When Do People Retire

When and why do people retire? The impact of work values, work quality, and national retirement characteristics on individual retirement age in 21 European welfare states

Maria Fleischmann, Ferry Koster, Pearl Dykstra, Joop Schippers

Introduction Work values and work quality have been recognized to be important antecedents of employee turnover (Beehr, 1986; Lambert et al, 2001). Research from the management literature shows that especially those ‘soft’ characteristics, i.e. the individuals’ work motivation or workers’ autonomy, are of major importance for individuals’ job satisfaction (Beehr, 1986; Shultz et al, 1998; Wang & Shultz, 2009). As such it is often hypothesized and consistently found that job dissatisfaction affects cognitive withdrawal from work and increases the intention of voluntary job turnover (ref.). It is arguable that work quality and work values does not only play a role for voluntary job turnover, but also for the intention to retire (Mein et al, 2000; Siegrist et al, 2006) and the decision to retire (Beehr, 1986; Hayward et al, 1998; Wang & Shultz, 2009; Siegrist & Wahrendorf, 2010). Nevertheless, the impact that work quality and work values can have on the decision to retire, has until now hardly been taken into account (Siegrist & Wahrendorf, 2010). Implementing a country-comparing perspective has instead become an increasingly interesting topic in research on retirement as well as public policy. With respect to policy, the aim is to increase labor market participation of older workers and the average retirement age, because the low actual retirement age together with a rising life expectancy entails that more people require pensions and other publicly financed arrangements for a longer period of time. The increase of the older population that relies on welfare state benefits is thus increasing relative to the labor force that contributes financing the welfare state (European Commission, 2009; Wise, 2010). To sustain the welfare state, multiple European countries agreed in 2002 in the Barcelona target to increase the effective retirement age by five years until 2010 (Liefbroer, 2009). After the

1 target year 2010 some countries managed to increase labor the retirement age, but there are still large differences between countries. Regarding social research, most studies investigating the impact of welfare on retirement age in a country comparing perspective take into account rather general national measures, such as GDP per capita of a country (Kim, 2009). Even though this can inform about the relation between retirement age and national characteristics, it does not provide information on the effect of country characteristics on retirement. In order to gain more insight into the actual welfare state characteristics associated with retirement, we propose to include country variables that measure the retirement scheme directly, namely the official retirement age, the minimum contribution period, and the net replacement rate. Referring to considerations about country variation with regard to the decommodification of the welfare state in post- industrial societies (Esping-Andersen, 1990), we assume that dependent on the availability of benefits and their coverage, differences in retirement age between countries can be explained. To approach the research question when and why individuals take the decision to retire, we include those individual characteristics for which it is known from prior research to influence retirement age (such as health, earnings). Additionally, we use the framework of push and pull factors and rational choice theory to derive expectations about the influence of work values and work quality. We furthermore add macro characteristics informing about the coverage and availability of a country’s retirement benefits and make assumptions about the interplay of individual and institutional characteristics. In order to investigate the effect on retirement age empirically, we make use of the second wave of the European Social Survey (ESS, 2004) and enrich this dataset with international pension indicators that were developed within the MULTILINKS-project (Keck et al, 2009). Thus, we will be able to study the impact of the individual and institutional setting on the individual retirement age for 21 European countries (N=3,898).

Pathways to retirement When studying the transition from employment to retirement in an international comparative perspective, it is interesting to gain some insight into the different pathways

2 to retirement first. Generally, people hardly ever explicitly choose the transition from full employment to full retirement (Blanchet et al, 2005; von Bohnsdorff, 2009; European Commission, 2009; Social Protection Committee, 2007). Rather, three main pathways from employment to retirement can be identified: via unemployment, sickness or disability insurance or pre-retirement schemes. If people receive unemployment benefits between employment and retirement, this can be an indication of involuntary retirement. It may indicate that employees got laid off by their employers, who expect them to be less productive or less willing to be trained (van Dalen et al, 2009, 2010; Karpinska et al, 2011) and therefore rather substitute older workers by more productive younger ones. Unemployment benefits as an intermediate step from employment to retirement occurs quite often in Germany, France or Denmark (Blanchet et al, 2005). Leaving the work force and receiving sickness or disability benefits will apply especially to people who have to leave the labor market due to health problems but are not yet in official retirement age. However, it appears that receiving these kinds of benefits is easier in one country than another. Sickness and disability benefits seem to be a pathway to retirement especially in for example the Netherlands or Spain (Blanchet et al, 2005, Gruber & Wise, 1999). Last, early retirement schemes can be provided by the firm, but there are also national systems that enable early retirement (Blanchet et al, 2005; Gruber & Wise, 1999). This indicates that even though retirement seems a rather homogeneous concept in the first place, there is variability between countries as to how this pathway looks like when regarded more closely. A more elaborate overview of the different benefit systems and the usage of various pathways to retirement can e.g. be found in Blöndal & Scarpetta (1999) and Gruber & Wise (1999) and for recently unemployed people in OECD report (2011). In this paper we will study the transition to retirement, but instead of focusing on the different pathways to retirement, our emphasis will on individuals’ self-reported retirement status. Thus, when interviewed, people decide themselves in which year they retired. This is regarded an appropriate measure of retirement status by researchers (Blanchet et al, 2005).

