transition from work to retirement

Transition from work to retirement

Evaluation of the 2012 labour force survey ad hoc module

Transition from work to retirement. Evaluation of the 2012 module

Preface

This report evaluates the 2012 labour force survey (LFS) ad hoc module (AHM), which examined the

transition from work to retirement. The main objective of the report is to assess the way in which the

module was conducted, by providing information on the quality of the data set and presenting preliminary

results. Recommendations relating to a possible repeat of the module as part of a future survey are also

included.

The EU LFS is a large-sample survey of private households, which provides detailed quarterly and annual

data on employment, unemployment and economic inactivity. The LFS was established by Council

Regulation (EC) No 577/98 of 9 March 1998 on the organisation of a labour force sample survey in the

European Union. This Regulation and its amendments set out provisions for the design, characteristics

and decision-making process of the survey. The transition from work to retirement was the subject of the

2006 LFS ad hoc module, and the same topic was chosen again for 2012 (Regulation No 365/20081). The

2012 proposal was prepared in the light of lessons learnt during the course of the 2006 LFS ad hoc

module and, where possible, appropriate changes were made. The involvement of a large number of

labour market specialists from national statistical offices, Eurostat and other Commission Directorate-

Generals also played an important role in the planning of the 2012 module. The national statistical offices

all contributed to a documentation exercise, for which each of them drafted a mapping between the

possible responses for the PENSTYPE variable (the type of pension the person is currently receiving) and

their national pension system. The evaluation of the 2006 module and the documentation produced in

preparing the 2012 module are publicly available.2 Both are designed to make it easier for researchers and

the public to understand and use AHM data. Administrative differences between the pension systems in

different countries are highlighted, and the areas in which, as a result, comparison between countries is

not possible, are made clear.

The first chapter of this document gives general information on AHM 2012. Subsequent chapters then

provide a detailed description of each variable, together with information as to the comparability of this

variable both across countries and between 2006 and 2012, and other information on data collection. The

annexes to the document include country abbreviations, the list of tables proposed for online publication

and the text of Regulation No 365/2008 with the list of variables.

This document is based on data sent to Eurostat before the end of 2013. Although minor revisions of the

data set may have happened after this date, the data was considered stable enough for analysis and

interpretation. The quality reports provided by participating countries were particularly useful in helping

Eurostat to interpret certain values and have also contributed to ideas for a potential repeat of the module.

Colleagues from many national statistical offices provided Eurostat with insight into the national

circumstances, explaining specific results that did not fit patterns seen in other countries. Eurostat would

like to thank all contributors.

This report was prepared by Diana Ivan and Håvard Lien of Eurostat’s unit working on labour market

statistics (F3).

Luxembourg, March 2014

1 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:112:0022:0024:EN:PDF

2 http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey_-_ad_hoc_modules


Table of contents

Preface ......................................................................................................................... 2 Table of contents .......................................................................................................... 3 Chapter 1: General information on the module.............................................................. 5

Executive summary for researchers .......................................................................................... 5 Recommendations relating to a repeat of the module ............................................................... 6 Description of the module .......................................................................................................... 6

Aims of the module and main findings .................................................................................................. 6 Participating countries ........................................................................................................................... 7 Target population .................................................................................................................................. 7 Main findings ......................................................................................................................................... 9 Description of the variables ................................................................................................................... 9 Links with AHM 2006 ............................................................................................................................ 9 Links with the core LFS ....................................................................................................................... 10

General issues relating to data collection ................................................................................ 10 Sample size ........................................................................................................................................ 10 Non-response rates ............................................................................................................................ 11 Other measurement issues ................................................................................................................. 12

Chapter 2: Quality analysis by variable ....................................................................... 14

1. PENSION: Person receives or does not receive a pension ................................................ 14 Short description ................................................................................................................................. 14 Filter conditions and codes ................................................................................................................. 14 Analysis of the questionnaires ............................................................................................................ 14 Analysis of the results ......................................................................................................................... 15 Conclusions and recommendations .................................................................................................... 22

2. PENSTYPE: Type of pension(s) currently received ............................................................ 23 Short description ................................................................................................................................. 23 Filter conditions and codes ................................................................................................................. 23 Analysis of the questionnaires ............................................................................................................ 24 Analysis of the results ......................................................................................................................... 24 Conclusions and recommendations .................................................................................................... 28

3. EARLYRET: Incidence of early retirement .......................................................................... 29 Short description ................................................................................................................................. 29 Filter conditions and codes ................................................................................................................. 30 Analysis of the questionnaires ............................................................................................................ 30 Analysis of the results ......................................................................................................................... 30 Conclusions and recommendations .................................................................................................... 33

4. AGEPENS: Age at which a person first received an old-age pension ................................ 34 Short description ................................................................................................................................. 34 Filter conditions and codes ................................................................................................................. 34 Analysis of the questionnaires ............................................................................................................ 34 Analysis of the results ......................................................................................................................... 34 Conclusions and recommendations .................................................................................................... 42

5. REASNOT: Main reason for not remaining in employment longer ...................................... 42 Short description ................................................................................................................................. 42 Filter conditions and codes ................................................................................................................. 42 Analysis of the questionnaires ............................................................................................................ 43 Analysis of the results ......................................................................................................................... 44 Conclusions and recommendations .................................................................................................... 45

6. WORKLONG: Wish to remain in employment longer .......................................................... 46 Short description ................................................................................................................................. 46 Filter conditions and codes ................................................................................................................. 46 Analysis of the questionnaires ............................................................................................................ 46 Analysis of the results ......................................................................................................................... 47 Conclusions and recommendations .................................................................................................... 48


7. REDUCHRS: Reduced working hours as a step towards full retirement ............................ 48 Short description ................................................................................................................................. 48 Filter conditions and codes ................................................................................................................. 49 Analysis of the questionnaires ............................................................................................................ 49 Analysis of the results ......................................................................................................................... 49 Conclusions and recommendations .................................................................................................... 52

8. STAYWORK: Main reason for remaining in employment .................................................... 52 Short description ................................................................................................................................. 52 Filter conditions and codes ................................................................................................................. 52 Analysis of the questionnaires ............................................................................................................ 52 Analysis of the results ......................................................................................................................... 52 Conclusions and recommendations .................................................................................................... 55

9. PLANSTOP: Plans to stop working in the future ................................................................. 55 Short description ................................................................................................................................. 55 Filter conditions and codes ................................................................................................................. 55 Analysis of the questionnaires ............................................................................................................ 56 Analysis of the results ......................................................................................................................... 56 Conclusions and recommendations .................................................................................................... 57

10. BUILDPEN: Information on pension rights built up to date ............................................... 57 Short description ................................................................................................................................. 57 Filter conditions and codes ................................................................................................................. 57 Analysis of the questionnaires ............................................................................................................ 57 Analysis of the results ......................................................................................................................... 58 Conclusions and recommendations .................................................................................................... 58

11. CONTWORK: Expectations of continuing working or looking for a job after starting to receive an old-age pension ...................................................................................................... 59

Short description ................................................................................................................................. 59 Filter conditions and codes ................................................................................................................. 59 Analysis of the questionnaires ............................................................................................................ 59 Analysis of the results ......................................................................................................................... 59 Conclusions and recommendations .................................................................................................... 61

Annexes...................................................................................................................... 62

Annex 1: Abbreviations ............................................................................................................ 62 Annex 2: Main AHM 2012 tables ............................................................................................. 63 Annex 3: Commission Regulation (EU) No 249/2011 ............................................................. 64


Chapter 1: General information on the module

Executive summary for researchers

The EU LFS sample size is about 1.5 million people and surveys are carried out every quarter. Only

private households are included. The survey is conducted by means of interviews with each individual in

the sample. The interview method varies across countries. In most countries, proxy interviews with

another person in the household are allowed. Interviews are generally conducted in person, at least for the

first wave, but subsequent follow-up interviews can be conducted by phone. Participation in the survey3 is

compulsory in seven EU countries and in two of the participating European Free Trade Association

countries.

The variables on which the LFS collects data will be referred to in this document as core LFS variables,

to distinguish them from the AHM variables. Their list is available as an annex to Regulation 377/20084

on codification and filters. Explanatory notes on each of the variables are also available5. Regulations on

multi-annual programmes of ad hoc modules and Regulations defining the list of variables to be collected

in a specific year provide further legal basis6 for the LFS AHMs.

Commission Regulation (EU) No 249/2011 adopting the specifications of the 2012 ad hoc module

defines the eleven variables on which data was collected in AHM 2012 and describes the target

population of the module and of each variable. A task force was commissioned to define a proposed list

of variables to be collected and to provide explanatory notes to accompany them. A document has been

prepared giving answers to frequently asked questions on the concepts covered by the variables. These

are all publicly available. This document summarises their main elements, and adds further information

on data comparability between countries and between surveys.

The first chapter explains in detail the structure of the target population of AHM 2012. It sets out which

populations are included and which are excluded from the module. Since the module focuses on people

involved in the transition from work to retirement, not all potential respondents aged 50-69 were

interviewed. The main side effect of the choice of target population for this survey is that analysis by

gender is limited, because the labour market participation rate is different for men and women.

The AHM 2012 database does not include a ‘non-applicable’ field (which applies to those not in the

AHM target population) for all countries for which data was collected. For this report, the size of the

‘non-applicable’ category for Germany, France, Austria, Sweden and Switzerland was estimated by

crossing the AHM data with the core LFS data.

Non-response rates by variable and country are also included in the first chapter. Any non-response rate

higher than 15 % will be systematically flagged in this document, as this is the level considered to make

the remaining data for that question and population unreliable. The reader is therefore made aware of the

limits of the data quality for specific countries and/or specific variables of the module.

The second chapter presents each variable in detail, from a data collection perspective as well as with a

view to a possible repeat of the module. At a glance, the quality of each variable can be summarised as

follows:

a good level of comparability: PENSION and AGEPENS;

comparison is possible, but analysis should take into account the specific differences existing at

national level: PENSTYPE, EARLYRET, WORKLONG, REASNOT, REDUCHRS and

STAYWORK; and

3 See table 3 for information on participation at AHM 2012 by country

4 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:114:0057:0084:EN:PDF

5 http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey_-_methodology#LFS_explanatory_notes

6 http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey_%E2%80%93_main_features_and_legal_basis


lowest quality variables whose use should be confined to national analysis (provided response

rates are sufficient): PLANSTOP, BUILDPEN and CONTWORK.

Please note that names of variables will always be given in capital letters. Definitions and code lists of the

variables are available in the subchapters of chapter 2.

With the exception of table 2 on sample size, table 4.1 and related graphs on percentile and mode, all data

is weighted.

Recommendations relating to a repeat of the module

Were a module with the same (or a similar) topic to be run again, a number of recommendations made in

the light of the 2012 experience should be taken into account. These recommendations were formulated

by experts from the national statistical institutes based on their experience of the data collection and

analysis conducted at national level, and by Eurostat based on their experience of analysing the dataset

for all countries.

(1) Consider changing the topic of the module from the transition from work to retirement to an

analysis of the whole population within a certain age group. In general, it is considered difficult

to collect detailed information on a complex phenomenon such as the transition from work to

retirement by means of a small number of questions that assume a linear progression from work

to retirement, because in practice the transition may be longer and atypical. A module focussing

on a transition of any kind will inevitably involve retrospective questions and questions about

future intentions. Experience, including from AHM 2012, has shown that these questions are

most difficult to deal with in an AHM.

(2) Choose simpler filters, both for the module and for each of the variables. Complex filters are

difficult to manage during the preparation of the survey, interviewing, data processing and data

analysis. For example, it would have been easier to collect comparable data across all countries

for an AHM whose only filter was age. Moreover, users would have benefited from a richer

dataset, allowing detailed analysis by gender and by country. A broader filter also reduces the

risk of the target population being too small. The drawback of this approach would be a slight

increase in the response burden but the effect of this could be mitigated throughout the module if

simpler variables were used.

(3) Reconsider the definition of a pension in the context of the module. Due to specific national

legal provisions, it is not always easy to distinguish between pensions and other social benefits

and this can often lead to a situation where similar social schemes are considered as a pension in

one country and as a different kind of benefit in another. The 2012 AHM included a proposal to

supplement the data collection with mappings of the pension systems in each country. This

approach has the advantage of offering greater transparency of data collection. Little can be done

however to improve the comparability at European level of any PENSTYPE data collected for

this module. Moreover, the documentation and updating of administrative information involved

in this exercise placed a considerable burden on participating countries.

Description of the module

Aims of the module and main findings

The aim of this AHM was to analyse:

how people leave the labour market;

why they leave the labour market;

why they do not remain in the labour market longer; and

for how long the active population aged 50 to 69 expects to be in the labour market.

The results were intended to be used to prepare the joint report on social protection and social inclusion,

and in the areas covered by the open method of coordination in the field of pensions and the Europe 2020


Strategy, and in particular for monitoring the guideline on increasing labour market participation.

Participating countries

The module was carried out in all EU countries (27 in 2012), Croatia, Iceland, Norway and Switzerland.

The aggregated EU totals include all 28 current EU Member States (i.e. the 27 Member States as of 2012

and Croatia). Annex 1 gives the country abbreviations used in this report.

Target population

The target population of AHM 2012 is people aged 50-69 either currently working or having worked

beyond age 50. The target population is the same as for the AHM 2006 on the transition from work to

retirement.

The target group excludes people who have not worked beyond age 50 on the basis of their reduced

proximity to the labour market and in order to reduce the volume of responses to be handled. It is

however important to verify whether excluding these respondents had any negative effects on data

analysis.

It was often difficult to identify the exact target population of the module at the point of collecting data.

In particular, some of the countries using paper questionnaires (Bulgaria, Greece and Hungary) reported

significant difficulties in ensuring that respondents respected the conditions imposed by each of the

filters. Many countries (including Malta and Switzerland, and a number of the countries using paper

questionnaires) had difficulties in extracting data on experiences of working beyond age 50 from the core

LFS, and had to collect the relevant information on age, work history and working life beyond age 50

again. In these cases, three extra questions were usually added to the interview as a check. There were

also instances of filters being applied when coding the data, rather than at the point of collecting the data.

This affected the data in the ‘non-answering’ category and in some cases resulted in the data not being

able to be used in the module. As noted in the Austrian report, having additional filters reduced the

number of observations of more narrowly defined variables. Filtering for a very specific target population

makes both understanding and communication of the data more difficult. It also limits the analysis of the

data, by precluding certain breakdowns, including by gender.

The following graph shows the target population of AHM 2012 compared to the total population aged 50-

69, by gender, for EU-28. While at EU level there are more women than men in the 50-69 age group

(52 % of the total population aged 50-69 are women), the target population of AHM 2012 (people aged

50-69, and currently working or having worked beyond age 50) contained more men than women. This is

because over three-quarters of the group that was not part of the survey was female.

Graph 1: Population aged 50-69 by gender, employment status and participation in AHM

2012, EU-28 (number of people, in millions)

Note: ‘not applicable’ values are estimated for Germany, France, Austria and Sweden.

0 5 10 15 20 25 30 35

Men, in employment

Women, in employment

Men, not in employment but in the survey

Women, not in employment but in the survey

Men, not in employment and not in the survey

Women, not in employment and not in the survey


In each EU country, there were more women than men who: (i) were not in employment; and (ii) have

not worked beyond age 50. There are however significant differences between countries, as shown in

graph 2. People who are not in employment and have not worked beyond age 50 are less likely to have

access to pension rights, although those who have worked in the past may still have pension rights.

Unfortunately, the data set provides no information at all on people who stopped working before age 50.

The Hungarian quality report points out that the choice of target population was more problematic for

countries with a lower retirement age, because people who do not work beyond age 50 are in general very

likely to be receiving a pension at the time of the interview or to be due a pension in the future, as a result

of their previous employment. Moreover, although the module included a special variable for past

contributions to several pension schemes (BUILDPEN), the results are unfortunately not available for

those who have worked in the past, but not beyond age 50. This has therefore detracted somewhat from

the usefulness of these results.

Graph 2: Non-applicable AHM 2012 population aged 50-69 by gender (% in the

population aged 50-69 of the same gender)

Note: values for Germany, France, Austria, Sweden and Switzerland are estimated.

Excluding those who have not worked beyond age 50 from the data also means that the results from

AHM 2012 cannot be generalised to apply to the full population aged 50-69 and its transition to

retirement. It is only in the case of the group in employment at the time of the interview that the analysis

has not been affected by the choice of target population, neither with respect to gender nor country. This

particular group represents only half of the total population aged 50-69 in the EU however, and the

percentage represented varies significantly by country, with employment rates ranging from 63 % in

Sweden to 34 % in Malta.

