Journal of Happiness Studies

, Volume 16, Issue 5, pp 1281–1298

Do Active Labour Market Policies Promote the Subjective Well-Being of the Unemployed? Evidence from the UK National Well-Being Programme

Research Paper

DOI: 10.1007/s10902-014-9549-9

Cite this article as:
Sage, D. J Happiness Stud (2015) 16: 1281. doi:10.1007/s10902-014-9549-9

Abstract

In the past 5 years, the UK government has expanded its efforts to understand, measure and incorporate indicators of subjective well-being (SWB) into the policy-making process. Utilizing the new data collected as part of the government’s well-being agenda, this paper investigates whether active labour market programmes (ALMPs) are associated with increased SWB amongst the unemployed. Unemployment has long been shown to be detrimental to mental health and happiness. In recent years, ALMPs have been increasingly proposed as potential mechanisms to improve the SWB of the unemployed. Using multiple linear regression models, the findings suggest that ALMPs do improve the SWB of the unemployed. However, there are three caveats. First, the effect of ALMPs appears to be far stronger for evaluative measures of SWB over affective measures. Second, the effect of ALMPs is larger for men than for women. Third, the impact of an ALMP is dependent upon the type of intervention: work-oriented ALMPs are more effective than employment-assistance ALMPs. In light of these findings, the theoretical and policy consequences are discussed.

Keywords

Unemployment Subjective well-being Active labour market programmes Happiness United Kingdom 

1 Introduction

During the past decade, governments in Europe and in other advanced democracies have expanded their efforts to understand, measure and incorporate indicators of subjective well-being (SWB) into the policy-making process (see Stiglitz et al. 2009; Office for National Statistics 2012). This has been driven by a range of factors, such as the reported well-being limits of economic growth (Easterlin 1974), the financial crisis (Davies 2012) and the expanding evidence base on the determinants of SWB (Diener et al. 1999). To this end, the UK government has recently made strides towards mainstreaming indicators of SWB into large-scale social surveys and policy evaluations, as well as developing a new National Well-Being Index (Dolan and Metcalfe 2012) to track SWB over time.

In this article, the data collected as part of the UK government’s programme is used to examine the impact of unemployment on SWB from a novel perspective. The background to the study is the wealth of empirical evidence that shows how unemployment is linked to—and appears to cause—a decline in SWB and other psychosocial indicators (see Paul and Moser 2009, for a meta-analysis). To explain the deleterious SWB effects of unemployment, theories have varied: from the effects of low income (Warr and Jackson 1985), the social norms attached to employment (Cole 2007) and the absence of the psychological functions fulfilled by paid work (Jahoda 1982).

Within this research context, there has been increased academic attention afforded to the types of interventions that might mitigate some of the harmful effects of unemployment. One type of intervention are active labour market programmes (ALMP), which have been hypothesized as holding the capacity to improve the SWB of the unemployed relative to the alternative of non-participation: ‘open unemployment’ (Strandh 2001). This argument is generally influenced by theories from social psychology that link paid work with the fulfilment of psychosocial needs, such as time structure and social status. Subsequently ALMPs—which to some extent ‘mimic’ the environment of paid work (Wulfgramm 2011)—have the potential to offer some of the same latent benefits. Whilst the empirical evidence on the SWB effects of ALMPs is limited, the evidence there is suggests a positive effect of participation (Creed et al. 1999; Andersen 2008; Wulfgramm 2011).

This paper aims to add evidence to the research base on the SWB effects of ALMPs. It first explores the argument—based on theoretical insights and empirical evidence—that ALMPs can improve the SWB of the unemployed. In the subsequent empirical sections, a range of multiple linear regression models are estimated on different indicators of SWB using the 2011–2012 Annual Population Survey (APS): the first UK survey to incorporate the new measures of SWB. The models control for a wide range of independent variables, as well as examining whether the impact of ALMPs varies by gender and type of ALMP. The final section considers the theoretical and policy implications of the results, which demonstrate that ALMP participants tend to have higher levels of SWB compared to the open unemployed, although this depends on the measure of SWB used, as well as the gender of the participant and the type of ALMP he/she is on.

2 Unemployment, Active Labour Market Policies and Subjective Well-Being

Within 6 months of becoming Prime Minister, the UK Conservative Party leader David Cameron (2010) announced his interest in SWB, outlining his intention to “start measuring our progress as a country, not just by how our economy is growing, but by how our lives are improving; not just by our standard of living, but by our quality of life”. Subsequently, the UK government has extensively consulted on how best to measure SWB and incorporate it into social research and policy-making. Three different indicators of SWB were consequently established: life satisfaction, life worth and affect (both positive and negative). The data collected on these indicators has now reached large sample sizes in the range of 150–300,000 people. Such large datasets give analysts the means to examine potentially uncommon attributes and influences on SWB that are impossible to examine in smaller datasets. One such attribute is participation in ALMPs: an activity that could, according to some (Strandh 2001; Sage 2013), promote higher SWB amongst the unemployed.

2.1 What are ALMPs?

ALMPs are generally seen as part of a shift in the landscape of the welfare state, wherein governments attempt to do more for those who are out-of-work than simply provide ‘passive’ social security benefits. ALMPs attempt to link the receipt of social security to participation in back-to-work interventions in an attempt to speed up labour market reattachment. ALMPs are now an integral component of welfare provision in many countries, generally supported by political parties of both the right and the left.