3 Theoretical approaches to retirement research Two theoretical approaches are generally used to model effects on retirement age (or the participation rate). These are the push and pull framework and rational choice theory. When identifying push and pull factors that influence retirement, pull factors are said to be positive factors that provide individuals a (monetary) incentive to retire and thus pull them towards retirement. Push factors, on the other hand, are individual-level characteristics that press people towards retirement, be it because of a poor health or bad job characteristics, for example (Blekesaune & Solem, 2005; Hofäcker & Pollnerova, 2006; OECD 2006, 2011; van Oorschot & Jensen, 2009). This means that individuals are expected to retire earlier if they are pulled or pushed towards retirement, and retire later if work detains them from retirement. Regarding retirement as a rational decision is also a prominent approach in research (Wang & Shultz, 2009). Modeling the retirement decision by means of rational choice theory (Coleman, 1990; Wang & Shultz, 2009), individual and country (welfare state) characteristics are assumed to provide a certain utility for retirement. Alternatively to retirement, utility could be derived from work outcomes or unemployment or disability benefits. This means, if the utility of retirement is higher than the alternative utility of work, individuals are expected to retire. Much prior results on retirement age stems from policy-oriented research (Blöndal & Scarpetta, 1999; European Commission, 2009; Liefbroer, 2009; OECD, 2011). This research is often less theoretically motivated, wherefore theoretical considerations about retirement age are less developed than in other research. Furthermore, much research investigates the effect of health on retirement, rather than asking about the reasons that led to the decision to retire (Siegrist & Wahrendorf, 2010). Still, research results from the various fields converge in their findings. Common characteristics included in studies are individuals’ characteristics (health, gender), their human capital (education, training, job tenure), job-related characteristics (sector or industry, fulltime/ part-time employment, earnings, unemployment), or social relations (partner, children). Research results shows that people with poor health (von Bohnsdorff, 2009; Hayward et al, 1989; Hayward et al, 1998; Mein et al, 2000; Schils, 2008) and women (Blöndal & Scarpetta, 1999; European Commission, 2009; OCED, 2011) tend to retire earlier. Human capital characteristics are

4 generally found to have a positive association with retirement age, meaning that individuals with higher education (Hayward et al, 1989; Hayward et al, 1998; Blekesaune & Solem, 2005), or longer job tenure (Hayward et al, 1989; Hayward et al, 1998, Schils, 2008) are more likely to retire later. With respect to job-related characteristics, retirement age is found to be lower for people that have to deal with a higher physical demand (Hayward et al, 1989, 1998; Blekesaune & Solem, 2005), for part-time workers (Hayward et al, 1998; Damman et al, 2010), or for workers that recently experienced unemployment (OECD, 2006). Social relations characteristics are found to be related negatively to retirement age, as individuals with a partner (Schils, 2008) or children (Damman et al, 2010; Schils, 2008) appear to retire earlier in some countries. Prior findings regarding monetary compensation from work (earnings, hourly wages or general wealth) and retirement age are not straightforward. A higher hourly wage is found to be related to earlier retirement in the US (Hayward et al, 1989; Hayward at al, 1998) and UK (Schils, 2008). Other studies however indicate that a higher hourly wage is related to later retirement in the Netherlands or Germany (Schils, 2008). With respect to wealth (e.g. home ownership, savings) it is found that wealthier people in the Netherlands are generally retiring later (Damman et al., 2010). Furthermore, comparative research included country characteristics to account for differences between countries. Results show that a higher unemployment rate in a country (Blöndal & Scarpetta, 1999; Fischer & Sousa-Poza, 2006 Kim, 2009), or a lower GDP per capita (Fischer & Sousa-Poza, 2006; Kim, 2009) is associated with a lower retirement age.

