TWIN PEAKS: An Analysis of the Gender Gap in Pension Income in England

Transcription

1 TWIN PEAKS: An Analysis of the Gender Gap in Pension Income in England Onyinye Ezeyi (University of Bath) Sunčica Vujić (University of Antwerp and University of Bath) Abstract: This paper investigates the gender gap in state and private pensions in England using data on retirees from the English Longitudinal Study of Ageing. The analysis finds that the female distribution of state pension income is bimodal, an idiosyncrasy that arises because a large proportion of women have pensions derived from their spouse s contribution record. Though there are no gender gaps in state pension coverage, the female-male state pension income ratio is 0.75 and Blinder-Oaxaca decompositions indicate that only a quarter of the gap in mean state pension income is explained by observed characteristics. The analysis is also extended to quantile regressions and decompositions reveal sticky floors in state pension income. The gender pension gap is more marked for private pensions than state pensions. Decompositions suggest that gender differentials in characteristics matter more for private pension coverage rates than private pension income levels. Specifically, differential characteristics account for half of the gender gap in private pension coverage but only 28% of the gender gap in private pension income. Quantile analysis of the gap in private pension income indicate that though there is greater volatility, the gap remains relatively close to the mean gap. The private pension estimates are not robust to selectivity corrections. Key words: gender pension gap, England, decomposition methods, quantile regression JEL: C21, C24, J31, J71 Corresponding author: Onyinye Ezeyi ome22@bath.ac.uk 1

2 1. Introduction Women have a higher risk of old age poverty than men and are more likely to claim means-tested benefits in retirement, indicating that they do not have adequate retirement income (Ginn, 2003; Department for Work and Pensions 2013). Women s higher propensity of poverty in retirement is related to their pension entitlement as pension benefits are the main source of income for retirees in the UK. In the 2013/2014 tax year, average weekly gross income for retired households in the UK stood at 487 (in 2014 prices), of which pension benefits accounted for 67% (Department for Work and Pensions, 2013). The pension income an individual receives in retirement is related to their labour market outcomes and personal characteristics since individuals pay contributions during working life to accrue pension rights and secure an income in retirement. Despite the abundance of research into the gender wage gap, little research has been conducted in the economic literature into the extent to which women s lower lifetime labour market outcomes translates into lower pension outcomes in later life. The historical dimension of the accumulation of pension rights mean that other factors emerge in the determination of the gender pension gap that may not be pertinent to the gender wage gap. An analysis of the gender gap in pensions for the UK is important for at least two reasons. First, increasing life expectancy together with women s greater longevity imply that, unless women s pension outcomes equalise with men s, women are likely to spend an increasing proportion of their lives at risk of poverty. Secondly, the restructuring of the UK state pension to a one-tier system and the government s emphasis on private pensions in helping individuals secure adequate retirement income mean that research on the gender pension gap can better enable the design of private pension policy in the UK. This paper contributes to the scant economic literature by providing a comprehensive analysis of the gender pension gap in England. The paper first examines the factors that determine pension coverage and pension income for state and private pensions 2

3 separately. The paper then uses Fairlie (1999) and Blinder (1973) Oaxaca (1973) decomposition to respectively decompose the gap in pension coverage and income into the explained and unexplained components. The analysis conducted in this paper is most similar to Even and Macpherson (1994) who examine the gender gap in occupational pensions for the US, Bardasi and Jenkins (2010) who investigate the gap in private pensions for the UK and Hänisch and Klos (2014) who examine old age income in Germany at the mean and for the entire pension income distribution. The results from these studies are mixed. Even and Macpherson (1994) find that among retirees, 80% of the predicted gap in occupational pension coverage and 70% of the predicted gap in occupational pension benefit is accounted for by gender differentials in characteristics. However, they do not employ regression-based decomposition techniques. Conversely, Bardasi and Jenkins (2010) find that between 33%-42% of the gap in private pension coverage is explained, while 8%-18% of the gap in benefit level is explained. However, unlike Bardasi and Jenkins, we are able to control for earnings and also extend our analysis to quantile regressions. Analysing German data from 2007, Hänisch and Klos (2014) find that only 26% of the gender pension gap is explained and that the largest share of the explained gap occurs at the bottom 25% of the pension income distribution. To the best of our knowledge, this is the first paper to examine the gender gap in UK state pensions using regression-based decompositions and to apply quantile decomposition techniques for both state and private pensions. The results from our analysis confirm the presence of gender gaps in both state and private pensions. While state pension coverage is virtually universal for both sexes, there are substantial gender inequalities in the level of state pension benefit received; the raw female-male state pension income ratio is Blinder-Oaxaca decompositions show that only a quarter of the gap in state pension income can be attributed to gender differentials in mean characteristics and that women s lower state pension income arises because they receive state pensions derived from their spouse s National Insurance contribution record. Results from quantile regressions provides the first evidence of sticky floors in state pensions. That is, the gap is largest at the bottom 30% of the state pension income distribution than at the top of the distribution but is decreasing as one moves up the distribution. Unlike state pensions, the analysis shows 3

