6 Years Occupational Strengthening Pensions Act (OSPA) in Germany:

Evidence from Current Employee Surveys

ROBERT PIOTR DOMBEK, RADEK JURČÍKa,*

Department of Law and Social Science Faculty of Business and Economics,

Mendel University in Brno,

Zemědělská 1, 613 00 Brno,

CZECH REPUBLIC

aORCiD: 0000-0001-6166-6525

*Corresponding Author

Abstract: - The aim of this study is to examine the effects of the Occupational Strengthening Pensions Act

(OSPA), introduced more than six years ago, on the demand for occupational pension provision (OPP) from the

perspective of employees subject to social insurance contributions in Germany. The study incorporates

theoretical perspectives on the prevalence of OPP from existing studies at the level of individual households

and firms. Data were collected via an online questionnaire from 236 people in Germany who are subject to

social security contributions. After receiving the completed questionnaires, they were analyzed and evaluated

using IBM SPSS Statistics. Descriptive and inferential statistical methods were used to analyze the survey data.

In particular, correlation and regression analyses were carried out to test the proposed hypotheses. The results

of the study show a significant correlation between age, income, and the desire for information, as well as the

reasons for not having a workplace pension and for having a mandatory workplace pension. These results

provide valuable insights into the extent to which OPP is widespread in Germany. In addition, the study

provides recommendations on how to increase interest in and take-up of OPP. The results of this study provide

employers and policymakers with a basis for achieving the OSPA's goal of increasing the prevalence of OPP. It

also contributes to the existing literature on possible improvements to OPP and the question of introducing

compulsory OPP in Germany. The study also highlights the mediating role of leadership style in the

relationship between organizational culture and organizational performance.

Key-Words: - Occupational Strengthening Pensions Act (OSPA), Betriebsrentenstärkungsgesetz, Demand for

Occupational Pensions, Savings Behaviour, Employer Subsidy, Tax Savings Social Security

Savings, Company Size, Distribution Rate of Occupational Pensions.

Received: January 6, 2024. Revised: June 29, 2024. Accepted: July 21, 2024. Published: September 6, 2024.

1 Introduction

In 2001, the Retirement Savings Act introduced a

private, state-subsidized old-age provision in the

form of the Riester pension. The introduction of the

Retirement Income Act three years later aimed at

modifying the basic tax conditions of the statutory

pension insurance. In this context, the three-layer

model replaced the previous three-pillar model, [1].

Just two years later, the Act on the Adjustment of

the Standard Age Limit was passed to reflect

demographic developments and to strengthen the

basic financing of the statutory pension insurance,

[2]. The core of this law was the introduction of a

standard age limit of 67 years, which will be

implemented with a gradual increase from 65 years

to 67 years, [3].

Two years later, in 2014, the maternity pension

was introduced with the aim of improving the

recognition of child-raising periods and the pension

at 63 for those insured for many years, [4]. After

the adoption of the 2014 pension package, no

further significant pension reforms followed until

the German government passed the Occupational

Strengthening Pensions Act (OSPA)

(Betriebsrentenstärkungsgesetz - BRSG) in summer

2017, which came into force on 1 January 2018, [5],

reforming part of the second tier of the German

pension system.

Considering that OPP looks back on a history

of more than 150 years and was introduced before

statutory pension insurance, statutory regulation did

not take place until 19 December 1974, 104 years

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1775

Volume 21, 2024

later, [6]. Initially, OPP consisted of four

implementation channels. By the mid-1990s,

almost every third employees in the private sector

had made provision for old age in the form of an

OPP. However, the demand for OPP stagnated in

the course of the 1990s. Good 28 years later, a legal

entitlement to OPP was established by the 2001

pension reform on 1 January 2002. From this point

on, every person in an employment relationship

was entitled to OPP. The aim of the mandatory

right to OPP was to counteract the stagnation in

OPP. However, the health reform of 2003, in which

it was decided through the Act on the

Modernization of Statutory Health Insurance, that

the full health and long-term care insurance

contribution must now be paid on OPP, made OPP

less attractive again from the perspective of

employees, [3]. As already mentioned, the OSPA

ultimately came into force on 01.01.2018. To

improve readability, the OSPA will no longer be

written out in full in the remainder of this research

paper. Instead, the abbreviation OSPA will be used.

A milestone was set with the introduction of the

OSPA. The OSPA pursues the political goal of

increasing the spread of OPP through greater

demand in order to secure the standard of living in

old age, [7]. The OSPA creates a special incentive

to take out OPP, e.g. through the mandatory

passing on of social insurance savings by the

employer, [1].

2 Literature Review

There are numerous academic publications dealing

with pension reforms, [8], [9], [10]. In particular,

there is a large body of literature dealing with OPP

prior to the introduction of OPP. [11], discusses the

possible reasons for the low level of occupational

pensions in Germany. [12], analyses the newly

introduced German occupational pension system. It

establishes a link between the pension benefits of

the beneficiaries, the mortality rate of the pension

recipients and the development of the financial

markets. The study offers insights from the

perspective of a pension beneficiary and compares

the pension with other savings schemes. Their

findings suggest that occupational pension schemes

could be a useful complement to the first and third

pillars of the pension system and offer some

comparative advantages over traditional defined

benefit and defined contribution plans. [13],

provides a good overview of the prevalence of OPP

in the period 1984-1999 in its 2001 Company

pension schemes Report. The study examines the

position of such plans in the context of the overall

pension system and provides an outlook for the

future, particularly in light of the new legislation.