Both theoretical approaches comprise advantages and disadvantages for modeling the retirement decision. Push and pull factors are unclear in their categorization of whether a specific individual characteristic is pushing towards retirement or pulling towards work. Furthermore, as workers are pushed or pulled, this framework seems to suggest that workers are rather passive in their decision. A disadvantage of rational choice on the other hand is that the worker cannot decide fully individually whether or not to retire. This is, because employers influence the decision by determining whether to employ the worker in the future (van Dalen et al, 2010; Karpinska et al, 2010).

5 Even though there are disadvantages for both theoretical approaches, they seem appropriate for the purpose of the current study. First, as both provide the same hypotheses with respect to retirement, using both frameworks allows us to relate to the different fields they stem from. Also, we can use the terminology of push and pull factors when hypothesizing about effects of work values and work quality on retirement, and the terminology of rational choice theory when making expectations about earnings or welfare benefits. Last, by phrasing all hypotheses in the same direction, namely towards retirement (rather than work), we can circumvent the problem of indistinct terming when using push and pull factors. We will thus model the decision of retirement with both the push and pull framework and rational choice theory.

Individual level: work quality, work values, and earnings The working life as well as the role of work in people’s lives changed in the post- industrial society. While work used to provide an income to fulfill the basic (deficiency) needs, most people in today’s society already achieved these needs, which makes them strive for the fulfillment of higher needs (‘growth needs’). Individuals do not just work for the money (see also Frey, 1997) but to obtain self-actualization, self-development, or self-fulfillment. Beyond working for earnings, they obviously want to achieve higher goals. In this context, individuals’ work quality and their work values have become more important. We argue that a better work quality and more work-related values increase the possibility to obtain needs such as self-actualization or self-fulfillment. If individuals’ work-related aims are fulfilled, this will lead to a higher work satisfaction or utility from work. With respect to the push and pull framework, we suggest that higher work quality will be related to a higher retirement age. This is, because a higher work quality pulls people towards work (rather than retirement). Retirement is thus postponed in comparison to someone with lower work quality (Siegrist & Wahrendorf, 2010). Indicators for a better work quality are for example if a worker experiences a higher autonomy or a lower physical demand at the workplace. We thus hypothesize that (H1a) the higher individuals’ work quality is the later they will retire.

6 Individual work values can give some indications which work features are important to individuals. Generally, the literature distinguishes two kinds of values towards work: intrinsic and extrinsic values, also named intrinsic and extrinsic motivation (see e.g. Frey, 1997; Ingelhart, 1990). While people holding extrinsic values will find income, status, or promotion possibilities important in a job, people with intrinsic values may approve workplaces that offer the possibility to use the own initiative, variety, or creativity. Independent of the sort of values by which they are driven, people will derive more satisfaction from work if their general motivation is higher. It is important to note that intrinsic and extrinsic values are not regarded as opposite poles on one single scale, but as two different indicators for values. This means that a person can be highly extrinsically motivated and intrinsically motivated at the same time. As a result, individuals with more pronounced work values will regard their work more important and thus retire later. We hypothesize that (H1b) the higher individuals’ work values are the later they will retire. Monthly earnings from employment are clearly financial benefits that influence the utility derived from work. According to rational choice theory, individuals would decide to work rather than retire, if the income from work (or: its subjective expected utility) exceeds income from retirement. This means that generally, an individual actor receives a higher utility from work, the higher the earnings are. We therefore hypothesize that (H1c) the higher individuals’ earnings are the later they will retire.

Institutional level: Generosity and availability of retirement benefits The concept of decommodification of the welfare state is often used as an indication of the relevance of work (Esping-Andersen, 1990). The more a welfare state is decommodified, the less dependent are individuals from employment in order to obtain earnings that suffice for live. In other words, welfare state benefits are encompassing enough to care for the individual and benefits are available to a broad group of people. The liberal welfare states, such as Great Britain or the US, generally provide less encompassing welfare benefits and benefits are available to fewer people than they are in the social-demographic welfare states Sweden or Finland. As pensioners are dependent on the retirement benefits in their country, the availability and generosity of these benefits will promote differences between countries.