0%

10%

20%

30%

40%

50%

60%

70%

80%

MT

EL IT BE

LU IE ES

HR

NL

CY

PL

EU

-28

PT

RO

AT

FR

DE SI

HU

UK

LT

SK

SE

BG LV

DK

EE FI

CZ

NO IS

CH

Men Women


Main findings

Amongst the target population at EU level:

• the average age at which respondents receive an old-age pension for the first time is 59 years, for

both women and men;

• 42 % are currently receiving a pension;

• the statutory old-age pension is by far the most common type of pension, with 81 % of those

receiving some form of pension receiving a statutory old-age pension;

• approximately four in 10 people receiving an old-age pension had taken early retirement; and

• the two most frequently cited main reasons for not remaining in employment for longer were

reaching eligibility for a pension and the respondent’s own health problems or disability (reasons

given by 37 % and 21 %, respectively, of economically inactive people receiving a pension).

Description of the variables

A full description of the variables, filters and coding, as defined in Commission Regulation (EU) No

249/2011, is available in Annex 3. The module contains the following 11 variables:

PENSION Person receives a pension

PENSTYPE Type of pension(s)

EARLYRET Early retirement

AGEPENS Age at which person first received an old-age pension

REASNOT Main reason for not remaining in employment longer

WORKLONG Wish to remain in employment longer

REDUCHRS Reduced working hours as a step towards full retirement

STAYWORK Main reason for remaining in employment (for respondents already receiving a

pension)

PLANSTOP Plans to stop working in the future (for respondents already receiving a

pension)

BUILDPEN Pension rights built-up to date

CONTWORK Expects to continue working or looking for a job after starting to receive an

old-age pension.

Links with AHM 2006

The policy background for AHM 2012 is similar to that of AHM 2006, namely monitoring participation

in the labour market. There are however no variables which are completely and directly comparable

between the two surveys. The evaluation of AHM 20067 made the following recommendations for

changes to be made to the variables were the module to be repeated. We have included only the six

variables that, in principle, cover the same content in 2012 as in 2006.

(1) REDUCHRS caused problems for respondents in 2006 because it asked about their future plans, when

in many cases they had not made such plans at the time of the interview, due in particular to changes in

the pensions regulation. The response item ‘progressive retirement schemes’8 was not used in several

countries because the concept itself was unfamiliar. The 2006 task force’s recommendation to simplify

7 The publication is available at http://ec.europa.eu/eurostat/product?code=KS-RA-08-012

8 “Progressive retirement scheme/part-time pension” was defined in the Transition from work into retirement publication, on page 48, as follows: 'this measure concerns older employees in some countries. This is part of measures to keep older employees in employment (incentives to stay at work). To avoid the exit from work, in case the employee wishes to decrease his/her working time before retiring, he/she could take a part-time job for example. It could be a “classic” part-time or what is called a “progressive retirement scheme/part-time pension”. The latter ensures a better remuneration than the “classic” part-time (e.g. 50% work paid 80%). In other words, it corresponds to a reduction of the number of hours worked with a less than proportional reduction in salary (e.g. 50% work paid 80%)'


this variable was followed in 2012.

(2) PLAGESTP (corresponding to AHM 2012 variable PLANSTOP) caused problems for the same

reason as REDUCHRS. Unfortunately, the fine-tunings proposed for 2012 did not solve the original

problem of people finding it difficult to answer questions about their future plans.

(3) REASRET (corresponding to AHM 2012 REASNOT) was reported to have too many response items

each of which was too detailed. This made it difficult to distinguish between several of the items.

Changes to this variable were proposed but not such as would necessarily simplify it.

(4) AGEPENS caused problems due to difficulties in understanding the expression ‘individual retirement

pensions’. Accordingly, this was changed to ‘old-age pension’ for 2012.

(5) OTHBENF (corresponding to AHM 2012 PENSTYPE) caused problems due to the interpretation of

the term ‘individual benefits’ in the explanatory notes. The 2012 survey asks for broad categories of

pension types.

(6) FININCTV (corresponding to AHM 2012 STAYWORK) had many missing values in its data set due

to the filter conditions being too restrictive in 2006. The advice relating to this variable was followed in

2012.

Links with the core LFS

The target population of the module is in part based on the International Labour Organisation (ILO)

employment status, which has three main subgroups: employed, unemployed, and economically inactive.

While the ILO status is obtained from a combination of several core variables (WSTATOR,

SEEKWORK, AVAILBLE, METHODA to METHODM), the AHM 2012 status is based on a simplified

version, derived from only two variables in the core LFS: WSTATOR (labour status during the reference

week) and SEEKWORK (seeking employment during the previous four weeks), in the following way:

Employed: WSTATOR (1, 2);

Unemployed (simplified): WSTATOR (3, 5) and SEEKWORK (1, 2, 4); and

Inactive (simplified): WSTATOR (3, 5) and SEEKWORK (3).

In the schematic overview of the relation between the variables, given on the last page of the explanatory

notes, the basic ILO terminology is used, without a clear indication of the intended simplification (in

respect of SEEKWORK). Whilst this is not ideal, the Regulation takes precedence over the addendum to

the explanatory notes, so the omission is not of material consequence.

The fact that the scheme does not include all WSTATOR categories does not have any impact on the

module, as those not included refer to people who are either younger than 15 years, older than 75 years,

or engaged in compulsory military service. None of these people are in the 50-69 years target group.

YEARPR (year in which person last worked) and YEARBIR (year of birth) are used in combination to

define the target population of the module.

General issues relating to data collection

This section gives detailed information on sample sizes and non-response rates. It also includes

information on differences in interviewing methods and experiences between countries.

Sample size

The sample size of AHM 2012 is determined by the number of people interviewed during the labour force

survey in the specific 2012 quarter(s).9 Only people aged 50 to 69 and meeting specific requirements

relating to labour market status (see the target population chapter for more details) were interviewed. The

following table shows, for each country, the number of interviews conducted and the percentage of the

target group population that this number of interviews represents.

9 See the reference period of the module (in table 3) for the specific quarter(s) by country.


Table 1: Sample sizes of AHM 2012, by country

AHM sample (persons interviewed)

AHM sample as a percentage of the corresponding population in each country (%)

EU-28 289 297 0.28 %

BE 4 641 0.23 %

BG 9 346 0.54 %

CZ 12 554 0.49 %

DK 6 208 0.49 %

DE 11 760 0.06 %

EE 2 917 1.02 %

IE 9 518 1.34 %

GR 12 284 0.61 %

ES 21 821 0.26 %

FR 16 916 0.13 %

HR 2 139 0.22 %

IT 28 855 0.26 %

CY 2 223 1.42 %

LV 2 112 0.47 %

LT 4 135 0.65 %

LU 4 527 4.74 %

HU 15 607 0.73 %

MT 1 121 1.65 %

NL 18 604 0.54 %

AT 7 955 0.45 %

PL 21 494 0.29 %

PT 9 562 0.44 %

RO 14 574 0.36 %

SI 3 601 0.80 %

SK 6 730 0.57 %

FI 7 465 0.55 %

SE 12 080 0.57 %

UK 18 548 0.15 %

IS 885 1.39 %

NO 5 060 0.51 %

CH 3 877 0.22 %

Note: the corresponding AHM 2012 population is the weighted total of ‘yes’, ‘no’ and blank answers from the PENSION variable.

Non-response rates

If the non-response rate is higher than 15 %, the data for that country for that variable was considered for

the purpose of this report to be of very limited use. Only nine of the 31 countries involved in the survey

have acceptable response rates (i.e. above 85 %) for all variables. The two variables PLANSTOP and

CONTWORK are of minimal use for analytical purposes due to the very high non-response rate at EU

level.


Table 2: Non-response rates in AHM 2012, by variable

PE

NS

ION

EA

RL

YR

ET

AG

EP

EN

S

RE

AS

NO

T

WO

RK

LO

NG

RE

DU

CH

RS

ST

AY

WO

RK

PL

AN

ST

OP

CO

NT

WO

RK

EU-28 2 % 4 % 5 % 4 % 6 % 11 % 12 % 35 % 19 %

BE 0 % 0 % 2 % 19 % 21 % 12 % 1 % 2 % 0 %

BG 3 % 0 % 0 % 0 % 0 % 0 % 0 % 60 % 52 %

CZ 0 % 0 % 0 % 0 % 0 % 0 % 1 % 5 % 6 %

DK 0 % 0 % 0 % 0 % 0 % 0 % 4 % 0 % 29 %

DE 8 % 27 % 30 % 26 % 33 % 21 % 42 % 45 % 19 %

EE 0 % 0 % 0 % 0 % 0 % 0 % 0 % 19 % 13 %

IE 5 % 0 % 2 % 0 % 1 % 57 % 2 % 16 % 8 %

GR 9 % 0 % 0 % 0 % 20 % 19 % 0 % 40 % 26 %

ES 0 % 0 % 2 % 0 % 5 % 2 % 1 % 67 % 17 %

FR 0 % 0 % 1 % 0 % 0 % 1 % 33 % 26 % 16 %

HR 0 % 0 % 0 % 0 % 0 % 2 % 18 % 89 % 0 %

IT 0 % 0 % 0 % 0 % 1 % 0 % 0 % 63 % 24 %

CY 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 %

LV 0 % 0 % 1 % 1 % 1 % 0 % 0 % 11 % 0 %

LT 0 % 0 % 1 % 0 % 0 % 11 % 0 % 0 % 46 %

LU 0 % 1 % 2 % 0 % 2 % 3 % 8 % 14 % 13 %

HU 3 % 0 % 0 % 0 % 0 % 1 % 0 % 48 % 0 %

MT 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 %

NL 1 % 0 % 1 % 0 % 1 % 1 % 4 % 19 % 15 %

AT 0 % 0 % 0 % 0 % 0 % 0 % 0 % 16 % 0 %

PL 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 %

PT 2 % 0 % 0 % 0 % 1 % 1 % 0 % 22 % 8 %

RO 6 % 0 % 0 % 0 % 0 % 3 % 0 % 83 % 61 %

SI 0 % 0 % 0 % 0 % 0 % 0 % 8 % 0 % 0 %

SK 0 % 0 % 0 % 0 % 0 % 0 % 0 % 5 % 3 %

FI 1 % 1 % 3 % 0 % 1 % 2 % 3 % 8 % 4 %

SE 0 % 0 % 0 % 1 % 1 % 3 % 1 % 52 % 17 %

UK 0 % 0 % 1 % 0 % 1 % 43 % 1 % 29 % 22 %

IS 2 % 1 % 3 % 35 % 37 % 15 % 13 % 82 % 32 %

NO 1 % 62 % 19 % 0 % 2 % 11 % 4 % 25 % 36 %

CH 2 % 1 % 9 % 2 % 1 % 1 % 17 % 25 % 31 %

Note: highlighted cells are those where the non-response rate is above the critical level of 15 %

Other measurement issues

The following table gives information on various aspects of how the survey was conducted in each

country; these are liable to influence the quality and comparability of the results:

the reference period(s), i.e. during which quarter(s) of 2012 the data was collected;

whether participation was compulsory or voluntary;

whether a proxy could answer on behalf of the respondent;

whether pilot surveys or other testing was carried out before the survey itself; and

the order in which questions were asked when collecting LFS and AHM data, i.e. whether AHM

questions were either integrated into the survey by topic, or asked all together after the LFS

questions.


Table 3: General measurement issues in AHM 2012

Reference period

Participation Use of proxies

Pilot survey or other testing AHM

questions after core LFS

BE Q2 Compulsory No Yes

BG Q1-Q4 Voluntary Yes Yes, field testing Yes

CZ Q1-Q4 Voluntary Yes No

DK Q2 Voluntary Yes Yes

DE Q1-Q4 Voluntary Yes Yes

EE Q2, Q4 Voluntary Yes Yes

IE Q2 Voluntary Yes Yes

GR Q2 Compulsory Yes Yes

ES Q1-Q4 Compulsory Yes Yes

FR Q1-Q4 Compulsory No Yes, field testing (185 and 283 respondents) Yes

HR Q2 Voluntary Yes Yes

IT Q2 Compulsory Yes No

CY Q2 Compulsory Yes Yes

LV Q2 Voluntary Yes Yes

LT Q2 Voluntary Yes Yes

LU Q1-Q4 Voluntary Yes Yes, field testing Yes

HU Q2 Voluntary Yes Yes

MT Q1-Q2 Voluntary Yes No

NL Q1-Q4 Voluntary Yes No

AT Q1-Q4 Compulsory Yes Yes, field testing (195 respondents) Yes

PL Q2 Voluntary Yes Yes

PT Q2 Voluntary Yes Yes

RO Q2 Voluntary Yes Yes, field testing (593 respondents) Yes

SI Q2 Voluntary Yes Yes

SK Q2 Voluntary Yes Yes

FI Q1-Q4 Voluntary Yes Yes, cognitive testing (22 respondents) Yes

SE Q1-Q4 Voluntary Yes Yes, cognitive testing Yes

UK Q1-Q4 Voluntary Yes No

IS Q2 Voluntary Yes No

NO Q1-Q4 Compulsory No Yes

CH Q1-Q4 Compulsory Yes Yes

The national reports on the interviewing phase of the survey paint a positive overall picture of the

experience. There are, however, several issues that would need to be addressed were the module to be

repeated, such as the method of collecting information on pension(s) (spontaneous answer of the user

versus administrative definition with examples) and the use of filters and the routing of the questionnaire

in general. More extensive testing of questionnaires, better mapping of national pension systems, and

more training for interviewers could have helped to avoid some of the problems which resulted in the low

quality of some of the data collected. In other cases, the complexity and changing nature of pension

systems, as well as respondents’ lack of understanding of them, created difficulties when collecting the

data for AHM. The interviewing method sometimes limited the options open to interviewers, as did some

of the variables themselves, which were too rigid, e.g. where ‘I do not know’ was not allowed as a

spontaneous answer. Other issues encountered included: questions being asked twice (for LFS and again

for AHM), difficult administrative concepts, and problems in recalling past events or in predicting future

decisions on retirement. These are likely to have had a negative influence on the quality of the data.

All of the points mentioned above should be re-assessed before any new data is collected on the same

topic. The various issues will be explored in more detail in the next chapter, under the relevant variables.


Chapter 2: Quality analysis by variable

This chapter assesses AHM 2012 in more detail, with analysis of each variable. The eleven variables

included in the module are presented in the same order as in the Regulation. This is the order of columns

in the database,10 but it does not imply that variables were collected in this order in all countries. The

questionnaires used in each country to collect the AHM 2012 data are available,11 often in several

languages.

1. PENSION: Person receives or does not receive a pension

Short description

The purpose of the variable is to split the target population into two groups: those currently receiving a

pension and those not currently receiving a pension.

Respondents were expected to decide, based on their own judgment, whether the type of benefit they

receive is a pension. The general condition for a payment to be considered as a pension was that it had to

be a regular and periodic benefit received in cash, other than a salary or wage. Lump-sum payments and

benefits in kind were excluded from the definition.12 A list of benefits which are not considered as

pensions was also drawn up13. Symbolic payments, even if labelled as pensions, were excluded.14

Filter conditions and codes

This question was asked to all respondents, i.e. people aged 50-69 who are either currently working

(WSTATOR = 1, 2) or have worked beyond the age of 50 (WSTATOR = 3, 5 and (YEARPR -

YEARBIR) > 49)). See the target population section for more information.

Analysis of the questionnaires

This variable is of particular importance: firstly, because it distinguishes between those receiving and not

receiving a pension; and secondly, because it acts as a filter for the rest of the module.

Ideally, the same question would have been used in all countries, to minimise the risk of introducing

national differences in a variable whose output was crucial for the whole AHM. In general, the

recommendation of asking respondents to judge for themselves whether they receive a pension was

followed. In some questionnaires however (the Belgian and Swiss questionnaires, for example), this

question was repeated for several types of pensions — mainly the ones from the PENSTYPE variable —

while in others (Spain, Portugal and Romania) additional types of pensions were already given as

examples in the opening question. In Bulgaria and Hungary, the interviewer first checked whether

respondents were receiving an old-age pension, and then asked about other types of pensions. It can be

assumed that these variations would not have fundamentally affected the comparability of the data but the

actual impact cannot be measured.

