, Podkarpackie, Małopolskie and Opolskie. In fact all the participating regions will be within the super-aged phase in less than two decades, the small transition period leaves little time to formulate and implement age management and socio-economic policy recommendations.

Figure 27 Ageing, aged, and super-aged society in Polish regions

1991 2001 2011 2021 2031

MazowieckieŁódzkie

LubelskiePodlaskieOpolskie

MałopolskiePodkarpackie

PomorskieŚląskiePoland

DolnośląskieKujawsko-Pomorskie

years

Ageing society (Share over 7%) Aged society (Share over 14%)

Super aged society (Share over 20%)

Share of population over 65 Source: OECD calculations derived from EuroStats and Polish CSO


National performance in key domains can optimise the design of regional and local policy actions

National performance in key domains, such as income security; health status; employment and education; and enabling environment, can capture the multidimensional nature of factors impacting labour markets and promote improvements at the local level. The Global AgeWatch index4 uses 13 indicators with an overall index that is calculated as a geometric mean of the four domains (HelpAge International, 2013).

The Index uses the following categories (see Figure below):

Wellbeing:

1. Income security, which refers to the coverage of pension incomes; old age poverty rate: the percentage of people aged over 60 with an income less than half the country’s median income; welfare of older people: the average income/consumption of people aged over 60 as a percentage of average income/consumption of the rest of the population; and GDP per capita.

2. Health status, which refers to life expectancy at 60 years-old; healthy life expectancy at 60; and psychological wellbeing: the percentage of people over 50 who feel their life has meaning compared with people aged 35-49 who feel the same.

Enabling attributes and capabilities:

3. Employment and education, which refers to employment of older people: measures the access to the labour market and their ability to supplement pension income with wages and their access to work related networks; and education status of older people specifically with secondary and higher education.

Enabling social environment of society 4. Enabling environment, which refers to social connections: the percentage of people over 50

who have relatives or friends they can count on when in trouble; physical safety: the percentage of people over 50 who feel safe walking alone at night in the city or area where they live; civic freedom: the percentage of people over 50 who are satisfied with the

4 Global age index supported by international organisations such as the World Bank, the World Health Organisation (WHO), the International Labour Organisation (ILO) and the United Nations Educational, Scientific and Cultural Organisation (UNESCO)


freedom of choice in their life; and access to public transport: is the percentage of people over 50 who are satisfied with the local public transportation systems.

Figure 28 Global AgeWatch Index domains and indicators

Source : HelpAge International (2013)

According to HelpAge International (2013) a number of low-income countries have shown that limited national resources do not have to be a barrier for providing for their older citizens. For example, non-contributory basic pensions as part of social welfare programmes, or free or subsidized healthcare for older people. Importantly, a key message is that is never too soon to prepare as countries are at different points on the ageing trajectory. Those that have significant populations of young people can potentially benefit from a ‘demographic dividend’, as they have large numbers of people of prime working age. According to a recent OECD (2013b) report, pension reforms have focused on later retirement ages, which will be at least 67 years by 2050 in most OECD countries, and increase private pension arrangements. As a consequence of these reforms are lower pension promise for workers who enter the labour market, thus working longer may assist to make up part of the reduction, another potential contribution is the benefits of homeownership and the possible sale, rent or reverse mortgage schemes. However, the report highlights the advantage of public services as ‘retirement-income enhancers’, such as healthcare and long-term care services which will “… play an increasingly important role in preventing old-age poverty among people requiring health and long-term care services” (OECD, 2013b: 15).

The index results of selected countries (Figure 28) shows how the northern countries of Sweden, Norway, and Germany are better placed with age management than Poland and Korea scoring significantly higher values overall. These higher values are the result of these countries being well

Global AgeWatch Index

Domains

1. Income security 2. Health status 3. Employment and education 4. Enabling environment

Indicators

1.1 Pension income coverage

1.2 Poverty rate in old age

1.3 Relative welfare of older people

1.4 GDP per capita

2.1 Life expectancy at 60

2.2 Healthy life expectancy at 60

2.3 Psychological wellbeing

3.1 Employment of older people

3.2 Educational status of older people

4.1 Social connections

4.2 Physical safety

4.3 Civic freedom

4.4 Access to public transport

Direct "outcome" indicators of older people's wellbeingProxy of enabling attributes/ capabilities of older people

Enabling social environment of society


advanced in the four domains (Income security, Health status, Employment and education and enabling environment) and therefore show the importance of policy progress in all dimension of age management. Poland was ranked 62 over 91 countries, chiefly due to the performance in the ‘employment’ domain as only 34% of the population aged 55-64 was employed and 60.7% of the population aged over 60 had a secondary or higher education (see Figures 30) compared with the developed countries of Sweden, Norway, Germany and USA (figure 31). However the low participation rate for the 55+ could be the result of high pension income and low poverty level. This contrast with Korea whereby they have high participation of older people in the labour market due to low pension income and high poverty levels after retirement (Lee, 2013). Nevertheless Poland compared well in income security due to the high pension coverage of 98.1% (people over 65 receiving a pension) and low old age poverty rate of 9.7% (people aged above 60 with an income of less than half the country’s median income).