7 In order to assess whether differences in retirement age between countries can be explained by different welfare systems, we will regard three institutional characteristics that can give an indication of how encompassing the welfare state is. These are the official retirement age, the minimum contribution period, and the net replacement rate. While the official retirement age and the minimum contribution period can provide information on the ‘availability’ of the retirement benefits, the net replacement rate gives insight into the coverage of the welfare state or its financial ‘generosity’. More encompassing welfare states would thus have fewer restrictions on the availability of the benefits and offer a greater coverage. We assume that more encompassing welfare state benefits will decrease the value of employment as a commodity. Stated differently, higher or more easily available retirement benefits will increase the utility a person has from retirement. We hypothesize that (H2) the greater the availability and the coverage of the retirement benefits are in a country the earlier will people retire. This means that the retirement age is assumed to be lower in countries with more encompassing retirement schemes and that the extent to which a welfare state is encompassing is expected to explain part of the differences between countries.

Data In order to investigate the hypotheses empirically, we use data from the second round of the ESS (ESS, 2004). This dataset encompasses about 47,500 respondents from 25 European countries. We are only interested in those respondents that are already retired. Furthermore, we restrict our sample to pensioners who retired in the last 15 years and were 45 years or older at the time of retirement. These restrictions are made because those people who retired prior to age 45 seem to be extreme in other respects as well, and because many questions are asked retrospectively, we restrict our sample to retirees of the last 15 years. To the individual level data we add macro-level indicators that were established within the MULTILINKS project. This database encompasses information on different welfare state characteristics, such as the official retirement age in a country for men and women, the net replacement rate for different forms of careers (interrupted etc.), and the minimum contribution period (Keck et al, 2009). As institutional data is not

8 provided for Switzerland, Iceland, Turkey, and the Ukraine, and after imposing the above mentioned restrictions, our basic sample refers to 3,898 respondents from 21 countries.

Operationalization Dependent variable The dependent variable is the age at which the respondent retired. It is generated as the difference between the year the respondents indicated to be retired and their respective birth year. This means that the year in which the respondent retires is a subjective assessment. This is rather frequently done in social research and as respondents can be assumed to remember the year of retirement quite well, this should provide a relatively accurate estimate of their retirement age (Blanchet et al, 2005). As stated above, we only include respondents that retired at age 45 or later. The descriptive statistics show that respondents’ age at retirement varies between 45 and 85 years of age. The mean retirement age for all countries is 60 (SD=5.17). Comparing countries, retirement age is lowest in Poland (about 55.5 years) and highest in Sweden (64.1 years). In Figure 1, we display the retirement age for each country in our sample. The median retirement age is indicated by the diamond marker, the upper bound of the boxplot reflects the 75th percentile, the lower bound of the boxplot the 25th percentile. The grand mean of 60 is indicated with a dotted line. We see that countries differ with respect to their median retirement age, but also the variation in retirement age is higher in some countries than others. France, Spain or Sweden for example has a rather low variation, while it is especially high in for example Poland, Hungary or Slovakia. As we do not have a sample of just retired respondents, we correct for the time someone already spent in retirement by including a variable that controls for the years the individual is already retired in the year of the interview. This variable is generated from the year of the interview and the year of retirement.

9 Figure 1: Boxplot of retirement age for each country in sample.

Independent variables Work quality is operationalized with the three variables work organization, work pace, and physical demand, which all refer to the respondent’s last job. Work organization measures the extent to which the respondents were allowed to decide how their daily life was organized; work pace in the last job measures the extent to which respondents were allowed to choose/change the pace of their work. Both variables take on values from 0 (‘I had no influence’) to 10 (‘I had complete influence’). Physical demand is retrieved from the ISCO-88 codes. We recoded each 4-digit code to its respective 2-digit code and assume that the higher the code, the higher is the physical demand of the job. Respondents who indicated to work in ‘armed forces occupations’ were coded to the mean 2-digit ISCO code. This way, our indicator for physical demand has 33 different values with a range between 10 and 93. Work values are divided in extrinsic and intrinsic motivation. As they are general ‘values’, this variable refers to the values the respondent carries at the moment of the interview. We however assume that since values are rather unchanging over time, they relate well to the values before retirement. For extrinsic motivation we generate a sum scale, including three items asking the respondents to indicate on a scale from 1 to 5 how