This variable played an important role in the routing of the questionnaire. Those answering ‘no’ (code 2)

10 AHM 2012 columns ranged from 197 to 218, with one or more digits per variable.

11 See description of the 2012 AHM at http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey_-_ad_hoc_modules

12 Explanatory notes, page 4.


14 Frequently asked questions, page 4.

Code Description

1 Yes

2 No

9 Not applicable (not included in the filter)

Blank No answ er or does not know


were routed outside the variables PENSTYPE, EARLYRET, AGEPENS, REASNOT, WORKLONG,

STAYWORK, and PLANSTOP. They were routed instead to REDUCHRS (if in employment),

BUILDPEN and CONTWORK. In most cases, those who wrongly answered ‘no’ to the first open-ended

question did not receive follow-up questions on the same topic. Those who answered ‘yes’ (code 1) were

routed towards the PENSTYPE question. The combination of an open-ended variable (PENSION) and a

yes/no variable (PENSTYPE), the latter based on a pre-determined list of administrative schemes and not

allowing ‘do not know’ answers, was not ideal in all cases. When faced with inconsistencies in a

respondent’s answers to the two questions, interviewers are likely to have made an ‘on the spot’ decision

and, as a result, the routing of the questionnaire was not always as consistent as might have been hoped.

Data was not collected for the variable PENSION in 2006, as a result of which we do not have any time

series data with which to compare the 2012 data. The results were, however, compared to the LFS

variables MAINSTAT (respondents’ own view of their main labour status)15 and LEAVREAS (main

reason for leaving last job or closing business). The testing of the model questionnaire had predicted that

data obtained for this variable would be of high quality and would be useful as a starting point for the

module. Results from the full survey generally confirm this.

Analysis of the results

The response rate was good in all participating countries.

Univariate analysis of a categorical variable offers limited options in terms of methods, but we can see

that this variable has the highest response rate out of all variables included in the module, at 98 % (table

2). The impact of the target population on any potential interpretation of the data is also evident.

Analysing the existence of pension rights based on a subgroup of the population aged 50-69 (moreover a

subgroup with an unequal gender distribution) is not without risks. This issue was discussed in the target

population section, where a breakdown by country and gender is given. Graph 1.1 provides an overview

of the distribution of this variable for the population aged 50-69, by country.

Graph 1.1: Distribution of the AHM 2012 PENSION variable (% of the population aged

50-69)

Considering only the target group of the AHM (i.e. excluding the respondents answering ‘not applicable’

from the graph above), 42 % of respondents in the EU receive a pension (see graph 1.2). A total of 19 of

the 31 countries in the survey are within ±5 % of this. The percentage of the target group receiving a

15 MAINSTAT is an optional variable in the LFS, measuring the (perceived) main labour status.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

MT

EL

HR IT BE IE PL

ES

LU

NL

RO

CY

EU

-28

HU

PT SI

UK

FR LT

AT

DE

BG LV

SK

EE

SE

DK FI

CZ

NO

CH IS

Yes No No answer Not applicable


pension is equal to the EU average in three countries (Finland, Greece and Portugal), and lower than it in

nine EU member states and in Switzerland, Norway and Iceland. The ‘yes-no curve’ in graph 1.2 is fairly

smooth and there are therefore no outliers. The highest value for ‘yes’, i.e. the percentage of the target

group receiving a pension (53 % in the Czech Republic) is two and a half times larger than the lowest

value (in Iceland). From a geographical perspective, the countries with the highest percentage of the

target group receiving a pension are eastern European (the Czech Republic, Slovenia, Slovakia, Romania

and Poland), whereas the countries with lower percentages of the target group receiving a pension are

more mixed, and include Mediterranean as well as north-west European countries (Iceland, Ireland, the

Netherlands, Cyprus, Spain and Norway), and also Hungary.

Graph 1.2: Distribution of the AHM 2012 PENSION variable (% of the target population

aged 50-69)

Graph 1.3 shows the split of people in employment receiving and not receiving a pension. This subgroup

is not affected by the choice of target population. The height of each bar represents the overall

employment rate for people aged 50-69 in each country. In all countries, only a small proportion of the

population is in employment and simultaneously receiving a pension. In general, countries with a

relatively high proportion of employed people receiving pensions also have a high employment rate, e.g.

Sweden, Estonia, the United Kingdom and Norway. There are also however several countries where

employment rates are high and the proportion of employed people receiving pensions is relatively low,

e.g. Germany, Denmark and the Netherlands.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

CZ SI

SK

RO PL

HR

EE

BG

FR LT

AT

MT

UK

LV

LU

SE FI

EL

PT

EU

-28 IT

DK

HU

BE

DE

ES

CY

NL IE

CH

NO IS

Yes No No answer


Graph 1.3: Distribution of the AHM 2012 PENSION variable for people aged 50-69 in

employment (% of the entire population)

Graph 1.4 shows that the majority of people receiving a pension are no longer in employment. At EU

level, 34 % of the AHM 2012 population receive a pension and are not in employment, while only 7 %

receive a pension and are in employment.

Graph 1.4: Distribution of the AHM 2012 PENSION variable for people aged 50-69, by

employment status (% of the AHM 2012 population)

On the basis of the graphs above, we can conclude that there is a strong link between employment status

and the PENSION variable, but that there are also many other aspects of the labour market that play a

role in determining the distribution of this variable. Some countries (such as Malta, Greece, Italy and

0%

10%

20%

30%

40%

50%

60%

70%

80%

SE

EE

DE

DK

UK

NL FI

LT

LV

CY

CZ

EU

-28

AT

PT IE FR

SK

RO

LU

BG

BE

PL IT ES

HU SI

HR

EL

MT IS

NO

CH

Yes No No answer

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

SI

CZ

SK

HR

EL

BG

FR

AT

PL

LU

RO

MT IT

HU LT

EU

-28

BE

LV FI

DK

PT

ES

EE

UK

DE

SE

CY

NL IE

CH

NO IS

In employment and PENSION=no In employment and PENSION=yes

Not in employment and PENSION=yes Not in employment and PENSION=no

No answer


Belgium — see graph 2) have a significant population who have not worked beyond age 50, and this

population was not interviewed. In other countries (such as Sweden, Estonia and the United Kingdom —

see graph 1.3) a high proportion of the population are in employment and receiving a pension, but in

general, those receiving a pension are no longer in employment, as seen in graph 1.4. Among those

receiving a pension, there are significant variations in their employment status at country level: over a

third of those receiving a pension are still in employment in Sweden, Estonia and the United Kingdom,

while only 3 % of those receiving a pension are still in employment in Greece. Finally (see graph 1.2),

more than half of respondents in the Czech Republic and Slovenia do receive a pension, while in Ireland

and the Netherlands fewer than 30 % do.

The next section discusses the aggregated PENSION data and analyses links between the PENSION

variable and the age of respondents at EU level.

Graph 1.5: Distribution of the AHM 2012 PENSION variable, by age groups and

employment status, EU-28 (million persons)

Unsurprisingly, the distribution of the PENSION variable changes significantly with the age of the

respondents. The majority of respondents below age 60 are still in employment and do not receive a

pension. The majority of respondents aged 60 or above are not in employment and do receive a pension.

Population groups who are in employment and receiving a pension, or not in employment and without a

pension are less prominent. While age 60 could be assumed to be a natural turning point for the EU

population in its transition from work to retirement, analysis based on data relating to pensions needs to

take into account the significant demographic differences at country level.

The following graphs examine in more detail the population aged 55-64, in order to describe the actual

transition from the labour market into retirement by analysing the population at the ages at which, in

many countries, this transition takes place. In the 50-54 age group, only a small proportion of people

receive pensions (6 % at EU level, with some country variations), and in the 65-69 age group, a very high

proportion do so (95 % at EU-level), thus illustrating that most transitions take place between the ages of

55 and 64. Ireland and the Netherlands are the only EU countries where the percentage of respondents

aged 65 to 69 receiving a pension was under 90 %. In Greece, Romania and Spain, 90 % of respondents in

this age group were receiving a pension. In some countries 100 % of the AHM population aged 65-69

were receiving a pension (Estonia, Malta and Latvia), indicating that the right to a pension becomes

universal at a certain age (at least) for those having worked beyond age 50.

0

5

10

15

20

25

30

50-54 55-59 60-64 65-69

No answer

Not in employment andPENSION=no

Not in employment andPENSION=yes

In employment and PENSION=yes

In employment and PENSION=no


The graph below shows the breakdown of the PENSION variable by 5-year age groups, 55-59 and 60-64.

In both age groups, there are significant differences between countries in the proportion of respondents

receiving a pension. In some countries, such as Denmark, Hungary, and Malta, there is a significant

increase in the proportion of respondents receiving a pension just after age 60. It is not surprising that

countries with a relatively low proportion of respondents receiving pensions in these age groups (Ireland,

the Netherlands, Spain and Cyprus) will tend to be in the lowest part of the overall PENSION distribution

(see graph 1.2). The overall proportion of Swedish respondents receiving a pension is however higher

than the EU average, even though a relatively low proportion of people in the 55-59 and 60-64 age groups

receive pensions. This is due the high proportion of respondents in the 65-69 age group receiving a

pension (98 %).

Graph 1.6: Proportion of ‘yes’ responses to the AHM 2012 PENSION variable, by

respondents’ age group (% in the corresponding age group)

We conclude the section dedicated to the age group 55 to 64 with a graph that shows the gender

differences among the 55-64 year-old AHM population. In most countries, women complete their

transition towards retirement before men. Countries where women retire earlier than men are also likely

to have a high overall proportion of respondents receiving a pension.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

SI

SK

MT

CZ

AT

PL

LT

FR

LV

RO

EE

LU IT

HR

BG

UK

HU

EU

-28

BE FI

EL

PT

DK

DE

CY

ES

SE

NL IE

NO

CH IS

55-59 60-64


Graph 1.7: Proportion of ‘yes’ responses to the AHM 2012 PENSION variable for the

AHM population aged 55-64, by gender (%)

As this variable was not included in the 2006 module. the best way of assessing the quality of the data is

therefore to compare it to the LFS MAINSTAT variable, as recommended in the explanatory notes. The

two variables are related, as PENSION classifies respondents according to whether they receive a

pension, and MAINSTAT classifies them by their main activity status, as judged by the respondents

themselves, with one option (code 4) being in retirement, in early retirement or having given up business.

By definition, the relevant values of the variables are not identical and so will not obtain exactly

overlapping population groups, but the two variables would be expected to show the same picture to a

large extent.

Graph 1.8: Proportion of ‘yes’ responses to the AHM 2012 PENSION variable for

selected categories of the LFS MAINSTAT variable, EU-28 (%)

Note: EU-28 average excluding Germany and the United Kingdom.

0%

10%

20%

30%

40%

50%

60%

70%

80%

SI

CZ

PL

SK

RO

AT

HR LT

EE

BG

UK

LV

FR

MT

LU

EU

-28

EL IT FI

HU

PT

DE

DK

BE

ES

CY

SE

NL IE

NO

CH IS

Men Women

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Retired Permanentlydisabled

Other inactiveperson

Unemployed Employed


Graph 1.8 confirms these expectations, with most of those who define themselves as retired also receiving

a pension, while people in employment or those unemployed are less likely to receive a pension. It also

shows that, at EU level, there are more respondents in PENSION = 1 than in MAINSTAT = 4 (i.e. more

people receiving a pension than who would describe themselves as in retirement, in early retirement or

having ceased business activities).

The next graph shows the correlation between those coded 4 for the core LFS variable MAINSTAT (in

retirement, in early retirement or having ceased business activities) and those coded 1 in the LFS AHM

PENSION variable (is receiving a pension), for the age group 50–69, by country. The clusters of

countries are familiar from graph 1.1, with Iceland and Ireland at the lower end (i.e. with a smaller

proportion of the population receiving a pension), and the Czech Republic and Slovenia at the higher end

(i.e. with a larger proportion of the population receiving a pension). Data for Germany and the United

Kingdom is not shown in graph 1.8 because they did not provide data for MAINSTAT in 2012. The data

points are all reasonably close to the trend line. At country level, the proportion of respondents answering

‘yes’ for the PENSION variable is also higher than the proportion answering code 4 for the MAINSTAT

variable, as was noted from graph 1.8. This can now be seen to be a systematic pattern that holds for all

countries, with the exception of Hungary and Croatia. In the case of Hungary, this is due to the recent

pension reform16 that has transformed several of the previous types of pension into social benefits. This

illustrates the sensitivity of this variable to national administrative definitions, and serves as a warning of

the errors that can occur if data is generalised and interpreted outside the AHM 2012 context.

Graph 1.9: Correspondence between the LFS MAINSTAT variable and the AHM 2012

PENSION variable (%)

It would also be possible to compare the PENSION variable to the core LFS LEAVREAS variable. The

LEAVREAS variable (main reason for leaving last job or ceasing business activities) is collected

annually from all respondents not in employment but who have previous employment history and have

stopped work within the last eight years. The overlap between this variable and the PENSION variable is

represented by the group of respondents aged 50-69 not in employment but having previous employment

history beyond age 50 and within the last eight years.

16 More information is available in the document mapping the national pension systems and the AHM 2012 PENSTYPE variable.

EU-28

BE

BG

CZ

DK

EE

IE

EL

ES

HR FR

IT

CY

LV LT LU

HU

MT

NL

AT PL

PT

RO

SI SK

FI SE

IS

CH

0%

10%

20%

30%

40%

50%

60%

0% 10% 20% 30% 40% 50% 60%

AH

M L

FS

2012,

PE

NS

ION

= 1

Core LFS, 2012, annual, MAINSTAT = 4


Graph 1.10: Proportion of ‘yes’ responses to the AHM 2012 PENSION variable for

selected categories of the LFS LEAVREAS variable, EU-28 (%)

As shown by graph 1.10, the two variables are correlated, as expected. A large majority of people who

left their last job due to retirement (whether normal or early) declare receiving a pension. This also holds

for people leaving the labour market for health reasons. The grouping ‘all other reasons’ on graph 1.10

includes the following codes from the LEAVREAS variable: dismissal (code 00), end of a contract of

limited duration (code 01), and other personal reasons. For all values of the LEAVREAS variable, the

distribution of the PENSION variable is in line with expectations.

Conclusions and recommendations

The form of this variable suggests that data can be collected using a very simple yes/no question, without

complicated routing or coding. Deciding whether or not one receives a pension (as defined by AHM

2012) might not however always be entirely straightforward. Difficulties in answering this were reported

to have occurred most often in situations where respondents received some benefits (in particular

unemployment benefits or disability benefits) that might be called pensions in everyday language, but

which are not considered as pensions for the purpose of this module. The opposite situation was also

reported to have occurred, where people receiving pensions (usually not old-age pensions) spontaneously

answered ‘no’ to the question. Countries having recently undergone changes to their pension systems (in

particular Bulgaria, Hungary and Poland) had to ensure consistency between the old and new systems in

terms of what is classed as a pension. In order to prevent errors resulting from these situations, national

mappings were prepared and linked the existing national terminology with the corresponding PENSTYPE

types of pension. The PENSION variable is by definition the sum of all the possible values for

PENSTYPE (i.e. receiving any of the possible types of pension included in the PENSTYPE variable

equals a ‘yes’ answer to the PENSION variable). It should however be noted that the conceptual

complexity of what is and what is not a pension was not fully accommodated by the yes/no question

which was supposed to be asked in the questionnaire.

In several countries (Bulgaria and Hungary, for example), data for this variable was not in fact collected

using a yes/no question, but was deduced from answers to other questions on the type of pensions

received. The complexity of the opening question also varied, ranging from the simple question ‘Do you

receive a pension?’ to questions listing several types of pensions received in that country. Depending on

the order in which questions were asked, the interview method, the training received by interviewers for

working on this module and their level of experience, answers to the PENSION variable may have

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Normal retirement Early retirement Illness or disability All other reasons


sometimes been re-coded in light of the information collected for the PENSTYPE variable. In other cases

however, it may not have been possible to ensure fully consistent coding.

Very few of the participating countries reported any problems in collecting data for this variable and the

response rate was good. The Netherlands report explained that their data would underestimate the number

of pensioners because it was difficult in some cases to make the respondents understand the module’s

broad definition of pensions. The report from Greece highlighted a situation which can arise in their

system where an individual is formally entitled to a pension, but the actual payment is delayed for more

than a year, thus making it difficult to know whether to answer ‘yes’ or ‘no’ to the question of receiving a

pension. Moreover, no country reported that their definition of the variable in the module differed from

the definition included in the Commission Regulation (249/2011). The response rate was good, there

were no outliers, and there was also strong correlation with MAINSTAT and LEAVREAS. We can

therefore conclude that the quality of data for the variable is good. The variable is however based on

national definitions and classifications of pensions and other social benefits. Conceptually its

comparability is unfortunately limited at any level higher than country level.