4 that there are gender gaps in both private pension coverage and income; only 63% of women had private pension coverage compared to 90% of men and the raw femalemale pension income ratio conditional on coverage stands at Decompositions of private pension coverage suggest that gender differences in average characteristics account for around half of the gap in probability of private pension receipt, while Blinder-Oaxaca decompositions suggest that 72% of the gap in private pension income is unexplained. The results for private pension income are not robust to selectivity corrections. The remainder of this paper is organised as follows. The next section discusses the institutional context of the UK pension system for the sample of retirees used in this analysis. It also provides explanations for why men and women may have differential state pension outcomes. Section 3 provides economic rationale for the demand and provision of pensions in the labour market and also examines the mechanisms through which the gender gap in private pensions may arise. The methodology used to decompose the gender gap in pensions in Section 4, while Section 5 describes the data and sample used in this analysis. Model estimates and the results of the decompositions are shown in Section 6. In Section 7, selectivity corrections are presented as robustness checks. Section 8 summarises the findings and discusses the policy implications of the results. 2. The Institutional Context In the UK, pensions are provided by both the State and private sector. In order to analyse the gender gap in pensions, it is necessary to understand the institutional context of the UK pension system. In April 2016, a new state pension system was introduced, however, because the sample of the sample of retirees analysed in this study built up their pension entitlement under the pre-2016 system, this section provides a brief overview of the state pension system until 2016 and also highlights 4

5 features of the state pension system that may have served as possible mechanisms of gender inequalities in state pensions. This section also describes private sector provision of pensions in the UK. 2.1 State Pensions For individuals retiring before April 2016, the state pension was made up a flat-rate pension known as the Basic State Pension and an earnings-related component known as the Additional State Pension. Individuals built entitlement to the state pension during their working lives by paying National Insurance contributions or were given National Insurance credits. It was possible, as it is in the post April 2016 system, to claim the state pension and continue in paid employment. Men and women of state pension age (65 and 63 years respectively in January 2016) with sufficient years (30 years) of National Insurance (NI) contributions or credits received the full Basic State Pension (BSP) of per week in the tax year as well as any entitlement to the Additional State Pension. Individuals with less than 30 years of NI contributions or credits received a pro-rata amount. The Additional State Pension received is a composite of the various earnings-related state pension schemes that existed i.e. the State Earnings Related Pension Scheme and the State Second Pension. The selfemployed did not build up entitlement to the Additional State Pension (ASP) and the ASP is not payable for the years in which employees were members of a contracted-out private pension scheme. For the sample of retirees under consideration, there are two main reasons why women s state pension outcome might be worse than men s. First, the UK state pension system introduced in 1948 was designed to reflect prevailing societal norms. In particular, the state pension system reinforced the male breadwinner-female homemaker model of familial division of labour. A man s NI contribution record bought two state pensions; one for himself (i.e. Category A pension) and one for his wife, valued at 60% of his entitlement to the Basic State Pension (i.e. Category B pension). In addition, there were strong incentives for married women to claim a state pension 5

6 based on her husband s NI record; until 1978, married women had the option to pay reduced rates of NI contributions in return for forfeiting entitlement to a state pension in their own right. This was known as the Married Woman s Stamp and a woman that elected to pay the lower NI contributions would receive a Category B pension on retirement. Women that did not opt into the Married Woman s Stamp had to pass the Half Test which required paying sufficient NI contributions for at least half of the number of weeks between their date of marriage and state pension age, to receive any state pension in her own right. Secondly, women spend a substantial period of time out of employment as due to their caring responsibilities in the home. Thus, historically, it has been more difficult for women to have the requisite number of years to claim entitlement to the full BSP. Since 1978, the NI system has taken into account time spent out of the labour market due to caring responsibilities. However, individuals still needed to have paid NI contributions for at least a quarter of their working life to receive any BSP at all and were required to have paid 20 years of NI contributions to receive the full BSP until Private Pensions Private pension provision in the UK consists of occupational pension schemes and personal pensions. Occupational pension schemes are organised by employers for their employees, while personal pension schemes are contracts between individuals and financial institutions. Personal pensions are the only private pension scheme available to the self-employed. Until 2012, employees had the option to contract out of the ASP and enrol in a private pension scheme, thereby paying a reduced rate of NI contributions. Prior to the commencement of automatic enrolment in 2012, the provision of an occupational pension scheme was at the discretion of the employer and firms also had the ability to set the eligibility criteria for scheme membership. Though there is great variety in private pension schemes, most pension schemes in operation in the UK can be categorised as either a defined benefit pension or a defined 6

