metadata: authors: 0: author: Rasul,Imran
1: author: Rogger,Daniel Oliver
2: author: Williams,Martin J.
count: Ghana
docna: 0: docna: Management and Bureaucratic Effectiveness :
            Evidence from the Ghanaian Civil Service
docty: Policy Research Working Paper
subtopic: Economics and Finance of Public
            Institution Development,Public Sector Administrative and Civil
            Service Reform,Administrative & Civil Service Reform,Democratic Government,De Facto Governments,Public Sector Administrative & Civil
            Service Reform,Labor Markets,Rural Labor Markets,Customs and Trade
teratopic: Public Sector Development,Rural Development,International Economics and Trade,Governance,Social Protections and Labor
abstracts: cdata!: A burgeoning area of social science
            research examines how state capabilities and bureaucratic
            effectiveness shape economic development. This paper studies
            how the management practices of civil service bureaucrats
            correlate to the delivery of public projects, using novel
            data from the Ghanaian Civil Service. This paper combines
            hand-coded progress reports on 3,600 projects with a
            management survey in the government ministries and
            departments responsible for these projects. The analysis
            finds that management matters: practices related to autonomy
            are positively associated with project completion, yet
            practices related to incentives/monitoring of bureaucrats
            are negatively associated with project completion. The
            negative impact of incentives/monitoring practices is partly
            explained by bureaucrats having to multi-task, interactions
            with their intrinsic motivation, their engagement in
            influence activities, and project characteristics such as
            the clarity of targets and deliverable outputs. The paper
            discusses the interplay between management practices and
            corruption, alternative methods by which to measure
            management practices in organizations, and the external
            validity of the results. The findings suggest that the focus
            of many civil service reform programs on introducing
            stronger incentives and monitoring may backfire in some
            organizations, and that even countries with low levels of
            state capability may benefit by providing public servants
            with greater autonomy in some spheres.
geo_reg_key: 1927320,517191
repnme: repnme: Management and Bureaucratic Effectiveness :
            Evidence from the Ghanaian Civil Service
display_title: Management and Bureaucratic
            Effectiveness : Evidence from the Ghanaian Civil Service
listing_relative_url: /research/2018/09/30433734/management-bureaucratic-effectiveness-evidence-ghanaian-civil-service
topicv3: Labor Markets m1326488 855,Individual Performance Management m1326767 2058,Public Service Delivery m1326771 728,Public Administration m1327723 723,Human Resource Management m1504248 2598
publishtoextweb_dt: 2018-09-25T00:00:00Z
historic_topic: Public Sector Development,Rural Development,International Economics and Trade,Governance,Social Protections and Labor
no_of_pages: 60
author_keys: 0: author_key: 1230528
1: author_key: 1345389
model_extractions: WPS8595 Policy Research Working Paper 8595 Management and Bureaucratic Effectiveness Evidence from the Ghanaian Civil Service _Imran Rasul Daniel Rogger Martin J.Williams_ Development Economics Development Research Group September 2018
Policy Research Working Paper 8595

# **Abstract**

A burgeoning area of social science research examines how state capabilities and bureaucratic effectiveness shape economic development. This paper studies how the management practices of civil service bureaucrats correlate to the delivery of public projects, using novel data from the Ghanaian Civil Service. This paper combines hand-coded progress reports on 3,600 projects with a management survey in the government ministries and departments responsible for these projects. The analysis finds that management matters: practices related to autonomy are positively associated with project completion, yet practices related to incentives/monitoring of bureaucrats are negatively associated with project completion. The negative impact of incentives/monitoring practices is partly explained by bureaucrats having to multitask, interactions with their intrinsic motivation, their engagement in influence activities, and project characteristics such as the clarity of targets and deliverable outputs. The paper discusses the interplay between management practices and corruption, alternative methods by which to measure management practices in organizations, and the external validity of the results. The findings suggest that the focus of many civil service reform programs on introducing stronger incentives and monitoring may backfire in some organizations, and that even countries with low levels of state capability may benefit by providing public servants with greater autonomy in some spheres.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at drogger@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
management and bureaucratic effectiveness: evidence from the ghanaian civil service<sup>_⇤_</sup> imran rasul daniel rogger martin j.williams<sup>_†_</sup> _JEL Classification: J33, O20._