Should the module be repeated, consideration should be given to the question of whether one single

variable is sufficient for the purpose of dividing the target population into two groups: those receiving

and those not receiving a pension. Were a similar variable to be used again as a filter for the rest of the

module, the risk of inconsistencies or errors and their impact on the overall data set should also be

assessed. Moreover, the concept of a pension was defined in 2012 at national level, as a specific provision

entitling an individual to selected social benefits. Possible ways of improving its comparability at

European level could be analysed in more detail.

2. PENSTYPE: Type of pension(s) currently received

Short description

The purpose of the variable is to determine which type of pension(s) the respondents who answered ‘yes’

to the previous question (PENSION) are receiving. However, not all participating countries asked the

questions in this order in their questionnaires. As shown in the code list provided, PENSTYPE has eight

possible answers: four types of old-age pension scheme, unemployment pension, disability pension,

survivor’s pension and other pension or type of pension unknown.

More than one answer could be given to this question, as one person can receive several types of pension

at the same time. The answer ‘do not know’ was not included as an option for this question. Lists of the

different pensions and benefits available in each country were prepared at national level and each

assigned to the relevant code.17


This question was asked to all respondents who answered ‘yes’ (code 1) to the question relating to the

PENSION variable.

17 A detailed document presenting the mapping of the types of pension available in each country onto the pension types from this variable is

available online at: http://ec.europa.eu/eurostat/statistics-explained/index.php/EU_labour_force_survey_-_ad_hoc_modules

Code Description

PENSTYP1 1: Yes; 0: No Old-age pension. Statutory scheme

PENSTYP2 1: Yes; 0: No Old-age pension. Occupational scheme

PENSTYP3 1: Yes; 0: No Old-age pension. Personal scheme

PENSTYP4 1: Yes; 0: No Old-age pension. Scheme unknow n

PENSTYP5 1: Yes; 0: No Unemployment pension

PENSTYP6 1: Yes; 0: No Disability pension

PENSTYP7 1: Yes; 0: No Survivor's pension

PENSTYP8 1: Yes; 0: No Other pension(s) or type of pension unknow n




Countries were advised to ask the PENSTYPE question only after the PENSION question. Most countries

followed this advice and collected information on whether pension benefits were received at all first, and

then asked about the type of pensions received. Some countries, including Belgium, Lithuania and

Switzerland, used a slightly different questionnaire structure. The risk of inconsistencies between the two

variables and the implications of this for the overall questionnaire were discussed in the PENSION

section.

For the PENSTYPE variable, mappings of pensions available in each country were prepared at national

level. These were helpful but required substantial documentation. Where national systems are extremely

complex (e.g. in Denmark and Italy) or undergoing changes (e.g. in Hungary and Poland), countries

reported difficulties in ensuring that all eight components of the variable were well defined and distinct.

Bulgaria and Sweden reported minor deviations in the implementation of this variable. In the case of

Bulgaria, this is due to a change made to the social security code in 2012, which separated social

disability pensions from disability pensions (PENSTYP6), with an estimated impact on the results of

PENSTYP6 of 12 %. Sweden reported that it did not use PENSTYP4, and that it included the data which

would have taken this value in PENSTYP8 instead, i.e. it combined the two codes as PENSTYP8.

In some countries (Finland and the Netherlands), the terminology of this AHM was not always familiar

and respondents had difficulty answering the question. For example, in Finnish, the concept of an old-age

pension is not always understood correctly. In some situations (reported in Finland and Italy and likely to

have occurred in other countries as well), the respondent received a benefit whose ‘label’ had changed at

some point in time, e.g. when a disability pension was automatically converted into an old-age pension at

a certain age. In these cases, respondents were not always able to indicate accurately the correct type of

pension they received. Errors in the PENSTYPE variable had an impact on the overall routing of the

questionnaire, as well as on the accuracy of the AGEPENS variable. It can however be assumed that the

impact of these cases on the overall data set was not significant.

A somewhat similar variable was collected in 2006, as discussed in the chapter on links with the AHM

2006. In Hungary, there was a major overhaul of the pension system in 2012, making any attempt at

comparison to the 2006 module meaningless.


This variable is defined as eight separate variables collated together. Each of the eight sub-variables

allowed yes and no answers, and, as a result, multiple types of pensions could be selected by each

respondent. Respondents receiving two (or more) types of pension are therefore counted as many times as

they receive pension types.

Unfortunately, the data for this variable is not easy to interpret at EU level, as very similar types of

pension could be classified in different countries as being under different schemes. Moreover, for some

types of pension (PENSTYP 5 or 6), similar social rights are classified as pension schemes in some

countries and social benefits (not included in the module) in others.

The table below shows the percentage of ‘yes’ answers out of the total number of answers for each

subcategory of the PENSTYPE variable, at EU level and by country.


Table 2.1: ‘Yes’ answers as a percentage of total answers for each of the AHM 2012

PENSTYP1 to 8 variables, EU-28 (% of those with PENSION = 1)

PE

NS

TY

PE

1

PE

NS

TY

PE

2

PE

NS

TY

PE

3

PE

NS

TY

PE

4

PE

NS

TY

PE

5

PE

NS

TY

PE

6

PE

NS

TY

PE

7

PE

NS

TY

PE

8

EU-28 81 % 16 % 8 % 2 % 1 % 9 % 8 % 5 %

BE 73 % 7 % 7 % 7 % 16 % 9 % 5 % 0 %

BG 90 % 1 % 0 % 0 % 0 % 11 % 3 % 0 %

CZ 90 % 0 % 4 % 0 % 0 % 9 % 12 % 0 %

DK 83 % 37 % 14 % 1 % 0 % 13 % 2 % 0 %

DE 86 % 19 % 17 % 12 % 0 % 11 % 16 % 15 %

EE 81 % 0 % 6 % 0 % 0 % 19 % 0 % 0 %

IE 46 % 49 % 5 % 2 % 0 % 6 % 7 % 2 %

EL 95 % 1 % 1 % 0 % 1 % 3 % 1 % 0 %

ES 67 % 3 % 2 % 0 % 10 % 15 % 11 % 4 %

FR 88 % 3 % 5 % 0 % 1 % 12 % 10 % 0 %

HR 67 % 0 % 0 % 0 % 0 % 27 % 3 % 7 %

IT 92 % 3 % 1 % 0 % 0 % 7 % 0 % 4 %

CY 89 % 3 % 2 % 0 % 0 % 6 % 7 % 0 %

LV 88 % 0 % 0 % 0 % 0 % 12 % 0 % 0 %

LT 85 % 0 % 0 % 0 % 0 % 12 % 12 % 5 %

LU 80 % 12 % 7 % 6 % 0 % 13 % 8 % 4 %

HU 97 % 0 % 0 % 0 % 0 % 0 % 14 % 0 %

MT 83 % 18 % 0 % 1 % 1 % 6 % 3 % 2 %

NL 57 % 54 % 10 % 2 % 0 % 17 % 12 % 2 %

AT 87 % 7 % 2 % 0 % 2 % 14 % 10 % 1 %

PL 81 % 0 % 0 % 0 % 0 % 0 % 3 % 10 %

PT 74 % 2 % 1 % 2 % 5 % 14 % 14 % 1 %

RO 85 % 0 % 0 % 0 % 0 % 14 % 1 % 0 %

SI 88 % 0 % 0 % 0 % 0 % 8 % 5 % 5 %

SK 84 % 0 % 1 % 1 % 5 % 8 % 20 % 0 %

FI 78 % 5 % 9 % 0 % 1 % 15 % 7 % 1 %

SE 84 % 74 % 47 % 0 % 0 % 6 % 6 % 6 %

UK 65 % 60 % 20 % 0 % 0 % 0 % 4 % 3 %

IS 18 % 49 % 5 % 0 % 0 % 37 % 9 % 0 %

NO 50 % 31 % 4 % 0 % 0 % 26 % 5 % 11 %

CH 73 % 58 % 10 % 6 % 0 % 9 % 7 % 4 %

The main conclusion to be drawn from this data is that statutory old-age pensions (PENSTYP1) are by far

the most commonly received type of pension. In the EU as a whole, 81 % of those who declared receiving

some form of pension receive a statutory old-age pension. The only countries where this pension type is

not the most common are Ireland and Iceland, where more people receive occupational old-age pensions.

In the majority of countries, more people are receiving statutory old age pensions than are receiving all

the other types of pension combined. The only exceptions to this are Germany, Ireland, the Netherlands,

Sweden, the United Kingdom and the European Free Trade Association countries, whose data does not fit

the same pattern. Seven countries (Bulgaria, Greece, Italy, Hungary, Poland, Romania, and Croatia) show

a very low use of all types of pension other than statutory old-age pension schemes.


The following graph shows the frequency of different combinations of pensions received by the same

respondent. Unlike for the PENSION variable, where each respondent receiving a pension is counted

only once, this variable counts the number of pensions, thus allowing the number of each of the eight

types of pensions being paid to be quantified. As can be seen on the graph below, in many countries the

stacked bar combining different types of pensions is only slightly above 100 %, indicating that in these

countries it is rare for one person to receive several pensions.

Graph 2.1: Distribution of the PENSTYP1 to PENSTYP8 AHM 2012 variable (% of ‘yes’

answers in total answers given for each PENSTYPE)

Note: the maximum height of the stacked bar would be 800 % if each respondent received all eight types of pension at the same time.

The data for PENSTYP5, the unemployment pension, reflects the national mappings, as the majority of

countries reported that this specific type of scheme did not exist. Ireland, Italy and Lithuania confirmed

that unemployment pensions do exist in their countries, but they are not reflected in the data collection

(and are likely to feature only on a small scale).

As PENSTYP1 is the most frequently received type of pension, the other categories of the PENSTYPE

variable will be assessed in relation to PENSTYP1, i.e. by comparing the proportion of respondents

receiving: 1) only PENSTYP1; 2) PENSTYP1 in combination with other types of pensions; and 3) one

(or more) of PENSTYP2 to 8 but not PENSTYP1.

0%

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HU

EL IT CZ

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-28

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NO IS

PENSTYP1 PENSTYP2 PENSTYP3 PENSTYP4



Graph 2.2: PENSTYP1 considered in relation to PENSTYP2 to PENSTYP8 (% of

respondents with PENSION = 1)

The previous graph shows that, in the EU as a whole, the majority of people who receive a pension are

receiving only a statutory old-age pension. There are however significant differences at country level, as

the percentage of people receiving only a statutory old-age pension (out of those in receipt of some sort of

pension) ranges from over 90 % in Greece to less than 5 % in Iceland. With the exception of certain

countries (Sweden, Germany, the Netherlands and the United Kingdom), the phenomenon of combining

pensions from different types of schemes is not very common.

The next section analyses the population group not receiving any of the old-age pensions (PENSTYP1 to

4 = no). This group represents 12 % of those receiving a pension. Considering data for this group only,

the total of PENSTYP5 to 8 as a percentage of this population, (i.e. the total number of these four types of

pension being paid, per person not receiving an old age pension), is fairly constant across the EU.

Furthermore, the figure is near to 100 % for most countries, which shows that, in these countries, when a

person does not receive an old-age pension, it is unlikely that that s/he will receive more than one of types

PENSTYP5 to 8. Germany is the only exception to this general trend. In the graph below, data is ordered

by PENSTYP6. A full analysis on each of PENSTYP5 to 8 could also be carried out, but would need to

include people receiving old-age pensions as well. Analysis of combinations of pensions does however

have limited potential, because the patterns seen in each country’s data generally say more about the

organisation of the pension system in that country than about the respondents themselves.

0%

10%

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30%

40%

50%

60%

70%

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90%

100%

EL

LV

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BG IT

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CZ

EE

FR LT

MT

AT

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HR FI

PT

EU

-28

LU

ES

BE

DK IE DE

UK

NL

SE

CH

NO IS

PENSTYP1=yes, PENSTYP2 to 8=no PENSTYP1=yes, at least another PENSTYP=yes

PENSTYP1=no


Graph 2.3: Distribution of the PENSTYP5 to PENSTYP8 AHM 2012 variable if

PENSTYP1 to PENSTYP4 = ‘no’ (% of ‘yes’ answers in total answers given for each

PENSTYP)

Note: in the data for Sweden, PENSTYP8 also includes PENSTYP4. The maximum height of the stacked bars would be 400 % if each

respondent received all four types of pension at the same time.

The possibilities for comparison to the core data or to AHM 2006 are quite limited. Although the 2012

PENSTYP1 to 4 variables (different types of old-age pension) do overlap to some extent with the

AGEPENS variable from 2006, the 2006 variable covers a wider range of pensions (not just old-age

pensions), and its main purpose was to determine the age of the recipients, not the type of pension.

PENSTYP6 (disability pension) has some overlap with OTHBENF = 1 from 2006, but again, the

variables are far from being exactly equivalent, as the 2006 variable also covers sickness benefits and

disability pensions. The 2006 module did not include any variables parallel to unemployment pensions

and survivor’s pensions (PENSTYP5 and PENSTYP7 respectively).


The PENSTYPE variable is constructed as a combination of eight different variables. The information

captured by this variable is by its very nature difficult to compare across countries, due to the differences

in legal frameworks and pension systems. Furthermore, some of the types of pension do not exist in all of

the countries in the survey, which makes total results from across countries difficult to interpret in some

cases. In some countries, it was difficult to code this variable due to the complexity of the pension

system. Nonetheless, national statistical institutes generally reported positive experiences. The absence of

an LFS variable to compare to means that it is not possible to carry out a data-based assessment of the

quality of the data for this variable. As noted in the Austrian quality report, comparisons with

administrative data sources would also be difficult, given the particular conventions followed in

collecting this data.

Were the module to be repeated, it would be important to consider whether data on all the types of

pensions included in 2012 can reasonably be collected by an AHM and, for each type of pension, whether

the data can provide comparable and meaningful information at EU level. This variable created a

relatively heavy burden in terms of data collection, as eight yes/no variables had to be merged into one,

and for each of these variables a list of possible corresponding pension schemes had to be prepared. In

addition, in the absence of the code ‘no answer/do not know’, respondents and interviewers sometimes

had to take difficult yes/no decisions. Unfortunately, this variable offers limited potential for analysis at

0%

20%

40%

60%

80%

100%

120%

140%

EE

LV

CZ

RO

DK

BG

HR FI

LT

AT SI

FR

NL IT

CY

PL

EL

SE

LU

SK

MT

EU

-28

PT IE ES

BE

DE

HU

UK IS

NO

CH



EU level. Some countries (Austria, Slovenia and Norway) suggested that less time should be spent

classifying pension types, given that the resulting classification will differ greatly between countries and

is inconsistent with administrative data.

Should it be decided to simplify variables for a possible repeat of the module, one question to consider

would be whether analysing only old-age pensions would be sufficient, as this would still provide scope

for extensive analysis but without placing an unnecessary burden on respondents. The current breakdown

by scheme (statutory, occupational, personal, unknown) shows how much the organisation of pension

systems varies from country to country, even when only considering old-age pensions. In addition, non-

old-age pensions are often very similar to social benefits, and their analysis at any level higher than

country level is hindered by the divergent administrative classifications and terminology. The following

graph is one suggestion for how this variable could be simplified. It shows separately: (i) those who

receive only an old-age pension (irrespective of the type of old-age pension); (ii) those who receive an

old-age pension and a non-old-age pension (i.e. those receiving at least one of the types of old-age

pension and at least one of unemployment pension, disability pension, survivor’s pension, or other

pension of unknown type); and (iii) those who exclusively have a non-old-age pension. As these three

groups are mutually exclusive and jointly exhaustive, the sum of the three (the total height of the bar) is

the overall level of pension coverage in each country. Graph 2.4 shows that old-age pensions are the

dominant subset. They represent 87 % of all pensions in the EU.

Graph 2.4: Distribution of those receiving only an old-age pension, an old-age pension

and a non-old-age pension, and only a non-old-age pension (% of respondents with

PENSION = 1)

3. EARLYRET: Incidence of early retirement

Short description

The purpose of this variable is to determine whether those currently in receipt of an old-age pension took

early retirement or stopped working at normal retirement age.

