Flexible contracts and subjective well-being.

Green, Colin P. ; Heywood, John S.

I. INTRODUCTION

This article estimates the influence of flexible--more contingent--employment contracts on job satisfaction and life satisfaction. Hedonic labor market theory suggests that workers sort across contract types maximizing their utility. To the extent that flexible contracts contain undesirable characteristics, this process generates either compensating earning differentials or other offsetting desirable characteristics (Rosen 1974). As a single illustration, flexible contracts exhibit greater job insecurity (Blanchard and Landier 2002), but job insecurity generates higher compensating earnings (Abowd and Ashenfelter 1981). Thus, the net influence of flexible employment contracts remains an empirical question.

We estimate the determinants of job satisfaction testing the prediction that the labor market generates equalizing differences associated with flexible contracts. As Hamermesh (2001, 2) puts it, job satisfaction is the only measure "that might be viewed as reflecting how (workers) react to the entire panoply of job characteristics" and as such "it can be viewed as a single metric that allows the worker to compare the current job to other labour market opportunities." Thus, job satisfaction measures allow a summary worker evaluation of the consequences of flexible employment contracts. (1) If such contracts consistently associate with large negative job satisfaction differentials, it becomes more difficult to argue for a hedonic or equalizing differences view of this aspect of the labor market. Yet, even in the presence of large job satisfaction differentials, it may be the case that workers in flexible contracts trade off lower job satisfaction for higher satisfaction in other aspects of life such as fulfilling family responsibilities, undertaking education, or arranging leisure activities. Examining overall life satisfaction tests the influence of flexible contracts on well-being in a framework that accounts for these potential trade-offs as well as the equalizing differences that may happen within the labor market.

This article estimates the relationships between a variety of flexible employment contracts and a range of dimensions of job satisfaction: job security, pay, hours, the work itself, and overall. Moreover, by controlling for worker fixed effects, we provide the first estimates that potentially account for sorting across the variety of employment contracts. By also estimating the determinants of life satisfaction, we provide evidence on whether flexible contracts may be associated with offsetting benefits outside the realm of work. Our evidence provides a counterbalance to earlier research (Beckmann et al. 2007; Booth et al. 2002; D'Addio et al. 2007; De Graaf-Zijl 2005a). Flexible contracts play at most a minor role in diminishing job satisfaction and this role is limited to diminishing satisfaction with job security. Moreover, flexible contracts play no role in diminishing overall life satisfaction among the employed. These results appear broadly supportive of labor markets generating equalizing differences for flexible contracts.

The next section discusses predictions and evidence about the relationship between flexible contracts and job satisfaction. The third section presents our data and testing methodology. The fourth section presents the initial results contrasting the cross section and fixed effects estimations. The fifth section presents extensions focusing on the role of job security and using measures of life satisfaction. The sixth section presents the conclusion.

II. FLEXIBLE CONTRACTS AND JOB SATISFACTION: THEORY AND EVIDENCE

Flexible employment contracts have become increasingly prevalent among the Organisation of Economic Cooperation and Development countries (Mangan 2000). (2) This increasing prevalence reflects changes in labor market regulation, technological change, and increasing female labor force participation. Past evidence suggests that flexible employment contracts are associated with lower levels of employer provided training (Arulampalam and Booth 1998; Draca and Green 2004), higher risk of social exclusion (D'Addio and Rosholm 2005), lower wages in the United Kingdom (Booth et al. 2002), and increased job insecurity (Blanchard and Landier 2002). On the other hand, flexible employment contracts may present a means (a "stepping stone") into permanent employment both in general (Addison and Surfield 2006; Guell and Petrongolo 2001) and via promotion within the firm (Green and Leeves 2004). In addition, increased employment flexibility may lead to overall higher employment and participation rates (Lazear 1990), serve as a critical bridge for those displaced by large-scale plant closing or layoffs (Farber 1999), and appeal to workers who desire flexible schedules (Morris and Vekker 2001).

The main theoretical point of this section is that in a competitive labor market, flexible contracts may be expected to generate offsetting benefits for the workers who take them. Moreover, we recognize the stepping-stone aspect as one of those benefits for those workers who desire permanent employment. (3) In an imperfect labor market in which search takes time, workers may take a job they dislike in order to have easier access to a desired permanent job. That easier access represents a benefit that may also be related to increased wages, more preferable hours or terms, improvements in the work itself, or the freedom to pursue activities outside of work. Critically, examining this theoretical point requires accounting for worker heterogeneity in job satisfaction. In this context, as in others, the workers in flexible contracts may retain individual unmeasured characteristics that differ from those not in flexible contracts and which influence outcomes. (4)

The basic economics of flexibility focuses on the coordination of worker effort. Deardorff and Stafford (1976) make clear that both firms and workers have preferences over the direction of this effort. The firm prefers that workers be flexible allowing it to coordinate effort across workers in the cheapest fashion (e.g., having all workers show up for the same shift with on-call workers to fill absences). On the other hand, workers prefer that the firm be flexible allowing them to work when it best fits their schedules (yields the most utility). Indeed, the term flexibility has been used to characterize both of these contract extremes. When the firm is being flexible, it is often identified as providing a family-friendly work practice such as "flextime" (Heywood et al. 2007). Yet, when the worker is being flexible as in short intensive hires or agency relationships, it is identified as a "flexible staffing arrangement" (Gramm and Schnell 2001; Houseman 2001). The probability that the firm's cost minimizing work arrangement and the workers' utility maximizing work arrangement coincide is essentially zero. (5) Thus, competition in product and labor markets should generate a higher wage if the contract more closely mirrors that desired by the firm and a lower wage if the contract more closely mirrors that desired by workers.