The rise of ALMPs can be seen within the context of two intertwined developments: socio-economic transformations and ideological change. On the one hand, the demands and pressures placed on labour markets and economies as a consequence of globalization have led to a revised view of unemployment and its causes, with a shift towards explaining unemployment as a consequence of supply-side deficiencies instead of weak labour demand. In this context, interventions like ALMPs—which aim to enhance and improve the supply of labour—are seen as more appropriate measures compared to traditional social security payments. On the other hand, ideological change has also favoured the expansion of ALMPs. ‘Welfare reform’ has become a leading trope, especially in the Anglo-Saxon welfare states, for governments aiming to improve work incentives and revive an ethic of personal responsibility within the welfare system. ALMPs—as programmes that are often mandated under threat of benefit sanction—incorporate these two key pillars of welfare reform.

In practice, ALMPs encompass a broad range of different interventions. These include intensive programmes of employment assistance, training programmes for the acquisition of new skills and qualifications, workplace experience placements and job creation schemes. This has led numerous critics to attempt to construct different typologies of ALMPs that, in broad terms, tend to fall within a dichotomous categorization (for a review, see Bonoli 2010).

Commentators have given several names to this dichotomy but the basic underlying principles are equivalent. The first kind of ALMP can be labelled ‘work-oriented’. These are schemes that link labour market reattachment to the development of specific work-related skills, such as training, qualifications and work experience. The second kind of ALMP can be labelled ‘employment-assistance’. These include schemes that generally involve an intensified programme of help and work-readiness, often based around the personal adviser model of employment support. ‘Work-oriented’ and ‘employment-assistance’ ALMPs are fundamentally different in two ways. First, they offer different philosophies of the route back to paid work: through either a ‘human capital’ approach in which there is a significant focus on developing an individual’s capabilities (work-oriented) or a ‘work-first’ approach in which the emphasis is on rapid labour market re-entry (employment-assistance). Second, as a consequence of these alternative approaches there are differences in the designs of the two schemes. Employment-assistance ALMPs focus on benefit sanctions, short-term ‘soft skills’ courses and personalized advice, whereas work-oriented ALMPs place a stronger emphasis on vocational training, skills, education and workplace experience.

Irrespective of the type of ALMP, Coutts (2009) makes the valuable observation that ALMPs act as form of intermediate labour market status—or ‘labour market limbo’—in which participants are neither formally employed or unemployed in the typical sense. Thus whilst ALMPs often fail to offer participants higher benefits for taking part (although there are exceptions, such as the German ‘One Euro’ job scheme), they do offer a very different environment to ‘open unemployment’; one which normally involves a significant degree of organized activity and daily routine. This is an environment that can, at least to some degree, mimic that of paid work in the formal labour market.

2.2 Existing Evidence on ALMPs

The expansion of ALMPs across many advanced welfare states has led to a vast literature on their effects. However, a major limitation of the evidence base is the overwhelming attention given to economic, labour market outcomes, such as re-employment, job stability and pay. On one level this should be expected. The foremost objective of ALMPs is to move participants back into the labour market; hence, it is unsurprising that this is the prime criterion that ALMPs are assessed by.

However, unemployment is far from a purely economic problem, with far-reaching health, psychological and social effects as well. It thus makes sense to consider the impact that labour market interventions have on these non-pecuniary effects of unemployment. In theory, as is expanded on below, ALMPs might be expected to raise the SWB of participants. For example, this could be achieved by providing a person with a daily time structure and opportunity to meet people, by offering more hope and confidence in finding paid work or by building self-esteem by improving skills and qualifications. Whilst ALMPs will always have re-employment and other labour market outcomes as their foremost aims, there is—in an age when the policy-making process increasingly takes note of the well-being effects of public policy—a strong case to be made for evaluating the SWB impact of interventions like ALMPs. In addition, the case is further strengthened when the extent of the psychosocial impact of unemployment is considered.

2.3 The Well-Being Impact of Unemployment and the Potential of ALMPs

Similarly to ALMPs, unemployment is also considered a foremost economic issue for public policy; yet in practice, there is a rich tradition of research into the social and psychological consequences of worklessness. This tradition has its roots in the Great Depression of the 1930s; studies such as Marienthal (Jahoda et al. 1972) and The Unemployed Man (Bakke 1933) were amongst the first to establish that unemployment had negative effects far beyond a loss of income.

Since the 1970s, the re-emergence of mass unemployment as an economic and policy issue in the rich market democracies has led to new attempts to understand how a lack of work can have negative effects on mental health and SWB. Research from a range of disciplines—including epidemiology, psychology and sociology—has shown how unemployment is associated with a wide range of psychosocial ills, such as suicide (Platt 1986; Blakely et al. 2003; Stuckler et al. 2009), low scores on multi-item scales of SWB (Clark and Oswald 1994; Thomas et al. 2005), depression (Jefferis et al. 2011) and feelings of shame (Eales 1989). Further research into the psychosocial costs of unemployment has shown evidence of ‘scarring effect’ in which unemployment has a long-term, sustained impact on SWB (Lucas et al. 2004).