Early retirement includes the following: anticipated old-age pensions, disability pensions, early retirement

pensions in the case of reduced ability to work, early retirement pensions for labour market reasons, early

retirement pensions due to seniority (long career or long contribution period) and early retirement

pensions for family reasons. In specific situations, full unemployment benefits and partial retirement

pensions can be considered as early retirement. Early retirement is defined in relation to the standard

0%

10%

20%

30%

40%

50%

60%

CZ SI

SK

RO PL

HR

EE

BG

FR

AT

LT

MT

UK

LV

SE

LU FI

EL

PT

EU

-28 IT

DK

HU

BE

DE

ES

CY

NL IE

CH

NO IS

Some type of pension, but no old-age pension

Old-age pension in combination with another pension type

Only old-age pension


retirement age for a given gender, occupational group, etc. People with low retirement ages should not be

systematically coded as receiving an early retirement pension, unless they were subject to specific early

retirement measures which go beyond what would otherwise be allowed in their profession.18 In cases

where a respondent is receiving multiple pensions, it is the one which started being paid first that

determines early retirement status.19

This variable does not have the same definition as the indicator from the European system of integrated

social protection statistics20 ‘anticipated old-age pension beneficiaries’. There are also differences

between this variable and the definition of early retirement in the LFS LEAVREAS set of variables, as

the focus of the LEAVREAS variable is on economic factors, such as difficulties in specific sectors of the

economy, while EARLYRET includes personal and labour market reasons.


This question was asked to all respondents receiving an old-age pension (PENSTYP1 = 1 or PENSTYP2

= 1 or PENSTYP3 = 1 or PENSTYP4 = 1).


This is a yes/no variable based on a concrete measure (early retirement). Respondents would be assumed

to remember the relevant information and be able to answer the question easily. This question was not

asked in 2006.

In Italy in particular, and also in a number of other countries, the complexity of the pension system

created uncertainty as to whether, in a given period, for individuals of a given age and given profession,

particular cases of retirement would count as early retirement or not. In the same countries, AGEPENS

was collected after EARLYRET, and interviewers could not assist respondents or check the consistency

of responses (this is why a suggestion is made in the report from Italy to consider collecting AGEPENS

before EARLYRET). In some countries, respondents receiving benefits from both statutory and

occupational schemes struggled to make the distinction between the two types, especially where there

was a misconception that employers make contributions to both pension systems. In Bulgaria, it was not

easy to communicate to respondents what ‘measures going beyond the normal rule for their profession’

are, in particular for professions with a lower retirement age (e.g. police officers). Finland reported

difficulties in interpreting early retirement in relation to part-time pensions.


Due to high non-response rates, the data from Germany and Norway must be used with caution. In the

case of Norway, this is because the question was not asked to people older than 66 years of age. The non-

response rate at EU level was 4 %.

Graph 3.1 shows how common it is to take early retirement in different countries, based on the proportion

of respondents answering yes and no.

18 Explanatory notes, pages 11-12.


20 The European system of integrated social protection statistics is built on the concept of social protection, or the coverage of precisely defined risks and needs including health, disability, old age, family and unemployment. It records the receipts and expenditure of the organisations or schemes involved in social protection interventions. See http://ec.europa.eu/eurostat/product?code=KS-RA-07-027 for more information.

Code Description

1 Yes

2 No




Graph 3.1: Distribution of the AHM 2012 EARLYRET variable (%)

The graph shows a very varied picture, with early retirement being close to non-existent in Bulgaria and

the Czech Republic, whilst applying to almost three in four pensioners in Italy and Ireland. Both Bulgaria

and Italy reported some difficulties in collecting information on this variable, as detailed in the previous

section. At EU level, around four out of ten people receiving an old-age pension had taken early

retirement. The proportion of people taking early retirement varies gradually across the graph, and there

are no striking outliers. No clear geographical pattern is evident.

Graph 3.2 analyses early retirement by gender. It shows that at EU level there are more men than women

taking early retirement (at EU level, around 60 % of those taking early retirement are male). The high

percentage of males amongst those taking early retirement in Malta is a result of the definition of the

target population for the module, which included gender. In general, the fact that more men than women

take early retirement is a direct consequence of the retirement age being higher for men than women in

many countries. This means that a man retiring before a certain retirement age would be counted as

having taken ‘early’ retirement, whilst a woman retiring at the same age might not be. The result can also

be explained by specific measures taken for certain occupations, in which the proportion of men and

women might not be equal. In 13 EU countries, early retirement is however more common among

women, with women representing over 60 % of those taking early retirement in Hungary, Latvia and

Estonia.

0%

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30%

40%

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60%

70%

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90%

100%IT IE ES

AT

PT

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LU SI

EU

-28

LV

MT

DE

SK FI

UK

RO

CY

LT

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EL

EE

CZ

BG IS

CH

NO

Yes No No answer


Graph 3.2: Proportion of men among EARLYRET = 1 (%)

It would be reasonable to expect a clear correlation between the rate of early retirement and the age at

which an old-age pension is first received. Graph 3.3 shows however that this is not the case — there is

only very weak correlation between these two variables.

Graph 3.3: The AGEPENS and EARLYRET variables plotted against each other (% and

age in years)

The LFS LEAVREAS variable provides information on the main reasons for leaving the last job or

ceasing business activities. Even if the definitions and the target of the two variables are different, the

comparison allows an assessment of the comparability of the data at EU level.

0%

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30%

40%

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60%

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90%

MT IT LU

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EU-28

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PT

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UK

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56 57 58 59 60 61 62 63 64 65 66

AH

M LF

S 2

012, E

AR

LY

RE

T, pro

port

ion o

f yes in

to

tal, p

er

cent

AHM LFS 2012, AGEPENS, average, in years


Graph 3.4: AHM 2012 EARLYRET = 1 among respondents who took early retirement

from their last job or from business activities (LEAVREAS = 06), (%)

Note: data from Germany and Norway is excluded from the analysis because of high non-response rates for the EARLYRET variable. Data

from Bulgaria and Iceland is not available for LEAVREAS = 6.

This graph confirms that the data should be interpreted with caution, as the correspondence between the

two variables (EARLYRET and LEAVREAS) differs significantly between countries, with Denmark, the

Czech Republic, UK and Finland showing the smallest overlap in respondents’ answers to the seemingly

related questions. In the case of Denmark, the reduced overlap is due to a problem in filtering for this

question, as people with PENSTYP1 = yes were not asked the question on early retirement. In Finland,

the low level of correspondence is likely to be a result of the different time horizon and precision of the

two variables: EARLYRET was asked after having collected precise information on several types of

pensions, while LEAVREAS was a more general variable, and the question was therefore probably easier

for respondents to answer.


The main challenge when using this variable is to provide meaningful information at aggregate level,

given that the variable itself is defined in relative terms. Retirement provisions which are very similar in

terms of what they offer and their conditions could be considered regular policy measures in one country

and early retirement in another. As a result, the label ‘early’ retirement can only be meaningful within a

group defined by occupation, age and gender, from a specific country. Then however, the sample from

this type of subgroup would be too small to allow detailed analysis.

The results for this variable show that patterns of early retirement vary greatly between countries, adding

a further dimension to the already divergent national situations and practices. This variable cannot easily

be benchmarked against other data sources (administrative or otherwise). As a result, it cannot be

interpreted in isolation, but only in the broader context of national data on pensions, pension age,

occupation, gender, etc.

Were the module to be repeated, further analysis should be conducted in order to establish whether this

variable could provide comparable and meaningful information at EU level.

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FR

EL

MT

EU

-28 FI

UK

CZ

DK

CH


4. AGEPENS: Age at which a person first received an old-age pension

Short description

The purpose of this variable is to determine the age at which the respondent started to receive his/her first

old-age pension.


This question was asked to all respondents receiving an old-age pension (PENSTYP1 = 1 or PENSTYP2

= 1 or PENSTYP3 = 1 or PENSTYP4 = 1).


This is the only numerical variable in the module, and as such allows more extensive analysis than is

possible for the other variables. There were some slight variations in the way in which data was collected:

in some countries, respondents were asked for the age at which they started to receive their first old-age

pension; in other countries, interviewers asked respondents for the year and month in which they started

to receive their first old-age pension and then calculated their age at that time from the year and month of

birth. These differences are not expected to have had a significant impact on the quality of the variable.

The variable is identical in content, but not in coding, to the equivalent variable included in the 2006

AHM module.


Due to the high non-response rate, the data from Germany and Norway must be used with caution. With

the exception of Germany, the response rate at EU level is very good, at 95 %. No major problems were

reported in collecting the data for this variable but a small number of respondents did have difficulties

recalling the date when they first received an old-age pension, especially in cases where an old-age

pension was first received after an unemployment pension.

Graph 4.1: Distribution of the AHM 2012 AGEPENS variable (average age in years)

Code Description

2 digits



52

54

56

58

60

62

64

66

SI

RO PL

SK

BG

HR

EL IT

UK

HU

AT

CZ

FR

LU

EU

-28

MT

EE

LT

LV

PT

BE IE DE FI

CY

ES

DK

NL

SE

CH IS

NO


The EU average for the age at which an old-age pension is first received is 59 years. The countries where

old-age pensions are received earliest are Slovenia, Romania, Poland, Slovakia, and Bulgaria. Among EU

Member States, the average age at which an old-age pension is first received is highest in Sweden, at

almost 64 years. Among all participating countries, Iceland and Norway have the highest average ages,

with the first old-age pension typically being received after 64 years. The variation across countries is

quite high for this variable, with eight years separating the highest (almost 65 in Norway) and lowest (less

than 57 in Slovenia) average ages. The geographical pattern in the data appears much like that seen in

graph 1.1 (PENSION). The correlation between these two variables is not surprising — when the average

age for starting to receive a pension is lower, the probability of receiving a pension and being in the AHM

target group will be higher.

Graph 4.2: Distribution of the AHM 2012 AGEPENS variable (average age in years), by

gender

Graph 4.2 displays the average ages at which respondents start receiving a pension, by gender. Countries

are ordered by the difference in years between the age of men and the age of women. In most EU

countries and two European Free Trade Association countries the average age at which respondents first

received an old age pension is higher for men than for women. A very clear east-west divide emerges,

with the difference between the average age for receiving a first old-age pension for men and women

being most pronounced (more than three years of difference) in Croatia, Slovakia, Slovenia and the Czech

Republic, and with smaller but still clearly visible differences in Poland, Hungary, Romania, Estonia,

Lithuania and Latvia. The countries where there is no difference at all between men’s and women’s

pension ages, or where women on average receive their first old-age pension at a higher age than men, are

western European or Mediterranean (Cyprus, Portugal, France, the United Kingdom, and Italy).

One possible way of assessing the quality of data for the AGEPENS variable is to compare it to the

expected duration of working life. The duration of working life indicator21 measures the number of years

a person aged 15 is expected to be active in the labour market throughout his or her life.

21 This indicator is derived from demographic data and labour market data. It is published online on the Eurostat database page as table reference

lfsi_dwl_a.

50

52

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58

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66

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EU

-28

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DE IE NL

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UK

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CH

NO

Men Women


Graph 4.3: AHM AGEPENS variable average by country, plotted against LFS 2012

working life indicator (duration of working life), age expressed in years

Graph 4.3 shows that there is a fairly strong correlation between these two variables, which provides

good grounds for believing AGEPENS to be measured accurately. As the length of working life

increases, so does the age at which respondents first receive an old-age pension.

Graph 4.4: AHM AGEPENS average by country, plotted against AHM PENSION (years

and %)

Graph 4.4 shows that, as the average pension age in a country increases, the number of respondents in the

target group of the AHM that receive a pension decreases, as would be expected. The fact that the

correlation between these two variables follows the expected pattern provides assurance that the quality

AT

BE

BG

CH

CY

CZ

DE

DK

EE

ES EU-28

FI

FR

EL HR HU

IE

IS

IT

LT

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NL NO

PL

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SI SK

UK

25

27

29

31

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37

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56 57 58 59 60 61 62 63 64 65 66

LF

S 2

012 in

dic

ato

r, D

ura

tio

n o

f w

ork

ing life, in

years

lfsi_

dw

l_a

AHM LFS 2012 AGEPENS, average age in years

BG PL

RO SI SK

EL HR

HU IT

UK AT

CZ

EE

EU-28

FR

LU MT LT LV

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ES CH

NL

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IS

NO

0%

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56 57 58 59 60 61 62 63 64 65 66

AH

M L

FS

2012,

PE

NS

ION

, pro

port

ion o

f yes to n

o,

per

cent

AHM LFS 2012, AGEPENS, average, in years


of the AGEPENS variable can safely be assumed to be good.

Graph 4.5. Difference in average AGEPENS between answer categories of EARLYRET

(EARLYRET = yes minus EARLYRET = no), by gender, difference expressed in years

Graph 4.5 shows the difference (in number of years) between the average age for AGEPENS for those

who did and those who did not use early retirement schemes. In Germany, Denmark, Belgium, Finland

and Norway, the average age at which respondents who did not use an early retirement scheme receive

their first old-age pension is lower than the average age for those who did use such a scheme. The

difficulties encountered in Germany, Denmark, Finland and Norway when collecting the EARLYRET

variable were mentioned in the previous section. The fact that for other countries the difference is a

positive value (as would logically be expected) is only an indirect argument to support the quality of the

data collected for the AGEPENS variable. The data should nonetheless be used and interpreted with

caution.

-4

-2

0

2

4

6

8

DE

DK

BG FI

HU

SK SI

RO

CZ

EE

EU

-28

FR

LV

LU

AT

BE

PL

NL

LT

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EL

HR

MT

CY

ES

PT

UK IE IT

NO

CH IS

Men Women


The following section, relating to the results in table 4.1 and graphs 4.6 and 4.7, uses unweighted data.

Table 4.1: AHM AGEPENS unweighted quartiles, mode, and mean, in years and curve

shape, by gender

The placement of the 25th, 50th (median), and 75th percentiles, together with the mode and the mean,

show the shape of the distribution of the age at which respondents start receiving their first old-age

pension. If the mean, median and mode are equal, the distribution is normal, as in the case of Lithuania

and Romania. Where the mean is the highest estimate of central tendency and the mode the lowest

estimate, the distribution is positively skewed, as in the case of Poland. Where the opposite is true (i.e.

the mean is the lowest estimate and the mode the highest), the data creates a negatively skewed curve.

This type of distribution is more common among the country data sets in the table above, with Ireland,

Latvia, and the Netherlands showing this shape curve. Only for two countries is the curve shape the same

for men and women (Ireland and Slovenia).

P25

P50

P75

Mean

Mo

de

Sh

ap

e

P25

P50

P75

Mean

Mo

de

Sh

ap

e

P25

P50

P75

Mean

Mo

de

Sh

ap

e

EU-28 56 60 62 59 60 57 60 62 59 60 55 59 60 58 60 Neg

BE 60 60 65 61 60 60 60 65 61 65 60 60 64 61 60

BG 55 58 60 58 60 56 60 62 58 60 55 57 60 57 55

CZ 57 59 61 59 58 60 61 62 61 62 56 58 59 58 58 Norm

DK 60 62 65 62 60 60 62 65 62 65 60 61 64 62 60 Pos

DE 60 61 64 61 60 60 62 64 61 60 60 60 63 61 60

EE 58 60 63 60 63 60 63 63 61 63 58 59 60 59 59 Norm

IE 58 63 65 61 66 Neg 58 63 65 61 66 Neg 58 62 65 61 66 Neg

EL 55 58 62 58 64 55 59 62 58 59 54 58 64 58 64

ES 60 63 65 62 65 60 63 65 62 65 60 64 65 62 65

FR 57 60 60 59 60 57 60 60 59 60 58 60 60 59 60

HR 55 58 60 58 60 58 60 63 60 60 Norm 54 55 60 56 55

IT 56 58 60 58 60 55 58 60 58 60 57 60 60 59 60

CY 60 63 63 62 63 60 63 63 61 63 60 63 65 62 63

LV 58 60 62 59 62 Neg 60 62 62 60 62 57 60 62 59 62

LT 59 60 62 60 60 Norm 60 62 62 61 62 58 60 60 59 60

LU 57 59 60 59 60 57 58 60 59 57 Pos 57 60 61 59 60

HU 57 59 61 59 60 59 60 62 60 60 Norm 56 57 60 58 57

MT 58 61 61 59 61 58 61 61 59 61 59 60 60 59 60

NL 60 63 65 62 65 Neg 61 63 65 62 65 Neg 60 62 65 62 65

AT 56 60 60 58 60 57 60 61 59 60 56 58 60 58 60

PL 55 56 60 57 55 Pos 56 60 61 59 60 55 55 59 56 55

PT 57 60 65 60 65 56 60 64 60 65 57 61 65 60 65

RO 55 57 59 57 57 Norm 56 59 62 58 62 Neg 55 57 58 56 57

SI 54 57 59 57 58 57 58 60 58 58 Norm 53 55 57 55 55 Norm

SK 55 57 60 57 55 60 60 62 60 60 Norm 55 56 57 56 55

FI 60 63 63 61 63 60 63 63 61 63 60 63 63 61 63

SE 61 63 65 63 65 61 63 65 63 65 62 63 65 63 65

UK 55 60 60 58 60 54 60 65 58 65 Neg 59 60 60 59 60

IS 62 65 67 65 67 62 65 67 65 67 62 65 67 64 67 Neg

NO 62 67 67 65 67 62 65 67 65 67 63 67 67 65 67

CH 62 64 65 63 64 62 65 65 63 65 62 64 64 63 64

All Men Women


Graph 4.6: Box-and-whisker plot for the AHM 2012 AGEPENS variable

A box-and-whisker plot is a powerful tool for illustrating both the central tendency of a data set as well as

the spread of the values. The length of the box represents the interquartile range (from the 25th to the

75th percentile). The square symbol inside the box marks the mean value. The horizontal line inside the

box indicates the median, and the vertical lines extending from the box show the minimum and maximum

values. The most obvious difference between the countries highlighted by the box-and-whisker plots is

that some of the lines are very long, and some are quite short. The data range is almost four times larger

for the country with the largest range than for the country with the smallest range.

