Temporary Workers Are Not Free-Riders: An Experimental Investigation

Dragone, Davide; Galeotti, Fabio; Orsini, Raimondello Working Paper Temporary Workers Are Not Free-Riders: An Experimental Investigation Quaderni - Working Paper DSE, No. 915 Provided in Cooperation with: University of Bologna, Department of Economics Suggested Citation: Dragone, Davide; Galeotti, Fabio; Orsini, Raimondello (2013) : Temporary Workers Are Not Free-Riders: An Experimental Investigation, Quaderni - Working Paper DSE, No. 915, Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE), Bologna, https://doi.org/10.6092/unibo/amsacta/3902 This Version is available at: https://hdl.handle.net/10419/159754 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/3.0/ ISSN 2282-6483 Temporary Workers Are Not Free-Riders: An Experimental Investigation Davide Dragone Fabio Galeotti Raimondello Orsini Quaderni - Working Paper DSE N°915 1 Temporary Workers Are Not Free-Riders: An Experimental Investigation1 10 December 2013 D. Dragone2, F. Galeotti3, R. Orsini4 Abstract We conduct an artefactual field experiment to study whether the individual preferences and propensity to cooperate of temporary workers differ from permanent contract workers. We find that temporary and permanent contract workers have different other-regarding preferences, but display similar contribution patterns in an anonymous Public Good Game. Students, instead, are more selfish and contribute less than temporary and permanent workers. Keywords: Temporary Worker, Decomposed Prisoner Dilemma, Dictator Game, Public Good Game, Field Experiment. JEL codes: C72, C93, D23, H41, J54 I. Introduction A temporary worker is an employee hired for a pre-determined time limit. In the last 25 years there has been a rapid diffusion of temporary employment in many industrialized countries, in particular 1 We thank Formula Servizi and Obiettivo Lavoro for their precious assistance in recruiting the experimental subjects. We thank Maria Bigoni, Marco Casari, Caterina Giannetti, Vera Negri Zamagni and the participants at the 2011 BEELab conference in Florence (Italy) for comments and suggestions. Financial support from the PRIN 2007/B8SC7A_002, the University of Bologna Strategic Project “Ethical Values and Competitiveness of Italian Cooperative Companies”, CFICEI (Centro di Formazione e Iniziativa sulla Cooperazione e l'Etica d'Impresa) and AICCON is gratefully acknowledged. The usual disclaimer applies. 2 University of Bologna, Dipartimento di Scienze Economiche, Piazza Scaravilli 2, 40126 Bologna, Italy; E-mail: davide.d[email protected] 3 University of East Anglia, School of Economics, Norwich Research Park, Norwich, NR4 7TJ, UK; E-mail: [email protected]k 4 University of Bologna, Dipartimento di Scienze Economiche, Strada Maggiore 45, 40125 Bologna, Italy; E-mail: [email protected] 2 in countries providing high levels of employment protection (Sala et al., 2012). From a firm’s perspective, temporary employment reflects the need for a flexible labor demand. Allowing for a higher turnover rate, flexible employment makes it easier for a firm to replace less productive people with more productive ones, and may as well favor the inflow of innovative ideas. On the other hand, a high turnover may hinder social cohesion and trust, and increase the probability of opportunistic behavior. Moreover, temporary employment may determine economic, psychological and social costs as temporary workers are often found to be less satisfied with their jobs; they also receive less training from the firms and are usually paid less than permanent workers (Booth et al., 2002). The recent diffusion of temporary employment has stimulated research aimed at assessing the economic and social impact of temporary work arrangements concerning, e.g., the existence of a gap in the working conditions of permanent and temporary workers, particularly in terms of working rights and training received by the firm, and the effect of wage differentials between temporary and permanent contracts (OECD, 2002), the role of temporary work as a stepping-stone towards regular employment (Ichino et al., 2008), the relationship between temporary work and job satisfaction (Booth et al., 2002), the effect of temporary status on the worker’s well-being, mental and physical health (Cuyper et al., 2008, Martinez et al., 2010, Rousseau, 1995). In this paper we investigate whether temporary and permanent workers differ in terms of propensity to cooperate and in terms of other-regarding preferences. Since these are crucial factors in affecting a worker’s productivity and performance on the job (Carpenter and Seki, 2005), our results can provide useful information for an employer who is contemplating which contractual arrangement best fits her needs. To carry out this investigation, we ran an artefactual field experiment (see Harrison and List, 2004) with three different subject pools: one made of Temporary workers, one made of Permanent workers and one of university Students. The subjects participated in a Dictator Game, a Decomposed Prisoner Dilemma and a Public Good Game. These tasks allowed us investigating the intensity of other-regarding preferences, as well as the individual propensity to cooperate, across the three different sample pools, in a controlled lab environment where we could measure the frequency and extent of opportunistic and cooperative behavior. The comparison between Temporary workers and Permanent workers is particularly interesting, as the latter pool was composed by members of a co-operative of workers. Co-ops are “autonomous associations of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly-owned and 3 democratically-controlled enterprise”,5 and they have specific institutional features that distinguish them from other firms in terms of purposes, control structures and allocation of profits. As the word co-op suggests, the importance of cooperation is one of the distinctive features of a co-op, together with the importance given to the values of self-help, self-responsibility, democracy, equality, equity and solidarity. For all these reasons, our a-priori expectation was that co-op workers would be particularly prone to cooperation, with significant and sizeable differences with respect to non-coop workers, in particular temporary workers who are not members of a co-op. Our results show that the cooperation rates of Students are similar to those reported in the literature with similar subject pools (e.g. Burlando and Guala, 2005; Croson, 1996; Andreoni, 1988). Temporary workers, instead, are significantly more cooperative and less opportunistic. In addition, they are also more other-regarding than Students and their behavior and preferences are very much similar to those of co-op Permanent workers. This is a rather surprising result because a priori we expected to obtain very different behavioral patterns when comparing Temporary workers with coop Permanent workers. Temporary workers did not know each other, and they shared very little common experiences, either in terms of education, training on the job or specialization. Moreover, the probability of meeting again in subsequent occasions is small, which makes reputation