> _⇤_ We gratefully acknowledge financial support from the International Growth Centre [1-VCS-VGHA-VXXXX33301] and the World Bank’s i2i trust fund financed by UKAID. We thank Julien Labonne, Anandi Mani, Arup Nath, Simon Quinn, Ra↵aella Sadun, Itay Saporta-Eksten, Chris Woodru↵and seminar participants at Oxford, Ohio State, PMRC, and the EEA Meetings for valuable comments. Jane Adjabeng, Mohammed Abubakari, Julius Adu-Ntim, Temilola Akinrinade, Sandra Boatemaa, Eugene Ekyem, Paula Fiorini, Margherita Fornasari, Jacob Hagan-Mensah, Allan Kasapa, Kpadam Opuni, Owura Simprii-Duncan, and Liah Yecalo-Tecle provided excellent research assistance, and we are grateful to Ghana’s Head of Civil Service, Nana Agyekum-Dwamena, members of the project steering committee, and the dozens of Civil Servants who dedicated their time and energy to the project. This study was approved by UCL’s Research Ethics Committee. All errors remain our own.

> _†_ Rasul: University College London and the Institute for Fiscal Studies [i.rasul@ucl.ac.uk]; Rogger: World Bank Research Department [drogger@worldbank.org]; Williams: Blavatnik School of Government, University of Oxford [martin.williams@bsg.ox.ac.uk].
# **1 Introduction**

A burgeoning area of social science research examines how state capabilities shape economic development [Besley and Persson 2011, Acemoglu and Robinson 2012, Pepinksy _et al._ 2017]. Much attention has been placed on understanding the e↵ectiveness of government bureaucracies, a key component of state capability. Bureaucratic e↵ectiveness matters for macroeconomic outcomes such as growth and inequality, and for microeconomics given the presumption that successful micro-evaluations of interventions can lead to them being e↵ectively scaled-up by government.

Despite the importance of bureaucratic e↵ectiveness, economic analysis of public sector agents has largely focused on the selection, retention, and response to incentives of frontline public sector workers, or ‘street-level’ bureaucrats. In contrast, we contribute to a nascent body of work studying the vital middle-tier of bureaucrats working in central government civil services, who are responsible for policymaking, administrative functions and for supervising frontline workers [Bertrand _et al._ 2017, Finan _et al._ 2017]. Specifically, we study whether the management practices that this professional class of civil servant bureaucrats operate under correlate to the e↵ective delivery of projects their Ministries and Departments are responsible for.<sup>1</sup> We do so in the context of a lower middle-income country, Ghana, at a time when many developing countries are engaged in reforming bureaucracies in line with the ‘good governance’ agenda of the World Bank and United Nations [Goldfinch _et al._ 2012, Hasnain _et al._ 2012].

Our analysis focuses on the professional grades of technical and administrative bureaucrats within 45 Ministries and Departments. To quantify the delivery of public projects, we exploit the fact that each organization is required to provide quarterly and annual progress reports. These detail targets and achievements for individual projects the organization is charged to deliver. Progress reports cover the _entire_ range of bureaucratic activity, including project types that have been much studied, such as procurement and infrastructure, but also areas of activity that have been far less subject to quantitative study, such as policy development, advocacy, human resource management, budgeting and regulatory design. We use these progress reports to identify 3628 projects underway during 2015, and to hand-code each project’s initiation and full completion.

To measure the management practices bureaucrats operate under, we follow the methodological approach of Bloom and Van Reenen [2007], and Bloom _et al._ [2012] (henceforth BSVR). We adapt their management surveys to the Ghanaian public sector setting, taking account of insights from the public administration literature [Rose-Ackerman 1986, Wilson 1989]. We elicited details on management practices in an _individual_ survey administered to bureaucrats. The surveys

> 1There are well-documented reasons why management practices could have di↵erent impacts on middle-tier bureaucrats than for lower-tier frontline public sector workers [Dixit 2002]. The selection, objectives and motivations of middle-tier of bureaucrats might di↵er. The nature of work for middle-tier bureaucrats might also di↵er: they might need to multi-task, and the mapping between e↵ort inputs and observable output is perhaps more uncertain. Finally, there can be specific labor market rigidities applying to middle-tier bureaucrats, leading to di↵erent dynamic selection e↵ects than for frontline workers.