In Malta, the highest age at which any respondents started to receive a pension was 65 years, whereas in

twelve other countries the highest age was 69 years, which is the highest possible maximum point, given

that the data was collected from a population aged 50 to 69. In Spain, France, Italy, Sweden, and the


United Kingdom, some respondents were recorded as receiving their first old-age pension in their early

thirties. An age of 30 years was set as a lower limit when editing the data for this variable, as any ages

below this would be very implausible and are highly likely to result from an error in data coding. It

should be noted that the spread of the data ranges does not show notable correlation with the average

pension age in each country. At the other end of the scale to the countries mentioned above, with very

low youngest ages and wide ranges, Iceland has the smallest range of ages over which respondents first

received an old-age pension, and the youngest age recorded was in the late fifties.

The interquartile range also differs between countries. As can be seen from table 4.1, Portugal has the

largest interquartile range, at 8 years. The countries with the shortest interquartile range, three years, are

Cyprus, Finland, France, Lithuania, Luxembourg, Malta and Switzerland. Relationships between the

various aspects of the data plots can also be analysed, e.g. it can be noted that France has a very wide

range but a very short interquartile range, whereas Greece has the exact opposite. This indicates that most

of the data from France is concentrated in the middle of the age range, with a few but very extreme

outliers, whereas Greece has no real outliers, but the age at which an old-age pension is first received is

much less concentrated in the middle of the age range.

Graph 4.7: Histogram with imposed Gauss curve for the AGEPENS variable, for all

participating countries

Graph 4.7 shows that the AGEPENS variable is not normally distributed. The far end of the tails are close

to a Gauss curve, but there are also two ‘peaks’, one in each of the two middle sections, on either side of

the centre of the distribution, as well as a very pronounced spike in the data at around 60 years of age.

The graph illustrates that, at European level, there is a high likelihood of receiving a pension for the first

time at the age of 60, with the other two ages where there is a concentration of pensions going into

payment being at around 55 and 65 years of age.


Graph 4.8: Distribution of the AHM 2012 AGEPENS variable, for all participating

countries, by gender (% in the male/female population receiving an old-age pension for

the first time)

Graph 4.8 shows that, although the clear peak in the data for both men and women is at 60 years, there

are proportionally more women than men first receiving an old-age pension at this age. The age at which

men most frequently start receiving an old-age pension is 60 followed by 65, whereas women most often

first receive an old-age pension at 60, and next most often at 55. These three main data points together

account for almost half of the total volume of data. Almost four times as many women start receiving

their first pension at the age of 60 than at the age of 65, whereas for men the equivalent figure is only 1.4

times. There is a similar pattern between the ages 55 and 65, in that women more often start receiving a

pension at 55 than at 65, whereas men are three times more likely to start receiving their first old-age

pension at 65 than at 55 years of age.

Graph 4.9: AHM AGEPENS variable in 2006 and in 2012 (average age in years)

0

5

10

15

20

25

30

35

30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68

Men Women

AT

BE

BG

CY

CZ

DE

DK

EE

ES FI

FR

EL HU

IE

IS

IT

LT

LU

LV

MT

NL

NO

PL

PT

RO

SE

SI

SK

UK

55

57

59

61

63

65

67

55 57 59 61 63 65 67

LF

S A

HM

2012,

AG

EP

EN

S, avera

ge in

years

, per

countr

y

LFS AHM 2006, AGEPENS, average in years, per country


This variable was also included in the 2006 AHM, although the question asked then was about the age at

which the respondent started receiving an individual retirement pension, and not an old-age pension.

Graph 4.9 provides a scatter plot of the two results against one another.

A deviation of plus or minus one year must be allowed for. This means that the results are consistent for

most countries.

Slovenia explained in their quality report for 2012 that the pension system has been under revision since

2006, and comparability has therefore been compromised, albeit unavoidably.

Table 4.2: Confidence limits for the AHM 2006 and AHM 2012 AGEPENS variable, in

2006 and 2012, for the outliers in graph 4.9 (average age in years)

As can be seen from the overview of the confidence intervals, the changes observed for Latvia and

Norway cannot be explained by wider confidence intervals. Comparative analysis between 2006 and

2012 should therefore be avoided for these countries.


Response rates were very good overall for this variable. None of the national quality reports indicate any

major deviations from the question or problems that would have an impact on comparability. Suggestions

for improvement came from Austria, whose report suggests that personal and occupational pensions

should have been excluded in the filter for this question, or that respondents should at least have been

asked about these types of pension separately from the other old-age pensions, as this would facilitate

comparison with administrative data. France and Greece report that some respondents had difficulty

determining or recalling the exact age at which they started to receive an old-age pension. These ideas

could be taken into consideration were the variable to be used again in a future module, but the general

assessment of this variable remains that the data is of good quality and few problems were reported in

collecting it.

5. REASNOT: Main reason for not remaining in employment longer

Short description

The purpose of this variable is to identify the main factor that caused the respondent to leave the labour

market. The moment of leaving the labour market is defined as the moment at which the respondent left

their last job. The list of possible reasons for not remaining in employment for longer included the

following: favourable financial arrangements, inability to find another job, reaching the maximum

retirement age, reaching pension eligibility, job-related reasons, and personal reasons. Only the main

reason was recorded. Where a respondent spontaneously answered ‘early retirement’, the question was

repeated in order to elicit the reason for taking early retirement.22


This question was asked to all inactive respondents (simplified ILO status: WSTATOR = 3, 5 and

SEEKWORK = 3) receiving a pension (PENSION = 1).


Mean estimate Mean estimate

Latvia 57.4 57.1 57.7 59.3 59.1 59.6

Slovenia 60.8 60.5 61.1 56.6 56.5 56.8

Norway 60.6 60.1 61.2 64.9 64.7 65.0

2006 2012

95 % Confidence limits 95 % Confidence limits



Data on a similar question was collected in 2006, under the AHM 2006 REASRET variable. Despite the

difference in name (‘Main reason for not remaining longer in employment’ for REASNOT in 2012 and

‘Main reason for retirement or early retirement’ for REASRET in 2006), the objective of the 2006

variable23 was the same as that of the 2012 variable, namely to establish the main factor that caused the

respondent to stop working, using a choice of responses better suited to older people. In 2006 however,

exit from the labour market was understood as being the time of retirement, which could affect the

comparability of the two sets of data.

The fact that this variable refers to the moment of leaving the last job detaches it to a certain extent from

the analysis of pensions, and could theoretically render the data less sensitive to variations resulting from

national definitions of pensions. For example, respondents who continued working after starting to

receive a pension from their ‘main employment’, e.g. taking a small part-time job or casual work, should

have referred to the moment of leaving their last job in their answer, even if the moment of retirement

could have been defined as the moment of starting to receive a pension. This nuance limits the

comparability of the 2006 and 2012 modules to those respondents who stopped work at the same age as

when they first received a pension. As seen at the end of the section on the AGEPENS variable, only

seven of the 31 participating countries show no difference between the average age of leaving the last job

(core 2012 data) and the age of first receiving a pension (AHM 2012 data). In practice however, the

overlap between the 2006 and 2012 variables might have been greater than intended — given that, in

most countries, questions on the age at which respondents first received a pension and on the reason for

leaving their last job were asked consecutively, and because several of the possible responses referred to

pensions and retirement, it is likely that some respondents were actually answering in reference to the

moment of leaving the job that provided them access to a pension.

The purpose of the 2012 variable is therefore identical to the LFS LEAVREAS variable on the main

reason for leaving the last job or ceasing business activities. The only slight difference is in the

populations being asked this question. For those respondents answering both the LFS LEAVREAS

variable and the AHM REASNOT variable, in is understandable that there may have been some

confusion.

A number of questions were raised during the planning24 of the module on the difference between codes 3

and 4. The intention of codes 3 and 4 was to distinguish between those who are forced to leave the labour

market because of their age and those who leave the labour market as soon as their age allows it. In

several countries, for example the Czech Republic, code 3 was not relevant. Most countries have however

included the response category in their questionnaire, because it could in principle have been applicable

to a small minority of respondents, or in specific sectors of activity or occupations, for example as a result

23 http://ec.europa.eu/eurostat/product?code=KS-RA-08-012


Code Description

1 Favourable financial arrangements to leave

2 Lost job and/or could not f ind a job

3 Had reached the maximum retirement age

4 Had reached eligibility for a pension

5 Other job-related reasons

6 Ow n health or disability

7 Family or care-related reasons

8 Other




of specific collective agreements between trade unions and employers.25 Finland reported problems in

translating codes 3 and 4. In general, response codes 3 and 4 posed some problems for respondents in

terms of understanding.

Austria and Italy reported that they added additional possible responses. In Italy, the response ‘fear of

pension age being raised’ was included and has been combined with the ‘other reason’ category when

coding the data. Even without additional responses being offered, this question was quite challenging for

respondents. There is a clear risk of low data comparability. The inherent subjectivity of the question

should also not be ignored — where there is a mix of reasons for not remaining in employment longer, it

is the respondent who decides which was the main reason.


Data from Germany, Belgium and Iceland includes a significant proportion of non-responses, and should

therefore be interpreted with caution. In Belgium, this was due to the data collection methods used.

A variable with ten possible values and a distribution that differs markedly between participating

countries is challenging to interpret in any form.

Graph 5.1: Distribution of answer categories for the AHM 2012 REASNOT variable (%)

Graph 5.1 shows the possible responses, ordered according to the proportion of respondents choosing

each at EU level. Two reasons emerge clearly as the most common ‘main reasons’ for stopping work:

‘had reached eligibility for a pension’ (37 % at EU level) and ‘own health problems or disability’ (21 % at

EU level); the former was also used as the basis for ordering the countries. Not counting the non-response

category or the response ‘own health problems or disability’, the proportion of respondents choosing

‘reached eligibility for a pension’ is equal to the sum of the remaining six answer categories. Nonetheless,

the graph shows a range of values for the proportion of respondents choosing this response across the EU,

from over 85 % in Malta and the Czech Republic to 12.9 % in Estonia. In 13 of the 31 countries, more

people answered ‘own health problems or disability’ than answered ‘reached eligibility for a pension’.

Moreover, graph 5.1 shows considerable differences between countries for the responses related to age

(codes 3 and 4). This could reflect an actual difference, but could also have resulted from the imperfect

choice of possible responses, which respondents found difficult to understand. There is no comparable

2006 data to use for benchmarking. The existing LFS variables refer to the last job, but when a

25 Explanatory notes, page 14, provides a full explanation for code 3.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

MT

CZ SI

BG

HU

EL

PL

AT

LU

FR

SK IT

RO

HR

EU

-28 FI

DK

CY

BE

LV

UK

SE

ES IE LT

NL

PT

DE

EE

NO

CH IS

Had reached eligibility for a pension Own health or disability

Had reached the maximum retirement age Lost job and/or could not find a job

Favourable financial arrangements to leave Other

Other job-related reasons Family or care-related reasons

No answer


respondent actually retired from an earlier rather than from the most recent job, it is not easy to confirm

the previous occupation or sector. It may be the case that this variable has failed to provide comparable

information on the role that age plays in the decision to retire.

Graph 5.2 provides an analysis of the frequency of main reasons for not remaining in employment longer,

by gender. At EU level, answers were quite similar for men and women, with two exceptions: ‘family

reasons or care related reasons’ was a more frequent answer among women (and not only at EU level but

also in each individual EU country), while ‘favourable financial arrangements for leaving’ was more

frequently chosen by men. These results match the distribution by gender seen in other core variables on

reasons for reduced participation in the labour market.

Graph 5.2: Distribution by gender of the responses for the AHM 2012 REASNOT

variable, EU-28 (%)

Unfortunately, there is no possibility for comparison between the 2012 and 2006 data, primarily because

the response ‘had reached eligibility for a pension’ was not included in 2006, but was the most frequently

chosen one at EU level in 2012.


There was a good response rate for this variable overall, with the exceptions of Belgium, Germany and

Iceland. None of the participating countries reported major problems in collecting data for this variable.

Two responses emerge clearly as being the predominant reasons for not remaining in employment longer:

‘reached eligibility for a pension’ and ‘own health problems or disability’. This may indicate that the

question was asked in a similar way across the participating countries in 2012. Moreover, the analysis by

gender provides the same main results as were obtained from similar core LFS variables. Country

differences are significant however. Given that the aim of the variable was to collect data on eight main

reasons which are similar to, but not identical to the responses offered for the LEAVREAS variable, full

comparability between countries cannot be guaranteed. Comparison with 2006 is also not possible.

Were the module to be repeated, consideration would need to be given to whether this variable can add

significant relevant information to the information already collected under the LFS LEAVREAS variable.

Guidelines issued on the basis of recent analysis performed as part of the overall exercise of evaluating

the current system of AHMs advise against the practice of adding a variable to the AHM whose main

purpose is to increase the target population of an LFS variable.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

No answer

Other

Family or care-related reasons

Own health or disability

Other job-related reasons

Had reached eligibility for a pension

Had reached the maximum retirement age

Lost job and/or could not find a job

Favourable financial arrangements to leave

Men Women


6. WORKLONG: Wish to remain in employment longer

Short description

The purpose of this variable is to establish whether the person would have preferred to remain in

employment for longer (be it in their last or any other job) at the point of leaving the labour market.

The variable is designed to reflect the preference of the respondent at the moment of leaving the last job,

so spontaneous answers such as ‘I would have liked to continue working but it was not possible for me to

do so’ should be coded26 as ‘yes’.


This question was asked to all inactive respondents (simplified ILO status: WSTATOR = 3, 5 and

SEEKWORK = 3) receiving a pension (PENSION = 1).


This variable is binomial as the question asks for a yes or no answer. The purpose of the variable was

sufficiently self-explanatory and there were no questions about it while the survey was being carried out.

The variable is subjective however and hypothetical, as it assumes that, in principle, it would have been

possible for all respondents to remain in employment longer. The reference to ‘any other job’ in the

definition of the variable added an extra level of complexity. This was most likely included to cover cases

where a ‘last job’ was not easy to identify, e.g. if a respondent had had a succession of short contracts or

spells of inactivity combined with periods of employment. When interpreting the data, users need to keep

in mind that for most respondents the variable relates to the last job they had, and measures respondents’

desire to continue working in the same job. For those with a less well-defined moment of ‘transition’

from a last job to retirement, the variable reflects the general desire to have a job, or to continue working.

One country (Italy) reported some problems in answering the question for people who are economically

inactive and only receive survivors’ pensions. Despite this, the non-response rate for Italy is only 1 %.

Nonetheless, even though such cases represent only a small proportion of the population, they provide a

useful example of illustrating the imperfect overlap between the labour market and those in receipt of

pensions. This also applies to other variables, such as REDUCHRS or REASNOT, albeit to a limited

extent.