a rather weak argument for inducing cooperation in a repeated interaction perspective. On the contrary, Permanent workers knew each other and interact together on a daily basis in the same workplace. In addition, they work for the same co-operative, and are constantly exposed to the values of the institution they work for. The comparison among Temporary and Permanent (co-op) workers is a useful starting point to understand what factors drive the propensity to cooperate of workers in general, and whether the possible differences in preferences and behavior may be driven by the specific type of contractual arrangement. To the best of our knowledge this is the first paper which applies the experimental methodology to a sample of Temporary workers. Our experiment provides new evidence, as measured in a controlled lab environment, on the workers’ preferences and propensity to cooperate, and can be a useful complement to more traditional sources of information, such as those based on surveys and questionnaires (e.g. Borzaga and Depedri, 2005; Novkovic et al., 2012). We also obtain information on the preferences and propensity to cooperate of co-op workers, on which previous 5 Co-ops around the world adhere to the same seven principles: Voluntary and open membership, Democratic member control, Member economic participation, Autonomy and independence, Education, Training, and Information, Cooperation among co-operatives, Concern for community (http://ica.coop/en/what-co-op/co-operative-identity-valuesprinciples). 4 experimental investigation is surprisingly scarce. A noteworthy exception is Burks et al. (2009), who provide field experimental evidence that employees at firms that pay for performance are significantly less cooperative than those who are members of cooperatives. Finally, by comparing the behavior of workers with a sample of university Students, we contribute to the experimental literature studying the external validity of experiments employing Students as subjects (for a review, see Frechette, 2009). The paper is structured as follows. In next section we describe the three sample pools employed in the experiment. In section 3 we present the experimental design, and in section 4 we report the results. Section 5 contains a discussion of the results and Section 6 concludes. II. The subjects pools: Temporary workers, Permanent workers, and Students The subjects taking part to the experiment were recruited from three different populations: Temporary employees, Permanent employees and undergraduate Students of the University of Bologna. Temporary workers. The pool of Temporary workers that participated to the experiment was supplied by Obiettivo Lavoro (OL), a large recruitment agency that operates mainly in Italy, with branches operating also in Bolivia, Brazil, Ecuador, Poland, Romania, Paraguay and Peru. OL operates in sectors such as health care and social assistance, cleaning and logistics, construction, large scale retail, hotel, catering, and tourism, with yearly total revenue of 308 million euros (operating revenue, 2012). It manages more than 1,400,000 profiles of workers to be hired to firms or institutions demanding labor force. Originally established as a co-operative company in 1997, OL was converted into a public limited company in 2003. It has adopted an Ethics Code and in 2007 it obtained the SA8000 certification for its Corporate Responsibility practices.6 The 72 subjects which OL supplied for the experiment where Temporary workers who had never participated in an economic experiment like ours, nor had ever had relations with OL before 2003. Permanent workers. The pool of cooperative members that took part to the experiment was supplied by Formula Servizi (FS), a workers co-operative company founded in 1975, which operates in five 6 SA8000 is a global social accountability standard for decent working conditions. The standard is based on the principles of international human rights and conventions of the International Labour Organisation (ILO), which encourage management to implement sustainable systemic changes in business operations. SA8000 aims to improve the work conditions in organizations; the standard governs child or forced labor, health and safety, freedom of association and right to collective bargaining, discrimination, disciplinary practices, work hours, compensation, and management system. 5 Italian regions (mainly in Emilia Romagna, where 75% of its revenue is raised). It supplies several services, mainly in sectors such as cleaning, catering, maintenance and logistics, with yearly total revenue of 55 million euros (operating revenue, 2012) raised both with private firms (30%) and the public sector (70%). FS has obtained the SA8000 certification for its Corporate Responsibility practices in 2003, and has adopted an Ethical Code in 2012. The total number of workers in 2012 is 1892, with a prevalence of women (83%) and an average age of 47 years. Among these workers, 892 are members of the cooperative (“soci”), 890 are employees, while 110 are outsourced workers. For our experiment we recruited 84 subjects only among cooperative members, therefore choosing to focus on the most “permanent” set of workers, and we excluded both employees and outsourced staff. Students. As a benchmark, we recruited 96 students from the Forlì Campus of the University of Bologna, using the subject pools maintained through ORSEE. Although being quite different from the other two samples of workers for their educational background and age, student subjects are meant to check the conformity of our experimental results with similar existing studies which are run mainly with student subjects. III. Experimental design The experiment is composed of two stages: a classification stage and a main stage. In the classification stage subjects are required to perform three tasks which are widely employed in the experimental literature to study other-regarding preferences. The subjects first play a one-shot Dictator Game, then they play a Public Good Game to assess their conditional willingness to contribute to a public good (Strategy Method) and finally they play a Decomposed Prisoner Dilemma. In the main stage the subjects play a repeated anonymous linear Public Good Game (12 repetitions). The experiment was incentivized and fully computerized, and anonymity was guaranteed both during the game and the payment procedures.7 In the one-shot Dictator Game each subject is randomly matched with another individual, and has to decide how to divide an endowment of 30 experimental tokens between herself and her matched subject. After each subject has made her decision, a random mechanism establishes whether her proposal or the proposal of the counterpart is implemented. Subjects who give less than 10 tokens 7 The experiment was programmed and conducted with the software z-Tree (Fischbacher, 2007). The computer screens and code can be provided from the authors upon request. 