Is utility related to employment status? Employment, unemployment, labor market policies and subjective well-being among Swedish youth

LABOUR ECONOMICS ELSEVIER

Labour Economics 4 (1997) 125-147

Is utility related to employment status? Employment, unemployment, labor market policies and subjective well-being among Swedish youth Tomas

Korpi

* ,l

Stockholm University, 106 91 Stockholm, Sweden

Received 3 June 1994; accepted 26 November 1996

Abstract Inherent in wage bargaining models and in models of job search is the assumption that utility is related to employment status. It is thus postulated that unemployment is associated with lower utility than employment, or that unemployment is moderated by manpower programs and unemployment benefits. Yet despite the centrality of such assumptions, empirical evidence on these issues is rarely presented. This paper presents such evidence, analyzing differences in subjective well-being among youth relating to employment, unemployment, participation in manpower programs and receipt of unemployment benefits. The results show that, relative to employment, unemployment has an unambiguously negative effect on well-being. Manpower programs seem to occupy an intermediate position. They are clearly better than unemployment and there are suggestions that they are worse than employment. JEL classification: J64; J65; J68 Keywords: Unemployment; Manpower programs; Unemployment benefits; Subjective well-being: Non-random selection; Unobserved heterogeneity

* Tel.: +46-8-163149; fax: +46-8-6125580. 1 This paper has benefitted from the comments of Anders BjSrklund, Per-Anders Edin, Jan Hoerct and an anonymous referee, as well as from seminar participants at Stockholm University. An5' remaining errors are of course my own. 0927-5371/97/$17.00 Copyright © 1997 Elsevier Science B.V. All rights reserved. PII S 0 9 2 7 - 5 3 7 1 ( 9 7 ) 0 0 0 0 2 - X

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1. Introduction

The relationship between employment status and utility is central to much of labor economics. Union models of wage formation for example often specify a union as maximizing an objective function with the union members' utility as employed and as unemployed as arguments and a key component of these models is the presumed existence of utility differences between the two labor market states (see e.g. Oswald, 1985). Utility differences between employment and unemployment also underlies models of job search, although the utility comparison here is assumed to be made by the individual (e.g. Devine and Kiefer, 1991). Furthermore, in addition to employment and unemployment, many models also distinguish states related to various labor market policies. The existence of employment and training programs targeted at the unemployed has thus been incorporated into some union models, where it has been assumed that the utility of participation in such programs differs from that of unemployment (e.g. Calmfors and Forslund, 1991). Another example of labor market policies are income support schemes and in search as well as union models it is often postulated that utility as unemployed is a function of the receipt of unemployment benefits (Devine and Kiefer, 1991; Oswald, 1985). Search models incorporating the presence of employment and training programs can also be found (e.g. Carling et al., 1996). Rarely, however, is an empirical foundation for these assumptions provided, and when any basis for the distinctions is furnished it most often is with reference to income differences between the various states. While it is clear that income differences are likely to be important, it is definitely not the only factor affecting utility. These assumptions would therefore become more palatable if an unequivocal relationship between employment status and some general measure of 'life satisfaction' could be demonstrated. Luckily, measures of how good or bad one feels about one's current situation are available in the form of the various scales psychologists have used to measure subjective well-being. The relationship between subjective well-being (sometimes also labelled psychological well-being or mental health) and employment/unemployment has also been the subject of an endless number of studies. There are thus evidence from different countries and time periods, cross-sectional as well as longitudinal, and there appears to be no doubt that in comparison to employed well-being among unemployed is substantially lower. In addition, there is also evidence that wellbeing is lower among long-term unemployed than among more recently unemployed and it is therefore commonly concluded that unemployment affects subjective well-being negatively. Nevertheless, doubts regarding the existence of a causal effect of unemployment on well-being linger. This scepticism springs from the likelihood of non-random selection into and out of unemployment, a selection possibly based on subjective well-being. Such systematic selection would imply that the positive correlation between unemployment and well-being may be the result of a causal

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effect from well-being to unemployment rather than vice versa. The problem of selection is furthermore often a problem of unobserved heterogeneity and it is notable that no negative health effects of unemployment were found in two studies that attempted to control for such heterogeneity. The widespread notion of a negative effect of unemployment on well-being may in other words be false. Moreover, there have been practically no analyses of the impact of public policy on well-being and the empirical basis for the distinctions between employment statuses used in economic models must therefore be regarded as less than satisfactory. In addition to its significance for economic theory, the relationship between employment status and well-being is of relevance for the debate on unemployment hysteresis. The central issue here is if there is a link between previous unemployment and future unemployment and a negative effect of unemployment on well-being may be such a connection. A lowered subjective well-being may thus lead to discouragement, an inability to acquire new skills, or unsatisfactory performance at job interviews, all translating into a low job offer probability. This may in turn generate a stock of unemployed unable to compete on the labor market, decreasing effective labor supply, driving up wage levels and produce a new equilibrium with a higher level of unemployment (Layard et al., 1991; Darity and Goldsmith, 1996). Finally, the effects of labor market policies on well-being should also be of interest for policy evaluation, as an effect on well-being may be one mechanism by which programs can affect the employment probability of participants. The purpose of this study is to investigate the relationship between employment status and subjective well-being, taking into account the possibility of non-random selection. To this order, models for selection based on both observed as well as unobserved variables are applied. The data used in the study come from a survey of unemployed youth in Sweden. In Section 2, theory and empirical evidence regarding the effects of unemployment and labor market policies on subjective well-being are briefly reviewed. Section 3 contains a presentation of the data and the models used in the analyses and Section 4 the results. In Section 5, finally, a summary and discussion of the results is found.