In Romania, data for this variable was not collected for those who answered ‘had reached eligibility for a

pension’ (code 4) to the question for the REASNOT variable. The reason for this is that code 4 in

REASNOT, when translated as ‘preference for leaving the labour market when reaching eligibility for a

pension’27, can be seen as equivalent to WORKLONG code 2 ‘does not wish to remain longer in

employment’. As the question was very sensitive to the exact wording chosen, the data should be

interpreted with caution. It is plausible that, in some cases, choosing code 4 for the REASNOT question

could have triggered a negative answer to the question on the wish to remain in employment longer. At

EU level (see graph 6.2), only approximately 12 % of those leaving the labour market on reaching the age

of eligibility for a pension state that they would have liked to continue working for longer, thus possibly

reflecting this. As detailed in the previous section, it is the REASNOT variable that is likely to suffer

from the lack of comparability of its response options, rather than the WORKLONG variable.


27 The formulation used in the Romanian questionnaire.

Code Description

1 Yes

2 No





Due to the high non-response rate, the data from Belgium, Germany, Greece and Iceland must be used

with caution. In Belgium, the high non-response rate was a result of the data collection methods used. In

Greece, it was more related to respondents’ own lack of certainty about their answer, in cases where the

situation at the time of leaving the labour market had been complicated, and possibly difficult.

Graph 6.1 shows that a majority of retired people receiving a pension in Europe did not wish to remain in

employment longer at the time of leaving their last job. The EU average for wanting to continue working

is slightly above one quarter (28 %) of respondents, whereas two thirds said they had not wanted to

continue working at the point of leaving the labour market. The remaining 6 % gave no response to the

question. There are only two countries where the proportion answering ‘yes’ to this question was over

50 %, Portugal and Estonia. In these countries therefore, the majority of those receiving a pension stated

that they would have liked to continue working at the point when they left the labour market. At the other

end of the spectrum, in Poland and Slovenia less than one in ten respondents answered ‘yes’, indicating

that they would have liked to continue working for longer. There is no obvious geographical pattern in

the results.

Graph 6.1: Distribution of answer categories for the AHM 2012 WORKLONG variable

(%)

Even though this variable is not perfectly correlated with the REASNOT variable, it would be reasonable

to expect there to be a relationship between a wish to stay longer in employment and the main reasons for

having left. An analysis at EU level (see graph 6.2) shows that, in general terms, the two variables are

related: those who left the labour market because they could not find a job are more likely to have wished

to stay in employment than the ones leaving as soon as they could reach eligibility for a pension. There

are no noticeable gender patterns. It should be noted however that the level of correlation is weaker than

would be expected, and the pattern does not hold at country level in many cases. For example, among

those who were ‘forced by law to leave their job’ (REASNOT = 3), the proportion answering ‘yes’ to

wishing to continue working (WORKLONG = 1) was expected to be higher. The fact that this

inconsistency arises when two variables are combined (i.e. the answers to one question are analysed for a

specific group defined by their answer to the other), supports the conclusion that the REASNOT variable

has limited comparability, for the reasons detailed in the previous section.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

PT

EE

CY

ES

UK

DK

LV FI

IE AT

MT

HR

BE

FR

LU

SE

NL

EU

-28 IT SK

DE

CZ

RO

HU

BG EL

LT SI

PL IS

CH

NO

Yes No No answer


Graph 6.2: Percentage of AHM 2012 WORKLONG = 1 variable, by answering

categories of AHM 2012 REASNOT variable and by gender, EU-28 (%)

There was no parallel variable in the 2006 module, and there is no link to any of the core variables. There

are therefore no alternative ways of making a comparative analysis of this variable.


Data for this variable was relatively easy to collect. The question was, however, subjective, hypothetical

and very sensitive to translation wordings, and for these reasons its comparability at EU level cannot be

fully guaranteed. Further testing of the variable would be recommended if it is to be included in a repeat

of the module.

7. REDUCHRS: Reduced working hours as a step towards full retirement

Short description

The purpose of this variable is to determine whether the respondent reduced his/her working hours in a

move towards full retirement, and, in cases where an old-age pension is being received, whether working

hours were reduced before or after the respondent started receiving his/her first old-age pension. Both

voluntary and involuntary, and both formal and informal reduction of working hours are relevant for this

question. A transition from a full-time to a part-time job is considered to constitute a reduction in working

hours.

In the case of respondents who are economically inactive, the period of reference for the question is the

time before the respondent left their last job. Where respondents are employed, the reference period is the

present. If respondents are in employment and not receiving a pension, code 2 cannot be applicable, and

as a result, the question becomes a yes/no question for this category of respondent. Similarly, if

respondents are inactive and receiving a pension (PENSION = 1) but not an old-age pension, the same

applies and the question becomes a yes/no question.



This question was asked to all respondents who were employed (ILO status: WSTATOR = 1, 2) and aged

55-69, and to all respondents who were inactive (simplified ILO status: WSTATOR = 3, 5 and

SEEKWORK = 3), receiving a pension (PENSION = 1) and aged 50-69.


In reviewing the survey, it became apparent that the wording of the variable had been too complicated,

and that the filter applied for the variable was also too difficult to manage. It was often difficult to

translate the phrase ‘in a move towards full retirement’, and this sometimes resulted in an expression

being used which was too abstract for respondents to understand. In Slovakia, Latvia and Croatia, the

possibility of reducing working hours as a way of leaving the labour market more gradually does not

exist, and therefore the answer was automatically code 3. Furthermore, respondents sometimes struggled

in distinguishing between codes 1 and 2, the correct choice being dependent on the moment at which a

respondent starts receiving his/her first old-age pension.

This question was asked to employed respondents with or without a pension, aged 55-69, and to inactive

respondents, with a pension, aged 50-69. The possible responses offered should have been different for

those receiving an old-age pension, and those not receiving a pension or receiving a pension other than an

old-age pension. Managing these filters proved to be difficult. It was suggested that the filters (age and

type of pension) could be expanded in order to facilitate data collection.


Due to the high non-response rate, data from Germany, Ireland, Greece and the United Kingdom must be

used with caution. The high non-response rate in Ireland was due to a problem with filtering which meant

that respondents who were working but not receiving a pension were not asked the question. The high

non-response rate in the United Kingdom was also due to a problem with filtering which meant that

inactive respondents were excluded. The overall non-response rate at EU level is relatively high at 11 %.

Reducing working hours as a step towards full retirement is not a common practice at EU level, with a

large majority of respondents answering ‘no’ to this question. The next most frequent of the responses

was ‘don’t know or no answer’. In view of this, any further breakdown of the ‘yes’ answers would be

problematic. The remaining categories are so small as to be almost meaningless to analyse. The data

should therefore be interpreted with care.

Code Description

1 Yes, before receiving the first old-age pension

2 Yes, since or after receiving the first old-age pension

3 No




Graph 7.1: Distribution of answer categories for the AHM 2012 REDUCHRS variable

(%)

Graph 7.1 shows the distribution of this variable in the participating countries, ordered by the proportion

of ‘yes’ answers. Only five of the 31 countries (the Netherlands, Belgium, Denmark, Finland and

Switzerland) have values of 10 % or more for the response ‘yes, before starting to receive the first old-age

pension’, with 18 % of respondents choosing this response in the Netherlands and 15 % in Belgium. In a

further seven countries, the proportion of respondents answering ‘yes, before starting to receive the first

old-age pension’ is between 5 % and 9 %. For the remaining 19 countries, the concept of reducing

working hours as a step towards retirement is virtually unknown. The response ‘yes, since starting to

receive the first old-age pension’ was chosen by over 5 % of respondents in four countries, with Finland

and the Czech Republic recording the highest proportion of people in this category, both 8 %. In 20

countries, 2 % or less of respondents chose this answer.

Graph 7.2 confirms that the possible responses offered for this variable were too detailed and that the

variable was very dependent on translation nuances. It is difficult to interpret the statistics on those who

did reduce their working hours (i.e. in order to assess the proportion of respondents reducing working

hours before and after starting to receive the first old-age pension), as the values at EU level are too low.

In addition, it is somewhat surprising that among respondents with a part-time job there is still a clear

majority (82 % at EU level) answering ‘no’ to the question of whether they reduced their working hours

as a step towards full retirement. The result is plausible however, as, for these respondents, the reference

period is the present, and in many cases, respondents reduced their working hours before making

retirement plans. Nonetheless, some doubt remains as to the value this variable adds to the survey.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

NL FI

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BE

DK

CZ

MT

PL

FR SI

UK

PT

LT

EE

AT

EU

-28

LU

EL IE

BG

RO

CY IT

DE

ES

HU

LV

SK

HR

CH IS

NO

No answer

Yes; since or after receiving the first old-age pension

Yes; before receiving the first old-age pension

No


Graph 7.2: Distribution of the AHM 2012 REDUCHRS variable, by economic activity and

type of job, EU-28 (number of people, in millions)

In 2006, the AHM included a variable with the same name but different filter conditions and possible

responses. It is not possible to apply the 2012 filter to the 2006 data exactly, or vice versa, because the

2006 data does not have the PENSION variable used in 2012, and the age group was more restricted in

2012 than in 2006. For the sake of comparison, we can however combine the responses into ‘yes’, ‘no’,

and ‘no answer’, and thus obtain more comparable, broader groupings.

Graph 7.3: The AHM REDUCHRS variable in 2006 and 2012, proportion of ‘no’ answers

(%)

0

5

10

15

20

25

30

Full-time job Part-time job Inactive personsreceiving a pension

No

Yes; since or after receiving the firstold-age pension

Yes; before receiving the first old-age pension

EU-27

BE

BG

CZ DK

DE

EE

IE

EL

ES

FR

IT

CY LV

LT

LU

HU

MT

NL

AT PL PT

RO SI

SK

FI SE

UK

IS

NO

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

AH

M L

FS

2012,

RE

DU

CH

RS

, per

cent of 'n

o'

answ

ers

, per

countr

y

AHM LFS 2006, REDUCHRS, per cent of 'no' answers, per country


There is a clear cluster in the upper right corner, which simply confirms the rarity of the practice of

reducing working hours as a step towards retirement at EU level, both in 2006 and in 2012. However,

there are also some significant outliers (Bulgaria, Island, Germany, Slovenia, Norway, Ireland and the

United Kingdom, confirming that comparison of this variable over time should be avoided.


This variable provides very little comparable information at EU level. The form in which the variable was

set up was clearly not adapted to the actual distribution of the variable. Were this variable to be included

in a repeat of the module, it would be advisable to restructure it.

8. STAYWORK: Main reason for remaining in employment

Short description

The purpose of this variable is to identify the main factor causing a person who receives a pension to

remain in employment.


This question was asked to all respondents who were employed (ILO status: WSTATOR = 1, 2) and

receiving a pension (PENSION = 1).


The purpose of this variable is to find out why people receiving a pension want to continue working. In

several countries, the question on the main reason for staying at work was asked without giving any

explanation of its purpose, and, as a result, most respondents could not see the link between the question

and the fact that they had already declared receiving a pension. In other countries (Austria, Cyprus,

Germany, Spain, Hungary, Italy, Luxembourg, the Netherlands, Portugal, Romania and Switzerland) the

context of the question was clearly explained, and the question was formulated as follows, or similarly:

‘you are receiving a pension or a pension-type benefit. Why are you still working?’. In Estonia, the

question was formulated differently, as: ‘Do you have a financial incentive for continuing to work now

that you are receiving a pension? If yes, please give details’. It can therefore be concluded that the

questionnaires are not fully comparable between countries, and this can be expected to have an effect on

the answers.

The possible reasons proposed to the respondents are classified either as being of a financial nature

(codes 1 to 3) or of a non-financial nature (code 4).

No countries reported significant problems with this variable, but there was a suggestion that code 4

should have been split, with personal fulfilment offered as a separate answer.


Due to the high non-response rate, the data from Germany, France, Croatia and Switzerland must be used

with caution. At EU level, the non-response rate is 11 %, which signals that the data should be analysed

with care.

Graphs 1.3 and 1.4 showed the proportion of respondents who are both employed and receiving a

pension, at EU level and at country level. Less than 7 % of the EU population aged 50-69 is in

employment while at the same time receiving a pension. Out of the total population of the module, 8 %

Code Description

1 To establish or increase future retirement pension entitlements

2 To provide sufficient personal/household income

3 Combination of 1 and 2

4 Non-financial reasons, e.g. w ork satisfaction




fall into this category. At EU level, there are significant differences between countries: over 15 % of

respondents are in work and receiving a pension in Estonia, Sweden and the United Kingdom, while the

equivalent percentage is less than 4 % in Greece, Spain, Hungary and Belgium. In interpreting the results

for this variable, it is important to bear in mind not only the different levels of labour market

participation, but also the differences between pension systems.

Graph 8.1: Distribution of answer categories for the AHM 2012 STAYWORK variable

(%)

Graph 8.1 presents the proportion of respondents choosing financial reasons (income, future pensions, or

a combination of the two) and non-financial (as for instance job satisfaction). The sum of all financial

reasons is used for ordering the countries in the graph. The proportion of respondents choosing each of

the individual responses within financial reasons is also shown, with the most frequently chosen reason

‘to provide sufficient income’ (code 2) at the base of the bars. In all countries, the current income

situation is more important than the future pension situation, with 37 % of respondents at EU level

choosing the response ‘to provide sufficient personal or household income’ as their main reason for

continuing work, and only 7 % choosing ‘to create or increase future retirement pension entitlements’.

The different financial reasons combined account for 59 % of responses at EU level. Non-financial

reasons were chosen by 29 % of respondents. Geographically, the split is almost a perfect east and south

versus west and north divide: financial reasons feature more strongly in the east and south while non-

financial reasons are more common in the north and west. The only exception to this pattern is Slovenia,

which fits more into the north-west group.

The data can be analysed in more detail at EU level by the type of job (full-time versus part-time) of

respondents who are working, and by whether respondents are receiving a pension. Graph 8.2 shows that

part-time work is more associated with staying in employment mainly for non-financial reasons, while

full-time work tends to be linked to financial reasons (and among them, the wish to establish future

pension entitlements). This result is not surprising, and is driven by those countries where part-time work

among the elderly is a frequent phenomenon, which is not the case in all EU countries.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

RO

SK

EL

EE

LT

LV

HU

BG PL

CZ

PT

CY IT ES

MT

HR

EU

-28

UK IE FI

BE

NL

FR

DE

LU

AT

SE SI

DK IS

CH

NO

No answer

Non-financial reasons; e.g. work satisfaction

Combination of 1 and 2

To establish or increase future retirement pension entitlements

To provide sufficient personal/household income


Graph 8.2: Distribution of the AHM 2012 STAYWORK variable, by type of job (full-time

or part-time), EU-28 (number of people, in millions)

In 2006 the FININCTV variable (main financial incentive to stay at work) collected information on

reasons for continuing work after starting to receive a pension, with a similar split between financial and

non-financial reasons. The filter for the question was reasonably similar: in 2006, respondents were

filtered on whether they receive an individual retirement pension, in 2012 on whether they receive a

pension. The possible responses were different however, in that they focused on financial incentives in

2006, the choices being ‘for a future pension’, ‘for current income’, and ‘none’. This factor, combined

with the size of the group answering the question (less than 10 % at EU level) suggests that analysis of

trends between 2006 and 2012 at EU level would not be advisable. Plotting the percentage of respondents

choosing non-financial reasons against each other for the two years confirms this.

0

0.4

0.8

1.2

1.6

To establish orincrease future

retirement pensionentitlements

To provide sufficientpersonal/household

income

Combination of 1 and2

Non-financialreasons; e.g. work

satisfaction

No answer

Full-time job Part-time job


Graph 8.3: FININCTV 2006 versus STAYWORK 2012, non-financial reasons (%)


The purpose of this variable is to provide insight into the reasons why people continue to work even after

starting to receive a pension or pension-type benefit. The picture that emerges is that financial reasons are

more important in south-eastern European countries and less important elsewhere. Pensions are not

always comparable however as they can be old-age pensions but can also be pensions of other types.

Being in employment can also mean different things, as some people work full-time and others work part-

time. The fact that respondents who work and receive a pension represent only 7 % of the EU population

precludes any more detailed analysis by comparable pension type or working hours. In view of this, we

can conclude that this variable contributes little information on the patterns of working while receiving a

pension. It should be subject to further testing (as part of which consideration should be given to the

nuances of the questionnaire) before being included in a future module.

9. PLANSTOP: Plans to stop working in the future

Short description

This is a forward-looking variable, intended to estimate the planned timing of ceasing all paid work or

business activities entered into for profit. Spontaneous answers such as ‘do not have a planned age’ or

‘not yet decided’ should have been collected as ‘blank’ answers.