6 are classified as self-centered, while those who give 10 or more are classified as beneficent (for a similar classification, see Brosig, 2002). In the second task, subjects are classified based on their behavior in a linear one-shot Public Good Game using the Strategy Method Technique (Fischbacher et al. 2001; Fischbacher and Gächter, 2010). Subjects are randomly allocated to groups of four individuals. An endowment of 200 tokens is to be allocated by each subject between a ‘private’ and a ‘public’ account. The individual payoff is determined according to the following function: =200−+0.5,   where  is player i’s contribution to the public account and  the contribution by the other members of the group. Since the contributions of the group to the public account are doubled and equally divided among the group participants, the marginal individual benefit from a contribution to the public good is 0.5. Subjects are first asked to make an unconditional contribution to the public good, and then to indicate their willingness to contribute to the public account, conditional on different possible contributions of the other group members. The possible average contributions range from 0 to 200, and are listed as multiple of 10 tokens. After the choices are made, one subject per each group is randomly selected and paid accordingly to her conditional contribution to the unconditional contributions of the other three members. The remaining players are paid accordingly to their unconditional contributions. In the third classification task, we employ a Decomposed Prisoner’s Dilemma Game, a classificatory task used both in the economic and psychological literature (e.g. Burlando and Guala, 2005; Brosig, 2002; Kuhlman and Marshello, 1975; Pruitt, 1967). The Decomposed Game is designed to study the distributional preferences of the subjects who are asked to choose between two possible allocations of money. For example, a subject must choose whether she prefers an allocation where she receives 130 tokens and the other participant receives 75 tokens, or an allocation where she receives 145 tokens and the other participants loses 39 tokens. Subjects are randomly and anonymously matched in couples and asked to make 24 choices between pairs of 7 allocations. The individual earnings are equal to the sum of the payoffs of the 24 choices made by the subject and by her co-participant, who remains the same throughout the 24 choices.8 No feedback about the co-participant’s choices is provided to the subjects during the classification stage: the subjects only receive information about their earnings at the end of the experiment. In addition, the order of the classification tasks is the same for all the subjects, and, therefore, cannot explain across-sample differences. After the classification stage, the subjects enter the main stage of the experiment and play a repeated linear 4-player Public Good Game (12 rounds). At the beginning of the first round, subjects are randomly matched in groups of four which remain the same over all rounds. The payoff function is identical to the one used in the Strategy Method, except for the individual endowment (20 tokens instead of 200 tokens). At the end of each round, each subject receives feedback about her contribution to the group account, the single contributions of the other members (whose identities are hidden),9 and her total earnings. Comprehension and familiarity with the experimental setup is obtained requiring the subjects to enter three forced inputs.10 After the first 12 rounds, the subjects engage in additional experimental tasks which we do not consider in this paper.11 After all tasks are completed, subjects are informed about their earnings and are required to complete a demographic questionnaire (reported in the Appendix). The experiment was conducted at the LES (Laboratorio di Economia Sperimentale, Forlì campus of the University of Bologna, Italy) and at the BLESS (Bologna Laboratory for Experiments in Social Science, Bologna campus of the University of Bologna, Italy) in the period July 2009 - January 2011.12 We ran a total of 18 sessions, with either 12 or 24 subjects per session. Each session was composed by homogeneous subject pools, for a total of 72 Temporary workers, 84 Permanent workers and 96 Students, none of which had previously participated in a similar experiment. No subject could participate in more than one session. The participants were randomly assigned to computer terminals, which were separated by partitions in order to avoid facial or verbal communication between subjects. Before proceeding with each task, subjects filled in a control 8 See Burlando and Guala (2005) and Brosig (2002) for more details. 9 The order in which the contributions of the other members were displayed was randomized in each round. 10 As shown in Bigoni and Dragone (2012), in a Public Good Game, on-screen instructions requiring forced inputs improve on subjects’ comprehension and familiarity with the experimental task. They also contribute to reduce both decision and waiting times without affecting the overall pattern of contributions. 11 The additional tasks consist of 24 additional rounds of the Public Good Game with some design changes with respect to the initial 12 rounds, and a Stug Hunt Game with framed instructions. Since the subjects where not informed about the future tasks, no distortion in their choices was artificially introduced by the experimenters. 12 In the Appendix we report details about dates and places of each session. 14 expect Conditional co-operators to provide high levels of contribution in the subsequent rounds. In contrast, since in the Student sample there is a higher share of Free riders, we would expect lower initial contributions, which in turn should induce Conditional co-operators to lower their contributions over time. Figure 2: Evolution of average contributions over time Figure 2 shows the average contribution in the first 12 rounds of the Linear Public Good Game. Initial contributions do not differ significantly, although we can observe some differences as the game unravels. In the Students sample, average contributions per round and total average contributions are below those by Permanent and Temporary workers. Comparing the contributions across the three samples for each round,21 we reject the hypothesis that the three samples come from the same population only for the last two rounds (Kruskal Wallis test, p = 0.084 and 0.026 respectively). Students contributed significantly less in the last rounds of the Public Good Game compared to Permanent (round 10, 11, 12)22 and Temporary workers (round 11, 12)23, but we do not detect any significant difference in the average contribution of Permanent and Temporary workers (Mann-Whitney test, p > 0.1). The Students’ contributions significantly decrease over time 21 We use the average of each Public Good Game group’s contribution as the unit of observation. 22 Mann-Whitney test p = 0.090, 0.053 and 0.024 respectively. 23 Mann-Whitney test p = 0.069 and 0.020 respectively. 