4 which they belong is pro-social and the organization chooses a compensation scheme that assumes that they will act pro-socially (see also Benabou and Tirole, 2006 and Andreoni and Bernheim, 2009). One prediction of this literature is that pro-social behavior should be greatest in organizations that have a pro-social mission and pay lower wages than the private sector (Frey, 1997; Francois, 2000; Besley and Ghatak, 2005; Brewer and Selden, 1998; Crewson, 1997; Perry, 1996; Perry and Wise, 1990; Sheehan, 1996; Tirole, 1994; Wilson, 1989). Organizations that can attract individuals who share the organization’s mission will undertake activities at lower cost and be subject to less shirking (Besley and Ghatak, 2003, 2005; Delfgaauw and Dur, 2007; Dixit, 2002; Francois, 2007; among others).

Governments, compared to private sector companies, are more likely to be seen by prosocial individuals as pursuing a pro-social mission; government compensation schemes also more closely resemble the pro-social compensation strategies that Ellingsen and Johannesson (2008) outline. Prendergast (2007) argues, though, that pro-sociality in government officials can lead to excessive generosity towards the beneficiaries of government programs, a prediction that underlines the need for evidence on whether government officials are, indeed, more pro-social. Evidence is sparse, however, about whether government employees are indeed more pro-social, or whether those with more pro-social attitudes actually work harder on tasks that benefit society.

Buurman, et al. (2012) examine data taken from the results of a large Dutch survey of workers. Respondents were compensated for participating in the survey and could choose what type of compensation they would receive: a gift certificate, a lottery ticket, or a charitable donation. Public sector employees (broadly-defined) were significantly more likely to make the “pro-social” choice, a charitable donation. We build on this work in two ways. In our experiments, the units of compensation are the same (money for the charity or money for the subject), which allows us to avoid the potentially confounding effects of pro-social and risk-taking behaviors when compensation also involves lottery tickets. In addition, our subjects did not know the details of our experiments prior to choosing to participate in them, avoiding the potential selection bias that could emerge when the choice to participate is influenced by knowledge of the treatment itself (e.g., compensation in the form of a gift certificate, lottery ticket or charitable donation).

Serra, et al. (2011) use a Generalized Trust Game to assess workers’ pro-social motivation and, to assess workers’ pro-poor orientation, they rely on workers’ response to a survey question asking them to rank the importance of eight job characteristics, including an “opportunity to help the poor”. Their behavioral measure of pro-social behavior is a proxy, trust. The dictator game that we analyze is a direct behavioral measure of pro-sociality.

Gregg, Grout, Ratcliffe, Smith and Windjeijer (2011) analyze the data from a survey of thousands of British workers, including employees in for-profit and (as in Buurman, et al., 2012) non-profit “non-caring” and “caring” (health, education and social care) sectors. Their evidence for pro-sociality is “behavioral” in the sense that it is the actual – self-reported – overtime hours that respondents work. Our measure of pro-social behavior, actual contributions to charity, avoids the problem of imperfect or biased reporting of unpaid overtime hours, as well as ambiguities in the interpretation of overtime work. For example, even if pro-social orientation is the most plausible explanation of unpaid overtime in the non-profit caring sector, it is also possible that non-profit employers attract less productive workers who need to work extra unpaid hours to achieve the same output.

Carpenter and Gong (2013) also examine the effects of mission orientation on effort. They record political party preferences of a group of U.S. university subjects, and then randomly assign