2. Employment status and subjective well-being There are a number of psychological theories relating employment status, in particular employment and unemployment, to well-being. Some examples are stage theory, which assumes that unemployed pass through successive stages in their response to unemployment (Eisenberg and Lazarsfeld, 1938); the functional model, focusing on the latent functions of employment (Jahoda, 1982); agency theory, emphasizing the individual's ability to influence events (Freyer, 1986); and the vitamin model, stressing the aspects of the environment surrounding the

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individual (Warr, 1987). Common to the theories specifically oriented towards the labor market appears to be a distinction between individual and environmental factors, with the theories varying in the relative weight attached to the two sets of factors 2. Theories focusing on individuals highlight their ability to cope with different situations, while the environmentally oriented theories emphasize the features of the situation the individual finds herself in. The latter is of course particularly pertinent to the impact of employment status and the factors listed by the so-called vitamin model are fairly representative of the type of environmental aspects believed to be related to mental health; opportunity for control, opportunity for skill use, externally generated goals, variety, environmental clarity, availability of money, physical security, opportunity for interpersonal contact and valued social position. Unemployment is assumed to score lower than employment on most of these features and consequently to be associated with a lower level of subjective well-being. These environmental features also suggest that there may be an effect of labor market policies on well-being. Receipt of unemployment benefits would thus improve one's economic situation. This would also be the case with manpower program participation in countries were participants receive benefits. In addition, program participation may also counteract other aspects of unemployment, e.g. the decreased variety within a person's life and the restricted interpersonal contact. Relative to unemployment, both income support schemes and manpower programs may therefore be associated with improved well-being. The literature on the relationship between employment, unemployment and subjective well-being has been reviewed by e.g. Banks and Ullah (1988), Feather (1990), Lahelma (1989), Warr (1987) and Winefield et al. (1993) 3. These reviews show that unemployment generally is found to be negatively correlated with well-being. There is, however, variation in the degree to which unemployment experience is related to lower well-being, differences associated with, inter alia, length of unemployment, sex and age. There are thus indications that well-being is lower the longer one has been unemployed, but also signs that this pattern may change after around six months of unemployment. Thereafter, the association between well-being and unemployment duration appears to remain constant and may even improve somewhat. Regarding differences between men and women, there are some suggestions that the negative association between unemployment

2 The theories mentioned above have all been developed for the analysis of the effect of work and unemployment on psychological well-being. There are also more general psychologicaltheories that have been applied to the question of the psychologicaleffect of unemployment, for example life span development theory, learned helplessness theory and expectancy valance theory. Reviews can be found in Feather (1990), Warr (1987) and Winefield et al. (1993). 3 There are also studies on other aspects of psychologicalhealth, for example the use of psychiatric services (e.g. Kieselbach, 1987) and suicide (e.g. Platt et al., 1992).

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and well-being is stronger among men. For age, finally, the correlations intimate a non-linear pattern in the psychological reaction to unemployment. It is for this study important to note that although there are indications that the effect is stronger among the middle-aged compared to both the young and the old, unemployment appears negatively related to well-being in all age groups. While positive effects of labor market policies on subjective well-being have been discussed, empirical analyses are scarce. Some recent studies (e.g. Lahelma, 1989; Ullah, 1990; Whelan, 1992) have examined the effect of both actual and subjective financial situation, the results suggesting a negative relationship between subjective financial strain and psychological health. The relationship to actual income is less clear, some studies reporting no effect of factual economic situation and others lower well-being with worsening economic situation. Most of the measures of actual income have been comprehensive, encompassing a number of income sources, but one study among Norwegian youth analyzed different sources separately. While the sign of the estimate suggested that the receipt of unemployment benefits may affect well-being positively, the effect was not significant (Rosvold and Hammer, 1991). As for the psychological effect of participation in manpower programs, there is some evidence relating to the British Youth Opportunities Program and Youth Training Scheme. Although fairly crude, the results suggest that during their participation in the program, the well-being of the participants ranks in between that of employed and unemployed. Once the program has ended, however, there appears to be no difference between the participants who return to unemployment and the continuously unemployed (Branthwaith and Garcia, 1985; Oddy et al., 1984; Stafford, 1982). Nevertheless, it has long been recognized, in particular in discussions on the effect of unemployment, that the causal analysis of the relation between subjective well-being and employment status is complicated by the possibility of non-random selection. Psychological health problems may be the reason for becoming unemployed, so observed differences in well-being between employed and unemployed need not be evidence of a causal effect of unemployment. Furthermore, since such problems may make it more difficult to find renewed employment, a similar caveat holds with regard to differences in well-being among long and short term unemployed. It is well known that if not properly controlled for, selection processes such as those sketched above generate selection bias in the parameters of interest and a number of models have been proposed for such situations 4. A principal distinction may here be drawn between models where selection takes place based on

4 For an extensive discussion of how the selection problem may be handled under different circumstances and/or assumptions, see Heckmanand Robb (1985).

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variables observable to the researcher and those where it is based on unobservable ones. In the former case, available information may be used to eliminate the selection bias in a straightforward manner. However, when analyzing the causal relationship between unemployment and well-being, the factors governing the selection process may be known only to a limited extent, or the data at hand may not allow an adequate modelling of these effects. In such cases, it may be possible to obtain unbiased estimates by modelling the unobserved heterogeneity. While such models have found frequent use in other areas, for example in analyses of the effects of training, there appears to be only two studies on the association between unemployment and subjective well-being using this approach. BjSrklund (1985) used interview data from a representative sample of the Swedish population between 15 and 75 years of age. He analyzed changes in well-being between the years 1968 and 1974, as well as between 1974 and 1981, using health measures based on four items and unemployment variables combining information on unemployment at the time of interviews and in the year preceding the interviews. To control for unobserved heterogeneity, BjiSrklund applied a conditional likelihood model (an analogue to the common fixed effects model). He found no significant relationship between unemployment and changes in wellbeing, even though well-being among unemployed was lower than among employed. The relation between unemployment and well-being was also studied by Edin (1988), using data from a sample of factory workers laid off in connection with a plant closure in Sweden in 1982. He studied changes in subjective well-being (measured through a twelve-item questionnaire) using observations shortly before the closing of the plant and around ten months later. Edin used a fixed effects model to control for unobserved heterogeneity and reported that there was no significant association between unemployment experienced between the interviews and changes in the well-being of the respondents. In neither of the two studies that controlled for unobserved heterogeneity was thus a causal effect of unemployment on well-being found. This challenges the received view of causation, as it implies that the cross-sectional correlations may be the result of selection. Together with the almost complete dearth of analyses of the impact of public policy, these results call for further investigation into the relationship between employment status and subjective well-being.