[14], looks at OPP after the introduction of the

OSPA. The report shows that after one year of the

OSPA, no meaningful interim results can be

reported. In their position paper, [15], analyse the

decisions of companies to offer occupational

pension schemes. Tax benefits and length of service

are cited as possible reasons for taking out an OPP,

[15]. [7], provides a clear illustration in his article

on OPP. In his work, the author provides a good

overview of the model-theoretical consideration of

OPP and summarises the results as part of a benefit

analysis, [7]. [16], analyses company pension

schemes in Germany and Austria. In addition to the

factor of company size, the structural factors that

influence the demand for company pension

schemes are also analysed.

This study shows that the market penetration of

OPP is stagnating among middle and upper-

management employees, while it has increased only

minimally among other employees.

The first section of the literature review briefly

presents the existing data sets on OPP at the

individual and household level and the second

section briefly presents the data sets on OPP at the

company level in Germany.

2.1 Data Sets on OPP at the Individual and

Household Level

Employer and Agency Survey (EAS)

The data come from, [17] and [18], own survey of

providers. The latest survey dates from 2019. The

survey of companies and providers of OPP analyses

in particular the dimensions of existing entitlements

and contribution amounts. It is broken down by

gender and type of OPP, [17], [18]. The question of

how many people have at least one OPP contract is

difficult to answer because the survey covers both

male and female members. For this reason, the

average number of contracts per capita is calculated

and the amount of pension entitlements is adjusted

by this factor. These data make it possible to

construct a time series that can provide additional

information on different developments in OPP.

Changes in the demand for OPP in the various

implementation channels can be well documented

and are therefore useful for a first analysis of the

effects of the OSPA, [17], [18].

Dissemination of Old-Age Provision

Among other things, the studies record the

contracts for which savings are currently being

made and the level of the individual's savings rate.

A special feature of this survey is that it records

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1776

Volume 21, 2024

whether an information letter is available. If such

an information letter is available, respondents are

asked to indicate their total savings contributions.

In addition to personal contributions, employer

contributions are also recorded and respondents are

asked about pension entitlements and the actual

capital stock, [18]. Although many assets are not

recorded in detail, it is at least possible to get an

initial picture of how OPP is used. Another

important feature of these surveys is the clear

distinction between OPP for employees in the

private and public sectors.

Old Age Security in Germany

The study was first conducted in 1986 on behalf of

the Federal Ministry of Labour and Social Affairs.

It has been conducted every four years since 1995.

Independent samples are also surveyed repeatedly

in this study. At the beginning of the study, people

aged between 55 and 80 were interviewed, and

from 2019, people aged between 60 and 85 will

also be asked about their income in old age for the

first time, [19]. In contrast to the studies described

so far, the results of the studies on old-age

provision in Germany do not provide new insights

into future gaps in provision, but rather into the

current level of provision of the respondents in the

55-80 and 60-85 age cohorts. For respondents who

are still working, on the other hand, the focus is on

whether they will receive OPP benefits in

retirement. The study thus captures the

concentrated pension patterns that change over time,

[19].

Life Courses, Aging and Well-Being

The research project Life Course, Aging and Well-

Being uses the statistical matching approach with

SOEP and modified SAPA data, which allows for

further refinement of the matching. The project

compares the life courses of baby boomers with

those of older birth cohorts and analyses the effects

of less stable family relationships and changing

employment histories on the accumulation of

pension rights, [20].

Survey of Health Ageing and Retirement in Europe

The survey of health ageing and retirement in

Europe panel study, led by the Munich Centre for

the Economics of Ageing (MEA), covers a

population of people aged 50 and over. The study

surveys people from 26 European countries,

Switzerland and Israel on issues related to

retirement planning. A special feature of this study

is that it documents the payout phases of OPP and

individual OPP. The study is also able to record the

dynamics, the type of payout, and the year in which

the pension was first drawn. In addition, people

who are not currently receiving a pension are asked

about any future entitlement to an OPP, the length

of time they have been saving, the average amount

saved, and the possible future amount of the OPP,

[21], [22], [23].

Savings and Retirement Provision in Germany

The saving and retirement planning in Germany"

study, also conducted by the MEA, surveys a

broader section of the population. This study was

first conducted in 2001 as part of a preliminary

survey, then in 2003/04, annually from 2005 to

2011, and most recently in 2013. The aim of this

panel study was to document dynamic changes in

savings behavior over time. The explicit

questionnaire differed slightly from survey to

survey. The number of contracts, the monthly

savings contributions, and the current balance were

asked in almost all surveys. In the case of spouses,

no distinction was made as to who made the

contributions. The 2007 survey also asked whether

the answers were taken from current documents or

whether they were only estimates. In theory, these

surveys could also be used to make statements

about the composition of savings contributions to

OPP. In other words, what proportion of the total

contribution was made by the employee, and what

proportion was made by the employer, [24].