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enumerated senior bureaucrats in managerial roles, as well as the less senior bureaucrats they manage. In contrast to much of the earlier work on management, we can therefore reconstruct management practices based on alternative sets of respondents in the organization. The measure of management practices used for our baseline analysis averages management scores over the most senior divisional-bureaucrat reports. We later consider alternative constructs, based on all senior bureaucrats in an organization (a top-down view of management), or as elicited from lower-tier bureaucrats being managed (a bottom-up view of management).

For each organization we construct two dimensions of management practice: (i) the _autonomy_ provided to bureaucrats; (ii) the provision of _incentives and monitoring_ of bureaucrats. The essence of the BSVR approach is to capture a holistic set of practices along each dimension, rather than coding very formal and specific rules or compensation scheme structures in place. Importantly, this approach aims to capture the actual management practices being used in practice, not an idealized version of what the organization’s practices are supposed to be on paper.

The autonomy index captures the extent to which bureaucrats of all levels are empowered to make meaningful contributions into policy formulation and implementation processes, and the flexibility with bureaucrats can use their discretion in responding to project peculiarities and introducing innovations. There are long-standing views in the public administration literature on the importance of autonomy. As Rose-Ackerman [1986] describes, at one extreme lies the view that public agencies ought to delegate decision making to bureaucrats, relying on their professionalism and resolve to deliver public services [Simon 1983]. At the other extreme lies the Weberian view that, because bureaucrats are self-interested, only an entirely rules-based system that leaves little to the individual judgement of bureaucrats can ensure consistent and acceptable levels of public service.

The incentives/monitoring management index captures the extent to which an organization collects indicators of project performance, how these indicators are reviewed, and whether bureaucrats are rewarded for achievements reflected in these indicators. The use of performance incentives are a central part of ‘New Public Management’ agenda that has swept through government bureaucracies over the past three decades, yet the evidence base on such reforms remains thin, and mostly based on evidence from frontline workers rather than the kinds of middle-tier civil servant working in central Ministries that we focus on here.<sup>2</sup> _A priori_ the correlation between bureaucratic output and the provision of such incentives in _public sector_ settings is uncertain because: (i) bureaucrats might need to exert multiple e↵ort types, not all of which are measurable; (ii) the process by which inputs are converted to outputs is uncertain; (iii) there can be competing views on the right way to implement bureaucratic outputs; (iv) bureaucratic objectives are not clear cut; and (v) performance incentives might crowd out the intrinsic motivation of those selfselected into the public sector [Gneezy and Rustichini 2000, Benabou and Tirole 2006, Francois

> 2Perry _et al._ [2009] review 57 studies on pay for performance in the public sector and conclude ‘pay-forperformance continues to be adopted but persistently fails to deliver’. Finan _et al._ [2017] overview recent evidence.

3
and Vlassopoulos 2008, Besley and Ghatak 2018].

Our research design exploits the fact that _multiple_ organizations conduct similar project activities. We thus measure the partial correlation of management practices with public service delivery _within_ project type, namely, conditioning on project type fixed e↵ects and so accounting for unobserved heterogeneity in bureaucracies arising from the composition of projects they are tasked to implement. Our key results are as follows.

First, codifying the progress reports reveals the importance of non-infrastructure projects in the work of bureaucracies. The most common project type in Ghanaian central government bureaucracies relates to human resource management. Comprising 29% of all projects, this reinforces the importance of understanding whether the management practices bureaucrats operate under correlate to bureaucratic e↵ectiveness. 23% of projects relate to policy advocacy and development, while the two traditional areas of quantitative study, infrastructure and procurement, together comprise around a third of projects.