Evidence regarding the psychosocial consequences of unemployment is now largely unequivocal; as a result, academics have increasingly turned their attention to exploring which interventions can mediate these harmful effects. Attention has been historically focused on the traditional institutions of the post-war welfare state, such as the role of generous benefit replacement rates and wide coverage in ensuring that large swathes of the population are sufficiently insured against the risk of unemployment. However, the expansion of ALMPs has been accompanied by a growing interest in the impact that such interventions have on the psychosocial environment of unemployment.

The idea that ALMPs can improve the SWB of the unemployed is based upon a theory of how and why unemployment has negative psychosocial effects. The logic of this argument proceeds in three steps. First, as opposed to unhappy people becoming unemployed, unemployment itself causes harmful outcomes: there is thus something unique about the environment of being unemployed that leads to low SWB (Murphy and Athanasou 1999). Second, the reason why this environment is detrimental to SWB is not exclusively related to loss of income. Whilst the experience of poverty often intensifies the harm wrought by unemployment, research shows that unemployment has negative psychosocial effects independently of personal income (Winklemann and Winkelmann 1997). Thirdly then, if economic conditions alone do not explain the causal, negative effects of unemployment, then there must be something socially and psychologically detrimental about the environment of being unemployed. Jahoda’s (1982) theory of latent deprivation has been the most influential contribution to the social psychology of unemployment, stating that paid work fulfils five “latent functions” that are vital for good well-being: time structure, social activity, collective endeavour, regular activity and status and identity.

If this is the case, it can be convincingly argued that there is something about the psychosocial environment of unemployment that causes negative SWB outcomes. Hence, if this environment is modified—through interventions such as ALMPs—then the negative outcomes of unemployment might be ameliorated. This theoretical account of ALMPs has been developed over the past decade, stating that if paid work has positive psychosocial attributes then ALMPs—which to some extent mimic paid work—have the potential to produce similar outcomes amongst participants. This has been argued by Richard Layard (2004), perhaps the most vocal advocate of ‘happiness economics’, who has supported the expansion of state-funded job guarantees (one type of ALMP) as a response to the happiness loss associated with unemployment.

The evidence that exists on the SWB effects of ALMPs is somewhat ambiguous (see Coutts 2009 for a review). Whilst there is some evidence of a positive association with ALMP participation relative to ‘open unemployment’, there are also studies that show no differences between the two groups. In a Danish study, Breidahl and Clement (2010) found no evidence that ‘activated’ unemployed people felt less stigmatized or had higher self-esteem than ‘unactivated’ unemployed people. Further, Strandh (2001) found that out of three different Swedish ALMPs only one type—workplace participation—was associated with higher SWB.

Nevertheless, the majority of studies into the well-being effects of ALMPs show a positive impact. This is true at broad cross-national level, where relatively high public spending on ALMPs has been shown to reduce the risk of suicide amongst the unemployed (Stuckler et al. 2009). In earlier research, perhaps the first studies to rigorously test the impact of ALMPs came from the USA and Finland, where the respective JOBS and Työhön programmes showed positive effects of participation on a range of psychosocial indicators (Vinokur et al. 2000; Vuori et al. 2002) Later research at a national level has similarly found a positive effect in numerous countries, such as Australia (Creed et al. 2001), Germany (Wulfgramm 2011) and the UK (Andersen 2008).

2.4 Remaining Questions

The UK Department for Work and Pensions (DWP) has recently recognized the potential of ALMPs to improve SWB amongst the unemployed (DWP 2010). However, they correctly observe that research is at a very early stage in the UK, where only a handful of quantitative studies exist (Oddy et al. 1984; Andersen 2008; Rahim et al. 2012). Further, up to now there are no studies that have utilized the newly collected UK well-being data to test whether or not ALMP participation is associated with higher SWB amongst unemployed people. As Deeming (2013) states, the published analyses by the Office of National Statistics (ONS) have focused on more basic types of analysis, such as cross-tabulations, on only a small number of variables. Thus, this article aims to be the first to examine the SWB effects of ALMPs using more advanced multivariate techniques on the new ONS data.

In addition, the subsequent analysis seeks to make three further original contributions. First, previous research (Kahneman and Deaton 2010) suggests that different types of SWB are influenced by different socio-economic and demographic factors. The following analysis will thus determine whether ALMPs affect certain types of SWB more than other types. Second, the impact of unemployment on SWB is known to be mediated by gender, with men reporting larger drops in SWB than women (Clark et al. 2001; Lucas et al. 2004). Therefore, it might be expected that ALMPs have a variable effect depending on whether a participant is male or female. Finally, ALMPs are far from a homogeneous form of intervention. As argued above, commentators have tended to distinguish between two types of ALMP: employment assistance ALMPs and work-oriented ALMPs. These two types constitute profoundly different types of intervention; therefore, it can be argued that there might be differential effects on SWB.

3 Data and Methods

The following analysis is conducted on the Annual Population Survey (APS) for the wave April 2011–March 2012. The APS is an annual cross-sectional survey that combines results from the five annual waves of the Labour Force Survey (LFS) and various LFS boosts across England, Scotland and Wales. The APS is a relatively large social survey and contains data on around 150,000 households and over 300,000 individuals. However, as proxy responses were not included for SWB questions, the number of SWB respondents is about 165,000.