Socio-Economic Panel

This survey was first carried out in 1984. The

German Socio-Economic Panel currently surveys

around 30,000 people from around 22,000

households each year. So far, about 22,000

households have been asked about their behavior

with regard to OPP. The surveys of the last two

years focused in particular on the acquired OPP

rights and the type of financing, [19]. A regular

survey on the status of OPP can also help to

increase the learning curve and ensure that

respondents provide more detailed information.

Private Households and their Finances

The panel study "Private Households and their

Finances", provides an additional database on the

financial structure of households with at least one

adult household member aged 18 or over. The

second and third surveys were conducted in 2014

and 2017 respectively and collected information on

household assets, the number of OPP contracts, and

other information on contributions and expected

pensions or lump-sum payments. Respondents are

also asked about the evolution of the replacement

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1777

Volume 21, 2024

rate of old-age pensions in relation to their net

income, [25], [26].

2.2 Data Sets on OPP at the Company Level

Structure of Earnings Survey

[27] and [28], is also responsible for the structure

of the earnings survey. It was first conducted in

1951 and has been conducted regularly every four

years since 2002. The special feature of this survey

is its accuracy due to the availability of information

on OPP from the pay slips of the respondents. The

survey covers a sample of about 60,000 companies

and about one million documented employment

relationships, although it focuses only on deferred

compensation, [28].

The literature review identified further 36

smaller studies by insurers or associations on the

prevalence of OPP in companies of different sizes

and in different sectors. Employees, on the other

hand, were surveyed 15 times, mainly on pension

provision in general. In general, OPP providers

were surveyed five times. In some cases, similar

target groups were found to be surveyed. The

employer surveys vary according to the size of the

enterprise. Overall, the surveys can be divided into

seven employer and six employee surveys,

although the number and order of enterprise sizes

vary.

3 Methodology

The literature review shows that even before the

introduction of the OSPA, many studies had

confirmed the need for OPP. Employee surveys

were conducted to validate and, where necessary,

supplement these findings. A questionnaire was

developed and pre-tested. A pre-test is always

necessary for written surveys and is intended to

provide information on the comprehensibility of the

questionnaire and the meaning of the cover letter or

similar elements, [29]. Participants were selected

using a random selection procedure. When

completing the questionnaire, the participants had

to pay attention to several criteria such as

comprehensibility, clarity, acceptability of the

questions, and graphic design. This was

communicated to them in advance. Minor changes

were made to the questionnaire as a result of the

pre-test. The data was collected via an online

survey in the DATAtab portal and took place from

21 January 2024 to 22 February 2024. The target

group for the survey was employees subject to

social security contributions from various

employment sectors in Germany. Membership of

the target group was ensured by the socio-

demographic survey. At the beginning of the survey,

participants were informed about data protection

regulations. The second category asked about

communication, the third about the existence of an

OPP, the fourth about the reasons for or against an

OPP and additional benefits, the fifth about the

financing of the OPP, the sixth about improvement

measures, and the final seventh categoryabout

socio-demographic characteristics. Participants

were interviewed in German and the results were

then translated into English. Outside of the

categories, there was a final open-ended question in

which respondents could express their opinions in

1-3 keywords. Contact with respondents was made

through personal networks, LinkedIn, Instagram,

contacting people in self-organized associations,

and Survey Circle. Once the completed

questionnaires were received, they were analyzed

and evaluated using IBM SPSS Statistics. In

particular, correlation and regression analyses were

carried out. The use of quantitative methods was

possible because the surveys were standardized. It

did not seem possible to generalize the results as

the number of respondents was relatively small

compared to the number of employees in Germany.

4 Data

The data was analyzed in terms of correlation,

regression, and interaction using 236 data sets. The

empirical examination of the data sets received and

found to be valid was divided into three sections:

correlation analysis, the chi-square independence

test the t-test for mean differences in independent

samples, and the descriptive statistics.

Spearman's rank correlation coefficient

The rank correlation analyses the undirected linear

relationship between two variables. Undirected

means that there is no dependent or independent

variable. Therefore, no causal statements can be

made. Spearman's rank correlation coefficient is

based on Pearson's product-moment correlation

coefficient r. However, this requires an interval

scale level of the correlated variables. Spearman's

rank correlation coefficient avoids this problem by

using the ranks of the cases in relation to these

variables instead of the values of the variables.

Therefore, the correlating variables in Spearman's

rank correlation coefficient only need to be

ordinally scaled, [30].

For the observations of the characteristic, the

ranks must first be assigned for each component,

[31]. If two or more observations have the same

characteristic, a so-called tie exists. The mean value

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1778

Volume 21, 2024

of the ranks to be assigned is then taken as the rank

of the individual observations, [32]. Spearman's

rank correlation coefficient compares the respective

ranks. As no distances are defined due to the

ordinal scale level, Spearman's rank correlation

coefficient is based only on the difference in the

ranks. If there are no ties, the rank correlation

coefficient is defined as, [32]:

(1)

The range of values for the correlations (R) is

between minus one and plus one, with two identical

rankings. In the case of positive correlations, high

values of one variable are associated with high

values of the second variable. Conversely, in the

case of positive correlations, low values of one

variable are associated with low values of the

second variable. In this case, the high values of one

variable are associated with the low values of the

other variable. Statements about the direction of the

correlation can therefore be derived from the sign

of the correlations, [30].