3. Data and methods

The data that has been used in the present study come from the Survey of Unemployed Youth in Stockholm, Sweden, a longitudinal survey covering the period 1981 to 1985 (Holmlund and Kashefi, 1987). The survey consists of a random sample of about 830 respondents drawn from among those 16 to 24 years of age registered as unemployed at the employment agencies in the County of Stockholm at the end of January 1981. The data used here come from two

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interviews, the first carded out between February and May 1981 and the second between February and June 1982. This time period covers the Swedish recession in the early 1980s. Unemployment then increased up to 1983, culminating with an overall unemployment rate of 3.5% and 8% among youth and decreased thereafter. This was at the time the deepest recession Sweden had experienced for decades and in accordance with the Swedish policy of actively fighting unemployment manpower programs were allowed to expand. When the unemployment rate peaked in 1983, the two main programs, labor market training and temporary relief work, encompassed 2.3% of the labor force (Johannesson, 1993). The effects of these programs have been subject to extensive debate. They have thus been seen as a major factor behind Sweden's low unemployment rates, but also as little more than hidden unemployment. Both programs have a normal duration of around six months, with the participants in relief work receiving market wages and those in training the equivalent of unemployment insurance. Of the unemployed not participating in manpower programs, during the first half of the 1980s around two-thirds received one of the two types of unemployment benefits: basic unemployment assistance and voluntary unemployment insurance. One central difference between the two benefit types relates to replacement rates. In the early 1980s, the average replacement ratio was around 70% among insured blue-collar workers and much lower among recipients of unemployment assistance. Among youth, coverage was lower and receipt of unemployment assistance more common (Bj~Srklund and Holmlund, 1991) 5. It is important to note that the sample was drawn from a stock of unemployed and that this study therefore presents analyses of the health effect of additional unemployment among already or previously unemployed. This may represent a limitation of the study. Nevertheless, it should also be noted that since labor market policies are targeted at unemployed, this qualification does not apply to the analyses of the impact of labor market policies. Another central aspect of the data is that the sample consists of unemployed youth and it should be remembered that previous studies have indicated somewhat milder effects of unemployment among youth than among adults. Finally, it may also be noted that this is a representative sample of unemployed in a major metropolitan area. The data include (a) background information for the period up to 1981, (b) information pertaining to the time of the various interviews and (c) continuous labor market histories starting in January 1981. In the labor market histories, the respondents were asked to distinguish between spells of unemployment, permanent employment, temporary employment, temporary relief work, labor market training,

5 The benefits also differ in eligibility requirements and the duration for which they can be received.

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participation in youth teams 6, regular education, on leave from a job, military service and the category 'other'. Regarding well-being, there is information on how often during the preceding month the respondents had (a) experienced sleeplessness, (b) headaches/migraine or (c) stomach pains and felt themselves (d) sad and dejected or (e) worried and restless. The ordinal scale responses to these five questions have been summarized into an index of subjective well-being, or more accurately, into an index of psychological distress (D). Like the vast majority of measures of subjective well-being found in the literature the measure used here is thus based on self-report assessment and the five questions also largely correspond to items previously used in the construction of scales of subjective well-being. In this context, it may be noted that there is evidence that physiological aspects are crucial for the analysis of low levels of well-being and that such items are included among the questions. This index has in turn been treated as an interval scale and used as the dependent variable in ordinary least squares regression. This approach is identical to that used in many other studies of subjective well-being and the great advantage with this data set is therefore that it combines a relatively good measure of well-being with very detailed information on labor market events. (The construction of the measure of well-being is discussed further in Appendix A and results obtained when using two alternative measures of well-being are also reported below.) Before presenting the actual models that have been estimated in these analyses, it may be helpful to outline the heuristic framework that has provided the background for the specifications. Thus, individual i's level of psychological distress at time t has here been expected to depend on i's labor market status at t, more specifically on whether i is employed (E), unemployed (U), in a manpower program (P) or outside the labor force (O). Previous studies also indicated the time spent in the current status to be important, that is current employment duration (ED), unemployment duration (UD), manpower program duration (PD) and outof-labor force duration (OD). Similarly, psychological health may depend on the time spent in the various states before the start of the current activity, i.e. on prior employment experience (EX), unemployment experience (UX), manpower programs experience (PX) and time spent outside the labor force (OX). Finally, health may depend on other person specific characteristics such as age and sex (here summarized into a vector denoted C). To facilitate the presentation, these ideas have been formulated as a simple 'distress equation': Dit = OLEEit q- OluUit -~- olppit + ogoOit -~- OtEDEDit + otuDUDit + otpDPDit q- OtoDODit q- otExEXit q._ O~uxUXit -~- OtpxPXit + O~oxOXit qt_ Olcfit '

(1) 6 A program started in 1984 consisting of subsidized work for 18 and 19 year old, mainly in the public sector.