The 2011–2012 wave used in this article was the first APS wave to incorporate the four new SWB questions. These four questions relate to the three different concepts of SWB that are outlined above—self-evaluative; eudemonic; and affective—and form the dependent variables that are analysed below (see Table 1). All four measures run on an 11-point scale from 0 to 10. For the indicators ‘life satisfaction’, ‘life worth’ and ‘happiness’, a higher score indicates a higher level of SWB, whilst it indicates a lower level of SWB for ‘anxiety’. For the subsequent analysis, the values for ‘anxiety’ are reverse coded to ease interpretation and comparison. An important criticism levelled at SWB questions, such as those used in this study, is that answers may be influenced by environmental factors and can thus produce biased responses. For example, responses to the happiness question—‘how happy did you feel yesterday?’—may be influenced by random shocks to respondents’ environments. However, as Dolan and Metcalfe (2012) state, the general academic consensus is that responses to SWB questions are broadly consistent over time, suggesting strong reliability and validity.
Table 1

SWB dependent variables

Variable name

Survey question

Dimension of SWB

Life satisfaction

Overall, how satisfied are you with your life nowadays?

Self-evaluation

Life worth

Overall, to what extent do you feel that the things you do in your life are worthwhile?

Eudemonic

Happiness

Overall, how happy did you feel yesterday?

Positive affect

Anxiety

Overall, how anxious did you feel yesterday?

Negative affect

The main independent variable of interest is labour market status, with the sample reduced to the two prime comparison groups: ‘open unemployment’ and ALMP (see Table 2). Regarding ALMPs, the prime advantage of the APS is its large sample size; ALMP participants routinely make up less than 0.5 per cent of survey respondents, so in smaller samples the number of ALMP participants is very low. In the APS, a total of 521 people report participating on a government training scheme, providing a relatively large ALMP cohort.
Table 2

Descriptive statistics

Variable name

Min/Max

Frequency

Per cent (unemployed group)

Per cent (ALMP group)

Dependent variables

Life satisfaction

0/10

7,234

Life worth

0/10

7,234

Happiness

0/10

7,234

Anxiety

0/10

7,234

Independent variables

ALMP

0/1

521

Unemployed

0/1

6,713

Work-oriented ALMP

0/1

115

Employment-assistance ALMP

0/1

162

Other ALMP

0/1

244

Control variables

Socio-economic group

 Higher managerial/professional

0/1

278

4.0

1.3

 Lower managerial/professional

0/1

667

9.3

8.5

 Intermediate occupations

0/1

595

8.2

8.6

 Small employers

0/1

218

3.1

1.7

 Lower supervisory/technical

0/1

196

2.7

3.1

 Semi-routine

0/1

959

13.5

10.8

 Routine

0/1

845

11.6

13.1

 Never worked/long-term unemployed

0/1

3,476

47.7

52.3

Marital status

 Single

0/1

3,993

54.4

65.8

 Married

0/1

1,898

27.2

13.8

 Separated

0/1

366

5.0

5.4

 Divorced

0/1

882

12.1

13.8

 Widowed

0/1

95

1.3

1.2

Highest qualification

 Higher education

0/1

1,649

23.3

15.9

 A-Level

0/1

1,533

21.2

20.9

 GCSE

0/1

2,064

28.4

29.9

 Other

0/1

1,036

13.8

21.7

 None

0/1

952

13.3

11.5

Ethnicity

 White

0/1

6,127

84.7

85.2

 Mixed race

0/1

105

1.4

2.3

 Indian

0/1

170

2.5

1.0

 Pakistani

0/1

149

2.1

1.5

 Bangladeshi

0/1

67

1.0

0.4

 Other Asian

0/1

136

1.9

1.7

 Black

0/1

380

5.1

6.9

 Other

0/1

100

1.4

1.0

Housing tenure

 Own outright

0/1

886

12.5

8.6

 Mortgage

0/1

1,707

24.0

18.4

 Rent

0/1

4,563

62.5

71.2

 Other

0/1

78

1.0

1.7

Age

18/65

7,234

Age2

324/4,225

7,234

 18–24

1,479

20.3

22.8

 25–34

1,704

23.6

23.2

 35–44

1,565

21.8

20.2

 45–54

1,494

20.4

23.6

 55–65

992

13.4

10.2

Female

0/1

3,538

49.1

46.8

Religious (people belonging to a religion)

0/1

4,430

61.2

61.8

Good health (people who report very good/good health)

0/1

5,335

74.1

69.7

In addition to labour market status, other basic socio-demographic variables are controlled for in the regression models. These include socio-economic group, marital status, highest qualification, ethnicity, housing tenure, age and gender. As well as being important controls, these variables are well-established determinants of SWB in their own right (for a review, see Diener et al. 1999). Other known correlates are also included in the analyses, such as good health and religious belief. As previous research has shown that the relationship between SWB and age is curvilinear—in that well-being tends to be high when people are younger, drop during middle-age and rise again in older age—a control of age-squared is also used. Only 18–65 year-olds were included in the regression models and missing cases were deleted through list wise deletion. The final sample of openly unemployed people and ALMP participants was 7,234.