Given heterogeneity in the cost for firms to provide flexibility to workers and heterogeneity in value of that flexibility to workers, a hedonic equilibrium should develop. Employers with higher costs in providing workers flexibility retain flexibility for themselves (flexible staffing arrangements) and pay higher wages attracting the workers who value flexibility less (Duncan and Stafford 1980). Those employers with lower costs provide staffing arrangements that are more beneficial to workers and pay lower wages. Thus, compensating earnings or other differences should emerge that offset the disadvantage to workers of flexible staffing.

This prediction receives support from a variety of empirical studies. Both Moretti (2000) and Del Bono and Weber (2008) show that otherwise equal workers earn significantly higher wages when working on seasonal jobs compared with similar permanent jobs. De Graaf-Zijl (2005b) confirms a positive compensating wage differential for on-call workers in the Netherlands. Such findings fit with evidence that workers are willing to pay for reduced unemployment risk (Van Ommeren and Hazans 2007). They also fit with studies of family-friendly work practices. Baughman et al. (2003) show that firms providing less scheduling flexibility for employees pay higher wages. Heywood et al. (2007) confirm sizable negative wage differentials both for more generous leave policies and for choice over working hours. Thus, when the firm retains flexibility in assigning work effort, wages are higher, and when workers gain favorable flexible arrangements, wages are lower. Finally, although workers may dislike the increased job insecurity associated with flexible contracts (Theodossiou and Vasileio 2007), the earnings required to encourage a worker into such contract may tend to equalize. This receives indirect empirical support from Abowd and Ashenfelter (1981), Li (1986), Heywood (1989), and Assaad and Tunali (2002) who each show that higher unemployment risk is compensated for with higher earnings.

Although such evidence does not suggest that equalizing differences should be taken for granted, it raises the possibility that job satisfaction, as a measure of on-the-job utility, need not be lower in flexible staffing contracts. Polivka (1996) shows that many workers in contingent jobs express a preference for such jobs. Also, the management literature finds that workers express greater job satisfaction when they view their contingent work as a choice rather than resulting from a lack of alternatives (Connelly and Gallagher 2004; Ellingson et al. 1998; Krausz et al. 1995). Yet, if workers in flexible staffing contracts are not able to find alternative contracts and are somehow crowded into a limited labor market that consists of only flexible contracts, equalizing differences may not emerge and job satisfaction could be persistently lower. We note that subjective satisfaction data have been used to test for compensating differences in a variety of contexts including, but not limited to, the labor market (Clark 1996; Cornelissen 2009; Poggi 2007; Stutzer and Frey 2008). Yet, beyond informing the theory, a finding of consistently lower job satisfaction would be of interest in its own right as lower job satisfaction is associated with the intention to quit a worker's current employment situation (Antecol arid Cobb-Clark 2006, 2009; Bockerman and Ilmakunnas 2009; Clark 2001).

Finally, we redress a sense in some policy circles that economics has been too fixated on the benefits of flexible contracts to firms without considering the position of workers. Thus, Guest et al. (2007) state that "much of the research and policy on new forms of employment has been dominated by labor economists who tend to under-emphasise the subjective expectations and the experiences of employees." We use just such experiences of employees to test the general prediction that labor markets are sufficiently competitive that the net employee benefits associated with flexible staffing arrangements tend to equalize with those associated with more traditional contracts.

III. DATA AND METHODOLOGY

The data used in this article are drawn from the British Household Panel Survey (BHPS). The BHPS is a nationally representative sample that each year interviews approximately 10,000 individuals from roughly 5,500 households. We use the waves of the BHPS corresponding to 1999-2004, as earlier waves did not contain detailed information on types of flexible employment contracts. (6) Within these waves, we identify those with a fixed term contract, those who work for a temporary agency, and those with other flexible contracts including casual workers, seasonal workers, and others. Appendix Table Al presents summary statistics for males and females separately. Briefly, women are more likely to be employed under flexible contracts, although the gender differences for some contract types, such as agency-based work, are not large.

In Appendix Table A2, we provide summary statistics for selected covariates split according to the contract type. Across a number of dimensions, workers on fixed term contracts are broadly comparable to permanent employees. Other flexible workers have markedly lower average weekly wages and are less likely to be unionized, hold a position with a managerial or supervisory role, or work in a large firm when compared with permanent employees. Agency workers are the youngest.

All job satisfaction questions in the BHPS are reported on a 7-value Likert scale, 1 being the least satisfied, 7 the most satisfied. At different times, a variety of job satisfaction questions have been included in the BHPS, but for the period in which the more detailed flexible contract type information is available, five job satisfaction questions are available. These are overall job satisfaction, satisfaction with pay, satisfaction with hours worked, satisfaction with job security, and satisfaction with the work itself. We restrict our sample to those individuals aged 20-65 and exclude the self-employed and those with missing data. This yields an unbalanced panel of 11,433 individuals.

Table 1 presents the mean satisfaction level for overall satisfaction and each of the four dimensions of job satisfaction. It does so for workers on permanent contracts and each of the flexible contracts. As the averages make clear, the workers on permanent contracts do not routinely report the greatest satisfaction. Out of the four contract types, they rank second in satisfaction with pay, third in satisfaction with hours, and third in satisfaction with the work itself. Workers on permanent contract do rank first in satisfaction with job security, and their advantage in satisfaction in this dimension is enormous.