The following applies to hypothesis tests:

Hypothesis 0 is rejected if p < (smaller) 0,05 and

therefore hypothesis 1 is assumed.

Hypothesis 0 will be retained, if p > or = 0,05.

Effect sizes are calculated in order to assess the

significance of a result. Spearman's correlation

coefficient is a measure of the effect size.

Categorization can be used to determine the extent

of the correlation found, [33].

|R| = 0.1 corresponds to a weak effect

|R| = 0.30 corresponds to a medium effect

|R| = 0.5 corresponds to a strong effect

5 Results

5.1 Descriptive Analysis

A total of 236 datasets were generated. The datasets

were completed by 90 women, 145 men, and one

person of mixed origin. The 30-39 age group was

the largest age group in the survey with 43.2% (102

records), followed by the 18-29 age group with

24.2% (57 records) and the 40-49 age group with

20.3% (48 records). The 50-59 age group was

represented by 7.6% (18 records). The group aged

60 and over was the least represented. Their share

was 4.7% (11 records). Of the respondents, 49.6%

were single (117 records), 42.4% married (100

records), 5.5% divorced (13 records), 1.3% in a

consensual union (3 records), 0.8% separated and

0.4% widowed (1 record). Just over half of the

respondents (50.8%, 120 records) did not have an

academic degree. 44.8% (105 records) had an

academic degree and 4.7% (11 records) had no

qualifications. Just under a third, 31.4% (74 records)

of the respondents had a gross monthly income of

more than 5001 euro. Just over a fifth, 19.1% (45

records), said they had a gross monthly income of

between 1000 and 2000 euro. 14.4% (34 records)

had a gross monthly income between 4001 and

5000 Euros, 13.1% (31 records) between 3001 and

4000 Euros and 11% (26 records) between 2001

and 3000 Euros. A further 11% (26 records) did not

report their gross monthly income. 76.7% (181

records) of the respondents were employed full-

time and 23.3% (55 records) were employed part-

time at the time of the survey. Of the respondents,

51.7% (122 records) worked in an

organizationorganization with more than 250

employees at the time of the survey. 21.6% (51

records) worked in an organization with 0-49

employees and 20.8% (40 records) in an

organization with 50-249 employees. 5.9% (14

records) said they did not know how many people

were employed in the organization. Small

enterprises have up to 49 employees, medium-sized

enterprises have 50-249 employees and large

enterprises have more than 249 employees, [31].

66.5% (157 records) of respondents gave their own

assessment of the future of OPP. 5% said they

thought the future was good. For further

information, Table 1, Table 2, Table 3, Table 4,

Table 5, Table 6 and Table 7 of the descriptive

statistics follow in the remainder of this chapter.

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1779

Volume 21, 2024

Table 1. Gender participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Masculine

145

61,4

Female

38,1

99,6

Miscellaneous

100,0

Total

236

100,0

Table 2. Age cohort participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

18-29

24,2

30-39

102

43,2

67,4

40-49

20,3

87,7

50-59

7,6

95,3

60+

4,7

100,0

Total

236

100,0

Table 3. Marital status of participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Single

117

49,6

Married

100

42,4

91,9

Registered life partnership

1,3

93,2

Living separately

94,1

Divorced

5,5

99,6

Widowed

100,0

Total

236

100,0

Table 4. Academic degree participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Not specified

4,7

120

50,8

55,5

Yes

105

44,5

100,0

Total

236

100,0

Table 5. Gross income cohort participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

-99

11,0

1000 - 2000 €

19,1

30,1

2001 - €3000

11,0

41,1

3001 - 4000 €

13,1

54,2

4001 - 5000 €

14,4

68,6

More than €5001

31,4

100,0

Total

236

100,0

Table 6. Type om employement participants

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Full time

181

76,7

Part-time

23,3

100,0

Total

236

100,0

Table 7. Employees by Company Size

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0-49

21,6

23,0

50-249

20,8

22,1

45,0

Over 250

122

51,7

55,0

100,0

Total

222

94,1

100,0

Missing

I don't know

5,9

Total

236

100,0

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1780

Volume 21, 2024

5.2 Inferential Statistical Analysis

Hypothesis testing was used to draw inferences

about the population from the sample data and to

test whether certain assumptions about the

population were correct.

Hypothesis 0 = "Age" and " How would you prefer

to be adequately informed about company pension

schemes? Already during onboarding" have no

statistically significant correlation.

Hypothesis 1 = "Age" and " How would you prefer

to be adequately informed about company pension

schemes? Already during onboarding" have a

statistically significant correlation.

The SPSS output is shown in the following Table 8.

Table 8. Correlation between age and desire for

information on OPP

The table shows the correlation between "Age"

and "How would you prefer to be adequately

informed about company pension schemes?