To analyse the relationship between SWB, unemployment and ALMPs, three multiple linear regression models are estimated for each of the four indicators of SWB: life satisfaction, life worth, happiness and anxiety. In the first set of models (Table 4), the analysis includes the main labour market independent variables and the full range of socio-demographic controls. In the second set, separate models for men and women are estimated for each indicator with ALMP participation as the prime independent variable (Table 5). The objective of these models is to test whether the effect of ALMPs on SWB varies between men and women. Finally, the third set of models divides the ALMP category into three types: ‘work-oriented’, ‘employment-assistance’ and ‘other’ (Table 6).1 The leading hypothesis is that open unemployment is negatively associated with SWB relative to ALMP. This has been previously proposed by Strandh (2001), Andersen (2008) and Wulfgramm (2011). However, it is also hypothesized that there will be differences in the effect of ALMP on SWB by gender and it is expected that men will benefit more from ALMP participation than women. Finally, it is predicted that ‘work-oriented’ ALMPs—which fulfil many of the ‘latent functions’ of paid work—will be associated with higher SWB than ‘employment-assistance’ ALMPs. This leads to three hypotheses:
  1. 1.

    The ‘openly unemployed’ will have significantly lower SWB on all indicators than ALMP participants.

     
  2. 2.

    ALMP participation will be associated with higher SWB for male participants relative to female participants.

     
  3. 3.

    Work-oriented ALMPs will be associated with higher SWB relative to open unemployment compared with employment-assistance ALMPs.

     

All estimates are weighted using the APS integrated household weight and analysed in Stata 11. Each model presents both unstandardized and standardized coefficients, with the latter enabling a more direct comparison of the strength of the independent variables. Standard errors are presented in parentheses.

4 Results

4.1 Descriptive Results

Table 2 shows descriptive statistics for all of the variables included in the linear models in Tables 4, 5 and 6, displaying the minimum and maximum values, the frequency within each category, the total as a percentage of the openly unemployed and the total as a percentage of ALMP participants. In total, 7.2 per cent of the total unemployed group report participation on an ALMP, with 1.6 per cent participating on work-oriented ALMPs, 2.2 per cent on employment-assistance ALMPs and 3.4 per cent on other ALMPs. The final two columns in Table 2 suggest few significant differences between the openly unemployed and ALMP groups. ALMP participants are less strongly represented amongst married people, with 14 per cent of ALMP participants reporting being married compared to 27 per cent of openly unemployed people, despite few apparent age differences between the two groups. In addition, ALMP participants appear less highly educated than the openly unemployed, as well as being less likely to be female and reporting good health. Logistic regression estimates of entry into the ALMP group confirm few significant differences with the openly unemployed.2

Table 3 shows weighted population estimates for the four indicators of SWB and the average score by labour market status. Overall, ALMP participants report higher mean SWB scores than the openly unemployed for life satisfaction, life worth and happiness. However, the differences are small, ranging from 0.15 points higher for life satisfaction to 0.10 for life worth. Further, for anxiety it is the unemployed who report being less anxious than the ALMP group. These estimates suggest that ALMP participation interacts with well-being in a non-uniform way. The final three rows of Table 3 suggest large differences in SWB between different ALMP types. Participants on work-oriented ALMPs record much higher mean SWB scores than those on employment-assistance ALMPs, with those on other ALMP types occupying an intermediate position between the two.
Table 3

Population estimates of indicators of SWB by labour market status

Labour market status

Mean life satisfaction

Mean life worth

Mean happiness

Mean anxiety

ALMP

6.48

6.98

6.79

6.28

Unemployed

6.33

6.89

6.65

6.42

Work-oriented ALMP

6.85

7.27

7.22

6.65

Employment-assistance ALMP

6.17

6.48

6.59

6.14

Other ALMP

6.51

7.17

6.73

6.19

4.2 Linear Regression Results

Table 4 shows the estimation results with labour market status as the main independent variable of interest and with the full range of control variables included. To recall, hypothesis (1) is that ALMP is associated with higher SWB than open unemployment. The estimates in Table 4 broadly support this hypothesis. In models 4a and 4b, ALMP is significantly associated with higher life satisfaction and higher life worth compared to open unemployment. Both effects are significant at the 99 per cent level and are comparable in size to the difference between religious and non-religious people. There is a smaller positive effect of ALMP on happiness, which is only significant at the 90 per cent level, whilst there is no evidence of a difference in the level of anxiety between the two groups. The estimates in Table 4 thus suggest that ALMP has a fairly modest but significant effect on the two self-evaluative measures of SWB and a much smaller, or even non-existent in the instance of anxiety, effect on the two affective measures of SWB.
Table 4

OLS regressions of indicators of SWB on labour market status, with socio-demographic control variables

 

(a) Life satisfaction

(b) Life worth

(c) Happiness

(d) Anxiety

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Current employment status (ref: openly unemployed)

ALMP

0.29 (.10)**

0.032

0.26 (.10)**

0.031

0.19 (.11)+

0.019

−0.04 (.14)

−0.004

Controls

Socio-economic group (ref: higher managerial)

 Lower managerial

0.06 (.15)

0.007

−0.00 (.14)

−0.00

0.20 (.17)

0.024

0.05 (.21)

0.005

 Intermediate

0.20 (.15)

0.024

0.10 (.15)

0.012

0.37 (.17)*

0.040

0.46 (.22)*

0.042

 Small employers

0.21 (.19)

0.016

−0.04 (.19)