Figure 29 Global AgeWatch Index results of selected countries

0 10 20 30 40 50 60 70 80 90 100

Korea

Poland

China

OECD Ave

Japan

USA

Germany

Norway

Sweden

Value

Enabling Environment Income Security Employment and Education

Health Status Overall rank and value

Source: http://www.helpage.org/global-agewatch/data/

Poland’s ‘silverprint’ (figure 29) illustrates the ageing management focal indicators that are well advanced such as pension coverage, old-age poverty rate, welfare, and social connections. The indicators that require urgent policy consideration: ageing transition, health life, employment and transport. Continued policy attention is required for relative psychological/mental wellbeing, educational attainment, physical safety and civic freedom. Combining these domains with the fact that youth population is declining significantly, as highlighted in the dashboard results, which will impact the social-economic stability of the labour force and economic benefits and services to the older generations requires a greater policy attention to make sure that pension coverage and old age poverty rates do not increase. The key to ensure older generation’s socio-economic sustainability is increasing the employment and educational and skills of older workforce (55-64) to


encourage longer working and productive life. Figure 30 compares the employment and educational attainment of older persons (55-64) in Poland with other selected countries, which highlights how Poland’s employment of older persons is significant below the northern countries of Sweden, Norway and Germany and educational attainment is also lagging. Compared to the OECD average, Poland is significantly behind in secondary or tertiary education attainment by persons aged over 60, however very comparable with the employment.

Figure 30 Poland’s Ageing Silverprint

0102030405060708090

100Aged 65+ (%) (2010)

Aged to super-aged society(years)

Pension coverage (%)

Old age poverty rate (%)

Relative welfare (%)

Life expectancy at 60 (years)

Healthy life expectancy at 60 (years)

Relative psychological / mental wellbeing (%)

Employment of older people (%)

Educational attainment (%)

Social connections (%)

Physical safety (%)

Civic freedom (%)

Access to public transport (%)

Poland's Silverprint

Source: data based in http://www.helpage.org/global-agewatch/data/, plus OECD calculations based on Eurostats


Figure 31 Employment (55-65) and educational attainment (60+)

0

10

20

30

40

50

60

70

80

90

100

Korea Poland China Japan USA Germany Norway Sweden OECD ave

%

Employment of older people Educational attainment

Source: http://www.helpage.org/global-agewatch/data/

Summarising the main issues and areas of policy response for Poland from the analysis of the dashboard and the ‘silverprint’ include:

• Poor population growth, low fertility and youth decline family friendly environment • Population ageing Age friendly environments, especially concerning wellbeing, safety,

health care, civic freedom and transport • Ageing workforce Workplace age management focusing on continuation of employment • Skills upgrading and education Innovative approaches to education and creating a

lifelong learning culture

Table 2 outlines the policy domains and response in relation the regional clusters, whereby urgent response was identified based on the dashboard indicator results of darker red shading (bad) combined with poor trend performances; sustain responses was identified based on a lighter red shading to yellow (fair to average performances) with positive trend results. As a consequence of the fast transition of aged to super aged societies in the majority of the regions age-friendly and workplace management becomes an essential policy focus area for all regions.


Table 2 Regional policy domains and response required

Cluster Region Family friendly policies

Planning age-friendly

environments

Workplace age management

Innovative approaches

to education

Lifelong learning

Central corridor

Kujawsko-Pomorskie

Urgent Urgent Urgent Urgent Urgent

Łódzkie Urgent Urgent Urgent Sustained Urgent Opolskie Urgent Urgent Urgent Sustained Sustained Śląskie Urgent Urgent Urgent Sustained Sustained

Eastern corridor

Podlaskie Urgent Urgent Sustained Sustained Urgent Lubelskie Urgent Urgent Urgent Sustained Sustained Podkarpackie Urgent Sustained Sustained Sustained Urgent

Stronger Axis

Mazowieckie Sustained Urgent Urgent Sustained Sustained Pomorskie Sustained Sustained Urgent Sustained Sustained Małopolskie Urgent Sustained Sustained Sustained Sustained Dolnośląskie Urgent Urgent Urgent Sustained Urgent

The following section will discuss the key policy domains in detail and provide examples of good practice.

http://www.paiz.gov.pl/polish_regions/voivodships/dolnoslaskie

Policies and Strategies for Regional Demographic Transit ion | 57

Policies and Strategies for Regional Demographic Transition

As stated in the previous section, there are five key policy domains which will be further discussed:

• Low population growth and fertility rates require programmes to promote family-friend regions

• Ageing societies requires critical planning for age-friendly environments • Workplace Age Management strategies can assure resilient ageing labour markets and

economic sustainability • Declining student enrolments and regional variation in tertiary education attainment require

innovative approaches to education • Stagnation of adults participating in education requires implementation of lifelong learning

programmes to sustain skills and innovation

Low population growth and fertility rates require programmes to promote family-friendly regions

Cluster Region Family friendly policies

Central corridor Kujawsko-Pomorskie Urgent Łódzkie Urgent Opolskie Urgent Śląskie Urgent

Eastern corridor Podlaskie Urgent Lubelskie Urgent Podkarpackie Urgent

Stronger Axis Mazowieckie Sustained Pomorskie Sustained Małopolskie Urgent Dolnośląskie Urgent

The dashboard revealed that all the regions are experiencing very low population growth as a result of low rates of natural increase and fertility rates below replacement levels (figures 31 to 33). As a consequence the proportion of youth (0-14) are declining in all regions (Figure 34), this decline has potential significant impacts on the population of structure and more importantly the working age population and sustainability of economic activities within the regions. Currently the youth dependency ratio are declining in all regions (figure 35), thereby freeing up resources to implement support structures and programmes to development family-friendly regions to increase fertility rates. As outline in the recent OECD (2013) report each region should have a long-term family policy that outlines the provisions to support parenting decisions. Developing institutional support structures such as financial assistance, social infrastructure and flexible forms of employment and workplaces



are options for promoting family building, values, monitoring family situations and recognising family problems. Thévenon (2011) identified six main aims family-support policies that can be considered:

1. Poverty reduction and income maintenance 2. Direct compensation for economic cost of children 3. Foster employment 4. Improve gender equality 5. Support for early childhood development 6. Raise birth rates

Figure 32 Population growth rates (2000 & 2010) (%)

-3.0-2.0-1.00.01.02.0

Population Growth Rates

2000 2010

Source: cal Eurostats

Figure 33 Rates of natural increase (2000 & 2010) (per ,000 people)

-4.0-2.00.02.04.0

Rates of natural increase

2000 2010

Source: cal Eurostats


Figure 34 Fertility rates (2000 & 2010)

0.00.51.01.52.0

Fertility Rates

2000 2010

Source: Eurostats

Figure 35 Youth population (2000 & 2010) (%)

0.05.0

10.015.020.025.0

Youth population (0-14)

2000 2010

Source: Eurostats

Figure 36 Youth dependency ratio (2000 & 2010) (%)

0.010.020.030.040.050.060.0

Youth dependency ratio

2000 2010

Source: Cal OECDStats, EuroStats and Netherlands Stats


Successful family policies require a national long-term policy at the same time that regions are supported by area initiatives that take into consideration the diversity of the family unit within rural/urban environments and allow flexibility for intraregional differences. As an example, Box 1 outlines family policy success factors within Demark and Sweden.

Box 1 Family policies initiatives

1. A culture of society supporting working parents – flexible working hours, parental leave entitlements, family benefits, childcare and family support services. Eligibility for social assistance should require participation in education, training or work experience placement in preparation for work. 2. Clear vision and goals at national level – give direction to local policy implementation and a clear context for local provision 3. Local implementation – Family policies are largely implemented by municipalities , which gives more scope for developing services that are locally responsive and allows more local control. 4. Guaranteed access to childcare – Demark has subsidised childcare guaranteed by municipalities for all children aged 6 months to 6 years. National legislative focus should be focused on promoting child development within an agreed curriculum, thereby creating greater coherence between day care facilities, school and after-school provision. Municipalities in Sweden have an obligation to provide pre-school activities for children whose parents work or study and an obligation to provide a minimum of 15 hours a week pre-school activity to children of unemployed persons or persons on parental leave. Fees are proportionate to parents’ income and to the number of children in a family. 5. Universal family support services – Sweden has a network of locally based family centres that provide maternal health care, child health care, open pre-school facilitates for parents and children and preventive social counselling. Different professional groups – midwives, paediatric nurses, paediatricians, pre-school teachers, social workers, psychologists - work together to promote good heath for children and parents, a strong social network around families and an “equal parenthood” between mothers and fathers. 6. Investment in parenting – Both countries have implemented parental leave schemes to allow parents to spend time with their children – 16 months collectively for Swedish parents and 52 weeks collectively for Danish parents. In Sweden there is a commitment to support parent before the birth of a child and during the time when parents are on parental level with all maternity and childcare centres offing parent training groups. Source :Eurochild (2010) http://www.eurochild.org/fileadmin/Events/2010/04_Study_Visit/FPS%20Study%20Visit%202010_ REPORT1%262.pdf

http://www.eurochild.org/fileadmin/Events/2010/04_Study_Visit/FPS%20Study%20Visit%202010_%20REPORT1%262.pdf



Ageing societies require critical planning for age-friendly environments

Cluster Region Planning age-friendly environments


Eastern corridor Podlaskie Urgent Lubelskie Urgent Podkarpackie Sustained

Stronger Axis Mazowieckie Urgent Pomorskie Sustained Małopolskie Sustained Dolnośląskie Urgent

The benefit of a healthier society is the increasing life expectancy whereby the Polish regions are all experiencing, but longevity has a fundamental impact on an ageing society. All regions are experiencing ageing of their population (see figure 36), although the ageing is not at the degree of the EU27 average, but the issue is how quickly the regions are progressing to a super-aged society which would require a more urgent policy focus.

Figure 37 Population 65 + (2000 & 2010)

0.02.04.06.08.0

10.012.014.016.018.0

Population 65+ years

2000 2010

Source: Eurostats



Figure 27 illustrated the variations in the ageing transitions for the participating regions of Poland. The regions in 2012 are either within the Ageing Society5 or the more advanced Aged Society5, such as Łódzkie, Mazowieckie, Śląskie, Lubelskie, Podlaskie and Opolskie. The projected transition from ‘aged society’ to ‘super aged society’ varies between approximately 19 and 17 years (Mazowieckie, Łódzkie and Lubelskie respectively) to 8 years (Dolnośląskieand Kujawsko-Pomorskie), less than two decades for all participating regions. This gives little time to adjust socio-economic impacts of ageing and therefore urgent policy response is needed to adjust this changing population structure.

Regional authorities shall consider how ‘age-friendly’ their urban and rural environments, whereby the physical and social environments enable people to remain healthy, independent and autonomous long into their old age. Older persons play a crucial role in their communities – they engage in paid or volunteer work, transmit experience and knowledge, and help their families with caring responsibilities. Older people can only make these contributions if they enjoy good health and if societies address their needs (Schlappa and Neil, 2013, 37). As a result local institutions and particularly town planning departments need to begin addressing issues with transport, infrastructure, pollution, housing, public spaces and services to adjust to the needs of the elderly population. Increase services in health and disease prevention, early investment in healthy lifestyles and active communities, which incorporate new approaches to the development of infrastructure and the provision of services, are designed to reduce medical costs in later life. Such investments include: community-based agencies for health and social support; facilitating non-profit/voluntary efforts; and fostering local resource sharing. The importance of continued resources and support to the white sector is of utmost importance considering the ageing of the population. Developing health clusters would assist by creating a network and pooling resources for the benefit of the community. As an example, Box 2 outlines a Scottish initiative in elderly care.