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were a c is a vector of parameters corresponding to C. There are a number of hypotheses that may be tested with such a specification. An effect of curren! unemployment is thus present if a U # a E or aUD 4= aED and of previous unemployment if aux 4: aEX. Regarding manpower program participation, currenl participation may differ from current unemployment, ap # au or apD # aUD and previous participation from previous unemployment, aPX # aux. Furthermore, current participation may differ from current employment, ae # aE or apD 4: aED and previous participation from previous employment, apx # aEX. The specification in Eq. (1) does not allow for an effect of the receipt of unemployment benefits. The possibility of such an effect can be introduced by distinguishing between unemployed with benefits (UWB) and those with no benefits (UNB) and rewrite Eq. (1) as Dit = OLEEit + a u w B U W B i t + otuNBUNBit + olpPit + o[oOit + OtEDEDit + OlUwBDUWBDit + o~UNBDUNBDit + o t p D P D i / + aoDODit + o~ExEXit + O~uxUXit + O~pxPXit + O~oxOXit -1- a c C i t ,

(2)

where UWBD is the unemployment spell duration of those receiving benefits and UNBD of those that do not. With this specification, an effect of unemployment on well-being is indicated by C~uwB 4: a E or aUWBD ~ ~ED or C~UNn # C~E or C%NBD 4= teED. An effect of unemployment benefits on the situation as unemployed would here be present if C%NB # C~UWB or C~UNBD=g C%WBD. There may also be differences in program effects, ap # auw B or O~pD :7~ OIUWBD. Turning now to the first of the estimated models, an initial impression of the potential determinants of subjective well-being can be obtained through traditional cross-sectional analyses. Here, psychological distress at the time of interviews has been analyzed using ordinary least squares. That is, Dit = xi, /3 + blit

(3)

where x is a vector of variables, /3 is a matching vector of parameters and u is a random error term. Apart from some minor modifications, the variables that have: been used in these analyses are the ones found in Eq. (2). Thus, there have been indicators of labor market status at the time of interview, namely 'unemployed with benefits', 'unemployed without benefits' (both at the time of interview). 'program participant' and 'out-of-the-labor-force' 7. (Note that the reference category has been 'employed'.) Furthermore, 'employment spell duration', 'unemployment spell duration with benefits', 'unemployment spell duration without benefits' and 'program spell duration' measure the duration of the ongoing spell at

7 As noted above, there are two forms of unemployment compensation in Sweden. Despite the differences between the two, data limitations have required that they be combined into one indicator. Likewise, the limited amount of data made it necessary to combine the two programs temporary relief work and labor market training into one category.

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the time of interview (in months) 8. In addition, measures of previous employment history have also been included, viz. 'employment experience', 'program experience' and 'unemployment experience' (in months, measured from the end of compulsory education up to but not including current activity)9. The personal characteristics that have been included are 'female', 'immigrant background' (foreign citizen or Swedish citizen whose parents were both foreign citizens) and 'upper secondary education' (attained an educational level equal to upper secondary education or above) 10. (Descriptive statistics are presented in Appendix

B). However, estimates of Eq. (2) in the form of Eq. (3) does not control for the possibility of health related selection. Two different approaches to controlling for such selection have here been tried. The first of these approaches is based on the idea that since health is presumed to be the factor governing selection, the estimates in analyses of health at t may be purged of selection bias if a measure of health at t - 1 is included. In the terminology of Heckman and Robb (1985), health at t - 1 acts as a linear control function. Briefly turning back to the framework, the equation for health at t would then be written as Dit = OlEEit q- otuUit q- ozpPit + aoOit q- aEDEDit q- ceuDUDit + o~pDPDit

q"- aoDODit q'- a E x A E X i q-- a u x A U X i + OtpxAPX i + OtoxAOXi -1- o,cCit A- OtDDit_ 1'

(4)

where AEX i = E X i t - EXit_l, AUX i = UXit- U X i t _ 1, APX i = PXit - PXit 1 and AOX i OXit- O X i t l" Such a specification has also been analyzed here, using the measure of psychological distress at the first interview as a predictor of distress at the third interview. It is important to note that the approximately one year period between the interviews should be sufficiently long for any changes in psychological well-being to take place. Recall that earlier research suggested that psychological effects surface fairly quickly. Again, ordinary least squares has been used and the other variables that have been included basically correspond to those in the cross-sectional analysis. The difference lies in the definition of the variables measuring experience in the various labor market states. Here 'Aemployment experience', 'Aunemployment experience' and 'Aprogram experience' measure the length of time spent in the three labor market states between the two =

8 It may be noted that the unemploymentduration variables measure the duration of the spell, not the length of time for which benefits have been received. 9 This holds for all experience measures except for the time spent in labor market training which is measured from the beginning of 1980. 10The variables missing in comparison to the formulations in the framework are the duration and experience measures for the status 'Out of the labor force'. These have not been included as they were of no major interest.

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interviews (in months), not including the duration of the current spell at the second interview 11 Nevertheless, the health measure at hand may not be an adequate control for the selection process. Specifically, there may be person specific factors affecting selection that are not captured by the available measure, that is selection may be based on unobserved heterogeneity. An example of such a factor are basic personality traits and the existence of such personality features have been extensively discussed in the literature. For example, Jahoda et al. (1933/1960) argued that an individual's reaction to unemployment was determined by the person's basic attitude. For the present study, the central aspect of such characteristics is that they may remain constant over an extended period of time. Such time invariant factors, so-called fixed effects, can be introduced into the model of Eq. (3) by rewriting it as D,, = x,,

+ u,, + f , ,

(5)

were J~ denotes the person specific fixed effect. As is well known, if selection is based on such time invariant unobserved heterogeneity, estimates of fl based on the formulation of Eq. (3) would be biased (see e.g. Hsiao, 1986, p. 4). Nonetheless, unbiased estimates may be obtained. Taking the first difference of" the observations,