−0.003

−0.07 (.22)

−0.005

0.21 (.27)

0.012

 Lower supervisory

0.24 (.20)

0.017

0.43 (.19)*

0.033

0.39 (.23)+

0.025

−0.00 (.28)

−0.000

 Semi-routine

0.08 (.15)

0.012

0.06 (.14)

0.010

0.18 (.17)

0.024

0.24 (.21)

0.026

 Routine

−0.01 (.15)

−0.002

−0.08 (.14)

−0.013

0.04 (.17)

0.004

0.07 (.21)

0.008

 Never worked/long-term unemployed

0.19 (.15)

0.043

0.14 (.13)

0.031

0.33 (.16)*

0.065

0.40 (.18)*

0.066

Marital status (ref: single)

 Married

0.77 (.08)***

0.145

0.62 (.07)***

0.122

0.66 (.08)***

0.111

0.43 (.10)***

0.060

 Separated

0.09 (.12)

0.009

0.07 (.12)

0.007

0.04 (.14)

0.004

0.15 (.18)

0.011

 Divorced

−0.11 (.09)

−0.015

0.07 (.09)

0.010

0.06 (.11)

0.008

0.21 (.13)

0.021

 Widowed

0.15 (.24)

0.007

0.52 (.24)*

0.026

−0.01 (.27)

−0.000

−0.07 (.35)

−0.002

Highest qualification (ref: no qualifications)

 Higher

−0.27 (.10)**

−0.050

0.12 (.09)

0.025

−0.00 (.11)

−0.001

−0.08 (.13)

−0.011

 A-level

−0.19 (.09)*

−0.034

0.12 (.09)

0.024

−0.01 (.11)

−0.002

0.06 (.13)

0.008

 GCSE

−0.26 (.09)**

−0.052

0.06 (.09)

0.012

−0.03 (.10)

−0.005

0.16 (.12)

0.023

 Other

−0.39 (.10)***

−0.062

−0.09 (.09)

−0.016

−0.22 (.11)*

−0.032

0.09 (.14)

0.011

Ethnicity (ref: white)

 Mixed race

0.14 (.19)

0.008

0.20 (.16)

0.012

0.22 (.22)

0.012

−0.42 (.27)

−0.018

 Indian

0.10 (.16)

0.007

0.06 (.16)

0.004

0.16 (.19)

0.010

−0.52 (.23)*

−0.027

 Pakistani

−0.31 (.18)+

−0.020

−0.17 (.17)

−0.011

−0.43 (.20)*

−0.025

−0.53 (.25)*

−0.030

 Bangladeshi

−0.40 (.25)

−0.018

−0.21 (.24)

−0.010

−0.45 (.28)

−0.018

−0.60 (.35)+

−0.020

 Other Asian

0.08 (.17)

0.005

−0.38 (.16)*

−0.026

0.33 (.18)+

0.019

−0.40 (.24)+

−0.019

 Black

−0.48 (.11)***

−0.052

−0.19 (.10)+

−0.021

−0.23 (.12)+

−0.022

−0.13 (.15)

−0.010

 Other

−0.30 (.18)+

−0.019

−0.43 (.17)*

−0.028

−0.35 (.21)+

−0.020

−0.94 (.25)***

−0.044

Housing tenure (ref: own outright)

 Mortgage

−0.27 (.09)**

−0.051

−0.12 (.09)

−0.024

−0.08 (.11)

−0.013

−0.36 (.13)**

−0.049

 Rent

−0.20 (.09)*

−0.033

−0.04 (.09)

−0.008

−0.07 (.10)

−0.013

−0.33 (.12)**

−0.052

 Other

−0.67 (.24)**

−0.043

−0.57 (.23)*

−0.030

−0.48 (.27)+

−0.022

−0.48 (.33)

−0.018

Demographics

 Age

−0.12 (.01)***

−0.694

−0.04 (.01)**

−0.229

−0.09 (.02)***

−0.488

−0.10 (.02)***

−0.449

 Age2

0.00 (.00)***

0.561

0.00 (.00)*

0.197

0.001 (.00)***

0.432

0.00 (.00)**

0.377

 Female

0.28 (.05)***

0.063

0.50 (.05)***

0.115

0.12 (.06)*

0.025

−0.20 (.08)**

−0.033

 Good health

1.12 (.06)***

0.218

1.00 (.06)***

0.204

1.21 (.07)***

0.211

1.01 (.08)***

−0.146

 Religious

0.16 (.06)**

0.036

0.16 (.05)**

0.037

0.20 (.06)**

0.039

−0.09 (.08)

−0.015

Intercept

7.94

 

6.27

 

7.08

 

7.83

 

N

7,234

 

7,234

 

7,234

 

7,234

 

R2

0.11

 

0.08

 

0.07

 

0.04

 

Significant at: 90 %; * 95 %; ** 99 %; *** 99.9 %

Regarding the other independent variables, there are some interesting findings in relation to how the controls are associated with the different indicators of SWB. Relative to people who are single, being married is associated with a positive and significant effect on all four indicators on SWB; this suggests that marriage—and arguably the economic security and social support that comes with it—acts as a protection against the loss of SWB associated with unemployment. With the exception of anxiety, women and religious people have significantly higher SWB than men and the non-religious. These finding parallels previous research on the differential impact of unemployment by gender and the influence of faith on well-being (Diener 1984). The relationship between highest qualification is generally negligible with the exception of life satisfaction, where those with higher levels of education are found to have lower life satisfaction compared to those with no qualifications. This suggests that unemployment hurts more for highly educated people, a conclusion that broadly supports the findings of Boyce et al. (2010). Finally, people who own their homes outright appear to have higher life satisfaction and lower anxiety than other types of tenants, whilst few effects were found for socio-economic class and ethnicity.