7 contribution pension. A defined benefit pension is an occupational pension that typically pays beneficiaries a pension according to a predetermined formula based on salary, tenure and an accrual rate whereas defined contribution schemes involve paying contributions into a pension fund that is invested and the accumulated contributions and returns at retirement is used to provide a pension for beneficiaries. All personal pensions in the UK are defined contribution pensions while occupational pension schemes can be of the defined benefit or define contribution type. The ASP was a defined benefit pension. 3. The Role of Pensions in the Labour Market Several arguments have been put forward to explain the demand and supply of pensions by individuals and firms respectively. One strand of the economic literature views individuals demand for private pensions as a form of retirement income insurance (Bodie 1990; Gustman et al. 1994). By receiving pensions as annuity income, recipients effectively insure against the risk that assets run out before death (i.e. longevity risk). Private pensions in particular mitigate the impact of potential reductions to state pensions and other pensioner benefits in future and also help ensure adequate replacement rate. Similarly, another strand of the literature explains individuals demand for pensions in terms of the desire to smooth consumption over the lifecycle. Intertemporal models of saving and retirement posit that individuals aim to maximise expected lifetime utility subject to their lifetime budget constraint in order to smooth consumption over the lifecycle (Modigliani and Brumberg, 1954; Feldstein 1974). In this framework, individuals demand for pension coverage stems from the desire to have adequate income in retirement to maintain pre-retirement standard of living. The theoretical literature also offers some insight into the role of occupational pensions in the labour market. The implicit contract theory of pensions postulates that the 7

8 matching of workers to firms in pension contracts (of the defined benefit type) induces strong worker-firm attachments. In the implicit contract theory, pensions are viewed as deferred compensation that impose substantial capital losses on workers that leave the firm before reaching normal retirement age because of pension back-loading (i.e. the disproportionate amount of pension benefit that is accrued in later years of service in defined benefit schemes) (Kotlikoff and Wise, 1988). By offering pensions, firms create strong incentives for workers to stay with the firm until reaching the retirement window. Consequently, firms offer pension schemes to attract productive workers and regulate worker turnover due to high job turnover costs. In this framework, occupational pensions are used as a sorting device that enable firms to identify and attract workers with low quit propensities since the workers that take up pension jobs are likely to be stayers (Ippolito 1985; 1987). Workers with low quit propensities will self-select into pension jobs and enter an implicit contract with the firm whereby workers effectively agree to long tenure with the firm, while the firm agree to not terminate pension schemes or lay off workers as it is concerned about their labour market reputations (Allen et al 1993; Cornwell et al. 1991). This suggests that while all individuals demand occupational pensions, only those with low quit propensities will take up pension jobs. However, Gustman and Steinmeier (1993) and Even and Macpherson (1996) have shown that turnover rates in jobs with defined contribution pensions, which are more portable, are similar to turnover rates in defined benefit jobs casting doubt on the effects of non-portable pensions in restricting job mobility. Instead, Gustman and Steinmeier (1993) argue that the lower turnover rates in pension jobs is due to the higher total compensation premium of pension jobs rather than pension back-loading. There are numerous channels through which a gender gap in private pensions might arise. First, the strong worker-firm attachments created by the incentive structure of defined benefit (DB) schemes imply that women are less likely than men to have pension coverage since women are more likely to change employers due to their fragmented work histories. For the majority of the sample under analysis in this study, 8

9 DB pensions would have been the predominant type of pension scheme offered by firms during their working life as define contribution schemes were only incorporated into national insurance system in the late 1980s. Consequently, the mobility restriction embedded in DB pensions together with women s discontinuous work histories would have served as a barrier to women s private pension coverage. Indeed, previous research on the gender pension gap has shown that gender differentials in labour market experience is the most important factor in the explained component of the gap in private pension coverage and benefit (Even and Macpherson, 1994; Bardasi and Jenkins, 2010; Hänisch and Klos 2014). Secondly, men s higher lifetime earnings than women will have implications for the gender gap in private pensions. For instance, because the tax advantages of private pensions rise with income, a larger proportion of men would demand private pension coverage than women because the tax-efficiency of pension saving rises with income. Nonetheless, given coverage, women s lower lifetime earnings than men translates into lower benefit levels from DB pension schemes and implies that women may face greater financial constraints to contributing to defined contribution (DC) schemes despite the increased portability of DC pensions relative to DB pensions. Thirdly, the occupational segregation of men and women may have consequences for the gender gap in private pensions since it was not uncommon for employers to have different pension schemes for different classes of employees. For example, employers operated senior-management schemes, staff schemes and works schemes that offered different accrual rates (Blake 2003). Figures from the Office of National Statistics show that in 2013 women accounted for 82% of workers in caring and leisure occupational group, whereas only a third of individuals working in the highest paid category of managers, director and senior officials were women. Thus, the over-representation of women in low-paid occupations may worsen women s pension outcome relative to men. Lastly, eligibility for occupational scheme membership was often defined in terms of the nature of employment and tenure. For instance, part-time workers were often excluded 9