Already during onboarding" -0,201amounts. The p-

value is 0,017. Therefore, hypothesis 0 is rejected

and hypothesis 1 is accepted.

Conclusion: "Age" and "How would you prefer to

be adequately informed about company pension

schemes? Already during onboarding" have a

statistically significant, negative correlation.

According to, [33], this is a weak effect (R=-0,201,

p=0,017, n=140).

Refer to the hypotheses formulated:

Hypothesis 0= "Age" and "In your opinion, what

are the reasons against taking out a company

pension scheme? I don't trust the state" have no

statistically significant correlation.

Hypothesis 1= "Age" and "What reasons do you

think speak against taking out a company pension

scheme? I have no trust in the state" have a

statistically significant correlation.

The SPSS output is shown in Table 9.

Table 9. Correlation between age and trust in the

state

The table shows that the correlation between

"Age" and "In your opinion, what reasons speak

against taking out a company pension plan? I don't

trust the state" is 0,199. The p-value is 0,038.

Therefore, hypothesis 0 is rejected and hypothesis 1

is accepted.

Conclusion: "Age" and " In your opinion, what

reasons speak against taking out a company

pension plan? I don't trust the state" have a

statistically significant, positive correlation.

According to, [33], this is a weak effect (R=0,199,

p=0,038, n=109).

Refer to the hypotheses formulated:

Hypothesis 0= "Monthly gross income" and " In

your opinion, what reasons speak against taking out

a company pension plan? I don't have any money

available“ have no statistically significant

correlation.

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1781

Volume 21, 2024

Hypothesis 1= "Monthly gross income" and "In

your opinion, what reasons speak against taking out

a company pension plan? I don't have any money

available“ have a statistically significant correlation.

The SPSS output is shown in Table 10.

Table 10. Correlation between monthly gross

income and no money for OPP

The table shows that the correlation between

"monthly gross income " and " In your opinion,

what reasons speak against taking out a company

pension plan? I don't have any money available " is

-0,549. The p-value is 0,000. Therefore, hypothesis

0 is rejected and hypothesis 1 is accepted.

Conclusion: "Gross monthly income" and " In your

opinion, what are the reasons against taking out a

company pension scheme? I have no money

available" have a statistically significant, negative

correlation (R= -0,549, p=0,000, n=99). According

to, [33], this is a strong effect.

Refer to the hypotheses formulated:

Hypothesis 0= "Monthly gross income" and " In

your opinion, what reasons speak against taking out

a company pension plan? My employer doesn't

offer this“ have no statistically significant

correlation.

Hypothesis 1= "Monthly gross income" and " In

your opinion, what reasons speak against taking out

a company pension plan? My employer doesn't

offer this“ have a statistically significant correlation.

The SPSS output is shown in the Table 11.

Table 11. Correlation between monthly gross

income and offered by the employer

The table shows that the correlation between

"monthly gross income " and " In your opinion,

what reasons speak against taking out a company

pension plan? My employer doesn't offer this" is -

0,205. The p-value is 0,042. Therefore, hypothesis

0 is rejected and hypothesis 1 is accepted.

Conclusion: "Monthly gross income" and "In your

opinion, what reasons speak against taking out a

company pension plan? My employer doesn't offer

this" have a statistically significant and negative

correlation (R= -0,205, p=0,042, n=99). According

to, [33], this is a weak effect.

Refer to the hypotheses formulated:

Hypothesis 0= "Monthly gross income" and " In

your opinion, what reasons speak against taking out

a company pension plan? I haven't dealt with the

topic yet“ have no statistically significant

correlation.

Hypothesis 1= "Monthly gross income" and " In

your opinion, what reasons speak against taking out

a company pension plan? I haven't dealt with the

topic yet“ have a statistically significant correlation.

The SPSS output is shown in Table 12.

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1782

Volume 21, 2024

Table 12. Correlation between monthly gross

income and dealt with the topic OPP

The table shows that the correlation between

"monthly gross income " and " In your opinion,

what reasons speak against taking out a company

pension plan? I haven't dealt with the topic yet " is -

0,395. The p-value is 0,000. Therefore, hypothesis

0 is rejected and hypothesis 1 is accepted.

Conclusion: "Gross monthly income" and " In your

opinion, what reasons speak against taking out a

company pension scheme? I haven't dealt with the

topic yet" have a statistically significant, negative

correlation (R= -0,395, p=0,000, n=99). According

to, [33], this is a medium effect.

Refer to the hypotheses formulated:

Hypothesis 0 = "Monthly gross income" and " Do

you think mandatory company pension schemes

make sense? I think a mandatory company pension

scheme makes sense.“ have no statistically

significant correlation.

Hypothesis 1 = "Monthly gross income" and "Do

you think mandatory company pension schemes

make sense? I think a mandatory company pension

scheme makes sense.“ have a statistically

significant correlation.

The SPSS output is shown in Table 13.

Table 13. Correlation between compulsory

company pension scheme and income

The table shows that the correlation between

"monthly gross income " and "Do you think

mandatory pension schemes make sense? I think a

mandatory company pension scheme makes sense"

is -0,047. The p-value is 0,498. Therefore,

hypothesis 0 is not rejected, but retained.