Following past research, the values of job satisfaction are fitted to the cumulative normal distribution through ordered probit estimates (see Clark and Oswald 1996; Clark 1997 among many others). The ordered probit estimation follows appropriately when the dependent variable has a natural ordering, such as from least to most satisfied (see McKelvey and Zavoina 1975 for details) and can be used to predict the probability of reporting each value for job satisfaction for variation in the values of the independent variables.

IV. INITIAL EVIDENCE

This section presents initial estimates of the relationships between contract type and job satisfaction. Throughout the article estimates are presented separately for males and females following from both the routine finding of separate job satisfaction regimes for men and women (Clark 1997) and from tests within our own sample rejecting the hypothesis of a common set of coefficients.

Table 2 presents pooled ordered probit estimates of the impact of flexible employment contracts on job satisfaction with the errors clustered by individual. Model 1 includes standard controls for personal characteristics, but allows all job characteristics including earnings to vary. (7) Fixed term contracts provide insignificantly different job satisfaction compared with permanent contracts. Agency contracts provide significantly less satisfaction, whereas other flexible contracts are associated with lower job satisfaction for men but not for women. Thus, in this simple specification, the role of flexible contracts is broadly negative but mixed, suggesting that in some cases other job characteristics including earnings may vary to compensate if there are undesirable characteristics.

We next introduce a range of job characteristics typically included in the estimation of job satisfaction. Standard controls included are tenure, usual hours, usual overtime, log wage, union membership, public sector employment, firm size, and whether the employee has a managerial or supervisory role. We also include other valuable controls available in the BHPS: employer provided pension, employer provided training, annual pay increments, controls for night shift and shift work, flexitime, annualized hours, term time work only, and job sharing. Again for brevity we do not report these estimates and they are available on request. (8) The estimates suggest a stronger negative pattern. Instead of only the coefficient on agency work being significant for women, all three types of flexible contracts take highly significant coefficients. This difference between the estimates in Models 1 and 2 would be anticipated if other characteristics compensate for undesirable aspects of flexible contracts. In other words, once hours, earnings, and a host of job characteristics are held constant, flexible contracts appear less desirable but allowing them to vary they are not less desirable. (9)

Although much of our emphasis will be showing that these patterns do not survive accounting for worker fixed effects, it is worth briefly pointing out the magnitudes of the effects. One possibility is to present the marginal effect on the probability of being in any particular category of satisfaction and these are available upon request. As an alternative, we present an implicit compensating wage differential. Following the tradition from at least Clark (1996), we project the increase in the log wage needed to exactly offset an increase in the probability of being on a flexible contract. In particular, the third entry in columns 3 and 4 of Table 2 show the increase in log wages needed to exactly offset a doubling in the sample probability of being in each of the types of flexible contracts. Thus, doubling the probability of being a male on a fixed term contract can be offset by an increase of 0.020 in the log wage, whereas doubling the probability of being in agency work requires an increase of 0.045 in the log wage. (10) The estimates for women are much larger but not because the estimates on flexible contracts are larger. Instead, the coefficient on log wages is much smaller for women and in many estimates fails to reach significance. This smaller coefficient has been routinely found by others and has caused Bender et al. (2005) to suggest that women do not value earnings to the same extent as men.

Critically, workers are likely to non-randomly sort into flexible contracts. Hence, the estimates we have been discussing may be biased by unobservable characteristics that influence both the propensity to be in flexible working contracts and the level of job satisfaction. At an extreme, inherently unsatisfied workers may sort into flexible contracts lowering the apparent job satisfaction. Alternatively, unmeasured worker characteristics such as lower initiative or ability may be correlated both with lower job satisfaction and with working in flexible contracts. (11) We investigate these possibilities by re-estimating individual fixed effects ordered probit versions of the models reported in Table 3 using a routine dedicated to this purpose in Limdep 8.0. (12) Again, the full results are available from the authors.

The estimates now depend only on the variance within workers across years. They follow from observing a given worker changing status into and out of flexible contracts and examining the change in job satisfaction. Thus, characteristics that do not change, such as race and gender, play no role in the estimates. Nonetheless, the influences of the remaining characteristics continue to differ by gender. For males, the estimates suggest that the negative effects of flexible contracts are largely eliminated. The failure to find statistical significance (with one exception) results from both the anticipated increase in standard errors and substantial declines in the point estimates. Indeed, one of the three coefficients now takes a positive sign. Similarly, the earlier suggestion that females on flexible contracts have dramatically lower job satisfaction is not supported by the fixed effect estimates. Instead of the three highly significant coefficients, only other flexible contract emerges with a weakly significant coefficient. In short, looking at Table 3, the earlier evidence of a strong negative effect of flexible contracts now emerges as much weaker. (13)

The pattern shown in Table 3 is not the result of a selected sample being used to obtain the fixed effect estimates. Critically, the same pattern of statistical significance emerges as did in Table 2 if one limits the sample to workers showing variation in contract status and so determining the fixed effect estimates. A related concern is that there are unmeasured factors correlated with changing contract type that also correlate with changes in job satisfaction. Thus, it may be that those leaving permanent jobs have unusually poor permanent jobs and that those leaving more flexible jobs have unusual good flexible jobs (those with a chance for advancement). This would potentially bias downward estimates based on movers. Although the sample of movers looks similar in a cross-sectional estimate, we tried to directly investigate this particular conjecture. In a sample of only workers in permanent jobs, we found modestly lower job satisfaction among those who would move to temporary jobs. Yet, in a sample of workers only in temporary jobs, those who would move to permanent jobs were no more satisfied. These results are available from the authors on request.