10 important it is for them when choosing a job to have a secure job, a high income, and good promotion opportunities. The resulting scale ranges from 0 to 12, with a mean extrinsic motivation of about 9. Intrinsic motivation is part of the same item-battery and asks how important the respondents find that ‘the job enables them to use own initiative’ when choosing a job. This variable is binary with a mean of 0.78, indicating that 78% of the respondents find it important to use their own initiative in their job. Individuals’ monthly earnings are generated from to the monthly household income and the percentage of income the respondent contributes to the household income. As household income is asked in twelve categories, each category is recoded to the respective income in Euro. While the higher bound value is taken for the lowest category (150 Euro or less), the lower bound value is taken for the highest category (10,000 Euro or more). For all other categories, the mean of the lower and upper bound is considered as the monthly household income. Afterwards, the household income is multiplied with the percentage the respondent indicated to contribute to the household’s income to retrieve individual monthly earnings and is transferred to a logarithmic scale.

*** Table 1 about here ***

Country characteristics There are three indicators that can be used to get an approximate idea about the retirement age in a country: Both the official retirement age and the minimum years of contribution can provide a measure for the age at which a person is allowed to retire officially. Additionally, the net replacement rate provides insight into the financial circumstances that might influence an individual’s decision whether or not to retire. Dependent on prior earnings, the composition of the household, or other household member’s earnings, the pension is set as a percentage of the earnings (see e.g. Blöndal & Scarpetta, 1999; OECD, 2011). Only when taking these indicators together we can get an approximate idea about why people retire earlier in one country than another. We thus measure the generosity of the welfare state with four variables. The official age at retirement for men and women separately, the net replacement rate for a standard career, and the minimum contribution period. As the official retirement age varies only between

11 57 and 67 for women and between 60 and 67 for men, we decided to recode the variables as to whether the official retirement age in a country is equal or higher to a retirement age of 65 (1) or lower (0). This variable is generated for women’s official retirement age and men’s official retirement age. We chose 65 years as the cutpoint as this is the most frequent official retirement age in the countries in our analyses. The net replacement rate and the minimum contribution period vary between 41 and 105, and 0 and 29.3, respectively. The mean net replacement rate is about 78 percent; the mean minimum contribution period is about 10 years. An indication of the minimum contribution period in a country as well as the net replacement rate per country is provided in Figure 2.

Figure 2: Descriptive figure of minimum contribution period and net replacement rate for countries in analyses, data from the MULTILINKS-project.

We see that the minimum contribution period in zero of close to zero years in the ‘social- demographic’ welfare states, about 10 to 15 years in most continental, Southern, liberal, and Eastern-European states, and only in Poland and Belgium higher than 20 years. For

12 the net replacement rate it appears that Estonia has the lowest net replacement rate with about 40 percent and Greece the highest with above 100 percent. Here, as with the minimum contribution period, no clear trend according to welfare state type appears.

Control variables Gender is measured by a dummy variable referring to male respondents. According to OECD standards, fulltime is a dummy variable indicating whether respondents worked more than 30 hours per week in their last employment and is opposed to part-time workers, those who worked 30 hours or less per week. Self-employment is a binary variable that refers to the last employment. The variable being self-employed (or working in a family business) is opposed to being employed in a firm. Health is a continuous variable measuring the respondents’ health on a scale between 0 and 4, with a higher value indicating a better health. Education is measured as the formal education in years; more than 20 years of education are recoded to the maximum value of 20 years. Last, we include a dummy variable indicating whether respondents were ever unemployed and seeking for work for a period of more than 3 months. The industry of the last employment is measured in 7 categories; ‘Agriculture, Mining’, ‘Manufacturing’ (reference category), ‘Supply, Construction, Trade’, ‘Service’, ‘Public, Community’, ‘Education, Health’, and ‘Missing’. Country characteristics On the country level, we control for the gross domestic product (GDP) per capita as well as a measure for social inequality (GINI). These data are retrieved from the Eurostat database (Eurostat, 2010). GDP is measured in 1000 Dollar units and ranges from 5.3 to 59.9. Social inequality is measured on a scale from 23 to 37.8 with a higher value indicating more social inequality. These variables provide the possibility to control for other country variables besides the retirement scheme in a country, and to compare the present results to earlier studies. Correlations between all national characteristics can be found in Table 2. We see that most characteristics correlate rather high. As such, GDP per capita is correlated negatively with social inequality as well as with the minimum contribution period, but positively with retirement age of both men and women. Social

13 inequality correlates highly with the minimum contribution period but only low with the other national characteristics. For the minimum contribution period we find a high negative correlation with women’s retirement age.