Dit-Dit_l=(Xit-xit 1)flA-(uit-uit_l),

(6)

is obtained. This can be seen to be independent of f,., that is time invariant unobserved heterogeneity has been eliminated from the model. In comparison to the earlier analyses, the variables that have been used here differ in that all constant ones (e.g. sex) are excluded from the model and the remaining ones have been converted into measures of change. Thus, there have been variables measuring change in labor market status between the interviews, viz. 'become employed', 'become unemployed', 'become program participant' and 'left the labor force'. As in the earlier analyses, 'become unemployed' has also been partitioned into 'become unemployed with benefits' and 'become unemployed without benefits' 12 There have also been measures of change in duration of current spell, namely

11 In addition, there is a second difference relating to the limited number of respondents who remained in the same employment status throughout the whole period. Since the measure of well-being at the first interview will include any effects of the duration of the spell up to that point, the duration measure at the second interview should not include the spell duration prior to the first interview. For these respondents, the measure of the duration of the current spell at the second interview thus measures the change in duration between the two interviews, that is the no. of months between the two interviews. ~2 Being measures of difference in z e r o - o n e variables, these variables take on the values (1, 0, - 1). For example, the variable 'become unemployed' takes on the value l if a person has become unemployed, the value 0 when no change in unemployment status has taken place and the value - 1 if the person has left unemployment.

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'Aemployment duration', 'Aunemployment duration' and 'Aprogram duration'. Finally, the previously defined variables 'Aemployment experience', 'Aunemployment experience' and 'Aprogram experience' have also been included.

4. Results A first impression of differentials in psychological distress relating to employment status are presented in Table 1, which gives the mean level of distress within each employment category at the time of the first interview. The first thing to note is the progressively increasing levels of distress associated with employment, program participation and unemployment. The increase is not particularly great, the difference between employed and unemployed of approximately one unit on the distress scale corresponds to a change in one of the five items from, for example, occasionally to fairly often. Nonetheless, given that previous research had indicated relatively small effects of unemployment among youth, the fairly small differences come as no complete surprise. Moreover, the differences in well-being are significant, the p-value for equality of the means is less than 0.001. Turning then to the multivariate analyses, the results from the cross-section analysis at the first interview are presented in Table 2. To start with, it may briefly be noted that distress among young women is markedly higher than among young men and that youth with a high level of education are better off than the rest. In contrast, psychological well-being does not appear to differ between youth with an immigrant background and other youth. The variables of primary interest are however those relating to unemployment, manpower programs and unemployment benefits. Beginning with the overall association between well-being and current labor market state, such estimates are shown in model 1. The measures of current spell duration have here been excluded, the estimates for the current labor market status variables thus showing the combined effect of currently being in a particular labor market state and the

Table 1 Mean values of psychologicaldistress by employmentstatus at the first interview Employmentstatus Mean Frequencies Employed Program Unemployed Unemployedwith benefits Unemployedwithout benefits Out of labor force Total

8.23 a 8.97 a 9.65 a 8.85 9.97 8.90 a 8.72

a P-value (X2-test) for equality of means < 0.001.

367 65 160 46 114 75 667

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current length of this spell. The results show that unemployed as a group clearly are worse off than employed (the comparison group) and this is in particular so for unemployed without benefits. Furthermore, distress among program participants is lower than among unemployed without benefits and no difference between the well-being of manpower program participants and that of employed could be established, suggesting that program participation does improve the well-being of unemployed. Regarding unemployment benefit recipients the results are indeterminate, the differences in distress observed between this and the other groups are all insignificant. Apart from the difference between program participants and unemployed without benefits, which now becomes insignificant, these conclusions also remain unaffected by the introduction of the distinction between occurrence and duration effects of current status in model 2 of Table 1. As for the effect of previous experience, previous unemployment is relative to both previous employment and program participation associated with an increased level of psychological distress, while previous program experience cannot be separated from previous employment 13 However, the cross-sectional models presented in Table 2 do not control for the possibility of health based selection. As discussed above, if selection takes place on observable health variables, unbiased estimates may be obtained after the inclusion of a so-called control function. Such estimates are shown in Table 3 and as could be expected previous psychological well-being has a strong influence on subsequent psychological well-being 14. Apart from this, most results show the now familiar pattern. Relative to employed, currently unemployed (both with and without benefits) have higher levels of distress, even after controlling for well-being at the previous interview. Likewise, program participants are better off than both groups of unemployed and no clear difference in well-being can be established between program participants and employed. Finally, there is no difference

t3 A similar analysis at the second interview (not shown) yielded some differences in the results:. distress among unemployedwith benefits was higher than among employed and program participants. unemployed without benefits were worse off relative to program participants even when the separate effects of occurrence and durationwere taken into account and there was no difference in the effects of previous program participationand previous unemployment.The general fit of the models as well as their sensitivity with respect to individual observationshas been analyzed through examinationsof residuals, leverages and various influence statistics. These analyses did not indicate any general problems with the specifications and additional analyses with what appeared to be particularly influentialobservationsexcluded (not shown) did not change any of the conclusions.To further test the specifications they have also been estimated with robust standard errors (standard errors insensitiveto heteroskedasticity, see e.g. White, 1980) as well as using a two-limit tobit specification(i.e. with the dependent variable censored from both above and below). Again, the results remainedunchanged. 14The questionof panel attritionrelated to well-beinghas here been analyzedthrough the estimation of a logistic model of the likelihoodof non-participationin the second interviewgiven participationin the first. The independentvariablescorresponded to the ones in model 1 of Table 3 and there was no significanteffect of well-beingat the first interviewon the likelihoodof non-participation.