One might also be concerned that a small number of movers between contract types yields imprecise estimates and large standard errors. Appendix Table A3 shows that the estimates are based on over 2,000 individual observations that move between flexible and permanent employment and that the transitions in each direction are roughly similar in number. Importantly, the sample of those on flexible contracts largely consists of movers. Appendix Table A4 presents the observed duration in each type of contract, 14 Essentially no workers are observed in their flexible contract category over all 6 yr. Instead, durations of a single year are the vast majority of those observed in flexible contracts. The same is not true for permanent contracts. Recognizing that those on flexible contracts may be more likely to also transition in and out of the labor force, we searched for workers who are only observed in a flexible contract. Thus, a worker observed in employment in only one of the 6 yr but was in a flexible contract would be included in this measure. The final row of Appendix Table A4 shows there are only a handful of such workers even using this more generous measure. (15) In sum, it is hard to suggest that a large number of workers are persistently segregated into flexible contracts.

Nonetheless, as a last check, we reestimated our models using one aggregated variable, flexible contracts, in an effort to improve precision. The resulting fixed effect estimates (available from the authors) continue to show that flexible contracts have no effect on male's job satisfaction (point estimates between -0.03 to 0.02). They also continue to show some support for a negative effect of flexible contracts on female job satisfaction (from -0.133 and just barely significant at the 10% level in Model 1 to -0.119 and not significant in Model 2). Although not unequivocal, the sum of our investigations leaves us reasonably confident in the fixed effect estimates and the resulting diminution of the negative influence of flexible contracts on overall job satisfaction.

Table 4 examines the dimensions of job satisfaction controlling for individual fixed effects. In three of the dimensions of job satisfaction, the influence of flexible contracts appears to be broadly positive. In estimating satisfaction with pay, all six coefficients are positive and two are statistically significant. In estimating satisfaction with hours, five of the six coefficients are positive and four of the five are statistically significant. In estimating satisfaction with the work itself, again, five of the six coefficients are positive with two of the five being statistically significant. Across all the 18 estimates for these three dimensions, the only negative and significant coefficient is that for other flexible contracts in the female satisfaction with hours estimate. In short, there remains a broad pattern suggesting, if anything, a general positive influence of flexible contracts on these dimensions of jobs satisfaction.

This broad pattern contrasts dramatically with the routinely large and negative coefficients on all six estimates of satisfaction with job security. Each coefficient emerges as statistically significant both with and without controlling for fixed effects. It seems very clear that flexible contracts of any type are associated with reduced satisfaction with job security. Following the methodology used earlier, we can identify the magnitude of the large role played by flexible contracts. Log earnings remain a positive and significant determinant of satisfaction with job security, and we again present how much would earnings need to increase to compensate for a doubling in the probability of being in a flexible contract. For males, the increase in log earnings is 0.094 for other flexible contracts, 0.146 for agency contracts, and 0.265 for fixed term contracts. As before, the female earning differentials are about half again as large because of a smaller coefficient on log earnings. The fact that these are much larger than those in Table 2 is yet another indicator that other aspects of these jobs seem to offset the obviously very large disadvantage of insecurity. In the next section, we pursue this by providing evidence on the importance of job security as a component of overall job satisfaction.

V. EXTENSIONS

This section provides two extensions to the results already provided. First, we examine in detail the relationship between flexible contracts and satisfaction with job security. We present estimates suggesting that if flexible contract jobs had the same security as permanent jobs, they would be largely preferred to permanent jobs. This finding is consistent with the suggestion of equalizing differences. Second, we explore the issue of whether some of the potential benefits workers see in flexible contracts accrue outside the realm of work by examining overall life satisfaction. These estimates suggest that flexible contracts do not diminish life satisfaction among the group of employed workers.

A. Flexible Contracts and Satisfaction with Security

A typical way to determine the importance of various job dimensions in overall job satisfaction includes the dimensions of satisfaction into an estimate of overall job satisfaction. Clark (1997) used roughly such a methodology to show that men and women differed in their valuation of job dimensions. In examining Dutch workers, De Graaf-Zijl (2005a) follows work by Van Praag et al. (2003) estimating overall job satisfaction as a composite of various dimensions of job satisfaction. In her estimates, she identifies job content (the work itself) as contributing the most to overall job satisfaction and finds that job security contributes the least to overall job satisfaction. Intermediate positions were held by satisfaction with pay, hours, working conditions, working times, and commuting distance. Examining the correlations between domains of satisfaction has also been used to explore the "spill-over hypothesis" in psychology that high or low satisfaction in one domain influences satisfaction in other domains (Wilensky 1960).

We return to our estimates of overall job satisfaction sequentially adding a single dimension of satisfaction (satisfaction with pay, with hours, etc.) as a control. This generates four estimates each with a different dimension added. We emphasize that the object is to control for satisfaction with that dimension to see what independent variation remains to be explained by the critical flexible contract variables. We, like those who have previously estimated similar models, recognize that the dimensions of satisfaction and overall satisfaction are surely endogenous and determined by other controls. We are not interested in the point estimate on the dimension of job satisfaction but what its inclusion does to the role of contract types.