For all variables that have missing values, we imputed the missing values with imputation by chain equations. This means, all variables in the imputation model are used to predict all the other variables. We included all variables that are used in the regression to predict retirement age, to make imputations for variables with missing values; for the ISCO-code and industry, we however left out the respective other variable, as this would have resulted in collinearity. Descriptive statistics of the sample without imputation and with imputation can be found in Table 1. It is comprehensible which variables have been imputed (i.e. fulltime, self-employed, health, unemployed, all work quality variables, work values variables, income) and to what extent the mean of the imputed and original sample differ. We analyze the 11 imputed datasets together with the original dataset and report the average relative variance increase due to nonresponse (RVI) in the results. This can provide some indication to what extent the imputed datafiles vary. The presented analyses with the imputed data hardly differ from analyses relying on the original data (results not shown).

Methods The analytical model should satisfy the requirement of exploiting the structure of the data. Given the hierarchical data, with individuals nested in countries, we specify two levels and apply a multilevel framework (see e.g. Goldstein, 1999). The advantage of using a multilevel framework in our case is that hierarchical models can take into account the layered (nested) structure of the data. Measuring errors are specified at each of the two levels. In this way, the error terms take into account that the individual observations within countries may be more alike than individual observations between countries. For calculating the models, we run linear regression with maximum likelihood random effects estimators.

14 Results We structure our results in the following way: We start with an intercept only model (Model 0), then we include the control variables (Model 1), and afterwards the independent variables on the individual level (Model 2). Finally, we include the country variables successively and separately (Model 3). The intercept only model shows that the grand mean for retirement age is 60 and has a variance of 4.6 within countries (i.e. between individuals in countries), and 2.5 between countries. The respective interclass correlation thus amounts to 0.3522. When including the control variables, we find the following (Table 3, Model 1): The longer individuals are already retired the lower was their retirement age. Men retire significantly earlier than women. The difference amounts to about nine months (0.7 years). Respondents who worked fulltime generally retire earlier than respondents who worked part-time. Furthermore, self-employees retire later than wage-earners. This difference is estimated to be more than one and a half years. The healthier a respondent is, the later he retires. Education is negatively associated to retirement age. This means, higher educated generally retire earlier. Respondents that ever experienced unemployment are found to retire earlier. With respect to the industry of employment, we do not find significant differences. Only those respondents that did not indicate in which industry they were working retire generally later than respondents in manufacturing. Including these control variables decreases both the variance on the individual as well as on the country level. The significance and direction of these relationships does not change when including the independent variables or macro-level variables. Therefore, we will not refer to these variables in the following models. Model 2 in Table 3 presents the results for the independent variables. We do not find a significant association between freedom in work organization and retirement age. Having more freedom with respect to work pace however significantly and positively influences retirement age. This means that better possibilities in adjusting the pace of work is related to a higher retirement age. For the physical demand of work our results show a negative and significant impact on retirement age. Thus, a higher physical demand decreases retirement age. The work values, extrinsic and intrinsic motivation,

15 seem not to relate significantly to retirement age. Also, the effect of income does also not appear significant. Similar results are also provided by models in which each independent variable is added separately to the regression (results not shown).

We display the impact of the country characteristics on retirement age in Table 4. Here, we include the same individual level variables as in Model 3 of Table 3 and add the country characteristics separately. Table 4 reports the effects of the variables together with the variances on the lower and higher level. For the control variables GDP per capita and social inequality we do not find a significant impact on retirement age. We find that a longer minimum contribution period is associated to a significantly lower retirement age. This means that in countries with a longer minimum contribution period the retirement age is generally lower. Countries with a national retirement age of 65 or higher for women have a significantly higher individual retirement age. The same directed effect is found for men’s national retirement age. Last, the net replacement rate does not show a significant impact on retirement age. Regarding the variance on the two levels, we especially find that women’s official retirement age contributes to a decrease in the variance between countries.

Conclusion and discussion Summing up the empirical results, we find that more freedom in deciding about the work pace is positively associated to retirement age. Also, a higher physical demand is related to earlier retirement. Even though we did not identify a significant effect of work organization on retirement age, we have quite good support for H1a, which expected work quality to have a positive relation with retirement age. Hypothesis H1b expected that individuals with higher intrinsic and extrinsic work values would retire later. This cannot be supported with the present analyses. Also hypothesis H1c, expecting a positive effect of earnings on retirement age, cannot be supported.