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Table 2 Determinants of psychological distress. Ordinary least squares estimates at the first interview. Standard errors in parentheses, n = 667 Variable

Constant Female Immigrant background Upper secondary education

Model 1

2

7.628 (0.291) 1.097 a (0.237) 0.300 (0.262) - 0.536 a (0.252)

7.697 (0.388) 1.100 (0.238) 0.301 (0.263) - 0.548 (0.254) - 0.033 I,m,,,p (0.137) 0.266 l,m,o,q (0.663) 0.139 l,m,o,q (0.317) 1.122 I,n,o,r (0.504) 0.029 l,n,o,r (0.193) 0.726 p,q,r (0.710) -0.214 p,q,r (0.315) 0.266 (0.466) -- 0.000 (0.006) 0.058 (0.015) - 0.018 (0.025) 0.10

Employment duration (ED) Unemployed with benefits (UWB)

0.496 b,c,e,g (0.477)

Unemployment duration with benefits (UWBD) Unemployed with no benefits (UNB)

1.221 b,d,c,h (0.342)

Unemployment duration with no benefits (UNBD) Program participation (P)

0.434 e,g,h (0.415)

Program duration (PD) Out of labor force (O) Employment experience (EX) Unemployment experience (UX) Program experience (PX) R-square

0.319 (0.390) - 0.000 i,k (0.006) 0.060 i,j (0.015) - 0.019 j,k (0.025) 0.10

P-values (F-tests) of specific hypotheses. a Coeff. = 0; < 0.10. b UWB = 0, UNB = 0; 0.005 UWB = 0; 0.30. d UNB = 0; 0.00. ¢ UNB = UWB; 0.18. f P = 0; 0.30. g P = UWB; 0.92. h p = UNB; 0.10. i UX = EX; 0.00. J PX = UX; 0.01. k p X = E X ; 0.45. I U W B = 0 , E D = U W B D , U N B = 0 , E D = U N B D ; 0.01. m U W B = 0 , E D = UWBD; 0.53. n UNB = 0, ED = UNBD; 0.00. o UWB = UNB, UWBD = UNBD; 0.40. p P = 0, ED = PD; 0.52. q UWB = P, UWBD = PD; 0.73. r p = UNB, PD = UNBD; 0.21.

b e t w e e n u n e m p l o y e d with and w i t h o u t benefits. Again, these results are unaffected b y t h e d i s t i n c t i o n b e t w e e n o c c u r r e n c e a n d d u r a t i o n in m o d e l 2. S o m e a d d i t i o n a l d i f f e r e n c e s in r e l a t i o n to t h e r e s u l t s o f T a b l e 2 c a n b e f o u n d a m o n g the variables m e a s u r i n g previous labor m a r k e t history. T h e negative effect

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139

Table 3 Determinants of psychological distress. Ordinary least squares estimates at the second interview Standard errors in parentheses, n = 517 Variable

Model

1 Constant

2 3.931 (0.339) 0.355 (0.032) 0.730 a

Psychological distress at first interview Female

4.183 (0.544) 0.337 (0.323) 0,774

(0.199) Immigrant background

(0.197)

- 0.166 (0.230) -0.424 a (0.205)

Upper secondary education

- 0.223 (0.229) -0.451 (0.203) - 0.011 I,m,n,p (0.038) 0.374 ~,m,o,q (1.024) 0,291 l,m.o,q (0.200) 0.408 l,n.... (0.577) 0.302 I,n.o,r (0.098) 0.472 p,q,r (0.610) - 0.134 p,q,r (0.089) - 0.372 (0.374) 0.015 (0.035) - 0.005 (0.042) 0.089 (0.051) 0.31

Employment duration (ED) Unemployed with benefits (UWB)

1.680 b.c.e.g (0.572)

Unemployment duration with benefits (UWBD) Unemployed with no benefits (UNB)

1.650 ~,J,e,h (0.394)

Unemployment duration with no benefits (UNBD) Program participation (P)

- 0.117 f,g,h (0.364)

Program duration (PD) Out of labor force (O)

- 0.282 (0.247) 0.018 i,k (0.026) - 0.015 i,j (0.037) 0.093 j.k (0.046) 0.29

Employment experience (EX) Unemployment experience (UX) Program experience (PX) R-square

P-values (F-tests) of specific hypotheses. Coeff. = 0; < 0.10. b UWB = 0, UNB = 0; 0.00. c UWB = 0; 0.00. d UNB = 0; 0.00. 5 UNB = UWB:: 0.96. f P = 0 ; 0.75. g P = U W B ; 0.01. h P = U N B ; 0.00. ~ U X = E X ; 0.44. J P X = U X ; 0.06 k PX = EX; 0.12. ~ UWB = 0, ED = UWBD, UNB = 0, ED = UNBD; 0.00. m UWB = 0, ED = UWBD; 0.01. n UNB = 0, ED = UNBD; 0.00. o UWB = UNB, U W B D = UNBD; 0.99. P P = O, ED = PD; 0.33. q UWB = P, U W B D = PD; 0.00. r p = UNB, PD = UNBD; 0.00. a

of

unemployment

on

current unemployment, employment

psychological

well-being

since no difference

and unemployment.

here

appears

is found between

The results in model

to

be

limited

to

the effect of previous

1 also suggest that previous

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T. Korpi / Labour Economics 4 (1997) 125-147

program participation is associated with higher levels of distress than both previous unemployment and employment 15 Still, if selection takes place based on fixed unobservables, the above estimates are biased as well. Unbiased estimates may then be obtained through a fixed effects model and such results are reported in Table 4. These results confirm those presented in Table 3. The conclusions regarding the effects of employment status drawn based upon the linear control function model are thus in all cases supported here. Regarding current labor market status, both types of unemployment are worse than employment. They are also worse than program participation and program participation cannot be separated from employment. Finally, the results indicate that previous experience does not affect current well-being 16 The treatment of the index as an interval scale may however be questioned. It is thus uncertain whether there is an equally great increase in distress when the index increases from say 5 to 6 as when it increases from 19 to 20. As a final check of the specifications used here, the linear control function and the fixed effects models have therefore been estimated using two alternative measures of well-being. The first these alternative dependent variables has been constructed by first dichotomizing the responses to each item (1 = had experienced the particular problem at least fairly often during the preceding month, 0 = had experienced it no more than occasionally) and then summing over the five items yielding a measure of well-being ranging from zero to five. The correlations between the dichotomized items and the measure of distress used in Table 1 to 4 ranged from 0.5 to 0.7 and the two overall measures correlated around 0.9. The second alternative has been obtained by a dichotomization of the original distress measure, where a respondent has been classified as distressed if the respondent's index score was greater than 10 (i.e. the average response to the five health questions a - e was greater than two). The correlation between this measure and the original one was around 0.8. The results from these alternative estimates (not shown) basically corroborate the earlier results ~7