This question was asked to all respondents who are employed (ILO status: WSTATOR = 1, 2) and

receiving a pension (PENSION = 1).

EU-27

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT CY

LV LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK IS

NO

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

AH

M L

FS

2012,

ST

AY

WO

RK

, non

-fin

ancia

l m

ain

re

ason, per

countr

y

AHM LFS 2006, FININCTV, non-financial main reason, per country



The most frequently occurring response is ‘no answer or does not know’, which makes this variable less

useful than the others. At EU level, 35 % of responses were coded as ‘blank’. The high non-response rate

is consistent with the comments from the participating countries, eight of which reported having problems

in collecting data for this variable, either because proxies were answering on behalf of respondents and

therefore did not always know their plans for the future, or simply because the respondents had not

planned or could not plan at what age they would retire (due to reforms to pension systems or for other

reasons). Unfortunately, the ‘blank’ code does not allow a distinction to be made between those who

meant that they had no planned age for retirement and those who refused to answer. Moreover, there are

countries where no or almost no respondents were coded as ‘blank’, suggesting that there may have been

different approaches taken in dealing with or coding ‘no response’. The analytical potential of this

variable is therefore very limited.

Offering ranges of years as response options may have helped a little, but the assumption of the existence

of a ‘plan’ going beyond the next decade may also have been one of the reasons for some respondents not

being able to give a response. In general, forward-looking and hypothetical questions often present

challenges in a survey.


Due to the high non-response rate, the data from Bulgaria, Germany, Estonia, Ireland, Greece, Spain,

France, Croatia, Italy, Hungary, the Netherlands, Austria, Portugal, Romania, Sweden, the United

Kingdom, Iceland, Norway and Switzerland must be used with caution.

Graph 9.1 Distribution of responses for the AHM 2012 PLANSTOP variable (%)

Code Description

1 In up to 1 year

2 In more than 1 year up to 3 years

3 In more than 3 years up to 5 years

4 In more than 5 years up to 10 years

5 More than 10 years



0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

BE

CY

DK

LT

MT

PL SI

SK

CZ FI

LV

LU IE AT

NL

EE

PT

FR

UK

EU

-28

EL

DE

HU

SE

BG IT ES

RO

HR

CH

NO IS

< 1 year 1 to 3 years 3 to 5 years 5 to 10 years > 10 years No answer


Graph 9.1 shows that the most common response is not an actual answer but is the ‘blank’ code. Croatia

has the highest non-response rate, at 95 %, followed by Romania, at 83 %. Only twelve of the

participating countries have a response rate higher than 85 %. It is clear that analysis is, at best, only

possible at country level.


One in three respondents in the EU has chosen not to answer the question about future retirement plans,

either because they do not have a plan or because they did not feel comfortable talking about such plans.

The problems with this question could also have been due to a badly chosen target group. The report from

Italy suggested that the question should be asked to all respondents currently in employment, and not just

to those receiving a pension. This is clearly the least successful variable in the module, and should

therefore not be repeated. As a general rule, variables on respondents’ future plans should be avoided.

10. BUILDPEN: Information on pension rights built up to date

Short description

The purpose of this variable is to collect information on the pension rights built up by the respondent to

date. The criterion measured by the variable is whether or not the person has either built up or is currently

building up pension rights (of one or more of the types indicated in the variable). If this is the case, an

affirmative answer should be given to this question even if the respondent does not yet have the right to

receive the pension.


This question was asked to all respondents aged 50-69 who are not currently receiving an old-age pension

(PENSION = 2, blank or (PENSTYP1 to PENSTYP4 = 0)), and who are either working currently or have

worked beyond age 50.


Several of the participating countries commented on the complexity of measuring this variable and

reported difficulties in collecting the data. The most problematic aspect lies in the understanding of the

phrase ‘pension rights the person has acquired so far’. The intention was to collect information on any

contributions made in the past for a pension that is to be paid in the future. When analysing the

questionnaires used in different countries it became apparent that the wording used differed considerably.

For example, in Belgium, Denmark, and Luxembourg, the question referred to ‘acquired pension rights’.

The UK questionnaire asked about the respondent’s expectation of future pension rights. In Bulgaria,

Spain, France, and Portugal, the intended question was asked, i.e. referring to contributions to the pension

system. In Poland, the question asked related to ‘being able to retire at the time of the question’ rather

than to ‘having built up pension rights (for future retirement)’, which of course had a major impact on the

results. Some respondents thought that pension rights were in force only at the moment when a pension is

received. The question was however asked to all those not receiving an old-age pension. Other

respondents did not know whether their past contributions would actually give them any pension rights.

There were also some respondents who took the view that the uncertainty surrounding pension systems

meant that the rights they had built up were not guaranteed.

The breakdown of the variable by scheme type was detailed and it was difficult to collect data as

respondents often did not know what type of pension rights they had (in particular in Bulgaria, Greece

and Lithuania). In some countries (the Czech Republic, the United Kingdom and Greece), several of the

Code Description

BUILDPEN1 1: Yes; 0: No Old-age pension. Statutory scheme

BUILDPEN2 1: Yes; 0: No Old-age pension. Occupational scheme

BUILDPEN3 1: Yes; 0: No Old-age pension. Personal scheme

BUILDPEN4 1: Yes; 0: No Old-age pension. Scheme unknow n



possible responses were not applicable. Respondents in occupational pension schemes are not always

aware that they are covered by such a scheme, or sometimes confuse the occupational pension scheme

with public sector old-age pension schemes. The filter determining which respondents were asked this

question was considered less than optimal (by Austria in particular), as it resulted in a high proportion of

responses under code 1, which did not create much scope for interesting analysis.

Not having a ‘don’t know’ answer was also a weakness of this variable.


Due to the high non-response rate, the data from Bulgaria, Denmark, Germany, Greece, Spain, France,

Italy, Lithuania, Romania, Sweden, the United Kingdom, Iceland, Norway and Switzerland must be used

with caution.

Graph 10.1: Proportion of ‘yes’ answers for the AHM 2012 BUILDPEN variable, by old-

age pension scheme (%)

The layout of graph 10.1 is the same as that of graph 2.1, in that each pension scheme is counted

separately, and the bar thus shows the total number of pension schemes where rights have been built up.

As one person can have rights in more than one type of pension scheme, the totals exceed 100 %. Most

countries can be seen to have a good level of coverage for at least one type of pension, typically statutory.

In Denmark, the Netherlands, Sweden, Iceland and Switzerland there is also a high occurrence of

occupational pension rights. Poland appears to have almost no coverage for any type of pension, but this

is for the reason explained above. Unfortunately, analysis at EU level is hindered by differences in the

translation of the question and changes made to adapt the question to national circumstances. It is

therefore recommended to analyse these results at national level only, referring in each case to the exact

wording of the question used.


Were the module to be repeated, this variable should be reviewed critically. Explanatory notes should in

future aim to provide examples to help explain the idea of ‘pension rights built up by the respondent to

date’ (where the respondent is not currently receiving an old-age pension). Alternatively, a different

wording could be used, focusing the variable on past contributions rather than on hypothetical rights. The

experience gained from collecting data on this variable in 2012 can serve as a starting point, and it should

be possible to identify best practices to be followed in the future.

0%

50%

100%

150%

200%

250%

300%

EU

-28

BE

BG

CZ

DK

DE

EE IE EL

ES

FR

HR IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO SI

SK FI

SE

UK IS

NO

CH

Statutory Occupational Personal Unknown


It is also worth emphasising once again the point made in the introductory chapter about the target

population: the choice of target population for this variable has additional disadvantages for analysis of

countries with a lower retirement age. This is because people who did not work after the age of 50 and

who are therefore excluded by the filter for this question, nevertheless have reasonable chances of

receiving a pension, either at the time of the interview or in the future, on the basis of their employment

before the age of 50. It is therefore unfortunate that the survey excluded these respondents from the

analysis of contributions to the pension system.

11. CONTWORK: Expectations of continuing working or looking for a job after starting to receive an old-age pension

Short description

This variable is forward-looking and examines whether those respondents currently building up old-age

pension rights expect to continue working or looking for work when they start receiving a pension. For

those respondents who expect to continue working or looking for work, the variable also distinguishes

between those who expect to need to work for financial reasons and those who wish to continue working

for non-financial reasons.


This question was asked to all active respondents (simplified ILO status: WSTATOR = 1, 2 or

(WSTATOR = 3, 5 and SEEKWORK = 1, 2, 4)) who are either building up or have built up old-age

pension rights (BUILDPEN ≠ 0000, 9999), and who are not currently receiving a pension (PENSION = 2,

blank).


A number of countries (Bulgaria, Switzerland, Estonia, Italy, the Netherlands and Slovakia) reported

difficulties in collecting information on expectations to continue working, because the question was

hypothetical and, in many cases, proved impossible to answer. Furthermore, the variable was intended to

combine not only the intention to work, but also the intention to look for work, which created further

difficulties. The complicated filter for the question added to the problems experienced in collecting data

for this variable.


There were high non-response rates for this variable in many countries: the non-response rate was 19 % at

EU level, with values above 50 % in two EU countries, Romania (61 %) and Bulgaria (52 %). The

following countries also recorded non-response rates higher than 15 %: Lithuania, Iceland, Norway,

Switzerland, Denmark, Greece, Italy, the United Kingdom, Germany, Spain, Sweden and France.

Code Description

1 Yes, for f inancial reasons

2 Yes, for other reasons

3 No, stop immediately w hen receiving old-age pension

4 No, stop before receiving old-age pension




Graph 11.1: Distribution of answer categories for the AHM 2012 CONTWORK variable

(%)

Graph 11.1 shows the distribution of the CONTWORK variable, with a majority of respondents

answering ‘no’ to the question on their expectations to continue working after starting to receive an old-

age pension. At EU level, the total of the two ‘no’ responses is 56 %. With the exception of the Czech

Republic, the group answering ‘will stop work immediately on starting to receive an old-age pension’ is

clearly larger than the group answering ‘will stop work before starting to receive an old-age pension’. For

those who do plan to continue either working or looking for a job after starting to receive an old-age

pension, financial reasons are more often cited than other reasons (16 % compared to 9 % at EU level).

Continuing to work for financial reasons is most common in Estonia, Latvia, Cyprus, Slovakia and

Lithuania, and least common in Slovenia, Austria, Spain, Denmark and Norway.

Graph 11.2 compares the occurrence of financial reasons as a main reason for expecting to continue

working after starting to receive an old-age pension (CONTWORK) and for remaining in employment at

present, while receiving an old-age pension (STAYWORK). The graph shows the number of people

citing financial reasons as a proportion of those who answered ‘yes’ to the questions on expecting to

continue working or looking for work and on remaining in employment, respectively. We would expect

to see a high level of correlation between these variables, even though they were both affected by high

non-response rates. In view of the high non-response rates, graph 11.2 should be interpreted with caution.

Iceland and Croatia have been excluded from the graph due to very small numbers for some of the

responses.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

SI

AT

ES

BE

HR

PL FI

EL

FR IT

HU

MT

SK

LU

LV

CY

PT

EU

-28

NL IE SE

DE

DK

UK

EE

BG LT

RO

CZ IS

NO

CH

No answer

Yes; for other reasons

Yes; for financial reasons

No; stop before receiving old-age pension

No; stop immediately when receiving old-age pension


Graph 11.2: Financial reasons cited in answers declaring expectation to continue

working (CONTWORK) and choice to remain in employment (STAYWORK) (%)

Although the linear trend is clearly visible and shows a somewhat expected pattern with countries more

severely affected by the crisis in the upper right corner and those less badly hit in the lower left corner, it

should be noted that both variables were affected by high non-response rates. There are several outliers,

including France and Estonia. It is very difficult to proceed with further interpretation of the results, and

to determine whether the deviations from the expected pattern are due to the definition of the variables

(including the definition of the related BUILDPEN variable) used in those countries or the way in which

the survey was carried out, or if there is genuinely a difference between the expectations and plans of

those currently still working and not yet receiving a pension, and the reality for those who are already

receiving a pension.


In general, forward-looking and hypothetical questions should be avoided in surveys, as illustrated by the

non-response rate and the feedback from those involved in collecting the data. Nonetheless, the data for

this variable shows a reasonable degree of correlation with the corresponding STAYWORK variable

asked to respondents currently in employment and receiving a pension. For future modules where this

variable is included, the Austrian quality report suggests using a more targeted question on the number of

hours the respondent plans to work after starting to receive an old-age pension, possibly combined with a

question on the number of hours by which working time is expected to be reduced before starting to

receive a pension, which would be collected in a more detailed version of the REDUCHRS variable. The

REDUCHRS variable caused some difficulties for data collection in 2012 however, and an increase in the

level of detail of this question would therefore be risky.

Were the module to be repeated, the CONTWORK variable should therefore be reviewed critically.

EU-28

BE

BG

CZ

DK

DE

EE

IE

EL ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

NO CH

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

AH

M L

FS

2012,

ST

AY

WO

RK

=3 / (

ST

AY

WO

RK

=3 +

S

TA

YW

OR

K=

4)

AHM LFS 2012, CONTWORK=1 / (CONTWORK=1 + CONTWORK=2)


Annexes

Annex 1: Abbreviations

EU-28 European Union of 28 Member States:

BE Belgium

BG Bulgaria

CZ the Czech Republic

DK Denmark

DE Germany

EE Estonia

IE Ireland

EL Greece

ES Spain

FR France

HR Croatia

IT Italy

CY Cyprus

LV Latvia

LT Lithuania

LU Luxembourg

HU Hungary

MT Malta

NL the Netherlands

AT Austria

PL Poland

PT Portugal

RO Romania

SI Slovenia

SK Slovakia

FI Finland

SE Sweden

UK the United Kingdom

IS Iceland

NO Norway

CH Switzerland


Annex 2: Main AHM 2012 tables

Several online tables presenting AHM 2012 data are available on the Eurostat website, at:

http://ec.europa.eu/eurostat/web/lfs/data/database

Respondents who receive a pension (PENSION/COL. 197)

This table shows the numbers of people (in thousands) who receive a pension and who do not receive a

pension. It also shows the number of people who were not in the target population of the survey (the

‘non-applicable’ group, by country). Results are shown by 5-year age brackets, by gender, and by

employment status.

Respondents who receive a pension, by type of pension (PENSTYPE/COL. 198-205)

The table shows the percentage of those receiving a certain type of pension in the target population of the

survey. Three breakdowns are available: respondents receiving any type of pension, those receiving an

old-age pension irrespective of the type and those receiving statutory old-age pensions only.

Age at which the respondent first received an old-age pension (AGEPENS/COL. 207-208)

This table shows mean and median ages (expressed in years) at which respondents received an old-age

pension for the first time. Results are shown by gender.

Early retirement among respondents who receive an old-age pension (EARLYRET/COL. 206)

The table shows the proportion of respondents who used an early retirement scheme out of those who

receive an old-age pension. The proportion not using an early retirement scheme and the proportion not

answering is also shown. Results are shown by gender. Results for Germany and Norway have been

excluded due to the high non-response rate.

Respondents who reduced their working hours as a step towards retirement (REDUCHRS/COL.

211)

The question was asked to two different sub-populations: 1) employed respondents; and 2) economically

inactive respondents receiving a pension. Please note that the target population is different to that of the

other questions in the survey as it includes respondents aged 55–69. The table shows those who reduced

their working hours in a gradual move towards full retirement as a percentage of the total number of

respondents to this question. Results are shown by gender and employment status. Results for Ireland and

the UK have been excluded due to incomplete data collection.

Economically inactive respondents who receive a pension who would have wished to remain longer

in employment (WORKLONG/COL. 210)

This variable gives information on the proportion of respondents, out of those who receive a pension and

are at the same time economically inactive, who would have wanted to remain longer in employment at

the time of leaving employment. Results are expressed as percentages and are shown by gender.

Main reason for respondents who receive a pension to continue working (STAYWORK/COL. 212)

This table shows the reasons for which respondents already receiving a pension remain in employment. In

cases where more than one reason applied, only the main reason was recorded. Results are shown by

current working arrangement (full-time or part-time).

Main reason for economically inactive respondents receiving a pension to stop working

(REASNOT/COL. 209)

Economically inactive respondents who receive a pension were asked for the main reason for which they

left employment. They were provided with eight possible responses. Results are provided by gender.


Annex 3: Commission Regulation (EU) No 249/2011

Source: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:067:0018:0021:EN:PDF

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:067:0018:0021:EN:PDF

transition from work to retirement

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