10 from scheme membership until 1995, thereby a significant proportion of women were unable to accrue occupational pension rights and instead remained contracted in the Additional State Pension. The earnings-related component of the state pension was primarily aimed at individuals that did not have access to an occupational pension scheme and was generally regarded as a less generous substitute for occupational pensions (Blake, 2003). Indeed, Barrientos (1998) finds that 60% of individuals with SERPS membership were women and that women were less likely to contract out of SERPS and enrol into a private pension scheme than men. 4. Methodology 4.1 Decomposition of Pension Income The determinants of pension income is estimated using ordinary least squares for the subsample of individuals with state (private) pension coverage separately for each gender: Y im = X im β m + u im Y if = X if β f + u if where, Y ig, is weekly net state (private) pension income for individual i sample of gender g = (m, f). Blinder (1973) and Oaxaca (1973) decompose the difference in the average pension income of the male and female sample as follows: Equation 1 Y m Y f = ( N m i=1 X im N f i=1 N m i=1 X if ) β f X im (β m β f) N m N f N m 10

11 where Y g = Ng i=1 Y ig N g. The first term on the right hand side of Equation 1 is the explained component i.e. the portion of the gap attributed to differences in the average characteristics of men and women. The second term is the unexplained component and represents the portion of the gap that arises from gender differentials in the returns to average characteristics. The unexplained component is commonly thought of as evidence of discrimination, however, it is important to bear in mind that it captures gender differentials in any important variables omitted from the model specification as well as discrimination (Altonji and Blank, 1999). 4.2 Decomposition of Pension Coverage Descriptive statistics and preliminary investigations revealed that state pension coverage is near universal and does not significantly differ by gender. As such, the determinants of state pension coverage are estimated for the pooled sample of men and women. Conversely, descriptive statistics showed large discrepancies in private pension coverage for men and women. Accordingly, the determinants of private pension coverage is estimated separately for each sex as follows: C ig = Z ig γ g + ε ig ε ig ~N(0, σ 2 ) C ig = { 1 if C ig > 0 0 if C ig 0 Pr(C ig = 1 X ig ) = Φ(Z ig γ g + ε ig ) where C ig is the unobserved contribution propensity for individual i of gender g which is determined by observed labour market and personal characteristics plus a normally distributed unobserved error ε ig. C ig is private pension coverage and takes the value of 1 if the individual sufficiently contributed to a private pension and 0 otherwise. Thus, the probability that individual i of gender g has private pension coverage is equal to the cumulative distribution function of the standard normal distribution of the 11

12 determinants of private pension coverage. Decomposition analysis is conducted using the methodology developed by Fairlie (1999) which decomposes the difference in the average predicted probability of private pension coverage between men and women into the component due to gender disparities in distribution of characteristics and into the component due to gender differentials in the process determining the probability of private pension coverage: Equation 2 C m C f = [ N m i=1 Φ(Z imγ f) N m N f i=1 Φ(Z ifγ f) ] N f N m + [ Φ(Z imγ m) i=1 N m N m i=1 Φ(Z imγ f) ] N m where N g is the sample size for gender g and C g is the average probability private pension receipt for gender g. In Equation 2, differences in the distribution of characteristics are weighted with the coefficient from the female sample and differences in the process determining private pension coverage are weighted with the male distribution of characteristics. The first term in the first parenthesis is the counterfactual distribution that would arise if the female sample had the same characteristics as the male sample i.e. women s average predicted probability of having a private pension if they assume mean characteristics of men. 5. Data 5.1 Sample The empirical analyses uses a sample drawn from wave 6 of the English Longitudinal Study of Ageing which surveys individuals aged 50 and over living in private households in England. The English Longitudinal Study of Ageing (ELSA) began in 2002 and is 12