5. Discussion Common to all three analyses of the effect of unemployment on subjective well-being presented here is the result that unemployment is associated with a

~5 The specification tests again revealed no general misspecification and neither exclusion of individual observations nor estimation with robust standard errors or specifying a limited dependent variable lead to any changes in the conclusions. 16 Again, the specification tests indicated no major problems with the model. Neither did they reveal any outlier of importance and the conclusions also remained unchanged when robust standard errors were used as well as when a two-limit tobit was estimated instead of OLS. 17 See Chamberlain (1980, Chamberlain, 1984) or Hsiao (1986) for a presentation of the conditional logistic likelihood model, the dichotomous dependent variable analogue to the fixed effect model.

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141

Table 4 Determinants of psychological distress. Fixed effects model: ordinary least squares estimates of change between the first and the second interview. Standard errors in parentheses, n = 523 Variable

Constant

Model 1

2

- 1.183 (0.204)

-

Aemployment duration (AED) Become unemployed with benefits (A UWB)

1.358 a,b.d,f (0.464)

Aunemployment duration with benefits (AUWBD) Become unemployed with no benefits (AUNB)

1.057 a,c.o.g (0.367)

Aunemployment duration with no benefits (AUNBD) Become program participant (A p)

- 0.128 e.f,g (0.437)

Aprogram duration (APD) Left the labor force Aemployment experience (AEX) &unemployment experience (AUX) &program experience (APX) R-square

-0.075 (0.301) 0.011 h,j (0.038) 0.006 h.i (0.050) 0.052 i.j (0.066) 0.04

1.511

(0.384) 0.024 kA,m,o (0.035) 0.820 k,l.n.q (0.610) 0.277 k,l,n,q (0.184) 0.710 k.m.,,.q (0.411) 0.223 k.m.n,q (0.096) 0.004 o,p,q (0.566) -0.021 o,p,q (0.095) 0.022 (0.323) 0.033 (0.046) 0.036 (0.057) 0.076 (0.074) 0.05

P-values (F-tests) of specific hypotheses. AUWB = 0, AUNB = 0; 0.00. b AUWB = 0; 0.00. c AUNB = 0; 0.00. d AUNB = AUWB; 0.56. e A P = 0 ; 0.77. fAP=AUWB; 0.01. gAP=AUNB; 0.02. hAUX=AEX; 0.93. ~APX= AUX; 0.60. J APX = AEX; 0.57. k AUWB = 0, AED = AUWBD, AUNB = 0, AED = AUNBD; 0.00. ~AUWB=0, AED=AUWBD; 0.01. mAUNB=0, AED=AUNBD; 0.00. nAUWB= AUNB, AUWBD = AUNBD; 0.88. o AP = 0, AED = APD; 0.82. P ALrWB = AP, AUWBD= APD; 0.01. q AP = AUNB, APD = AUNBD; 0.01. a

l i m i t e d but d i s t i n c t d e c r e a s e in s u b j e c t i v e w e l l - b e i n g . This n e g a t i v e e f f e c t m a y h o w e v e r b e restricted to c u r r e n t u n e m p l o y m e n t . W h i l e the c r o s s - s e c t i o n analysis did i n d i c a t e a n e g a t i v e e f f e c t o f p r e v i o u s u n e m p l o y m e n t this w a s n o t s u p p o r t e d b y the a n a l y s e s o f c h a n g e o v e r time, s u g g e s t i n g that the d e p r e s s i v e e f f e c t o f u n e m p l o y m e n t m a y b e transitory. In earlier studies, the p o s s i b i l i t y o f h e a l t h b a s e d s e l e c t i o n has o f t e n p r e v e n t e d similar results r e g a r d i n g the e f f e c t o f c u r r e n t u n e m p l o y m e n t f r o m b e i n g i n t e r p r e t e d as e v i d e n c e o f a causal effect. This is not the c a s e here, as t w o o f the a n a l y s e s control for s u c h s e l e c t i o n (for s e l e c t i o n b a s e d

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on observable psychological well-being and on unobservable fixed effects, respectively). Furthermore, since the different methods yield the same result, the problem of health based selection may have been exaggerated in previous literature. It has thus been pointed out that "alternative nonexperimental estimators will produce the same estimate only if selection bias is not a problem" (Heckman et al., 1987, p. 417). These results must therefore be regarded as strong evidence of a causal effect of unemployment on well-being. The clear negative effect of current unemployment differs from the results in the two other studies that have tried to model unobserved heterogeneity (BjSrklund, 1985; Edin, 1988). One explanation for this may relate to the distinction between current and previous unemployment. None of the other studies discriminated between the two and if the unemployment variables in the other studies primarily measured previous unemployment, which seems likely given the samples and the variables used in the studies, the results may concur. However, there are other possible explanations as well. BjiSrklund (1985) used rather crude measures of well-being and unemployment and the difference in results may thus be due to the superior measures used here. Edin (1988), on the other hand, studied factory workers that had been notified of the closure of their plant prior to the first health measurement and there may therefore have been a decrease in well-being prior to the time period studied. The majority of this sample was also made up of middle-aged women, while the sample here contains an equal proportion of young men and women. As noted earlier, there are indications that women have less trouble coping with unemployment. Furthermore, the unemployed lived in a small town that already had experienced a number of large plant closures whereas the sample here is a random sample of unemployed in a metropolitan area. The reaction to unemployment may differ between situations where it is a collective experience and situations where it is an individual one. In addition to the negative effect of current unemployment on subjective well-being, it is also clear that relative to unemployment participation in manpower programs is associated with an improvement in well-being. Again, this effect may be limited to current participation, since no difference has been found between previous participation and unemployment in the analyses of changes in well-being. Relative to unemployment, participation in a manpower program thus seems to generate a temporary improvement in subjective well-being. Moreover, no clear difference between employment and program participation has been established, so this improvement may equal that associated with obtaining a regular job. The results are more mixed when it comes to the effects of receipt of unemployment benefits, the evidence is here, at least partly due to data limitations, contradictory and no definite conclusions can be drawn. The discussion of the discrepancy between previous studies and the results presented here indicate some issues that should be kept in mind when interpreting the results. Thus, the results refer to youth and other age categories may react differently. However, with respect to the negative effect of unemployment previ-