Conclusion: "Gross monthly income" and " Do

you think a mandatory company pension scheme

makes sense? I think a mandatory company pension

scheme makes sense." have no statistically

significant correlation (R=-0,047, p=0,498, n=210).

The Levene test has proven that it can be assumed

that variance homogeneity exists, that the

significance is 0,981 and therefore > 0,05.

Therefore, the hypotheses 0 and 1 for the t-test for

equality of means were formulated in the further

course:

Hypothesis 0: There is no significant mean

difference between the female and male

respondents when answering the item: "How

satisfied are you with your company pension plan?

Hypothesis 1: There is a significant mean

difference between the female and male

respondents when answering the item: "How

satisfied are you with your company pension plan?

This p-value is p= 0,244 and therefore > 0,05.

Hypothesis 0 is therefore not rejected but retained.

There is therefore no significant mean difference

between the female and male respondents when

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1783

Volume 21, 2024

answering the item: "How satisfied are you with

your company pension plan?".

The SPSS output is shown in Table 14.

Table 14. Independent samples test for differences

in satisfaction with company pension schemes

between the sexes

6 Discussion

The empirical analysis of the employee surveys

showed that people aged between 18 and 40 in

particular wanted to be informed about the

company pension scheme during the induction

process. The proportion of the over-40s stated that

they did not want to be informed about the

company pension scheme during the induction

process. There is a statistically significant negative

correlation between age and how respondents

would prefer to be informed about the company

pension scheme. According to, [33], this is a weak

effect (R= -0,201, p=0,017, n=140).

It was also shown that the variable's age and

reasons for not having an OPP, such as not trusting

the state, have a statistically significant positive

correlation. The 20-40 age group was the most

likely to cite mistrust of the state as a reason.

According to, [33], this is a weak effect (R=0,199,

p=0,038, n=109).

Statistical significance was also found between

the variables of gross monthly income and the

reasons for not having an OPP. A large number of

respondents with a gross monthly income of more

than €5,001 stated that this was not due to their

financial means. Respondents in the income group

between €1,000 and €2,000 gross per month were

more likely to cite financial resources as the reason.

There is a statistically significant negative

correlation between gross monthly income and

available monthly resources (R=-0,549, p=0,000,

n=99). According to, [33], this is a strong effect.

A further empirical examination of the

variables of gross monthly income and the reasons

for not having a company pension, in this case, the

employer not offering a company pension, has

shown that the correlations between the two

variables examined are statistically significant and

have a negative correlation (R=-0,205, p=0,042,

n=99). According to, [33], this is a weak effect.

The fact that the variables of gross monthly

income and the reasons why respondents have not

yet addressed the issue of OPP, and therefore do not

yet have a contract, could be empirically proven.

These variables have a statistically significant

negative correlation (R= -0,395, p=0,000, n=99).

According to [33], this is a medium effect.

The correlations between gross monthly

income and the existence of a mandatory OPP are

not statistically significant (R=-0,047, p=0,498,

n=210), which was also empirically proven.

The t-test for mean differences for independent

samples showed that men and women are

approximately equally satisfied with their company

pension scheme. There is therefore no significant

mean difference between the female and male

respondents.

Participants in the employee surveys were

selected by the study director according to their

employment status to ensure that the sample of

participants reflected the population of all

employees in the Federal Republic of Germany on

22 February 2024. The sample was representative

and the results can be and generalized to the whole

population.

7 Conclusion

In summary, the data situation on OPP in Germany

is very heterogeneous. For further reforms of OPP

in Germany, existing data gaps should therefore

first be closed by including additional variables in

existing data sets. In addition, the data situation

should be improved by providing administrative

data from employers and contributors and linking

them with survey data. Finally, researchers should

be given easier access to existing data sources. In

this way, the determinants of supply and demand

for OPP can be estimated and possible social policy

measures can be identified in good time. As the

demand for OPP has stagnated in recent years, it is

necessary to examine whether and to what extent

the law on strengthening OPP will promote the

further spread of OPP. In addition, given the

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1784

Volume 21, 2024

constantly changing economic environment, it is

necessary to analyze what other factors might be

responsible for the stagnation of the penetration

rate and how these might be remedied or

compensated for by changes.

The authors also recommend that the OSPA

conduct a gendered analysis of the impact on

demand for OPP, as the inclusion of gender in

research and statistics is important to ensure a fair

and diverse perspective. It is important to note that

gender includes not only binary categories such as

female and male, but also other gender identities.

Gender-specific indicators, such as type of

employment and/or marital status, are necessary to

identify gender-specific trends and needs. An

analysis of the datasets analyzed in this article

would follow the recommendation that

questionnaires should be designed in a gender-

sensitive way. This differentiation would have the

advantage that the gender analyses could be used to

develop and evaluate gender-equitable policies.

The results of this article have shown that OPP

is an issue that sometimes causes uncertainty

among employees. In Germany, OPPs have a

number of weaknesses and are not keeping pace

with labor market developments and demographic

change. This could become an increasing problem

as the level of benefits in the state pension system

falls. The question therefore arises as to how OPP

can fill these gaps. In view of these facts, it is

advisable to analyze international pension systems

in order to gain initial insights for a better design of

the German occupational pension system for the

future. For the purposes of this study, countries

should be selected that face similar future problems,

have statutory pension systems similar to

Germany's, and whose demographic trends are

worrying.