13 collected biennially, accordingly, there were six waves of ELSA between 2002 and The estimating sample is restricted to the cross-section of retirees in wave 6 that also participated in the wave 3 life history interview. The wave 3 life history interviews contain retrospective data on marital, fertility and employment histories. Information from the wave 3 life history interviews augmented with information from subsequent waves form the basis of the independent variables used in the regression analysis. This study focuses on pensioners in England and respondents that are not observed as retired in wave 6 are excluded from the analyses. However, the pension system in the UK is such that retirement cannot be explicitly defined as a discrete event. This is because it is possible to claim the state pension and remain in employment. It is also possible to receive a private pension and continue working provided it is not with the same firm. Since there may be a gradual transition from employment to retirement for some individuals, we define retirement in terms of three variables; respondents selfreported employment status, a dummy variable indicating whether the respondent is of above state pension age and the current working status variable deduced from survey filtering. The age restriction is imposed because those that retire before state pension age are not representative of the population of retirees as they are likely to be those with substantial pension wealth or those with ill-health. The final sample comprises 1,577 women and 1,188 men at or above state pension age. 1 There are four dependent variables in the regression equations: state pension coverage, the log of net state pension benefit, private pension coverage and the log of net private pension income. State pension benefit is the sum of income from the Basic State Pension and the Additional State Pension deflated to 2014 prices, expressed in weekly terms. An individual has state pension coverage if they receive a positive amount of state pension benefit in retirement. Private pension coverage is defined in terms of the receipt of a positive amount of private pension income and private pension income is defined as the 1 State pension age is 65 years for a man. For the majority of the female sample under analysis, female state pension age is 60 years. However, since 2010 the female state pension age has been increasing to equalise with the men s. Consequently, some women in the sample have a state pension age greater than 60 years. 13

14 sum of pension income received from occupational pensions and annuity income. Pension income is inextricably linked to labour market outcomes during working life. Therefore, the explanatory variables included in the pension coverage and benefit equations include a set of work history variables intended to capture engagement with the labour market; years of work experience between ages 20 and 60, years spent as self-employed between ages 20 and 60, years spent working part-time between ages 20 and 60 and starting wage of last job before retirement. The model also includes birth cohort, educational qualifications and marital status. The full set of explanatory variables is shown in Table 1 in the appendix. While the English Longitudinal Study of Ageing contains many variables that are potentially important determinants of pension coverage and income, retrospective data on firm characteristics such as industry, union coverage status and public-private sector distinction is unavailable. Data on firm size is only available for those that are observed in employment in any one wave of ELSA or those that were in employment during the Health Survey for England. Consequently, when firm size is included in the model specification for private pensions, it is likely to be for the subsample of pensioners that are younger than the full sample. 2 Another drawback of ELSA is that retrospective earnings data is only available for jobs where the respondent was an employee. Including wage in the regression specification means that the analysis is restricted to respondents whose last job of career was not in self-employment. 5.2 Descriptive Statistics State pension coverage is near universal at approximately 99% for both the male and female samples. Despite this, there are inequalities in state pension income. Conditioning on coverage, average net weekly state pension income for men and 2 The distribution of birth cohort for the subsample of individuals with firm size information; born before 1934, and after 1942 is 0.30, 0.35 and 0.30 for the male sample and 0.23, 0.27 and 0.50 for the female sample respectively. 14

15 women is 147 and 110 respectively. Accordingly, the raw gender gap in average state pension income stands at 25%. 3 That is, men s average net weekly state pension income is 25% higher than women s average net weekly state pension income. Men s median net state pension income amounts to 146 per week compared to 119 per week for women. Thus, the raw gap in state pension income is smaller at the median than the mean. Descriptive statistics also show that the raw gender gap in average net private pension income is 80% for the whole sample. Specifically, average net weekly private pension income for the entire sample of men is almost five times greater than their female counterpart ( 68 vs. 14 respectively). Amongst those with private pension coverage, men receive nearly twice as much private pension income as women ( 123 vs. 64 respectively) with the corresponding raw gap of 48%. Such large discrepancies in the conditional and unconditional gap highlight differences in the private pension coverage rates of men and women. Indeed, descriptive statistics indicate that less than two-thirds of women (63%) receive any private pension income whereas 88% of men receive income from a private pension. Moreover, the median net private pension income without conditioning on coverage is 122 and 25 per week for men and women respectively, while the conditional median net private pension income is 151 and 74 per week for men and women respectively. The conditional and unconditional raw gaps in mean private pension income do not significantly differ from the associated median. Figure 1 shows the distribution of log average weekly net state pension income by gender. Several key features emerge from the kernel density plot. First, it can be seen that for both men and women, the distribution of state pension income remains flat until approximately 33 and becomes flat again just before reaching 403. The flat left tail is the result of the minimum number of qualifying years needed to claim any state pension that was in force for individuals retiring before 2010, whilst the right tail represents the fact that there is a maximum state pension that an individual can receive made up of the full Basic State Pension and the full Additional State Pension. Second, it can be seen that the male state pension distribution situated to the right of the female distribution and that there is a high degree of concentration in the upper end of the 3 Defined as [1-(average female pension income/average male pension income)]*