Box 2 Reshaping Care in Scotland

The Reshaping Care for Older People is a Scottish Government initiative aimed at improving services for older people by shifting focus towards anticipatory care and prevention. The ‘Reshaping Care for Older People: A Programme for Change 2011-2021’ outlines the following key themes:

• Partnerships in a community business model to keep people out of the formal care system. • Helping people remain at home using telecare and home adaptation, supporting healthy ageing

through diet, exercise and fall prevention. • Creating effective care pathways including anticipatory care plans, managed care networks, re-

enablement, and implementation of dementia strategy.

Sources : COSLA, Scottish Government and NHS Scotland (2010) http://www.scotland.gov.uk/Resource/0039/00398295.pdf

5 Where the share of the population aged over 65 - Ageing society: greater 7% and less than. Aged society: greater than 14% and less than 20%. Super-aged society greater than 20%


http://www.scotland.gov.uk/Resource/0039/00398295.pdf


Workplace Age Management strategies can assure resilient ageing labour markets and economic sustainability

Cluster Region Workplace age management


Eastern corridor Podlaskie Sustained Lubelskie Urgent Podkarpackie Sustained

Stronger Axis Mazowieckie Urgent Pomorskie Urgent Małopolskie Sustained Dolnośląskie Urgent

The ageing society does not only impact the infrastructure and services of local and regional areas, but also the sustainability and stability of economic activities. In 2010 the majority of the regions were experiencing increasing employment rates (see figure 37) with the exception of Małopolskie, Lubelskie, which provides a small period of opportunity for regional workforce ageing policy action.

Figure 38 Employment rate (15-64) (2000 & 2010)

0.020.040.060.080.0

Employment rate (15-64)

2000 2010

Source: Eurostats Polish regions’ elderly dependency ratio is increasing thereby creating a potential dependency burden on workers to support social security and public health systems. As stated earlier, the transition from an aged society to a super-aged society in less than a decade for some regions and a maximum of two decades for others, a focal indicator in this case is the proportion of the population aged between 55-64 (older working age), essentially those who are coming up to retirement. All the participating regions have an increasing older working age, some regions experiencing higher



proportions than others (see figure 38), thereby increasing the pressure economic activities within regions and future retirements.

Figure 39 Population aged 55-64 (2000 & 2010)

0.02.04.06.08.0

10.012.014.016.0

Population 55-64 years

2000 2010

Source: Eurostats

In 2010 Poland’s legislative retirement age was 65 for men and 60 for women, during that year the average age of people becoming retired was notably lower for men and slightly lower for women within all regions (figure 39). Importantly there is a gender gap between the average age of people becoming retired, in the majority of the regions, men retire later, than women, Małopolskie’s gap is very small (0.6) while Mazowieckie is 4 year. Of note is that Śląskie has an opposite trend occurring whereby women are retiring later than men (3.8 years) (Figure 39).


Figure 40 Average age of people becoming retired and office rates (2010)

50.052.054.056.058.060.062.064.066.0

Average age of people becoming retired Men

Women Offical rate Male

Offical rate Female

Source: Polish CSO

Starting in 2013 Poland has implemented a phased increased in official retirement age to 67, by 2020 for men and 2040 for women, although it is a step in the right direction, it still does not stop premature retirement due to either health, care related, financial, job lost, job related problems or preference to stop working. A key policy response is to implement programmes to foster a new work continuum, ranging from full-time to part-time within employment options for companies, governments and other sectors to extend the length, variety of and engagement in working-life; leading to longer employment and increased productivity for people across all sectors. This will extend the working age while allowing people to meet the requirements of family and community and will in turn improve personal, family and community health. Inter-generational engagement in changing working conditions needs to also be taken into account.

Another reason that older workers leave the workplace is the increasing competition from younger and better educated persons; the widespread use of technology; and unsupportive work cultures and behaviours. Encouraging companies to implement age management practices, such as flexible working hours; opportunities for older workers to update their skills and better health and/or safety programmes would encourage older workers to stay within the working environment. Governments and companies can play a role in facilitating work after retirement as show in the examples provided in Box 3 and 4. Promoting a new work continuum would also provide opportunities for the younger generations to interact and learn from their older co-workers/mentors.


Box 3 Facilitating work after retirement

Governments can play a role here by shaping labour markets, developing equal opportunity and social protection policies as well as tax and benefit systems. For example, in Sweden, employers are exempt from payroll taxes for all employees over the age of 65. A pilot scheme in Italy offered workers who were about to retire the possibility to postpone retirement by three years, and add employer and employee social security contributions to their income.

Companies can also play a role, with measures aimed at attracting and retaining pensioners. Examples include the Ship Design and Research Centre in Poland, where 7% of its employees are retirees. Most of these people work in areas in which they have expertise that the company does not want to lose. As pensions in Poland can be low in comparison to the increasing cost of living, work has become a necessity for many, even for the relatively well-off. A recent national law, however, requires pensioners to resign and re-apply for their jobs to continue receiving a pension in addition to their working income. For some this might mean the end of their employment.

Some companies also specifically recruit older workers. One example is Seniorjobbarna in Sweden, which conducts agency work in areas such as crafts, cleaning and gardening. Another is the Austrian Senior Expert Pool, which provides consultancy services, mainly in management or in highly specialised technical areas. In both cases, the option of working part-time and with flexible working hours was considered crucial in attracting and retaining retirees.