The fundamental result is summarized in Table 5. Satisfaction with job security is included in the full specification without fixed effects. The inclusion causes a dramatic change from Table 2 with each of the three types of flexible working arrangements contracts significant positive determinants of overall job satisfaction for both genders. Moreover, this result emerges from either Model I or II and either with or without worker fixed effects. Equally important, this result is not simply a function of including any dimension of job satisfaction. It is unique to job security. Including any of the other dimensions of job satisfaction does not change the pattern shown in Table 2. There remains a predominance of negative coefficients on the flexible contract variables, several of which are statistically significant for each gender. (16)

The fundamental point is that lower satisfaction with job security generates the lower overall satisfaction observed in the estimates that do not control for fixed effects. This dramatically differs from the Dutch results discussed earlier in which satisfaction with job security played little or no role in generating the lower satisfaction observed in flexible contracts. Similarly, there is no evidence in our UK data that dissatisfaction with the work itself generates overall dissatisfaction. Including this dimension of satisfaction as a determinant of overall satisfaction does not dislodge the negative influence of flexible contracts as would be implied by the Dutch results.

Thus, the fixed effects results are indicative of two related possibilities. First, the absence of strongly lower overall job satisfaction in the fixed effects estimate (Table 4) suggests sorting. Workers with lower inherent job satisfaction appear sorted into flexible contracts. Although the extent of this sorting is not sufficient to eliminate the influence of flexible contracts on satisfaction with job security, it is sufficient to eliminate their influence on overall job satisfaction. This remains broadly consistent with the theory of equalizing differences. Second, once accounting for this sorting, flexible contracts lower satisfaction with job security but tend to have a broadly positive influence on other dimensions of satisfaction (Table 4). This pattern is confirmed by recognizing that when satisfaction with job security is held constant, flexible contracts have a positive influence on overall job satisfaction (Table 5). We note again that to the extent flexible jobs provide stepping stones to permanent jobs, otherwise less desirable jobs may be associated with higher job satisfaction for workers interested in permanent jobs.

B. Flexible Contracts and Life Satisfaction

The consequences of flexible contracts can extend beyond their influence in changing on-the-job utility. Workers may trade off lower job satisfaction for higher satisfaction in other aspects of life such as fulfilling family responsibilities, undertaking education, or arranging leisure activities. We examine this by estimating the impact of flexible employment contracts on individuals' overall life satisfaction. The life satisfaction question in the BHPS is "How satisfied/dissatisfied are you with your life overall?" to which respondents provide a 1 to 7 Likert scale response, where 7 is the highest satisfaction. This variable has been used extensively in the literature on happiness and life satisfaction (Clark 2006; Oswald and Powdthavee 2008) to capture the consequences of major labor market changes such as unemployment, illness, and retirement.

We estimate two broad groups of specifications. First, we estimate ordered probits of life satisfaction for all workers aged 20-65 in the BHPS, where the control variables are those in Table 2. Second, we estimate ordered probits of life satisfaction for the sample of all respondents (including the unemployed and those out of the labor market), where the controls are the same, and also include an indicator for permanent employment. We estimate these with and without individual fixed effects.

As the top panel in Table 6 shows, the cross-sectional estimates reveal a wide variety of negative partial correlations between flexible contracts and life satisfaction. This might suggest that having a flexible contract lowers life satisfaction. Yet, controlling for the worker fixed effects causes every significant coefficient to vanish and reveals more positive coefficients than negative. This suggests that the satisfaction of workers moving between contracts is largely unaffected by the movement.

The results in the second panel show that for the sample of all respondents, permanent employment is associated with a large increase in life satisfaction, an increase that is equally evident in both the cross section and fixed effect estimates. The cross-sectional results show that both men and women in agency contracts report lower life satisfaction. The fixed effects estimate causes the male coefficient to fall in half and no longer be significant while it causes the female coefficient to switch sign revealing a large positive increment associated with agency work. The female coefficient for other flexible contracts is now also positive and statistically significant. Although the fixed effect estimates show a significant negative coefficient for males on other flexible contracts, the overall pattern continues to suggest the role of equalizing differences.

VI. CONCLUSION AND DISCUSSION

We began with a suggestion that if most workers have a choice between permanent and flexible contracts, equalizing differences may create roughly similar on-the-job utility between the two types of contracts. In a parsimonious pooled cross section that included only basic worker characteristics, agency work was associated with lower overall satisfaction for both genders and other flexible contracts associated with lower overall satisfaction for men. As more controls were added to these estimates, the negative role of flexible contracts appeared stronger.

A second set of specifications controlled for individual worker fixed effects. First, there was far less evidence of a negative influence on overall job satisfaction from flexible contracts. Only other flexible contracts had a weakly significant negative influence and this was only for women. Some coefficients were positive and the overwhelming majority were smaller than in the pooled estimate and insignificant. Second, the fixed effect estimates run separately by dimension suggest that imprecision is not the issue. Those estimates show that flexible contracts had broadly positive influences on three of the tour dimensions of job satisfaction and a sharply negative influence on satisfaction on job security. In other words, the lack of a persuasive result in the overall satisfaction resulted from offsetting influences on the disaggregate dimensions. This was further supported by evidence that holding constant satisfaction with job security, all three types of flexible contracts had positive influences on overall job satisfaction for each gender. Finally, we showed that flexible contracts are generally not associated with diminished life satisfaction in estimates that control for worker or respondent fixed effects.