16 distribution, implying that men receive a higher amount of state pension income than women. Finally, the distribution of state pension income is bimodal for the female sample and presumably represents the idiosyncratic feature of the UK state pension system that permitted female retirees to claim a state pension using their spouses national insurance contribution record that was worth 60% of their spouse s entitlement. Figure 2 depicts the distribution of state pension income for the female sample by birth cohort and reveals that the proportion of women receiving close to the full state pension has increased between the oldest and youngest cohorts. [Place figure 1 here] [Place figure 2 here] Figure 3 shows the distribution of private pension income by sex. In addition to receiving a lower amount of private pension income than men, the figure shows that the variation in private pension income is greater for women than men. A larger proportion of women receive a net private pension income that is less than 55 per week and most women are clustered around the 90 mark whereas most men are clustered around the 300 mark. Table 1 reports the sample means of the variables used in the analysis of the gender pension gap. The male sample have higher levels of education attainment than the female sample, though the gap in educational qualifications diminishes when comparing the distribution of education between the subsamples of men and women with private pension coverage. The raw gender gap in wages from last job before retirement is 54%, though this decreases to 49% when the sample is restricted to individuals with private pension coverage. On average, women have 11 years less work experience than men, with the gap reducing marginally to 10 years when comparing individuals with private pension coverage. Women spend a longer period of time working part-time compared to men irrespective of private pension coverage status. The number of years spent in 16

17 self-employment is small for both men and women. Nonetheless, men spend approximately three times as long in self-employment than women who spend an average of one year. While only 28% of women are from the three highest occupational classification levels, this percentage is 43% for the male sample. This proportion increases to 35% for women and 46% for men when the sample is restricted to those with private pension coverage. 6. Results 6.1 State Pensions State Pension Coverage Table 2 shows the probit estimates for the pooled sample of men and women. As descriptive statistics indicated, the estimates suggest that the probability of state pension coverage does not significantly differ by gender. 4 The probit estimates indicate that the probability of having a state pension does not significantly differ by level of education, occupational classification or accumulated work experience during working life. However, birth cohort is an important determinant of state pension coverage; older aged individuals are more likely than those from younger cohorts to receive a state pension. The results from the pooled regression also suggest that married individuals are less likely than unmarried individuals to receive a state pension. 5 Sample means by gender and marital status show that married individuals in the sample are younger than individuals not currently married and so the effect of being married may be capturing the age effect. 4 This is confirmed by the Wald test which fails to reject the null hypothesis that the female interactions are jointly equal to zero. 5 I use a dummy variable for married in the state pension coverage equation since being single, never married and being separated perfectly predict success of state pension coverage. 17

18 State Pension Income Estimates of the determinants of state pension income are presented in Table 3. Columns 1 and 3 depict the estimates for state pension income for the male and female sample respectively, while columns 2 and 4 introduces partner s weekly state pension income in the model specification. 6 There are strong cohort effects in state pension income, though the effect differs by gender. While men born before 1943 receive a higher amount of weekly net state pension income than men born on or after 1943, women from earlier cohorts receive a lower amount of state pension income than women born after The heterogeneity in the effect of birth cohort is likely due to the fact that men s labour market attachment did not change significantly in the 20 th century whereas successive cohorts of women significantly increased their labour force participation. In addition, policies introduced to the National Insurance (NI) system to improve women s state pension outcomes would have had the greatest impact on the cohort of women born after For both sexes, education and occupational classification have no statistical association with state pension income. The relationship between starting income of last job before retirement and state pension income is weak for both men and women. This is unsurprising given that the state pension is a flat-rate benefit with a small earningsrelated component. As expected, work experience has a significant and positive impact on state pension income, though the effect is small. It is interesting to note that the magnitude of the effect of work experience on state pension income is similar for both men and women which is consistent with the UK NI system whereby a year s worth of NI contributions provides individuals with a pro rata state pension income in retirement. For both men and women, the longer the proportion of time spent as selfemployed, the lower the amount of state pension received. This is due to the fact that the self-employed only accrue entitlement to the BSP and not the earnings-related component. Similar to work experience, the size of the coefficients does not differ significantly by gender. Years spent in part-time employment have essentially no effect on men s state pension income but negatively impacts the amount of state pension 6 Approximately 68% of men and 41% of women have a partner. 18

