at the median and 65th percentiles. Similarly, local governments, represented by the triangles, are spread relatively evenly across the distribution of federal organizations. One local government exhibits management quality above the 90th percentile of management in the entire Nigerian Government. The distribution also exhibits a classic WMS feature, a long tail of poorly managed organization. Bringing up the scores of the tail of poorly managed organizations at the state and local levels would substantially increase the mean level of quality at these tiers, and of management in Nigeria’s public sector more generally.

To highlight this variation in management practices, we can turn to the Kaduna local government data. To investigate the extent of variation within a single state, we measured the quality of management across six local governments there. The WMS scores of these local governments are marked with filled triangles in Figure 1. We can see that even within a single state, with a single coordinating state government, local governments are managed heterogeneously. At the top of the distribution, one local government is in the top decile of all organizations in our sample for its quality of management. Other local governments have management scores below the 20th percentile. For some reason, the Kaduna state government is not harmonising best practices in management across the local governments it supervises. There would seem to be significant potential for inter-governmental transfers of best-practice in management within and across tiers.

These statistics imply that one of the most important elements of the organizational environment for a civil servant, the quality of management she works under, is highly varied across organizations. The experience of being a civil servant at the federal organization at the top of the distribution in Figure 1 is likely to be substantially different to that of a civil servant in the state government at the bottom of the distribution. This variation is exhibited even within the state of Kaduna and across the Federal Government, where there are common sets of public service rules. Thus, these descriptives are evidence that formal rules are not driving a key feature of organizational practice.

We cannot compare our scores directly to those in other WMS studies, as the published z-scores are always defined within sample. However, we can focus on a single quantitative measure of management that can be compared across sectors. In our sample, 68% of the organizations never collect data on key performance indicators. Thus, the median management practice in the public sector is no activity on our index of monitoring. Lemos and Scur (2016) provide WMS assessments for a range of African firms. They note that the median African firm tracks most of their performance indicators formally, and specifically that those in Nigeria have tracking mechanisms of some sort. Thus, on a margin frequently argued to be key to productivity, the public sector falls well behind its private sector counterpart.

# **4 The Characteristics and Experiences of Civil Servants**

We now turn more fully to investigating those surveys that focussed on measuring the experience of the individual civil servant directly. We begin by describing further basic characteristics of the sample in each of the countries we study. Table 4 presents average statistics for each of the samples of civil servants interviewed. Column (1) presents a simple average across the country statistics available. Note again that Ethiopia’s surveys were both at the organization-level and so the country is not represented in this section.

In terms of the age pyramid, Table 4 describes how homogenous civil service averages are across most of the countries we study, with the Philippines acting as a slight outlier. The mean official is in their forties, with a standard deviation of roughly 10. The number of officials below 30 years of age is frequently below 10%, and many senior positions are filled by older members of the service.

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