8 10 12 14 16 Contribution 0 3 6 9 12 Period Permanent workers Students Temporary workers 15 (Spearman ρ = -0.192, p = 0.001), which is a recurrent finding in the literature (see, e.g. Andreoni, 1988; Croson, 1996). Interestingly, there is no significant downward trend for Temporary and Permanent workers (Spearman ρ = -0.016 and -0.060, p = 0.820 and 0.343), with an average contribution that remains quite constant throughout the 12 rounds of the Public Good Game. Result 3: Temporary and Permanent workers contribute on average more than 70% of their endowment and their contributions remain stable over time. Students, instead, contribute less than workers and their contributions decrease over time. To study how contributions depend on the history of the game, we employ a Poisson-logit maximum-likelihood hurdle model to separate the decision of contributing in two steps (see, e.g., Nikiforakis, 2008). First, with a logit model we study whether the subjects decide to contribute or not, then with a zero-truncated Poisson model we study the decision about the amount of the contribution, conditional on contributing a positive amount. Table 5 displays the results of this estimation. In a first model (Hurdle model 1), the independent variables are the sample dummies (the baseline category is “Temporary”), a time variable, the positive and negative deviations of i’s contribution from the average group contribution in period t – 1, the individual i’s contributions made in t – 1 and t – 2, and, as in previous regressions, the socio-demographic characteristics of the subjects. In a second model (Hurdle model 2), we also include the classification dummies obtained from the classification tasks. In particular, we consider being Individualistic, Competitive or Reciprocating in the Decomposed Game, Beneficent in the Dictator Game, and being Conditional, Unconditional or a Free rider in the Strategy Method. The results of the estimation appear to be consistent with our expectations based on the shares of Free riders, Unconditional and Conditional co-operators detected in the classification task (in particular, in the Strategy Method). From the first model we observe that Students are less likely to contribute a positive amount compared to Temporary and Permanent workers. This result may be explained by the larger proportion of Free riders and the smaller proportion of Unconditional contributors among Students. Indeed, once we include the classification dummies in the regressions (Hurdle model 2), the point estimate for the variable Students decreases and becomes only weakly significant, whereas the variable Free rider is negative and strongly significant, suggesting that subjects who are classified as Free Riders in the Strategy Method are less likely to contribute to the public good.24 In both the first and second model, we also find that the probability of not 24 There is also some weakly significant evidence that Reciprocating and Individualistic subjects are less likely to contribute, whereas Beneficent subjects are more likely to contribute. 16 contributing to the public good significantly increases across periods, and it increases if the subject’s contribution in the previous period had not matched the average contribution of her group. There is also evidence that subjects are more likely to contribute a positive amount the higher their contribution in the previous rounds (this effect is small, but highly significant).25 When considering the decision of how much to contribute (conditional on contributing a positive amount), in both models we observe that current contributions are positively correlated to past contributions, and they increase if the subject’s contribution in the previous period was smaller than the average contribution of the group. Furthermore, subjects who contributed above the average in the previous period adjust their decision and reduce their contribution in the current round, and that older and more educated subjects contribute more than younger subjects. Finally, in the first model we also have some weakly significant evidence that, conditional on contributing a positive amount, Permanent workers contribute less than Temporary workers. Table 5: Poisson-logit maximum-likelihood hurdle model HURDLE MODEL 1 Decision to contribute Decision of how much to contribute dy/dx Std. Err. p>z dy/dx Std. Err. p>z Contribution t-1 0.007*** 0.001 0.000 0.738*** 0.045 0.000 Contribution t-2 0.003*** 0.001 0.002 0.247*** 0.027 0.000 Positive deviation (t-1) -0.015*** 0.002 0.000 -0.305*** 0.046 0.000 Negative deviation (t-1) -0.010*** 0.002 0.000 0.521*** 0.113 0.000 Period -0.009*** 0.002 0.000 -0.030 0.024 0.211 Male -0.015 0.014 0.283 0.131 0.209 0.531 Married 0.039* 0.020 0.051 -0.030 0.241 0.899 NoReligion -0.029* 0.017 0.093 -0.086 0.256 0.738 Degree 0.021 0.014 0.119 -0.640*** 0.240 0.008 Age 0.001 0.001 0.235 0.029** 0.013 0.024 Permanent -0.035 0.024 0.157 -0.459* 0.266 0.085 Student -0.044** 0.018 0.017 -0.085 0.264 0.749 Obs 1512 1336 HURDLE MODEL 2 Decision to contribute Decision of how much to contribute dy/dx Std. Err. p>z dy/dx Std. Err. p>z Contribution t-1 0.007*** 0.001 0.000 0.732*** 0.045 0.000 Contribution t-2 0.002** 0.001 0.013 0.245*** 0.027 0.000 Positive deviation (t-1) -0.015*** 0.002 0.000 -0.306*** 0.046 0.000 Negative deviation (t-1) -0.009*** 0.002 0.000 0.513*** 0.113 0.000 Period -0.009*** 0.002 0.000 -0.031 0.024 0.202 Male -0.017 0.012 0.174 0.107 0.214 0.618 Married 0.030 0.020 0.124 -0.051 0.244 0.835 NoReligion -0.016 0.016 0.292 -0.121 0.258 0.639 25 In the first model, we also find that married subjects are more likely to contribute to the public good, and that atheist or agnostic subjects are less likely to contribute, although these estimates are only weakly significant. 17 Degree 0.008 0.013 0.532 -0.592** 0.242 0.015 Age 0.001 0.001 0.453 0.028** 0.014 0.048 Permanent -0.035 0.022 0.115 -0.369 0.286 0.197 Student -0.035* 0.018 0.056 -0.086 0.281 0.758 Beneficent 0.027* 0.014 0.063 0.023 0.256 0.929 Reciprocating -0.124* 0.067 0.062 0.699 0.472 0.138 Individualistic -0.132* 0.072 0.065 0.578 0.485 0.233 Competitive -0.087 0.097 0.367 -0.165 0.686 0.810 Conditional -0.005 0.016 0.772 0.062 0.259 0.812 Free rider -0.135** 0.050 0.007 -0.866 1.147 0.450 Unconditional -0.025 0.027 0.351 0.394 0.491 0.422 Obs 2520 2292 Notes: the decision to contribute is estimated with a logit model with clustered standard errors at individual level. The decision of how much to contribute is estimated with a zero-truncated Poisson model with clustered standard errors at individual level. In the table, we report the average marginal effects of the independent variables (see Bartus, 2005). * p<0.1, ** p<0.05, *** p<0.01. V. Discussion Before running the experiment we expected to find a significantly lower propensity to cooperate in the group of Temporary workers with respect to the group of Permanent (co-op) workers, as the former are less likely to know each other and they have received no specific training on the values of cooperation and mutualism. The experimental results show, instead, that Temporary and Permanent workers contribute substantially and in a very similar way to the public good over the 12 rounds of the game. This result holds even if there are some differences in preferences, and even if Temporary workers tend to be slightly more individualistic than Permanent workers. A possible explanation for the results in the Public Good Game relies on the large proportion of Unconditional contributors in both the Temporary and Permanent workers samples (and, analogously, to the