16 Regarding the hypothesis on the higher level, we operationalized coverage by the minimum contribution period and the official retirement age. While we find the expected effect for the official retirement age, we find a negative effect for the minimum contribution period, which is the opposite than hypothesized. This provides some unexpected insight, namely that people in countries with a higher official retirement age generally retire later, but that people in countries with a longer minimum contribution period are found to generally retire earlier. For the net replacement rate in a country we do not find a significant association with retirement age. In total, we can thus not accept hypothesis H2, which expected that individuals in more generous welfare states would retire later. Even though in our analyses we make use of a sample of individuals who retired in the last 10 years, the results of our control variables are in line with prior research. As such we find that men retire later than women, self-employed later than wage-earners and workers with a better health retire later as well. Moreover, we see that fulltime employed and unemployed retire earlier. However, the work values extrinsic and intrinsic motivation does not prove to influence retirement age in our analyses. Reasons for this can be found in the type of the data: Respondents are asked retrospectively about their working career and information about working fulltime or part-time or work quality is easily provided retrospectively by the respondent. Characteristics such as income and values however are asked for the time point of the interview. Even though research assumes that values are rather consistent over time (Frey, 1997), changes might occur after an incidence like retirement. Then, they do not provide a good approximation of the values prior to retirement. This means, while our results are informative with respect to ‘factual’ characteristics, they might be to a lesser extent with regard to respondent’s values. Future research can try to assess the effect of work values by using data that is collected closer to the actual transition into retirement or by using longitudinal data with information about values during employment and retirement outcomes at a different point in time. For the insignificant effect of income, a similar rationale applies. As the measure of income refers to the income the respondent receives while retired, it might not be a very good approximation for pre-pension earnings. This can also be an explanation, for why earlier research quite consistently found an impact of earnings on retirement age.

17 Our analyses provide evidence of the following. First, the individual characteristics known from prior research to have an impact on retirement age are found to influence retirement age in our analyses as well. Second, individuals with higher work quality were expected to retire later; evidence for this is provided by our results. Following these results, policy or social researchers should not only take into account general individual characteristics such as the health or the income when investigating retirement age, but also include information about the work quality an individual experiences. As workers with a better work quality are found to retire later, offering a work environment that stimulates work quality could also help increase the retirement age or older workers’ participation rate. Third, work values do not prove to significantly affect retirement age. Since we theoretically assume that individuals with higher intrinsic or extrinsic work values retire later, we advice future research to consider work values when studying retirement age. Using data from before and after retirement could provide the necessary knowledge about work values prior to retirement and their impact on retirement age. Last, the country characteristics included in these analyses differ from prior research due to the clear focus on retirement benefits. While we do not find an effect of GDP per capita or inequality on retirement age that were also included in prior research, we do assess that the official retirement age of men and women significantly relates to individuals’ retirement age. Future research using with longitudinal data could compare the actual retirement age in countries before and after changes in the official retirement age were adopted. This can yield a better approximation of whether a higher retirement age is indeed due to policy changes.

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21 Table 1: Descriptive statistics original sample and imputed variables. Original sample Imputed variables Variable Range Obs. Mean St.dev Obs. Mean St.dev Retirement age 45 - 85 3898 60.099 5.160

Years in retirement 0 - 9 3898 4.455 2.704 Gender (Male=1) 0 / 1 3898 0.535 Fulltime employed 0 / 1 3499 0.858 46377 0.856 0.351 Self-employed 0 / 1 3803 0.189 46681 0.192 0.394 Health 0 - 4 3892 2.419 0.899 46770 2.419 0.898 Years of education 0 - 20 3858 10.371 3.816 46736 10.373 3.810 Unemployment > 3m 0 / 1 3888 0.182 46766 0.182 0.386 Industry Agriculture, mining 0 / 1 3898 0.100 Manufacturing 0 / 1 3898 0.230 Supply, Construction, Trade 0 / 1 3898 0.166 Service 0 / 1 3898 0.181 Public, community 0 / 1 3898 0.114 Education, Health 0 / 1 3898 0.158 Missing 0 / 1 3898 0.051 Work quality Work organization 0 - 10 3749 5.863 3.657 46627 5.868 3.657 Work pace 0 - 10 3730 5.569 3.683 46608 5.595 3.679 Physical demand 10 - 93 3741 52.643 25.722 46619 52.818 25.732 Work values Extrinsic motivation 0 - 12 3140 8.918 2.170 46018 8.904 2.242 Intrinsic motivation 0 / 1 3163 0.789 46041 0.781 0.414 Income (log) 0 - 9.21 3173 6.463 1.138 46051 6.444 1.146

