Three of the surveys asked officials about whether their colleagues committed an appropriate number of hours to their work. This is the closest to a measure of effort that the surveys provide, and thus we use it with the caveat that it is an imperfect proxy. Importantly, they were not asking about the _respondents_ hours of work but their perceptions of _other peoples_ , reducing our concern that the responses would be biased. Table 4 provides the average assessments of respondents as to the proportion of their colleagues that left work early or spent “a lot of time on personal matters (more than two hours)”.<sup>31</sup> We can see that a significant proportion of civil servants do not work the full day, and the proportion is relatively stable across Indonesia, Pakistan and the Philippines. Across civil service settings, around 17% of staff are not working their contracted hours.<sup>32</sup> Civil servants in these three countries were also asked what proportion of civil servants’ working hours _exceeded_ their contractual hours.<sup>33</sup> Across the board, the average proportion of staff perceived by survey respondents to be over-working exceeds those under-working by a significant margin. Table 4 indicates that over-workers make up roughly a third of civil servants. In Indonesia, roughly half of officials believed they could not be responsive to new requests because the organization was “already overloaded with work”. The majority of civil servants committed to their work are overloaded while a minority of their colleagues are shirking their basic responsibilities.

To what extent are the additional efforts of the over-workers compensation for the lack of effort of the under-workers? Evidence from Indonesia would suggest that the link is weak. Figure 4 plots the proportion of early leavers in each of the Indonesian organizations for which we have data. We see that there is wide variation in the proportion of staff said to under-work, or ‘early leavers’. We can then plot the proportion of ‘late stayers’ in an organization on the same figure (ranked by the proportion of early leavers as well) to assess whether there is a pattern of compensation. The line of best fit through the markers of late stayers is positive but shallow, with a p-value of 0.15. From this small sample of evidence, there does not seem to be a trend that civil servants are making up for the lack of effort of their colleagues. Rather, some organizations contain both few early leavers and many late stayers, and others the reverse. Better understanding the time use of public officials would allow us to assess the welfare consequences of these results.<sup>34</sup>

# **Correlates of Productivity**

We now turn to analysis akin to ‘growth accounting’, an exercise that attempts to decompose productivity into its constituent determinants. Famous examples in the macroeconomics literature are Klenow and Rodriguez-Clare (1997) and Hall and Jones (1999), who find that income differences across rich and poor countries can be most keenly explained by human capital and ‘technology’. This last term is a catch-all for management quality, the application of frontier knowledge, and anything else that cannot be explained by included variables. Bloom et al (2016) find that the organizational incentive environment accounts

> 31The exact question was, ‘On any given day, what is your best guess of the approximate percentage of others of your rank in [your organization] who stop work and leave early, or spend a lot of time on personal matters (more than two hours)? (1) 0 -10% (3) 20-30% (5) 50-100% (2) 10 -20% (4) 30-50%’.

> 32In the Philippines, 40% of staff believe that “A substantial number of others at your level are not productive during work hours.” Of these staff, 40% believe that “the annual performance appraisal process identifies individuals that do not contribute.” While there is a fair chance that poor performers will be identified, this does not seem sufficient incentive to perform. This may be consistent with the fact that over 60% do not agree with the statement that “Punishments are applied to those who do the least to further the goals of the department.”

> 33The exact question was, ‘On any given day, approximately what percentage of others of your rank in [your organization] continue to work past official hours? (1) 0 -10% (3) 20-30% (5) 50-100% (2) 10 -20% (4) 30-50%’.

> 34Since the questions on effort were asked about ‘others of your rank’, we can create averages of the propensity to stay late at work at the rank-organization level in Indonesia, leaving us with 45 units of observation. To the extent that it is a meaningful exercise, we can then regress these outcomes on averages of the variables described in previous sections. We find that, even conditional on age, the longer the average length of service at an organization, the less likely officials are to stay late. The perceived prestige of the organization also has a positive impact on the proportion of late stayers.

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