19 income women receive in retirement, though the effect is small. This result may be due to the fact that men in the sample only spend an average of six months in part-time employment compared to 8 years for women and the NI system in the UK is such that workers only accrue entitlement to the State Pension once their weekly income from any specific job is over a threshold known as the lower earnings limit. Current marital status is strongly associated with the amount of state pension income women receive and is not as important for men. Married women receive a lower amount of weekly net state pension income than unmarried women; on average, a single woman that has never married can expect a state pension that is 35% higher than a married woman, while a widowed woman s weekly net state pension is 56% higher than a married woman. Widowed women are able to inherit their deceased spouse s state pension, accordingly their state pension income will be higher than those of married women on average. Controlling for partner s state pension income (columns 2 and 4) does not change the qualitative results. However, while the coefficient on partner s state pension income is positive for both sexes, the coefficient on women s state pension income is more significant and nearly twice the effect on men s, suggesting that women s state pension income is more closely linked to their partner s state pension income. This indicates that married women are likely to be claiming Category B state pensions, which are derived pensions valued at 60% of their spouse s entitlement. Blinder-Oaxaca Decomposition Error! Reference source not found. presents the Blinder-Oaxaca decomposition shown in Equation 1. The gender gap in predicted average weekly net log state pension income is 44 (column 1). That is, men s average weekly net state pension income is approximately 30% higher than women s state pension income. Differences in the average characteristics of men and women account for only a quarter of the gap in average weekly net state pension income, whilst gender differentials in the returns to average characteristics account for around three-quarters of the gap. While having the same amount of labour market experience as men increases women s state pension 19

20 income, having the same distribution of current marital status as men or spending an identical amount of time spent in self-employment is detrimental to women s state pension income. Although differentials in the work history variables are significant variables in the detailed decomposition of the explained gap, it is differences in the returns to birth cohort, marital status and occupational classification that emerge as the most important factors in the unexplained gap. The significance of birth cohort and marital status in the unexplained gap is consistent with the evolution of state pension policy which initially comprised gender-specific rules that operated through women s marital status but were subsequently abolished. Columns 3 and 4 in Table 4 presents the Blinder-Oaxaca decomposition when state pension income of respondents partners is included in the model specification, thus the sample is restricted to only men and women with partners. 7 The gender gap in weekly net state pension income increases to 60 with the corresponding female-male ratio of average weekly net state pension income amounting to nearly 0.60, providing further evidence that married women s state pension income are Category B pensions. Again, differences in the returns to characteristics accounts for the majority of the gender gap in state pension income. The detailed decompositions indicate that discrepancies in labour market engagement is the most important factor affecting the explained component of the gender gap in state pensions. 6.2 Private Pensions Private Pension Coverage Probit estimates of private pension coverage with and without firm size in the model specification care presented in Table Error! Reference source not found.5. 8 The two specifications are presented because controlling for firm size greatly reduces the sample size and the resultant sample comprises individuals from younger cohorts. The 7 This comprises either married or cohabiting individuals. 8 Housing financial wealth variables were included in the model specification but had zero effect on private pension coverage despite being significant only for the female sample. As such, the preferred model specification excluded housing and non-housing wealth. 20

21 results show that there is a cohort effect in the probability of private pension coverage for the male sample at 10% level and none at all for the female sample. Education has statistical associations with probability of having a private pension for both sexes, though the effect is stronger for women. For both sexes, current marital status is associated with the probability of private pension receipt. However, similar to the empirical findings in the gender wage gap literature, there is heterogeneity in the effect; being married appears to be a pension premium for men and a pension penalty for women. The estimates show that a single woman who has never married is more likely to have private pension coverage than a married woman, whereas there is no difference between married and single men s probability private coverage. This result is most likely due related to individuals engagement with the labour market since women that have never married are more likely to have stronger ties to the labour market than married women, whereas men of differential marital status have stable work histories. The estimate of marital status also show that widowed women are more likely to have private pension coverage than married women, which is probably due to survivor benefits paid out from a deceased spouse s private pension. The negative effect of widowhood for men may be due to the fact that they are older aged men that did not have access to occupational pension schemes during their working life. As expected, for both men and women, more years of work experience increases the probability of receiving a private pension income, while time spent in self-employment significantly reduces this probability. It is possible that the negative impact of selfemployment on private pension coverage arises because the majority of private pension income originates from occupational pensions and the self-employed typically rely on personal savings and assets to fund their retirement consumption. 9 Starting wage of last job before retirement is only an important determinant of women s private pension coverage status, consistent with the idea that women with higher wages are more likely to contribute to a private pension scheme. 9 In 2012/13, Personal pensions account for 5% of retirement income for male pensioners and 2% for female pensioners (ONS Pension Trends 2012). 21