The aim of this study was to determine the

impact of the OSPA on the demand for OPP. To

this end, employee surveys were conducted. It was

shown that respondents want to be informed about

the possibilities of a company pension scheme as

early as the induction phase. It was also shown that

the respondents did not trust the company pension

scheme because they did not trust the state.

Financial reasons and the reluctance of the

employer to offer a company pension are also

reasons why some of the respondents do not have a

company pension contract.

References:

[1] Fiche, C. (2020). Pension Projections

Exercise 2021, [Online]. https://economy-

finance.ec.europa.eu/system/files/2021-

05/de_-_ar_2021_final_pension_fiche.pdf

(Accessed Date: March 1, 2024).

[2] Caliendo, M., & Hogenacker, J. (2012). The

German labor market after the Great

Recession: successful reforms and future.

challenges. IZA Journal of European Labor

Studies, 1, 1-24, [Online].

https://link.springer.com/content/pdf/10.1186

/2193-9012-1-3.pdf (Accessed Date: June 27,

2024).

[3] German Council of Economic Experts –

Annual Report. (2016/17). Pension

Provision: Strengthen the three pillar model,

[Online]. https://www.sachverstaendigenrat-

wirtschaft.de/fileadmin/dateiablage/gutachten

/jg201617/chapter_seven__2_.pdf (Accessed

Date: April 30, 2024).

[4] Schmähl, W. (1999). Pension Reforms in

Germany: Major Topic, Decisions and

Developements. In: Müller, K., Ryll, A.,

Wagener, HJ. (eds) Transformation of Social

Security: Pensions in Central-Eastern

Europe. Contributions to the economy.

Physica, Heidelberg.

https://doi.org/10.1007/978-3-642-58654-

5_6.

[5] Hofelich, A., & Rein, M. (2018). The act to

strengthen company pensions is coming –

with implications for all employers. Berlin:

Your world first January 2018/05,

Employment law – in brief, CMS Hasche

Sigle Employment & Pensions Practice Area

Group, [Online].

https://cms.law/en/media/local/cms-

hs/files/publications/newsletters/employment

-law-in-brief-january-2018 (Accessed Date:

June 15, 2024).

[6] Börsch-Supan, A., Reil-Held, A., & Wilke,

C. B. (2007). How an unfunded pension

system looks like defined benefits but works

like defined contribtuions: the German

pension reform. [Online].

https://madoc.bib.uni-

mannheim.de/1560/1/meadp_126_07.pdf

(Accessed Date: June 27, 2024).

[7] Bäcker, G. (2017). New regulations on

occupational pensions in Germany. ESPN

Flash Report 2017/63. European Commision,

[Online].

https://docslib.org/doc/1331307/new-

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1785

Volume 21, 2024

regulations-on-occupational-pensions-in-

germany (Accessed Date: July 7, 2024).

[8] Bonin, H. (2001). Will it last? An assessment

of the 2001 German pension reform. The

Geneva Papers on Risk and Insurance. Issues

and Practice, 26(4), 547-564.

https://doi.org/10.1111/1468-0440.00139

[9] Börsch-Supan, A. H., & Wilke, C. B. (2004).

Reforming the German public pension

system (pp. 9-10). Institute of Economic

Research, Hitotsubashi University, [Online].

https://cis.ier.hit-

u.ac.jp/Japanese/publication/cis/dp2004/dp22

6/text.pdf (Accessed Date: July 7, 2024).

[10] Bonoli, G., & Shinkawa, T. (Eds.). (2006).

Ageing and pension reform around the

world: evidence from eleven countries.

Edward Elgar Publishing.

[11] Dummann, K. (2008). What determines

supply and demand for occupational pensions

in Germany?. Journal of Pension Economics

& Finance, 7(2), 131-156. doi:

10.1017/S1474747208003557.

[12] Chen, A., & Rach, M. (2021). Current

developments in German pension schemes:

What are the benefits of the new target

pension?. European Actuarial Journal, 11(1),

21-47. https://doi.org/10.1007/s13385-020-

00247-w.

[13] German Federal Bank. (2001). Company

pension schemes in Germany. Monthly

Report March 2001, [Online].

https://www.bundesbank.de/resource/blob/70

6058/8512d67b67b761a2215e7f2ffb928c65/

mL/2001-03-company-pension-data.pdf

(Accessed Date: June 28, 2024).

[14] Hogan Lovells. [2019]. Workplace pensions

in Germany: what you need to know,

[Online].

https://www.hoganlovells.com/~/media/hoga

lovells/pdf/2019/2019_08_14_german_pensi

on_schemes__client_note.pdf?la=en

(Accessed Date: April 19, 2024).

[15] Hernæs, E., Piggott, J., Zhang, T., & Strøm,

S. (2006). The determinants of occupational

pensions. Available at SSRN 1032786,

[Online]. https://hdl.handle.net/10419/63024

(Accessed Date: February 12, 2024).

