12 wages do not necessarily deter the most highly motivated from applying to the public sector, the result that emerges from their field experiment. One reason to believe that our measure of ability is less sensitive to motivation is that it is uncorrelated with our measure of motivation.

The formulation of effort as a multiplicative function of ability and motivation is intuitive and common. The exact function is of course unknown, however. We therefore also examine the robustness of our results to an alternative assumption, that effort is an additive function of ability and motivation, so that we correct public sector effort for ability by using the expression: epub − epriv.

We conducted two treatments using a between-subjects design at the University of Indonesia. Each treatment had one of two possible public sectors, one with a “low” flat salary, of 1400 tokens per round, and one with a “high” flat salary of 2200 tokens per round. Since we are primarily concerned with intrinsic motivation in this paper, salaries were chosen to ensure intrinsic motivation would play a large role in the decision to join the public sector. All subjects in the low salary treatment were sufficiently capable of manipulating sliders that they could earn more in the private sector (piece rate) task. About 90 percent of subjects in the high salary treatment could earn more in the private sector task.

Once they were familiar with both the private and public sector tasks, subjects were given a choice of sectors – private or public – and then completed three further rounds of either the private or public sector task, corresponding to their choice. This is called the “sector choice task”, which incentivizes the decision to choose between the public and private sectors. This allows us to isolate the effects of the public sector wage on the intrinsic motivation of workers who choose employment in the public sector.<sup>11</sup> After completing all of the games involving sliders, subjects engaged in two additional tasks. One, not of concern here, was a risk measure (using the Eckel and Grossman elicitation method, Eckel and Grossman, 2002). The other was an extensive survey recording subject demographics. Finally, towards the end of the session, subjects were asked for a volunteer to assist with payment to the charity. First, the volunteer would roll the (four-sided) die to determine the task that would be paid out at the end of the session. Next, the volunteer would verify payment by accompanying an experimenter to the closest bank and make the cash donation directly to the bank account of the charity.

UI and STAN students received 25,000 IDR as their show-up fee. Average earnings from the experiment were around 120,000 IDR. All sessions were conducted during March 2012 and March 2013 and took about 2 weeks, on each occasion, to complete in each institution. In addition, since subjects used a mouse to manipulate the sliders, care was taken to utilize identical mice at each location and to use the same screen resolution on the computers to minimize differences across samples. Since this was an individual task, multiple treatments took place within the same session. Subjects were randomly assigned to seats within the computer lab and subjects in adjoining seats were given alternating treatments.

> 11 The final task, Task 4, was simply a continuation of the sector choice task, Task 3, but contains a treatment shock. Subject participation in this task had no influence on the earlier tasks; analysis of Task 4 is , beyond the scope of this paper.