22 Time spent in part-time employment and occupational classification matters more for women s private pension coverage than men s; women from top-level occupations are significantly more likely to be receiving private pension income than women from elementary occupations. The finding aligns with the evolution of private pension policy in the UK; at the time the sample of pensioners were still of working age, employers were permitted to exclude part-time workers from joining their pension scheme (thus disproportionately affecting women). In addition, UK policy enabled employers to impose pension scheme membership as a condition of contract until 1988 and this was particularly common for top-level occupations. Including firm size in the model specification does not change the qualitative results; as expected, the results in columns 2 and 4 indicate that individuals that worked in smaller firms are less likely to receive a private pension. Decomposition of the private pension coverage The gender gap in private pension coverage is decomposed according to Equation 2 and the detailed decompositions of the explained component are shown in Error! Reference source not found.6. Gender differences in the distribution of characteristics account for 51% of the gender gap in the average predicted probability of private pension coverage. Including firm size in the model specification marginally decreases the explained to 50%. If women had the same distribution of characteristics as men, their average predicted probability of private pension coverage would increase by around Decompositions of the private pension coverage with and without firm size suggests that gender disparities in the distribution of years work experience and parttime work are the two most important factors in the explained gap in private pension coverage. Private Pension Income OLS estimates of private pension income for the subsample of men and women with private pension coverage are shown in Table 7. Columns 2 and 4 includes firm size of last job before entering retirement which imply that the resultant estimates are based on the sample of pensioners who were observed in employment in at least one wave of 22

23 ELSA or HSE. Overall, it is immediately clear that labour market characteristics are more closely linked to private pension income than state pension income. There are strong cohort effects for the male sample; men from earlier birth cohorts receive lower private pension income than men born after This might be due the expansion of occupational pension schemes that occurred in the 1950s and 1960s, which meant that men from younger cohorts would have had a longer period of time to build up pension entitlement. For the female sample, women born before 1934 have significantly lower private pension income than women born after Across all specifications and for both sexes, higher levels of educational attainment are strongly associated with higher private pension income, though there are substantial differentials in the magnitude of the effect. The return to education is much larger for men than women; columns 1 and 3 indicate that though the average man with degree-level education receives a private pension income that is 88% greater than a man with no qualifications, this effect is only 56% for the female counterpart. Thus, the estimates suggest that while education is more strongly associated with men s private pension income, education matters most for women s coverage status. Marital status is an important determinant of private pension income. For both men and women, cohabiting individuals receive a larger amount of private pension income than those that are currently married. However, similar to finding in private pension coverage status, there is heterogeneity in the effect of marriage. Women that have never married receive a higher amount of private pension income than married women, whereas men that have never married receive a lower private pension than married men. Again, women s marriage pension penalty may be due to their fragmented work histories. The returns to labour market experience are more important and greater for women than men. Specifically, on average, an extra year of work experience between ages of 20 and 60 years of age increases female private pension income by 1.6%, whereas there is no statistical association between men s private pension income and accumulated work experience or years spent working part-time. As expected, an additional year of part-time employment reduces women s private pension income by 2.1% but has no effect on men s private pension income. 23

24 For both sexes, occupational classification is an important determinant of private pension income though the effect is stronger for women. Women from professional occupations receive a private pension income that is approximately twice the amount that women from elementary occupations receive, whereas this figure is 87% for the male counterpart. Starting wage of last job before retirement does not seem to matter for the amount of private pension income individuals receive, which may be due to the fact that for the sample under analysis, defined benefit pensions were the main type of pensions available during their working life and was typically related to final salary. Once firm size is included in the model specification, coefficient estimates increase in absolute terms. The size of firm an individual previously worked for is an important correlate of the amount state pension income they receive. A woman who worked in a firm with 2 to 4 workers can expect a pension income that is half as much as a woman that worked in a firm with more than 1000 workers, while a man that previously worked in a firm with 2 to 4 workers can expect about 66% less. This finding is consistent with incentive models of the wage structure in which firms wage structure follows a steeply rising age-earnings profiles so as to discourage shirking at work (Lazear, 1981; Akerlof and Katz, 1989). In this framework, large firms will offer pensions because pensions can be provide a cost-efficient way of monitoring worker effort. This is because of pension back-loading and the substantial capital losses associated with the termination of the employment contract prior to normal retirement age. Blinder-Oaxaca Decomposition Columns 1 and 2 of TableError! Reference source not found. 8 show the Blinder- Oaxaca decomposition of private pension income of without controlling for firm size. The estimates show that men s average weekly net private pension income is approximately 50% higher than women s average weekly net private pension income. The decomposition indicates that only 28% of the gender gap in private pension income is attributable to differences in the mean characteristics of men and women. The most important factor contributing to the explained gap is the number of years women spend in part-time employment, followed by gender differentials in accumulated labour market experience. Gender differentials in the returns to marital status emerges as the 24