Thus, at a minimum, we think it is too early to dismiss the notion that equalizing differences may exist between permanent and flexible contracts. Obviously, more work could be done. First, it is surely the case that the type of contract represents a choice both by firms to offer them and by workers to accept them. Accounting for this choice proves difficult. In our case we would have a choice across four sectors (permanent, fixed term, agency, and other) that would need to be imbedded in an ordered probit estimation of job satisfaction. One might still be worried about worker fixed effects and one would, even then, still have a reduced form of the simultaneous worker and firm choice processes. Second, we have not identified which characteristics might play an equalizing role. Simple experiments with changes in specification do not identify immediate candidates. We removed wages from many of our later estimates and the results did not markedly change. We note that the BHPS does not have a particular rich vector of variables describing physical working conditions and to the extent such conditions play a role remains unknown. Although more detailed experiments may be useful, we emphasize that much of the statistical traction comes from accounting for worker fixed effects. Third, although we have suggested that our results may differ from those in more regulated labor markets, further comparative studies are needed to draw a firm conclusion. Despite these limitations, it remains the case that in our preferred fixed effect estimates, offsetting influences on the dimensions of job satisfaction emerge and overall satisfaction (either job or life) are not routinely lower in flexible contracts.

ABBREVIATIONS

BHPS: British Household Panel Survey

APPENDIX

TABLE A1
Summary Statistics

Variable Male Female

Fixed term contract 0.019 0.027
Agency work 0.007 0.009
Other flexible contract 0.010 0.018
Age (yr) 39.196 39.443
Tenure (yr) 0.200 10.382
Married 0.596 0.577
Dependant child 0.005 0.317
A level 0.220 0.191
Diploma 0.092 0.076
Degree 0.134 0.142
Higher degree 0.042 0.032
Log pay 6.667 6.371
Normal hours 39.646 30.173
Overtime hours 3.990 2.164
Union member 0.285 0.321
Public sector 0.232 0.450
Manager/supervisor 0.415 0.320
Firm size
 50-99 workers 0.256 0.269
 100-499 workers 0.249 0.186
 500+ workers 0.175 0.158
Observations 19,007 19,782

Source: BHPS 1999-2004, employees aged 20-65.

TABLE A2
Selected Summary Statistics by Contract Type

 Permanent Fixed Term

 Male Female Male Female

Age 38.845 39.189 36.976 37.069
Tenure 10.743 10.722 7.346 8.211
Log weekly pay 6.674 6.385 6.484 6.295
Usual hours 39.542 31.182 36.788 27.917
Union member 0.317 0.363 0.185 0.299
Public sector 0.232 0.452 0.424 0.764
Manager/supervisor 0.426 0.349 0.224 0.175

Firm size

0-49 workers 0.295 0.355 0.296 0.330
50-100 workers 0.260 0.276 0.203 0.294
100-499 workers 0.261 0.200 0.257 0.146
500+ workers 0.184 0.170 0.245 0.230
Observations 18,568 18,998 335 521

 Agency Work Other Flexible Contract

 Male Female Male Female

Age 35.431 35.783 39.187 38.537
Tenure 5.723 6.075 9.293 8.627
Log weekly pay 5.473 5.434 5.662 5.463
Usual hours 38.810 32.491 34.120 22.753
Union member 0.080 0.161 0.160 0.205
Public sector 0.153 0.255 0.267 0.541
Manager/supervisor 0.058 0.075 0.240 0.131

Firm size

0-49 workers 0.190 0.248 0.527 0.474
50-100 workers 0.372 0.286 0.173 0.328
100-499 workers 0.277 0.211 0.207 0.138
500+ workers 0.161 0.255 0.093 0.060
Observations 137 161 150 268

Source: BHPS 1999-2004, employees aged 20-65.

TABLE A3
Yearly Transitions In and Out of Permanent Employment

 Year of Transition

 1999-2000 2000-2001 2001-2002

FTC to permanent 101 102 105
Permanent to FTC 96 100 87
Agency to permanent 36 35 36
Permanent to agency 38 46 49
Other flexible to permanent 89 62 94
Permanent to other flexible 56 60 86

 Year of Transition

 2002-2003 2003-2004 Total

FTC to permanent 82 93 483
Permanent to FTC 98 75 456
Agency to permanent 35 30 172
Permanent to agency 27 29 189
Other flexible to permanent 90 74 409
Permanent to other flexible 72 60 334

Source: BHPS 1999-2004, employees aged 20-65.

TABLE A4
Observed Duration in Contract Type, BHPS, 1999-2004

 Contract Type

Years FTC Agency Other flexible Permanent

1 306 129 210 2479
2 59 18 15 1694
3 24 2 4 1575
4 4 1 0 1510
5 3 1 0 1174
6 2 0 0 2223
Workers observed in only 38 21 19 5135
 the one contract type

Notes: BHPS 1999-2004, employees aged 20-65. These are the number of
observed duration spells of from 1 to 6 yr and the sum of workers
observed only within a particular contract type.

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(1.) Satisfaction with the job has also been seen as one of the major "domains" that together with satisfaction with leisure, health, and others aggregate to an overall measure of subjective well-being (Van Praag et al. 2003).

(2.) In the United Kingdom, the growth in flexible contracts has been concentrated in the rise of agency work (Forde and Slater 2005).

(3.) The concern with stepping stones comes from the job search perspective in which a critical issue is whether the taking of flexible employment increases or decreases the probability of eventually taking permanent employment. One recent study suggests that flexible employment neither increases the chances for permanent employment nor increases the chance for future unemployment and as such simply represents "access to work" for those who might otherwise be unemployed (Kvasnicka 2009).