low proportion of free riders). This may have helped a sustained high level of cooperation for Conditional contributors, thereby maintaining high average contribution rates. In contrast, the higher share of Free riders among Students might have induced Conditional cooperators to lower their contributions over time in response to the low contributions of free riders. This interpretation is consistent with the results shown in Table 5, which allow joining and comparing the information on the distributional preferences of the subjects obtained in the Classification stage of the experiment with the Strategic behavior observed in the repeated Public Good Game. A second possible explanation is that workers, irrespective of whether they are employed under a temporary or permanent contract, are less selfish than Students. This explanation would suggest that socialization processes due to working experiences and age (or both) could be major factors. If workers have learnt that cooperating provides long-run benefits, they may have brought in the lab 18 this experience and use it when contributing in the Public Good Game. Students, instead, are more used to individual rather than team work and have less experience with repeated interactions and the related reputational concerns. Note that the above result cannot be due to demand effects, as we ensured anonymity and, if anything, we should expect this effect to operate in the same direction in all sessions. Also, the results cannot be due to reputational concerns within the lab, as we guaranteed anonymity in the whole experiment. Subjects only knew that the pools were homogeneous. This might have induced an in-group bias. For example, Temporary workers may have chosen their contributions based on mutual insurance considerations. Accordingly, they might have contributed to the public good knowing that the other group members were also Temporary workers, and this may have stimulated high contributions. However, this effect should be stronger among the Permanent workers, as they work for the same cooperative and meet each other daily, but we detect no significant difference with respect to Temporary workers. This is a particularly important result, as it shows that Temporary and Permanent arrangements do not affect the propensity to cooperate to a public good when workers are part of a homogeneous group. As far as we know, this is the first experimental evidence showing this result. A different, but related, question which we leave for future investigation is whether heterogeneous groups composed by both Temporary and Permanent workers display the same levels and trends of contributions. Our a priori expectation of a higher contribution rate in Permanent workers was based on the fact that they knew each other, that they work in the same place, and that the common employer is a coop which actively emphasizes the values of mutualism and cooperation. It is however possible that other factors may have driven the behavior of Permanent workers toward an unexpected direction. Knowing each other is not a guarantee per se of a high social capital and willingness to cooperate, as human relationships can improve, but as well deteriorate over time. Analogously, being constantly exposed to the values of mutualism does not ensure these values are internalized by workers, since these values may possibly be rejected. If this were the case, we should observe low contribution rates. The result that the observed contribution rates of Permanent workers are significantly higher than those of Students and that they remain quite high over time (about 60% of the initial endowment), however, does not support this hypothesis. The high degree of cooperative and other-regarding behavior observed among Temporary workers may be also explained by what social and labor psychologists refer as impression management, that is the systematic attempt by temporary workers to behave in a way that pleases the employee (Leary 19 and Kowalski 1990). Such an attitude might have been brought by the Temporary workers into the lab, and push them to cooperate. Although this possibility cannot be excluded a priori, we made very clear that the participation to our experiment was a one-shot experience, and that in no way we would have communicated the results of their individual choices to Obiettivo Lavoro. Another possible explanation is that, contrary to our priors, co-op workers are not the only workers that had been exposed to the values of cooperation and mutualism. After all, the recruiting agency which supplied the Temporary workers was originally established as a co-op and, although it converted into a public limited company in 2003, it adheres to the Social Responsibility practices, it has an Ethical code and its guiding principles are (according to its Charter of Values) attentiveness, collaboration, improvement, equity, transparency, and integrity. We cannot exclude that these factors have had an influence on the preferences and behavior of the Temporary workers that took part in our experiment, but we do not think it has played a major role because there is very little interaction between the Temporary workers and the staff of the recruiting agency, which is a simple intermediary between employers and workers. If anything, there may have been an interaction with the temporary employers, some of which also have Ethical codes and adhere to the Social Responsibility practices, while some others do not. More in general, it is possible that the common social environment in which both Temporary and Permanent workers live has played a major role on working people. The social environment can overwhelm the role of investments in the values of cooperation by the co-operative, or the possible differences induced by Permanent and Temporary work arrangements. This can be the case, as the places where the experiments were conducted (located within the Emilia-Romagna region) are characterized by high levels of social capital and generalized trust (Bigoni et al., 2013). This may have shaped in a similar way the behavior of both Temporary and Permanent workers, as well as that of the Students raised in Emilia-Romagna. However, this conjecture is not consistent with the finding that Students display significantly lower contribution rates. Hence, if the reason for the scant difference in the contribution rates of Temporary and Permanent workers relies on the existence of a high social capital at the regional level, one should also explain why this seem to affect more workers than students. This requires additional data aimed at understanding whether our results also hold in regions where social capital is low. VI. Conclusions 20 The rapid diffusion of temporary employment in many industrialized countries, in particular in countries providing high levels of employment protection, has raised questions concerning the economic and psychological effects of this form of contracts. Several studies have indicated the existence of a gap in the working conditions of Permanent and Temporary workers, particularly in terms of wages and working rights, and on the psychological consequences of being employed on a temporary basis. To the best of