Source : European Foundation for the Improvement of Living and Working Conditions (2011)

Box 4 Senior enterprise examples

The Senior Enterprise project6 aims to raise awareness about how the over 50s can engage with enterprise and the benefits that can flow from that engagement. This could be through starting a business, alone or with others; acquiring or investing in a business; advising an entrepreneur; or supporting innovation within a business owned by another.

The four-year project (2010-14) is a response to the challenge of ageing populations in Europe. The change in demographics is viewed in an almost entirely negative light by many people, but the promoters of Senior Enterprise believe that the over 50 age group is a source of untapped potential that could be used to drive forward Europe's national economies.

It is intended that, as a result of Senior Enterprise, more businesses will have been started, more investment will have been made and more senior citizens will be active as advisors in new and developing businesses. The project is being implemented by partners in Ireland, the UK and France, and nine observers across north-western Europe.

PATRON Project7

This Grundtvig project identifies and tests ways to transfer skills that senior managers and entrepreneurs have developed in their working lives which have helped them to develop their creativity, competitiveness, management and entrepreneurial capacities. Young entrepreneurs and managers benefit from this skills transfer in the participating countries and regions. The methods and results are disseminated through the project’s website, so these can be used in other participating regions.

For details: http://www.patronproject.org.

6 http://europa.eu/ey2012/ey2012main.jsp?catId=975&langId=en&mode=initDetail&initiativeId =785&initLangId=en 7 http://www.age-platform.eu/en/age-policy-work/solidarity-between-generations/best-practices/985-

employment

http://www.seniorenterprise.ie/who-is-involved/

http://www.patronproject.org/

http://europa.eu/ey2012/ey2012main.jsp?catId=975&langId=en&mode=initDetail&initiativeId%20=785&initLangId=en

http://europa.eu/ey2012/ey2012main.jsp?catId=975&langId=en&mode=initDetail&initiativeId%20=785&initLangId=en

http://www.age-platform.eu/en/age-policy-work/solidarity-between-generations/best-practices/985-%09employment

http://www.age-platform.eu/en/age-policy-work/solidarity-between-generations/best-practices/985-%09employment


As noted earlier there appears to a gender gap relating to retirement age whereby women retire earlier than men. As noted by OECD (2012) ageing population and low fertility rates, many countries will experience a shrinking labour force over the next 20 years, the report states that Poland along with Czech Republic, Germany and Japan (assuming a constant male and female participation rate) would experience severe decline in labour force participation rates. However, according the OECD (2012) using the convergence scenario whereby male participation remain constant (2010 level) and the gap between male and female labour force participation in halved by 2030, the project increase in labour force will exceed 20% by 2030 with significant effects in Poland along with Brazil, Chile, Chez Republic, Greece, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, Slovak Republic and Spain.” Encouraging women to stay in work longer would assist labour force participation rates in light of an ageing population, this is important due to the fact gender equality in the labour force participation is the key to sustaining economic growth (OECD, 2012).

Although the dashboard can provide policy directions, it is important for the regions to invest in research into the employment structures within the economic activities which would assist in formulating age management policies specific to regional and local social-economic context.

Declining student enrolments and regional variation in tertiary education attainment require innovative approaches to education

Cluster Region Innovative approaches to education

Central corridor

Kujawsko-Pomorskie Urgent Łódzkie Sustained Opolskie Sustained Śląskie Sustained

Eastern corridor

Podlaskie Sustained Lubelskie Sustained Podkarpackie Sustained

Stronger Axis

Mazowieckie Sustained Pomorskie Sustained Małopolskie Sustained Dolnośląskie Sustained

The dashboard revealed a drop in students enrolled in education (figure 40) as a ratio of population, this could be a consequence of the declining youth proportions in the regions, nevertheless further in depth research is required to ascertain the cause for this decrease. These declining trends enforce the importance of regional family policy in an effort to increase fertility rates in the regions. However resources for a small period of time could then be redirected to other urgent policy areas such age management.




Figure 41 Students enrolled in education (2000 & 2010) (% of population)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Students enrolled in education

2000 2010

Source: Eurostats

A positive trend across Poland is the significant increase in the enrolment of students in tertiary education as ratio total students, reflecting the increasing requirement for higher level of skills within a changing economic environment. However there are fundamental differences between regions in tertiary education attainment in employment and labour force (figure 41), these differences may reflect the varying regional economic activities and the vocational facilitates provided for each region. Again further research is required to ascertain the cause of the differences, and highlight policy appropriate local context policy response. For regions that have limited facilitates and resources for vocational education, programmes such as distance education or open universities provide opportunities (see example in box 5) to students whereby the vocational facilities are not available. Combined with government assistance the benefit of these programmes is that the youth will more likely stay and develop a career within the region, rather than migrating to other region which has the vocational facilities.


Figure 42 Tertiary education attainment per employment and labour force (2000, 2010)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Tertiary education attainment per employment and labour force

2000 labour force 2000 employment 2010 labour force 2010 employment

Source: Eurostats


Box 5 Open Universities Australia

Open Universities Australia (OUA) enables access to a large choice of online tertiary education options and services. Open Universities Australia was formed as the Open Learning Agency of Australia Pty Ltd (OLAA or OLA) in late 1993 as a private company. Originally owned by Monash University, OLA was charged with the goal of identifying, developing and delivering new and innovative learning and tertiary educational opportunities to all Australians. In 2013 Open Universities Australia is owned by seven leading Australian universities and offers programs from 20 leading academic providers across Australia. Potential students have the option to utilise the OUA Pathways which recommends a targeted preparatory courses, a combination of four units, within their preferred field which prepares the student for the full course. Students, also have the option of undergraduate or postgraduate courses in fields such as business, health, law & justice, arts & humanities, education , IT, and Science & engineering. The students have access to financial assistance such as:

• FEE-HELP a Commonwealth Government loan scheme set up to help eligible students defer paying fees for undergraduate and postgraduate units. The 2014 lifetime limit on the FEE-HELP loan is $96,000 (except for medicine, dentistry and veterinary science students where the limit is $120,002). FEE-HELP loans are repaid through the Australian Taxation Office once your income reaches the minimum threshold for compulsory repayment ($51,309 for 2013-14).