[16] Wiß, T. (2018). Divergent occupational

pensions in Bismarckian countries: the case

of Germany and Austria. Transfer: European

Review of Labour and Research, 24(1), 91-

107.

https://doi.org/10.1177/1024258917748258.

[17] Federal Ministry of Labour and Social

Affairs. (2020). Research report 565,

Distribution of old-age provision 2019 (AV

2019) - Final report, [Online].

https://www.bmas.de/SharedDocs/Download

s/DE/Publikationen/Forschungsberichte/fb-

565.pdf?__blob=publicationFile&v=1

(Accessed Date: October 1, 2024).

[18] Federal Ministry of Labour and Social

Affairs. (2020). Research report 565/M,

Distribution of old-age provision 2019 (AV

2019) - Methodological report, [Online].

https://www.bmas.de/SharedDocs/Download

s/DE/Publikationen/Forschungsberichte/fb-

565-

methodenbericht.pdf?__blob=publicationFile

&v=3 (Accessed Date: October 1, 2024).

[19] Rasner, A. (2012). The Distribution of

Pension Wealth and the Process of Pension

Building: Augmenting Survey Data with

Administrative Pension Records by

Statistical Matching, [Online]. https://api-

depositonce.tu-

berlin.de/server/api/core/bitstreams/7782978

7-5075-4336-b2e6-99ce6474f8d0/content

(Accessed Date: June 28, 2024).

[20] Simonson, J., Gordo, L. R., & Titova, N.

(2011). Changing employment patterns of

women in Germany: How do baby boomers

differ from older cohorts? A comparison

using sequence analysis. Advances in Life

Course Research, 16(2), 65-82. doi:

10.1016/j.alcr.2011.03.002.

[21] Börsch-Supan, A., Brandt, M., Hunkler, C.,

Kneip, T., Korbmacher, J., Malter, F., ... &

Zuber, S. (2013). Data resource profile: the

Survey of Health, Ageing and Retirement in

Europe (SHARE). International Journal of

Epidemiology, 42(4), 992-1001. doi:

10.1093/ije/dyt088.

[22] Börsch-Supan, A., Czaplicki, C., Friedel, S.,

Herold, I., Korbmacher, J., & Mika, T.

(2020). SHARE-RV: linked data to study

aging in Germany. Yearbooks of Economics

and Statistics, 240(1), 121-132.

doi.org/10.1515/jbnst-2018-0034.

[23] SHARE-ERIC (2024). Survey of Health,

Ageing and Retirement in Europe. Release

Guide 9.0.0, [Online]. https://share-

eric.eu/fileadmin/user_upload/Release_Guide

s/SHARE_release_guide_9-0-0.pdf

(Accessed Date: July 8, 2024).

[24] Coppola, M., & Lamla, B. (2013). Saving

and old age provision in germany (save):

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1786

Volume 21, 2024

Design and enhancements. Journal of

Contextual Economics–Schmollers Yearbook,

(1), 109-116.

https://doi.org/10.3790/schm.133.1.109.

[25] Von Kalckreuth, U., Eisele, M., Le Blanc, J.,

Schmidt, T., & Zhu, J. (2012). The PHF: a

comprehensive panel survey on household

finances and wealth in Germany, [Online].

https://www.econstor.eu/bitstream/10419/599

99/1/719704995.pdf (Accessed Date: June 30,

2024).

[26] Bundesbank, D. (2023). "Household Wealth

and Finances in Germany: Results of the

2021 Household Wealth Survey".

Bundesbank Monthly Report, [Online].

https://www.bundesbank.de/resource/blob/90

8924/3ef9d9a4eaeae8a8779ccec3ac464970/

mL/2023-04-vermoegensbefragung-data.pdf

(Accessed Date: June 30, 2024).

[27] Eurostat. (n.d.). Structure of the earnings

survey, [Online].

https://ec.europa.eu/eurostat/web/microdata/s

tructure-of-earnings-survey (Accessed Date:

December 17, 2023).

[28] European Commision. (2024). SME

definition, [Online]. https://single-market-

economy.ec.europa.eu/smes/sme-

definition_en (Accessed Date: July 10, 2024).

[29] Häder, M. (2022). Empirical social research:

an introduction. Springer Nature.

[30] McCormick, K., & Salcedo, J. (2017). SPSS

statistics for data analysis and visualization.

John Wiley & Sons.

[31] Field, A. (2013). Discovering statistics using

IBM SPSS statistics. Sage Publication.

[32] Rao, C. R., Shalabh, Toutenburg, H., &

Heumann, C. (2008). The Multiple Linear

Regression Model and Its Extensions. Linear

Models and Generalizations: Least Squares

and Alternatives, 33-141.

[33] Cohen, J. (1992). Statistical power analysis.

Current directions in psychological science,

1(3), 98-101.

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

The authors equally contributed in the

presentresearch, at all stages from the formulation

of the problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflicts of interest to declare.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.e

n_US

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2024.21.145

Robert Piotr Dombek, Radek Jurčík

E-ISSN: 2224-2899

1787

Volume 21, 2024