our knowledge, no paper has so far investigated whether there exist differences in the individual preferences and in the propensity to cooperate and free-ride of Temporary workers with respect to Permanent ones. In this paper we address this question from an experimental perspective. This allows providing an incentive compatible source of information on the individual characteristics and behavior of workers under different contractual arrangements. Although an overall assessment on the desirability of temporary and permanent contracts must necessarily include the impact of relevant dimensions of individual well-being, such as the economic and psychological impact of temporary arrangements, information on individual behavior in a strategic environment with free-riding opportunities can be very useful for an employer who is considering which contractual arrangement best suits her needs. We consider three types of subjects: Temporary workers, Permanent workers and Students. Before running the experiment we expected the group of Temporary workers to cooperate less and to exploit the opportunity of free-riding more than Permanent workers. This expectation was based on the fact that Temporary workers did not know each other and had never met before. In contrast, the Permanent workers physically work in the same offices and they meet on a daily basis. In addition, they were recruited among workers of a Co-op where the values of cooperation and mutualism are actively transmitted and enforced. We find some differences in the distributional preferences of the two groups of workers, but a very similar behavior in a Public Good Game. Workers, irrespective of the type of their contractual arrangement, begin with high levels of contribution to the public good, and contributions remain high over time. Instead, in the sample of Students that we used as a control, contributions begin at high levels, but then decline considerably over time. While the latter result is very much in line with the previous experimental evidence on the Public Good game, the high and steady level of contributions by workers is a less common finding. A possible explanation for this result is that the different contractual arrangements, and the consequent economic and psychological effects, play a minor role with respect to other factors. For example, socialization and learning on the job may have induced both Temporary and Permanent workers to behave similarly and avoid free-riding opportunities. Also, in-group and mutual insurance considerations may have driven Temporary 21 workers to contribute to the public good. In either case, the result that Temporary workers cooperate more than the control group of Students, and as much as Permanent co-op workers, is a new and unexpected outcome which paves the way to investigating whether this result will translate into productivity at work, outside the lab. This venue of research is left for further investigation. 22 Appendix A.1 Subjects’ socio-demographic characteristics Characteristics Permanent Student Temporary Gender (n=84) (n=96) (n=72) Female 58 (69.05%) 52 (54.17%) 43 (59.72%) Male 26 (30.95%) 44 (45.83%) 29 (40.28%) Age (n=84) (n=96) (n=72) Mean 41.64 23.94 31.67 St. dev. 9.19 4.57 9.39 Marital Status (n=84) (n=96) (n=72) Married 44 (52.38%) 1 (1.04%) 13 (18.06%) Unmarried 40 (47.62%) 95 (98.96%) 59 (81.94%) Nationality (n=84) (n=96) (n=72) non-Italian a 7 (8.33%) 5 (5.21%) 8 (11.11%) Italian 77 (91.67%) 91 (94.79%) 64 (88.89%) Religion (n=84) (n=96) (n=72) Agnostic/Atheist 9 (10.71%) 28 (29.17%) 15 (20.83%) Christian 71 (84.52%) 64 (66.67%) 42 (58.33%) Other b 4 (4.76%) 4 (4.17%) 15 (20.83%) Education (n=84) (n=96) (n=72) Lower Secondary School or less 56 (66.67%) 95 (98.96%) 52 (72.22%) Upper Secondary School or more 27 (32.14%) 0 (0%) 14 (19.44%) Other 1 (1.19%) 1 (1.04%) 6 (8.33%) Years of work (n=36) c (n=72) Mean 19.42 10.22 St. dev. 10.59 9.01 Years of work in coop (n=36) c Mean 10.01 Std. Dev. 6.88 Years of work as Temporary (n=72) <1 41 (56.94%) >1 31 (43.06%) Working days as Temporary worker (last 12 months) (n=72) Mean 46.04 Std. Dev. 87.55 Working days as Temporary worker (total) (n=72) Mean 92.22 Std. Dev. 189.96 Months worked in coop (n=71) d Mean 14.2 Std. Dev. 83.97 Student status (n=72) Only worker 58 (80.56%) Lower Secondary School or less 1 (1.39%) Upper Secondary School or more 11 (15.28%) Other 2 (2.78%) Notes: a 7 were Albanian, 1 Brazilian, 2 Moldavian, 1 Polish, 5 Romanian, 2 Senegalese, 1 Serb, and 1 Hungarian. b 2 were Buddhist, 1 Indu, 6 Muslim, and 14 did not specify. c This information was collected only for a subset of Permanent workers. d One subject did not specify how many months she worked in a coop. 23 If we compare the proportion of males and females across the three samples, we do not detect any statistically significant difference (Chi-squared test, p = 0.122). In pairwise comparisons, the only statistically significant different occurs between Permanent workers and Students. In particular, the proportion of females is significantly lager in the Permanent workers sample compared to the Students sample (p = 0.041). There is no statistically significant difference in the proportion of females between Temporary and Permanent workers, and Temporary workers and Students (p = 0.224 and 0.472 respectively). The three samples statistically significantly differ with respect to age (Kruskal Wallis test, p = 0.000). In particular, Permanent workers are significantly older than Students and Temporary workers respectively (Mann-Whitney p = 0.000), and Temporary workers are significantly older than Students (p = 0.000). If we look at the marital status of the subjects, the three samples statistically significantly differ both in aggregate (Chi-squared test, p = 0.000) and in pairwise comparisons (p = 0.000). In particular, the proportion of Permanent workers who are married is significantly larger than Students and Temporary workers. Similarly, the proportion of married subjects in the Temporary workers sample is significantly larger than in the Students sample. Almost the totality of the participants is Italian (92%). Only few subjects are not from Italy. Those who are not Italian are Albanian, Brazilian, Moldavian, Polish, Romanian, Senegalese, Serb, or Hungarian. If we compare the proportion of non-Italian across the three samples, we do not detect any statistically significant difference (Chi-squared test, p = 0.370). A similar result is obtained in pairwise comparisons (p > 0.1). If we look at the religious affiliation, subjects statistically significantly differ in their religious beliefs across samples (Chi-squared test, p = 0.000). This evidence is also supported in pairwise comparisons (Chi-squared test, p < 0.01). More specifically, the fraction of Christians is larger among Permanent workers than Temporary workers and Students. Students are generally more agnostic/atheist. The proportion of participants who are neither Christian nor agnostic/atheist is larger among Temporary workers compared to Students and Permanent workers. In general, Permanent workers are more religious than Students (p = 0.002) and Temporary workers (p = 0.081). In contrast, Temporary workers are not statistically significantly more religious than Students (p = 0.221). If we compare the level of education, the three samples statistically significantly differ (Chi-squared test, p = 0.000). In particular, a higher proportion of Students possess a higher degree compared to Permanent and Temporary workers (Chi-squared test, p = 0.000). No statistically significant difference occurs between Temporary and Permanent workers on the level of education (Chi-squared test, p = 0.124). If we compare the years of work between Permanent and Temporary workers, Permanent workers have more years than Temporary workers (Mann-Whitney p = 0.000). 