(4.) For instance, Addison and Surfield (2009) show that the advantage in job continuity of those on permanent contracts versus flexible contracts shrinks dramatically after accounting for such individual heterogeneity.

(5.) This results from the differences in the distribution of desires across firms and workers and by search costs that make sorting imperfect. See Duncan and Stafford (1980) for more details.

(6.) Prior to 1999, flexible contracts were overly aggregated not allowing variations within subgroups of flexible contracts. For instance, fixed term contracts and agency workers were grouped together.

(7.) Specifically, we control for age, marital status, presence of a dependent child, and education. Covariate estimates for these follow standard patterns previously reported (Clark 1997) and are available on request.

(8.) Estimates of the association between job characteristics and job satisfaction broadly conform to the signs and significance reported in numerous other studies using the BHPS (Clark and Oswald 1996; Green and Heywood 2008).

(9.) We note that dividing our sample by age shows the results to be remarkably robust. As an illustration, the pattern of significance in Table 2 is repeated in a subsample of 18-to 35-yr olds.

(10.) We imagine a change in the probability of a flexible contract equal to the existing proportions given in Appendix Table A1. This change is multiplied by the coefficient on the particular flexible contract from columns 3 and 4 of Table 2 and divided by the coefficient on the log wage variable to provide our estimated change in log earnings.

(11.) Existing US evidence suggests that unmeasured worker heterogeneity largely accounts for the apparent lower earnings of flexible contract workers (Addison and Surfield 2005).

(12.) The Limdep routine is "fixed effects ordered choice models, E.18.5.1" and its advantages and limitations are discussed in Greene (2001).

(13.) We note that in simple wage equations controlling for individual characteristics, all three types of flexible contracts take large and significant negative coefficients. Although we recognize the identification difficulties in directly estimating compensating differentials, accounting for fixed effects causes a typical reduction by as much as half in the size of these coefficients. These estimates are available from the authors.

(14.) We emphasize that these are observed durations as the true expected duration may differ because our sample period truncates duration. For example, those observed in a particular contract category in the first sample year may have actually been in that category for several years prior to sample period.

(15.) We explored whether the job satisfaction of the relatively few workers observed only in flexible contracts differs from those observed in flexible contracts but who also have periods in permanent jobs. We could uncover no compelling pattern of differences across the different job satisfaction measures.

(16.) These three additional estimates are available from the authors upon request.

COLIN P. GREEN and JOHN S. HEYWOOD *

* We would like to thank Uwe Jirjahn and seminar participants at the University of Hanover, Lingnan University, and the University of Trier for helpful comments on earlier drafts. C.G. is grateful to the Bowland Charitable Trust for their ongoing financial support.

Green: Department of Economics, Lancaster University, Lancaster, LAI 4YT, UK. Phone (44) 1524 594667, E-mail [email protected]

Heywood: Department of Economics, University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, W1 53201. Phone 1-414-229-4310, Fax 1-414-229-5915, E-mail [email protected]

doi: 10.1111/j.1465-7295.2010.00291.x

TABLE 1
Job Satisfaction and Temporary Contract Type (Mean Values on 7-Point
Likert Scale)

 Overall Pay Hours

Permanent (41902) 5.364 4.935 5.207
Fixed term contract (1028) 5.293 5.064 5.367
Temporary agency (378) 4.682 4.513 5.126
Other flexible contract (603) 5.298 4.860 5.349
Observations 43,911

 Work Security

Permanent (41902) 5.436 5.555
Fixed term contract (1028) 5.514 3.656
Temporary agency (378) 4.845 3.207
Other flexible contract (603) 5.513 3.778
Observations

Source: BHPS 1999-2004, employees aged 20-65.

TABLE 2
Job Satisfaction and Flexible Working Arrangements: Ordered Probit
Estimates

 Male (I) Female (II)

Fixed term contract -0.068 -0.062
 [0.064] [0.051]

Agency work -0.581 * -0.397 *
 [0.093] [0.089]

Other flexible contract -0.189 ** -0.107
 [0.095] [0.071]

Personal characteristics [check] [check]

Job characteristics

Log likelihood -28645.5 -27951.9

Observations 19,048 19,782

 Male (II) Female (II)

Fixed term contract -0.031 -0.146 *
 [0.066] [0.053]
 (0.020) (0.223)

Agency work -0.375 * -0.319 *
 [0.095] [0.090]
 (0.0-15) (0.172)

Other flexible contract -0.133 -0.218 *
 [0.097] [0.073]
 (0.026) (0.226)

Personal characteristics [check] [check]

Job characteristics [check] [check]

Log likelihood -28348.044 -27678.8

Observations 19,048 19,782

Notes: 1999-2004 BHPS employees aged 20-65. Controls included in all
estimates but not identified in the text; region and year dummies.
Personal characteristics include age, marital status, presence of a
dependent child, and education level. Job characteristics include
tenure, usual hours, usual overtime, log wage, union membership,
public sector employment, firm size, whether the employee has a
managerial or supervisory role, employer provided pension, employer
provided training, annual pay increments, controls for night shift and
shift work, flexitime, annualized hours, term time work only, and job
sharing. Robust standard errors clustered at the individual level are
shown in square brackets. The implicit compensating differential in
log wages is shown in parentheses.

*, **, and *** indicate statistical significance at 1%, 5%, and 10%
level, respectively.