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143

ous research suggests that any difference is most likely to be in the direction of a greater unemployment effect. This would also seem to suggest that the effect of program participation would be similar in an adult sample, yet the myopia often characterizing the behavior of youth may lead to the program effect being greater among youth than among adults. The results also pertain to a sample of (initially) unemployed, many of them with a history of unemployment. It is unclear how these results would compare with results from an analysis of never previously unemployed. Finally, two models controlling for health based selection have been included in this analysis. Further attempts at such selection control are needed, the literature on the effect of training suggest that much can be gained from applying different selection methods and carrying out specifications tests. To conclude, this paper focuses on the relation between employment status and subjective well-being or utility (Clark and Oswald, 1994). Theory as well as earlier research would seem to suggest that employment, program participation, unemployment with unemployment benefits and unemployment without benefits are associated with progressively increasing levels of distress. These results also contain some evidence of such a hierarchy, evidence of relevance for economic theory and policy. The negative effect of unemployment and positive effect of program participation are thus in accordance with the assumptions of both union models of wage formation and models of job search, namely that unemployment is an unpleasant experience most people would want to avoid and that this experience may be moderated by participation in employment and training programs. A negative impact of unemployment on well-being may also be one link between current and future unemployment and therefore of relevance for the debate on unemployment hysteresis.

Appendix A. Measuring subjective well-being A number of different measures of subjective well-being can be found in the literature, the vast majority of them based on self-report assessment (Diener, 1994). The measures range from simple questions like "Taking all things together, how would you say things are these days?" to complex scales constructed from a number of different questions relating to various aspects of well-being and distress (see e.g. Warr, 1987, for an overview). The basic idea behind the scales is that the different questions measure different aspects of subjective well-being and that a combination of the responses may increase the reliability of the measure of well-being (see e.g. DeVellis, 1991, for a general introduction to the construction of scales). Since more information in general tends to be preferable to less, it is not surprising that comparisons show multi-item measures to perform better than single-item measures (e.g. Larsen et al., 1985). Irrespective of their number, the items used focus on feelings regarding ones current situation, feelings which are described by adjectives such as happy,

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uneasy, contented and sad. However, in addition to questions about feelings, evidence on physiological processes, such as muscular tension, stomach problems and insomnia, are often included in measures of subjective well-being and such questions appear to be particularly important when interest is focused on low levels of well-being (Warr, 1987). Responses are recorded on an ordinal scale, with possible distinctions being made between either the intensity or the persistence of ones feelings, i.e. very happy, often sad. The responses are then combined and treated as an interval scale in the analyses, see for example studies based on the widely used General Health Questionnaire (e.g. Clark and Oswald, 1994). The measure of subjective well-being used in these analyses has been generated from information regarding how often during the preceding month the respondent had experienced: a. b. c. d. e.

sleeplessness, headaches/migraine, or stomach pains and felt themselves sad and dejected, or worded and restless.

Responses were measured on an ordinal scale, viz. 1 = never, 2 = occasionally, 3 = fairly often and 4 = very often. There are a couple of points that should be noted here. First, like many other inventories, the questions only refer to negative features and do not cover the full range of subjective well-being. On the other hand, the questions include an item on both anxiety (question e) and depression (question d), which are the two principal dimensions of well-being (Warr, 1987, 1990). Equally important, the questions also cover the physiological symptoms deemed necessary to identify particularly low levels of well-being. Although being somewhat limited in range, the questions will therefore probably provide an adequate picture of low levels of subjective well-being, or distress. The measure of subjective well-being has then been constructed by assigning each response category the value associated to it in the ordinal scale above (e.g. occasionally = 2) and then summing over the five questions. The result is an index of distress, D, ranging from 5 to 20. This is the measure that has been used in the ordinary least squares analyses. Again, a comparison may be made with the General Health Questionnaire, where the same approach often is used (e.g. Edin, 1988).

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Appendix B. Descriptive statistics at the first interview, n = 667

Variable Psychological distress Female Immigrant background Upper secondary education Employment duration Unemployed with benefits Unemployment duration with benefits Unemployed with no benefits Unemployment duration with no benefits Program participation Program duration

Mean 8.72 0.52 0.29 0.40 1.02 0.07 0.08 0.17 0.26 0.10 0.16

Std. Dev. 3.17 0.50 0.45 0.49 1.26 0.25 0.48 0.38 0.85 0.30 0.61

Min 5 0 0 0 0 0 0 0 0 0 0

Max 20 1 1 1 9 1 5 1 6 1 5

Out of labor force Employment experience Unemployment experience Program experience

0.11 19.25 6.21 2.05

0.32 21.11 8.42 4.97

0 0 0 0

1 99 91 60

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