30 Ichino, A., F. Mealli, and T. Nannicini. 2008. “From Temporary Help Jobs to Permanent Employment: What Can We Learn from Matching Estimators and Their Sensitivity?” Journal of Applied Econometrics 23 (3): 305–327. Kuhlman, D. M., and A. Marshello. 1975. “Individual Differences in the Game Motives of Own, Relative, and Joint Gain.” Journal of Research in Personality 9 (3): 240–251. Leary, M. R., and R. M. Kowalski. 1990. “Impression Management: A Literature Review and TwoComponent Model.” Psychological Bulletin 107 (1): 34–47. Liebrand, W. B. G. 1984. “The Effect of Social Motives, Communication and Group Size on Behaviour in an N-Person Multi-Stage Mixed-Motive Game.” European Journal of Social Psychology 14 (3): 239–264. Martínez, G., N. De Cuyper, and H. De Witte. 2010. “Review of Temporary Employment Literature: Perspectives for Research and Development in Latin America.” Psykhe 19 (1): 61–73. Nikiforakis, N. 2008. “Punishment and Counter-Punishment in Public Good Games: Can We Really Govern Ourselves?” Journal of Public Economics 92 (1–2): 91–112. Novkovic, S., P. Prokopowicz, and R. Stocki. 2012. “Staying True to Co-Operative Identity: Diagnosing Worker Co-Operatives for Adherence to Their Values.” Advances in the Economic Analysis of Participatory & Labor-Managed Firms 13: 23–50. OECD. 2002. “Taking the Measure of Temporary Employment.” In OECD Employment Outlook, 127–185. Organisation for Economic Co-operation and Development. Pruitt, D. G. 1967. “Reward Structure and Cooperation: the Decomposed Prisoner’s Dilemma Game.” Journal of Personality and Social Psychology 7 (1): 21–27. Rousseau, D. 1995. Psychological Contracts in Organizations: Understanding Written and Unwritten Agreements. Sage. Sala, H., J. I. Silva, and M. Toledo. 2012. “Flexibility at the Margin and Labor Market Volatility in OECD Countries.” The Scandinavian Journal of Economics 114 (3): 991–1017. 31 Instructions (translation from Italian; bold, italics and other formatting options are as in the original version of the instructions) INSTRUCTIONS Introduction Welcome to the Laboratory of Experimental Economics of the University of Bologna. ou will participate in a study on the individual behavior of about one hour and a half. If you read these instructions carefully, you can, depending on your decisions, earn some money. For your convenience, instructions are provided both on screen and on paper. Your earnings will be calculated in florins and will be converted into Euros at the end of today’s session. Every florin equals 1 euro cent. Payment will be made in cash at the end of this session and it will be done in such a way that no other participant will know how much you have earned. he experiment is divided into various stages. At each stage you will be asked to make some decisions or to answer a few simple questions. From now on it is forbidden to talk to the other participants, or communicate in any other way. If you want to ask a question, raise your hand. STAGE ONE Situation In this stage each of you is randomly matched with another participant. The identity of the participant with whom you are matched remains anonymous. You will never know with whom you are matched. For each pair of participants, the computer assigns 300 florins, which are randomly given to only one of the two members of the couple. The other participant gets nothing. Those who receive the 300 florins can decide whether to keep them all or give part of the florins to the other participant they are matched with. Those who have not received the 300 florins, instead, can only receive florins from their partner. You cannot currently know whether you are one of those who will receive the 300 florins, because those who will receive 300 florins will be randomly selected at the end of stage seven. What you should do in stage one At this stage we ask you to indicate how you would divide 300 florins between you and the other person, in case you are randomly selected to receive the 300 florins. If, at the end of stage seven, you actually receive the 300 florins, then your choice will be implemented. If, instead, your partner 32 will be selected, her/his choice will be implemented, and you will receive the amount of florins indicated by her/him. Push the button "Continue" and make your choice. STAGE TWO Situation In this stage, each of you is randomly matched with three other participants to form a group of four persons. The identity of the other participants is anonymous and you will not know with whom you are matched. Each person receives 200 florins and must decide how many florins to put in her/his own personal account and how many to invest in a project. The overall payoff is given by the personal account plus the earnings resulting from the project. Earnings from the personal account: For each florin you put in your personal account you will earn exactly one florin. For example, if you put 200 florins in your personal account (and therefore you do not invest in the project), you will earn exactly 200 florins. If you put 60 florins in your personal account, you will earn 60 florins. Earnings from the project: The earnings resulting from the project depend on your choices and the choices of the other members of the group. For each member of the group, the earnings from the project will be determined as follows: 1) All florins given by the group members are summed up. 2) The sum is doubled. 3) The doubled sum is divided into four equal parts and assigned to each group member. Now let's see two examples to better understand how the earnings from the project are calculated: Example 1: If the sum of all contributions to the project is 300 florins, each group member will receive individually: (300 florins multiplied by 2 and then divided by 4) = 150 florins from the project. Example 2: If the four members of the group invest 25 florins each, and then the sum of their investment is 100 florins, each group member will receive (100 florins multiplied by 2 and then divided by 4) = 50 florins from the project. Practice in stage two 33 Please answer the following questions. The purpose is to practice with the computation of the earnings you will get. The answers you give to these questions will not affect your final earnings. (If you like, you can use the electronic calculator that you can activate by pressing the small button at the bottom of the screen). Each member of the group has 200 florins at his disposal. Suppose that none of the four members of the group (including you) contributes to the project.  How much will your total earnings be (income + personal project)?  