TABLE 3
Job Satisfaction and Flexible Working Arrangements: Fixed Effect
Ordered Probit Estimates

 Male (I) Female (I)

Fixed term contract 0.056 -0.080
 [0.098] [0.080]

Agency work -0.342 * -0.184
 [0.189] [0.137]

Other flexible contract -0.118 -0.191 ***
 [0.126] [0.105]

Personal characteristics [check] [check]

Job characteristics

Log likelihood -199143.3 -19159.4

Observations 19,048 19,782

 Male (II) Female (II)

Fixed term contract 0.062 -0.079
 [0.099] [0.080]

Agency work -0.161 -0.048
 [0.142] [0.141]

Other flexible contract -0.070 -0.194 ***
 [0.128] [0.106]

Personal characteristics [check] [check]

Job characteristics [check] [check]

Log likelihood -19784.2 -19037.9

Observations 19,048 19,782

Notes: 1999-2004 BHPS employees aged 20-65. All other controls are as
in Table 2. Standard errors are shown in square brackets.

*, **, and *** indicate statistical significance at 1%, 5%, and 10%
level, respectively.

TABLE 4
Dimensions of Job Satisfaction: Fixed Effect Ordered Probit Estimates

 Male Female

 Pay

Fixed term contract 0.383 * 0.400 *
 [0.095] [0.095]

Agency work 0.120 0.16
 [0.139] [0.140]

Other flexible contract 0.095 0.126
 [0.123] [0.152]

Log likelihood -22033.990 -22039.93

 Security

Fixed term contract -1.242 * -1.331 *
 [0.095] [0.076]

Agency work -1.676 * -1.664 *
 [0.142] [0.144]

Other flexible contract -1.672 * - 1.622
 [0.159] [0.125]

Log likelihood -21024.91 -20096.40

Observations 19,048 19,782

 Male Female

 Hours

Fixed term contract 0.296 * 0.149 **
 [0.096] [0.077]

Agency work 0.374 ** 0.222
 [0.143] [0.140]

Other flexible contract 0.400 ** -0.267 **
 [0.156] [0.127]

Log likelihood -21813.670 -21313.730

 Work itself

Fixed term contract 0.222 * 0.121
 [0.098] [0.081]

Agency work 0.132 -0.126
 [0.143] [0.144]

Other flexible contract 0.547 * 0.001
 [0.158] [0.132]

Log likelihood -20044.230 -19837.530

Observations

Notes: 1999-2004 BHPS employees aged 20-65. All other controls are as
in columns 3 and 4 of Table 2. Standard errors are shown in square
brackets.

*, **, and *** indicate statistical significance at 1%, 5%, and 10%
level, respectively.

TABLE 5
Job Satisfaction Controlling for Satisfaction with Job Security:
Ordered Probit Estimates

 Pooled

 Male Female

Fixed term contract 0.585 * 0.517 *
 [0.066] [0.057]

Agency work 0.394 * 0.311 *
 [0.109] [0.093]

Other flexible contract 0.509 * 0.324 *
 [0.105] [0.081]

Log likelihood -26253.595 -26144.749

Observations 19,007 19,782

 Fixed Effects

 Male Female

Fixed term contract 0.637 * 0.432 *
 [0.103] [0.084]

Agency work 0.647 * 0.562 *
 [0.145] [0.147]

Other flexible contract 0.989 * 0.435 *
 [0.167] [0.136]

Log likelihood -18580.53 -18100.05

Observations

Notes: 1999-2004 BHPS employees aged 20-65. All other controls are as
in columns 3 and 4 of Table 2. Robust standard errors clustered at the
individual level in square brackets for the pooled estimates.

*, **, and *** indicate statistical significance at 1%, 5%, and 10%
level, respectively.

TABLE 6
Life Satisfaction and Flexible Employment Contracts: Ordered Probit
Estimates

 Male

 Pooled Fixed Effects

Employees only

Fixed term contract -0.095 0.149
 [0.067] [0.122]

Agency work -0.229 ** 0.218
 [0.104] [0.188]

Other flexible contract -0.227 ** -0.130
 10.0971 [0.151]

Log likelihood -21637.13 -12536.75

Observations 15200

All respondents

Fixed term contract -0.004 -0.023
 [0.045] [0.072]

Agency work -0.264 * -0.130
 [0.086] [0.127]

Other flexible contract -0.070 -0.225 **
 [0.052] [0.075]

Permanent 0.216 * 0.288 *
 [0.015] [0.036]

Log likelihood -39487.07 -24159.40

Observations 25,796

 Female

 Pooled Fixed Effects

Employees only

Fixed term contract -0.157 ** 0.108
 [0.063] [0.116]

Agency work -0.369 * 0.002
 [0.099] [0.177]

Other flexible contract -0.220 * -0.208
 [0.080] [0.131]

Log likelihood -22168.83 -12885.11

Observations 15506

All respondents

Fixed term contract -0.049 0.090
 [0.042] [0.063]

Agency work -0.132 *** 0.220 **
 [0.073] [0.112]

Other flexible contract 0.041 0.166 *
 [0.043] [0.063]

Permanent 0.186 * 0.071 **
 [0.013] [0.028]

Log likelihood -48284.30 -30561.32

Observations 30,400

Notes: 1999-2004 BHPS employees aged 20-65. All other controls are as
in columns 3 and 4 of Table 2. Robust standard errors clustered at
the individual level in square brackets for the pooled estimates.

*, **, and *** indicate statistical significance at 1%, 5%, and 10%
level, respectively.