With regards to hypothesis (2)—that ALMPs will have a differential effect on SWB by gender—the estimates in Table 5 show some tentative evidence in support. This is clear in models 5b and 5c in Table 5, which show that although the life worth and happiness of male ALMP participants is significantly higher than openly unemployed men, there is no difference between the two groups amongst female respondents. Further, although no significant results were found for the effect of ALMPs on anxiety, the regression estimates point in different directions for men and women: suggesting that ALMPs might have a negative effect on anxiety for women but a positive one for men. However, ALMPs appear to be more effective in raising the life satisfaction of women compared to men. For female ALMP participants, the effect of participation on life satisfaction is fairly strong and statistically significant at the 95 per cent level. For men however, the effect on life satisfaction is weaker and falls just short of statistical significance at the 90 per cent level. Consequently, although men seem to benefit more from ALMPs than women, the results equally suggest some advantages for female participants too.
Table 5

OLS regressions of indicators of SWB on labour market status by gender, with socio-demographic control variables (estimates not shown)

 

5a. Life satisfaction

5b. Life worth

5c. Happiness

5d. Anxiety

Men

Women

Men

Women

Men

Women

Men

Women

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Current employment status (ref: openly unemployed)

ALMP

0.22 (.14)

0.025

0.34 (.14)*

0.039

0.30 (.14)*

0.036

0.16 (.14)

0.019

0.39 (.15)*

0.040

−0.07 (.17)

−0.01

0.15 (.18)

0.012

−0.26 (.20)

−0.021

Intercept

8.65

 

7.15

 

6.73

 

5.99

 

7.70

 

6.28

 

7.89

 

7.51

 

N

3,696

 

3,538

 

3,696

 

3,538

 

3,696

 

3,538

 

3,696

 

3,538

 

R2

0.10

 

0.12

 

0.08

 

0.07

 

0.08

 

0.07

 

0.04

 

0.05

 

Significant at: 90 %; * 95 %; ** 99 %; *** 99.9 %

Finally, hypothesis (3) predicted that compared to open unemployment, work-oriented ALMPs would be more effective in raising SWB compared to employment-assistance ALMPs. The results in Table 6 show this to be unambiguously the case. Relative to open unemployment, work-oriented ALMPs are associated with significantly higher life satisfaction, life worth and happiness, with similar results for other ALMPs in relation to life satisfaction and life worth. This suggests that programmes that focus on providing training or work experience are capable of improving the well-being of unemployed people. However, as suggested by the population estimates in Table 3, there are no significant differences between the openly unemployed and those enrolled upon employment-assistance ALMPs. Such programmes tend to focus on providing an intensified system of employment advice as opposed to close labour market integration. The results in Table 6 thus give credence to the application of Jahoda’s theory to ALMPs, suggesting that schemes that more closely mimic the routines and habits of paid work are significantly more effective in boosting well-being. Finally, as was also shown in Tables 4 and 5, there is no evidence of an ALMP effect on anxiety.
Table 6

OLS regression of indicators of SWB on labour market status by ALMP type, with socio-demographic control variables (estimates not shown)

 

Life satisfaction

Life worth

Happiness

Anxiety

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Unstd.

Std.

Current employment status (ref: openly unemployed)

Work-oriented ALMP

0.42 (.20)*

0.023

0.41 (.20)*

0.024

0.42 (.23)+

0.021

0.19 (.28)

0.008

Employment-assistance ALMP

0.18 (.17)

0.011

−0.05 (.17)

−0.003

0.22 (.20)

0.012

−0.13 (.24)

−0.006

Other ALMP

0.29 (.14)*

0.023

0.39 (.14)**

0.033

0.07 (.16)

0.005

−0.10 (.20)

−0.006

Intercept

7.93

 

6.26

 

7.07

 

7.82

 

N

7,234

 

7,234

 

7,234

 

7,234

 

R2

0.11

 

0.08

 

0.07

 

0.04

 

Significant at: 90 %; * 95 %; ** 99 %; *** 99.9 %

5 Discussion

The results in Tables 4, 5 and 6 suggest that participation in ALMPs is, relative to ‘open unemployment’, associated with increased feelings of SWB for at least three dimensions: self-evaluation (life satisfaction); eudemonia (life worth); and positive affect (happiness). Though not large and not comparable with the well-being impact of re-employment, these differences are statistically significant when a wide range of socio-demographic variables are controlled for. This suggests that moving people onto ALMPs has the serious potential to improve quality of life amongst the unemployed.