What will the individual earnings of the others members of the group be? 2. Each member of the group has 200 florins at his disposal. Suppose you put $200 florins in the project and each of the other members of the group puts 200 florins.  How much will your total earnings be (income + personal project)? Start of Stage Two Now the choice situation we have just described begins. You will be given 200 florins and you will decide how much you want to put in your personal account and how much in the project. The mechanism for calculating earnings is the one just described. What you should do in stage two In this stage you will make two kinds of choices: we will call the first "single choice" and the second "choice in the table." Your earning in this stage depends both on what you have chosen in the "single choice", and on what you have chosen in the "choice in the table" Single Choice With the single choice you have to decide how many of the 200 florins you want to put in the project. You also have to indicate how much you think that others are investing in the project. If your guess is at 3 florins or closer from the actual average, you earn 3 extra florins. On your screen you will see this: 34 After pressing the "OK" button, you will go to the "choice in the table." Choice in the table: The screen for the "choice in the table" will look like this: For example, in the third cell of the first column you are asked to indicate how much you would like to contribute to the project if the average contribution of each of other members of your group is 20 florins. Or, in the third cell of the second column you are asked to indicate how much you would like to contribute if each of the other group members contributes (on average) 130 florins. 35 Results of stage two After all participants to the experiment have given their answers, the computer will randomly select a person in each group. The computer will take the choices made by the other 3 people in the "single choice" and it will compute the average of their contributions. Then it will consider what is the contribution choice indicated by the fourth person in the "choice in the table" in correspondence of the average contribution of the other three members. By combining this information, the computer:  Will compute the total contribution of the group by adding the three individual contributions (single choice) and the contribution given by the selected person (choice in the table);  Will determine the earnings from the project, by doubling the total amount of the contributions to the project;  Will give a quarter of the doubled sum to each member of the group. Since you do not know who will be selected by the computer to determine the choice in the table, when you have to fill in the single-choice and the choice in the table, you have to think carefully about both types of choice because both can prove to be decisive in the determination of your earnings. The computer draw and the result of these computations will be communicated at the end of stage seven. Press the "Continue" button to begin. STAGE THREE Situation At this stage you have to choose between two options, Option A and Option B. The two options are related to sums of money that you and another participant will earn. For example, you may be asked to choose between two options, A and B, where option A is a gain of 145 florins for you and a loss of 39 florins for another participant, while Option B means a gain of 130 florins for you and a gain of 75 for the other participant. The other participant will have to choose from the same options. An example of the choice between A and B is the following: 36 There is a total of 24 pairs of choices, and you will be matched with the same participant (selected at random by the computer at the beginning of stage three) for all 24 pairs of choice. The identity of the other participant will remain anonymous, and no one will know who has been matched with. Your payoff depends on your choices and on those of the other participant, and it is given by the sum of the choices made by you and the other participant. Going on with the previous example, if you choose option A (a gain of 145 florins for you, a loss of 39 loss for your partner), and the other chooses option B (a gain of 130 florins for her/himself and a gain of 75 florins for you), you will earn 145 + 75 = 220 florins, while the other participant will earn -39 +130 = 91 florins. If, instead, also the other chooses option A, you will earn 145 + 75 = 220 florins, while the other participant will earn -39 +130 = 91 florins. What you should do in stage three In this stage we ask you to make 24 choices between options A and B. The options will be different each time. Results The overall outcome of your choices will be known only at the end of stage seven. In any case, you will be paid privately and you will not know the identity of the other participant, nor she/he will know yours. 37 Before starting with stage three, we ask you to answer some questions. The purpose is to practice with the computations of the earnings you will get. The answers you give to these questions will not affect your final earnings. In the situation described below: If both choose option B  how much do you earn?  how much does the other participant earn? If you choose option B, while the other participant chooses A  how much do you earn?  how much does the other participant earn? STAGE FOUR Situation 38 You will make choices similar to those of stage two, the one in which you received a sum of money and had to choose how much to invest in a common project and how much to put in your personal account. As before, the sum of money invested in the project is doubled and then divided among four anonymous participants, and your earnings will be the sum of these florins and of those that you put in your personal account. The participants in your group will be randomly selected by the computer from all the participants to this experiment and they will remain the same throughout this stage. Unlike before, every time you and the other three participants choose how much to invest in the project, the individual contributions will be immediately communicated to all participants in the group. To protect anonymity, the participants are indicated with letters A, B, C or D that the computer randomly assigns at each round. This means, for example, that letter A can indicate different people in the course of the phase. Along with your choice of contributing in the project, we will ask you what you think the others are contributing to the project, on average. If your prediction is at 3 or less florins from the actual average, you will earn three extra florins. What you should do in stage four This stage consists of 12 rounds. In each round you are given 20 florins and you are asked to choose how much to invest in the project (12 choices), and to indicate what you think is the average contribution of the other participants (12 forecasts). Results After you have made your choice and your forecast, you will be informed about the others’ contributions and how much you have earned. Payment will take place privately at the end of stage seven. 