• The Australian Government pays the loan amount directly to your course provider on your behalf and a HECS-HELP debt is then recorded with the Tax Office against your Tax File Number. The debt is then to be repaid once your repayment income is above the minimum threshold.

• VET FEE-HELP is a Commonwealth Government loan scheme which assists students to pay for all or part of the TAFE tuition fees when studying RMIT's Diploma of Logistics through Open Universities Australia.

• Students are able to apply for VET FEE-HELP assistance directly with RMIT. If eligible, students may borrow up to the FEE-HELP limit over their lifetime. The combined lifetime limit for FEE-HELP and VET FEE-HELP loan is $93,204 (as at January 2013). The FEE-HELP limit is indexed on 1 January each year.

• The Commonwealth Government applies an additional 20% loan fee to the amount of VET FEE-HELP assistance provided. The loan fee will be included in your VET FEE-HELP debt to be repaid through the Australian taxation system once your repayment income is above the minimum threshold.

Source: http://www.open.edu.au/


Stagnation of adults participating in education requires implementation of lifelong learning programmes to sustain skills and innovation

Cluster Region Lifelong learning Central corridor

Kujawsko-Pomorskie Urgent Łódzkie Urgent Opolskie Sustained Śląskie Sustained

Eastern corridor

Podlaskie Urgent Lubelskie Sustained Podkarpackie Urgent

Stronger Axis

Mazowieckie Sustained Pomorskie Sustained Małopolskie Sustained Dolnośląskie Urgent

As the population ages, authorities will need to boost labour force participation rates, lifelong learning is a key process that would enable the older generations to stay within the labour force. Participation of adults in education is a key aspect in social and economic development and indicator for lifelong learning, an important process as it increases people capacity to work by providing the knowledge, skills and confidence to enter, remain or return to work8.

Within the Polish regions there has had limited improvement in adults participating in education and remains well behind the EU-27 average (figure 42). Mazowieckie has the highest participation rate followed by Pomorskie (in 2010) and therefore are in a better position to implement programmes to further encourage adult education within their regions. Podkarpackie, Łódzkie and Kujawsko-Pomorskie appear to struggling to even increase the adult participation rates in education. It is the investment (of both time and money) in adult education and training that is essential for meeting the changing labour force skill demands, therefore the local communities need to be able to adapt (OECD, 2012). “Lifelong learning has been a defining goal for education and training policies for many years, emphasising the need for organised learning to take place over the whole lifespan and across the different main spheres that make up our lives (“life-wide”)” (OECD, 2012, p.72). Regional authorities need to implement programmes that foster life-long learning, not only focusing on the older population but instil the culture within society by promoting lifelong learning values. Box 6 and 7 provides two innovative examples of lifelong learning

8 http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4102.0Chapter6202008


http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4102.0Chapter6202008


Figure 43 Participation of adults in education (2000 & 2010) (%)

0.01.02.03.04.05.06.07.08.09.0

10.0

Participation of adults in education

2000 2010 EU27 (2000) EU27 (2010)

Source: Eurostats

Box 6 Genial - Generations at the workplace (Austria)

Demographic change will require enterprises to take more social responsibility and to access the resources of older employees to stay in the market, and it will require employees to invest in their abilities, in their competencies, and in their health. The Genial project of the Provincial government supports these needs by assisting employees to develop their work-life balance in order to maintain their health, but also tries to elicit more individual responsibility for life-long learning through to an advanced age, to stay open-minded about new technologies, and to achieve a different attitude towards ageing. Genial is based on three pillars:

• Public relations and awareness raising; • Specific projects realised in companies; • Network building to exchange experiences and develop new measures and instruments to support the

process. The project also enables enterprises to better understand and deal with the human capital they can generate, while enhancing the work experiences of older employees. The portfolio of activities is comprised of specific ageing analyses, work ability indices, specific support for putting concrete activities in place, and more.9 Within the framework of the project, the ‘Qualification Association Genial’10 was founded, offering qualifications in health and work-ability issues, seminars for managers (e.g. on modern, more motivationally oriented leadership), and content-related issues. Currently, the Qualification Association Genial has 7 member companies and delivered 20 measures to approximately 230 people from March to July 2012. Source: Förschner (2012)

9 Genial: http://www.genial.or.at 10 Qualification Associations are instruments of active labour market policy whereby one or more large

companies together with a number of smaller companies within a region engage in common qualification measures for their staff. Often companies within the same field and geographical area have the same needs regarding qualification, but it is too complicated and expensive for single organisations to go alone. Qualifications Associations are supported by the AMS and the ESF, and receive higher funding if they offer measures for older workers.


Box 7 Intelligent personnel management for logistics (IPL)

The pilot project IPL, funded by the Ministry of Labour, Social Integration and Welfare in North Rhine-Westphalia and the European Social Fund, focuses on improving human resource management. Approaches to implementing life-long learning as a component of demographically sensitive human resources work were generated from the results of the IPL project:

• Promoting vocational education and training • Additional training for people with immigrant backgrounds • Part-time training • Dual higher education study programmes in logistics. • Further qualification of older workers in warehouse management and professional driving • Mixed-aged teams – designed to retain the knowledge and experience of older workers within

companies, to foster intergenerational learning, and to prevent the development of age-specific stigmas among employees

• On-the-job training • Job rotation schemes and mixed work • Employee discussions on specific topics.