Beyond this, there are three other key findings of importance for well-being and public policy. First, ALMPs appear far more effective in improving evaluative measures of well-being (what people think about their lives) as opposed to affective ones (people’s emotions). In general terms, the coefficients in Table 4 showed that the difference between the unemployed and ALMP groups was strongest for life satisfaction and life worth, whilst there is no evidence whatsoever of a difference between the two groups for anxiety in any of the analyses. This is not too surprising: both Diener (1984) and Kahneman and Deaton (2010) have argued that evaluative measures of SWB have different determinants to affective measures. In the instance of employment, it would appear that labour market status has less of an impact on how we feel each day and more of an impact on how we view ourselves. The judgements we make about our lives are not necessarily linked to the quality of our everyday emotions.

Second, the evidence from Table 5 showed that the well-being benefits brought about by ALMPs varied by gender, suggesting a stronger effect for male participants than female ones. This is not surprising; as unemployment is known to hit men harder, policies that bring them closer to the labour market are likely to have a positive effect on SWB. Conversely, the negligent or small SWB effects of ALMPs for unemployed women may reflect the difficulty some women have in balancing efforts to find paid work with other responsibilities, such as childcare. All in all, more research is needed on the differential effects of ALMPs within further groups, such as age and educational background.

Third, the theoretical background to much existing work on ALMPs is based upon an application of Jahoda’s theory of the latent benefits of paid work. This is the idea that the features of the environment of employment—such as time structure, social activity and daily routine—are responsible for many of the psychosocial benefits of being in work. The evidence from Table 6 supports this application of Jahoda’s theory. The estimates showed that ALMPs that more closely mimic the environment and routines of paid work had a large and significant effect on SWB compared with unemployment, whilst employment-assistance ALMPs—which focus on intensified advice—had no impact on SWB. These findings strengthen the argument that in order to improve the SWB of the unemployed, interventions should focus on ALMPs that closely reflect the reality of the labour market.

However, there are numerous limitations to the study that need to be cautioned against. First, it is unclear whether the costs of ALMPs justify the benefits to well-being that they seemingly bring about. ALMPs are costly interventions, with many governments spending between 0.5 and 1 per cent of GDP annually. A valid question is whether the deleterious psychosocial costs of unemployment can be reduced in other, less expensive ways. Second, cross-sectional data are only able to expose associations between variables rather than attribute causation. As Winklemann and Winkelmann (1997) observe in relation to the negative effects of unemployment on life satisfaction, cross-sectional studies are unclear in terms of the direction of causation. With regards to this study for example, unemployed individuals with higher SWB may be more likely to enrol on ALMPs. Further, there may be important variables omitted from the analysis. ALMP participants may be more likely to have a stronger work ethic, for example, and work ethic may be correlated with higher SWB. This would imply that the observed differences found in this paper are spurious. Like Winklemann and Winkelmann (1997), future research should exploit longitudinal data such as the British Household Panel Study (BHPS) to explore whether ALMPs are associated with higher SWB when fixed effects are controlled for. Third, there are far more sophisticated indicators of psychological functioning available in many other datasets. These include the GHQ-12 and Cantril’s Self-Anchoring Scale of life satisfaction. Further research should explore the effect of ALMPs on these purer measures of well-being.

6 Conclusion

This paper is set in the context of the recent emergence of SWB as an important part of the policy-making process. In particular, it explores the relationship between SWB and unemployment and considers whether ALMPs have the effect of increasing SWB amongst the unemployed. The central idea is that paid employment provides an environment that is conducive to good well-being. Consequently, ALMPs—which to some extent mimic this environment—may provide some of the same psychological benefits as paid work to the unemployed. To test this hypothesis, data were analysed from the 2011 to 2012 wave of the UK Annual Population Survey: the first survey to incorporate the new indicators of SWB devised by the UK government. The results showed that there was a positive SWB effect of ALMP participation relative to ‘open unemployment’. However, there were three caveats. First, the effect of ALMPs was stronger for evaluative measures of well-being compared to affective ones. In line with previous research, this suggested that labour market status more strongly predicts how we judge our lives as to how we feel each day. Second, the effect of ALMPs was stronger for men than women, suggesting that ALMPs have varying effects dependent on how different groups are affected by unemployment. Third, in line with Jahoda’s theory, ALMPs that more strongly replicated paid work were far more effective than ones that offer an intensified system of employment support.

The central conclusion therefore is that certain types of ALMPs may bring about well-being benefits for certain groups amongst the unemployed. For policy-makers and politicians that advocate the application of well-being research to public policy, this is an important finding. Unemployment is long established as one of the most damaging life events for subjective well-being and there is seemingly little that governments have done to assist mental functioning amongst the unemployed. There is thus an urgent need for interventions that promote the psychosocial resilience of unemployed people. ALMPs appear to be one way to do so.

Footnotes
1

‘Work-oriented’ ALMPs include the following schemes: Work Based Learning for Young People; Work Based Learning; Entry to Employment; Work Trials; Training for Work; Ready for Work; and Work Experience. ‘Employment-assistance’ ALMPs include: the New Deal; New Enterprise Allowance; and the Work Programme. ‘Other’ ALMPs include respondents who report being on a government training scheme but do not specify which one.

 
2

Logistic regression estimates confirm that ALMP participants are significantly less likely to be married than the openly unemployed group. They are also significantly less likely to be of Indian ethnicity and significantly more likely to report ‘other qualification’ as highest education level and ‘other’ as housing tenure.

 

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.School of Applied Social ScienceUniversity of StirlingStirlingUK

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