Country characteristics GPD per capita 5.3 - 59.9 3898 22.984 12.707 Social inequality (Gini) 23 - 37.8 3898 28.929 4.511 Minimum contribution period 0 - 29.3 3898 10.559 7.932 Net replacement rate # 41 - 105 3771 78.324 15.624 Retirement age>= 65, women 0 / 1 3898 0.514 Retirement age>= 65, men 0 / 1 3898 0.695 Note: # net replacement rate not available for Norway; results rely on individuals of 20 countries only.

22 Table 2: Correlations between national characteristics of welfare states. a b c d e GPD per capita 1 Social inequality (Gini) -0.365 1 Minimum contribution period -0.483 0.422 1 Net replacement rate # 0.073 0.115 0.175 1 Retirement age 65, women 0.491 -0.051 -0.421 0.226 1 Retirement age 65, men 0.543 0.093 -0.038 0.210 0.676 Note: # net replacement rate not available for Norway; results rely on individuals of 20 countries only.

23 Table 3: Multilevel regression results for age of retirement. Model 0 Model 1 Model 2 Coef. s.e. Coef. s.e. Coef. s.e. 60.08 61.48 62.72 Constant 0 0.553 *** 3 0.678 *** 7 1.029 *** Years in retirement -0.152 0.027 *** -0.158 0.027 *** Gender (Male=1) 0.698 0.157 *** 0.748 0.162 *** Fulltime employed -0.533 0.235 * -0.568 0.237 * Selfemployed 1.763 0.266 *** 1.591 0.276 *** Health 0.234 0.088 ** 0.227 0.089 * Years of education -0.133 0.023 *** -0.163 0.028 *** Unemployment > 3m -1.121 0.195 *** -1.090 0.195 *** Industry Agriculture, mining 0.277 0.299 0.125 0.303 Manufacturing ref. ref. Supply, Construc- tion, Trade 0.037 0.234 -0.091 0.236 Service -0.296 0.229 -0.403 0.232 Public, community -0.252 0.265 -0.347 0.267 Education, Health 0.100 0.258 -0.024 0.263 Missing 1.514 0.363 *** 1.332 0.369 *** Work quality Work organization -0.041 0.034 Work pace 0.075 0.033 * Physical demand -0.011 0.004 ** Work values Extrinsic motivation 0.053 0.050 Intrinsic motivation -0.454 0.253 Income (log) -0.075 0.093

Level 2 variance (between) 2.510 0.396 2.409 0.381 2.404 0.381 Level 1 variance (within) 4.617 0.052 4.483 0.051 4.470 0.051 rho 0.228 0.056 0.224 0.055 0.224 0.055 ICC 0.3522 0.3495 0.3497

N (Level 2) 21 21 21 N (Level 1) 3,898 3,898 3,898 N (Imputations) 11 11 11 Average RVI 0.034 0.120 Note: # net replacement rate not available for Norway; results rely on individuals of 20 countries only. *** p<0.001. ** p<0.01, * p<0.05.

24 Table 4: Results of national characteristics on retirement age. Social inequality Min. contribu- Retirement age Retirement age Net replacement GPD per capita (Gini) tion period 65, women 65, men rate # Coeff. s.e. Coeff. s.e. Coeff. s.e. Coeff. s.e. Coeff. s.e. Coeff. s.e. National charac- 0.060 teristic 0.059 0.037 0.038 0.119 -0.122 * 2.821 0.872** 2.496 1.048* -0.022 0.034 Level 2 variance (between) 2.268 0.360 2.397 0.381 2.196 0.349 1.953 0.312 2.129 0.338 2.337 0.380 Level 1 variance (within) 4.470 0.051 4.470 0.051 4.470 0.051 4.470 0.051 4.470 0.051 4.474 0.052 rho 0.205 0.052 0.223 0.055 0.194 0.050 0.160 0.043 0.185 0.048 0.214 0.055 ICC 0.3366 0.3491 0.3294 0.3041 0.3226 0.3431 Note: # net replacement rate not available for Norway; results rely on individuals of 20 countries only. *** p <0.001. ** p <0.01, * p <0.05.