Source: CEDEFOP (2012)

IN CON CLU SIO N | 74

In conclusion – Speed of demographic transition requires priority and sustained policy action

As indicated in the OECD studies of demographic transition (2013), overall, response to demographic change need a strategic co-ordinated policy that manages sustainable economic development not only on a regional basis, but also within the local context. The analysis discussed in this report shows the relationship between the demographic and economic themes in the dashboard and the domains in the global index.

The demographic change dashboard revealed that since 2000 Polish regions all experienced notable performance improvements. The results also highlighted three different performing regional clusters which can need different strategic approaches:

• Central corridor (Kujawsko-Pomorskie, Łódzkie, Opolskie and Śląskie) average performing regions in 2010 however indicating good improvement trends, nevertheless are the weakest regions in Poland.

• Eastern corridor (Podlaskie, Lubelskie and Podkarpackie) average performing regions in 2010 along with bad performance trends, these regions all border with external countries.

• Scattered stronger axis (Mazowieckie, Pomorskie, Małopolskie and Dolnośląskie) with fair to good performances in 2010 and associated positive trends from 2000-10 (except Małopolskie).

All regions should continue efforts on encouraging population growth, increase fertility rates, supporting youth integration in labour markets, age management, and resources in skills and education which provides the backbone to a strong economy. Five strategic policy areas were highlighted in which regions should concentrate their initiatives (urgent or sustained) (Table 3):

Table 3 Policy domains and response

Policy domain Response Priority action Sustained action

Programmes to promote family friendly regions

Implement family –friendly support structures such as financial assistance, social infrastructure and employment flexibility. These structures should take into consideration the diversity of the family unit, regional and local context within rural/urban environments and allow flexibility changes in the family home.

Kujawsko-Pomorskie Łódzkie Opolskie Śląskie Lubelskie Podlaskie Podkarpackie Małopolskie Dolnośląskie

Mazowieckie Pomorskie



Critical planning for age-friendly environments

Consider in policy formulation how ‘age-friendly’ their urban and rural environment, whereby the physical and social environment enable people to remain healthy, independent and autonomous long into their old age. Addressing issues with transport, infrastructure, pollution, housing, public spaces and services to adjust to the needs of the elderly population. Increase services in health and disease prevention, early investment in healthy lifestyles and active communities, which incorporate new approaches to the development of infrastructure and the provision of services, are designed to reduce medical costs in later life

Kujawsko-Pomorskie Łódzkie Opolskie Śląskie Lubelskie Podlaskie Mazowieckie Dolnośląskie

Podkarpackie Pomorskie Małopolskie

Initiatives to stimulate workforce age management

Foster a new work continuum, ranging from full-time to part-time within employment options for companies, governments and other sectors to extend the length, variety of and engagement in working-life; leading to longer employment and increased productivity for people across all sectors. Encouraging companies to implement age management practices, such as flexible working hours; opportunities for older workers to update their skills and better health and/or safety programmes

Kujawsko-Pomorskie Łódzkie Opolskie Śląskie Lubelskie Mazowieckie Pomorskie Dolnośląskie

Podlaskie Małopolskie


would encourage older workers to stay within the


working environment. Research investment into the effects of ageing on employment structures within the economic activities which would assist in formulating age management policies specific to regional and local social-economic context.

Innovative programmes to support education

Implement and promote innovate programmes such as distance education and open universities to provide opportunities to students to continue their education where vocational facilities are not available. Investment in research to ascertain the cause regional variation in tertiary education attainment to ascertain appropriate policy response appropriate to the regional and local context.

Kujawsko-Pomorskie Łódzkie Opolskie Śląskie Lubelskie Podlaskie Podkarpackie Małopolskie Mazowieckie Pomorskie Dolnośląskie

Encourage a culture of lifelong learning

Develop programmes to foster lifelong learning focusing on increasing the skill level of young and older workers and instil the culture within society of lifelong learning values. Firm initiatives and employee incentives are required to initiate interest in skills and training development.

Kujawsko-Pomorskie Łódzkie Podlaskie Podkarpackie Dolnośląskie

Opolskie Śląskie Lubelskie Małopolskie Mazowieckie Pomorskie

REFERE NCE S | 77

References

Cedefop (2012) Working and ageing: The benefits of investing in an ageing workforce, Publications Office of the European Union, Luxembourg.

COSLA, Scottish Government and NHS Scotland (2010), Reshaping care for older people: A programme for change 2011-2021, http://www.scotland.gov.uk/Resource/0039/00398295.pdf

EuroChild (2010)Family policies that work best for children: Fighting child poverty and promoting child well-being, The Family and Parenting support thematic working groups study visit to Sweden and Denmark, 26-30 April 2010, Report Parts I & II, http://www.eurochild.org/fileadmin/Events/2010/04_Study_Visit/FPS%20Study%20Visit%202010_ REPORT1%262.pdf

European Foundation for the Improvement of Living and Working Conditions (2011) Living longer, working better – Work after retirement, http://www.eurofound.europa.eu/pubdocs/2011/663/en/1/EF11663EN.pdf

Förschner, M., Partnership strategies for demographic change and ageing: Lessons learnt from a Study Visit to the Province of Carinthia, Austria, in October 2012, OECD/LEED.

HelpAge International (2013), Global AgeWatch Index 2013: Insight report, HelpAge International, London.

OECD (2013a) Demographic Transition and an Ageing Society: Implications for local labour markets in Poland. OECD publishing, Paris

OECD (2013b) Pensions at a Glance 2013: Retirement-Income System in OECD and G20 Countries, OECD publishing, Paris.

OECD (2012), Closing the Gender Gap: Act Now, OECD Publishing, Paris.

Thévenon, O. (2011), Family Policies in OECD Countries: A Comparative Analysis, Population and Development Review, 37: 57–87.

Schlappa, H., and Neil, W.J.V. (2013), ‘From crisis to choice: Re-imagining the future in shrinking cities’, Cities of Tomorrow - Action Today URBACT II Capitalisation, URBACT, Saint-Denis.

Lee, S-H (2013) “Economic Issues relating to the Aging, Aged, and Super-aged Society in Asian Countries’, Regional Economic Development Strategies in Pre-emptive Response to Aging, Aged and Super Aged Society, November 6, 2013, Korea

http://www.scotland.gov.uk/Resource/0039/00398295.pdf



A N N E X | 78

Annex Appendix 1 – Notes for Dashboard

PopGR, PopYR, PopWR, PopER – Source: calculated from Eurostats, and OECDstats

PopYR and PopER – OECD 2010 Estimated value

PopOWR – OECD 2000 (is 2008) value calculated from OECDstats

LifeE, and LifeEM – EU-27 2000 (is 2002) and 2010 (is 2009) for Less than 1 year, Poland (2000 & 2010) life expectancy at birth.

LifeEF – EU-27 2000 (is 2002) and 2010 (is 2009) for Less than 1 year, Poland (2000 & 2010) life expectancy at birth. OECD 2000 and 2010 (ave. of 31 countries excluding Israel)

Cbrate – EU-27 average for the 27 countries excluding Ireland, however it seems it was included in the UK stats. OECD missing data

Cdrate – EU-27 average for the 27 countries excluding Ireland, however it seems it was included in the UK stats. OECD missing data

Fert – EU-27 2000 (is 2002); Eu-27 2010 (is 2009); OECD average

InMort – OECD average, for 2010 (is 2009)

PrIn – EU-27 and OECD missing data

GDPcap – OECD missing data

YDR and EDR– OECD cal from OECDstats. Excludes Turkey.

EcDR – EU-27 and OECD missing data

UEmpOR - Due to methodological limitations (small number of respondents aged 55-64 in each regions, which are classified as unemployed) we recommend to be cautious in drawing conclusions from all of these data.

StenED and STenTED – Regional data 2000 (is 2001) and 2010 (is 2008). OECD ave for 32 countries, not including Slovenia (missing data)

TerEdAtEm – OECD missing data

TerEdLF – EU-27 missing data; OECD 2000 ave. Australia, Italy - 2001 data, No data from: Canada, Chile, Estonia, Ireland, Israel, Japan, Slovenia and Turkey (2000). OECD 2010 ave – 2008, Australia – 2005, Iceland, Korea, NZ, US – 2006, Switzerland – 2007 No data from Canada, Chile, Estonia, Ireland, Israel, Japan, Slovenia and Turkey. Regional data 2010 (is 2008)

PaAdEd, PaAdEdM and PaAdEdF – EU-27 estimated. OECD missing data. Regional data 2000 (is 2001 low reliability).

A N N E X | 79

Note on Contributors

Dr. Cristina Martinez-Fernandez is a Senior Policy Analyst on Employment and Skills, Green Growth and South-East Asia at the Organisation for Economic Co-operation and Development (OECD), Local Economic and Employment Development (LEED) programme. She works on issues related to the challenges of skills and training systems for SMEs, entrepreneurial and innovation activities; industrial policy, climate change and the transformation of labour markets into the low-carbon economy; the challenges of demographic change and an ageing society for skills and employment development. Cristina also manages the OECD/LEED Initiative on Employment and Skills Strategies in Southeast Asia (ESSSA). Before joining the OECD she was an Associate Professor at the Urban Research Centre, University of Western Sydney in Australia where she led the Urban and Regional Dynamics Programme which analyses industry change, urban performance and socio-economic development within the frameworks of innovation, globalisation and the knowledge economy.

Dr. Tamara Weyman works as a contracted expert for the OECD, working on various projects involving employment and skills, SMEs development, South-East Asia, territorial development policy, and demographic change and sustainability. Recently Tamara has been involved in publications such as ‘Martinez-Fernandez, C.; I.Miles; T.Weyman (2012) The Knowledge Economy at Work: Skills and Innovation in Knowledge Intensive Services Activities, Edward Elgar; Martinez-Fernandez, C.; P.Chorazy; T.Weyman; and M.Gawron. (2011), The Territorial Dimension of the European Social Fund: A Local Approach for Local Jobs, OECD; OECD (2012) Skills development and Training in SMEs, OECD publishing OECDpublishing; Martinez-Fernandez, C.; N.Kubo; A.Noya; and T.Weyman (2012), Demographic Change and Local Development: Shrinkage, Regeneration and Social Dynamics, OECD; and a chapter in a forthcoming book Schatz, L.; D.Leadbeater; C.Martinez-Fernandez; and T.Weyman (2013), ‘From “up north” to “down under”: Dynamics of shrinkage in mining communities in Canada and Australia’ in Stories of Tough Times: International perspectives and policy implication in shrinking cities, Routledge. Tamara worked as a Research Associate at the Urban Research Centre, University of Western Sydney (UWS) and completed her PhD on Spatial Information Sharing for Better Regional Decision Making in 2007 at UWS. Since 2009, Tamara has been involved in the COST Action TU 0803 “Cities Regrowing Smaller”.

Prioritising Actions for Demographic Transitions and Ageing in selected regions of Poland

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