Second, management practices robustly correlate with the project completion success of civil service bureaucracies. The two dimensions of management practice emphasized by the public administration and economics literatures, autonomy and incentives/monitoring, robustly correlate to project completion rates. However, they have _opposing_ correlations with project delivery: a one standard deviation increase in management practices related to providing autonomy to bureaucrats is associated with a 25% increase in the likelihood a project is initiated and a 28% increase in the likelihood it is fully completed; in contrast, a one standard deviation increase in management practices related to the provision of incentives or monitoring to bureaucrats is associated with a 28% _decrease_ in the likelihood a project is initiated, and a decrease of 18% in the likelihood it is fully completed. These magnitudes are of economic as well as statistical significance, against the backdrop that 21% of public sector projects are never started and only 34% are fully completed.

A chief concern in interpreting results is that management practices might be endogenous to organizational performance, so that the negative result could in part pick up the fact that if an organization has low project completion rates, it increases the provision of incentives/monitoring to its bureaucrats. We address such reverse causality using an instrumental variables strategy that exploits the fact that similar interviews on management practices had previously been undertaken for a subset of the same civil service organizations in 2013, by one of us in a separate and independent study [Williams 2015]. We thus instrument current practices related to incentives/monitoring with each organization’s historic practices along the same dimension, exploiting the persistence of management practices within organizations [Gibbons and Henderson 2013]. The exclusion restriction requires that past management practices related to incentives/monitoring only impact current project delivery through their persistent e↵ects on contemporaneous management practices related to incentives/monitoring. These IV estimates continue to find a statistically significant negative e↵ect of incentives/monitoring on project completion, and suggest that the OLS results may actually underestimate the negative conditional e↵ects of incentives/monitoring. We consider this 4
suggestive evidence that our core results are not driven by reverse causality.

To understand the mechanisms driving this negative e↵ect, we then investigate four channels suggested by incentive theory through which the detrimental impacts of management practices related to incentives/monitoring for bureaucrats might occur. First, bureaucrats might need to multi-task in their work environment, needing to exert some types of e↵ort that can be labelled as ‘processing’ and does not directly increase project completion rates, while also needing to exert more productive types of e↵ort that do raise project completion rates. Our management practice measure might then capture an incentive system that places excessive regulatory burden or ‘red tape’ on bureaucrats that has been argued to cause bureaucrats to mis-allocate e↵ort towards processing activities [Kelman 1990, Baker 2002]. Consistent with this, we find the negative partial correlation between incentives/monitoring and project completion rates is even _more negative_ when bureaucrats need to coordinate/negotiate internally with other bureaucrats in their organization, or need to coordinate with external stakeholders.

Second, incentives/monitoring might crowd out the intrinsic motivation of bureaucrats. To investigate this, as part of our civil servants survey we measured the public service motivation (PSM) of bureaucrats, using an abbreviated version of the standard Perry scale [Perry 1996]. We find the negative impact of management practices related to incentives/monitoring are partly ameliorated when bureaucrats in the organization score higher on the PSM dimensions of ‘compassion’ and ‘public interest’. As in Ashraf _et al._ [2014], our evidence thus suggests incentives/monitoring _crowd-in_ the e↵ort of intrinsically motivated bureaucrats, partly (but not entirely) ameliorating the negative e↵ects of practices related to incentives/monitoring.

Third, management practices related to incentives/monitoring might be subject to _subjective_ performance evaluation (SPE). While SPE has the benefit of being based on a more holistic set of assessments, such subjective assessments also give rise to other biases and dysfunctional responses, especially the desire of agents to engage in influencing activities to curry favor with superiors [Milgrom 1988, Milgrom and Roberts 1988]. If so, the increased use of such mis-targeted incentives or key performance indicators can lead bureaucrats reallocating e↵ort towards non-productive tasks, _reducing_ project completion rates. We examine this hypothesis using two measures of the social connections between non-senior bureaucrats to their senior managers: whether they overlapped in time at university, and whether they belong to the same ethnic group. Along both dimensions of connectedness, we find the negative impact of incentives/monitoring on project completion becomes significantly worse.

Fourth, there might be specific project characteristics, such as the clarity of their target or output, that impact the ability of organizations to put together a well-designed set of incentive/monitoring practices. We find there is a far more detrimental impact of practices related to incentives/monitoring for projects that have poorly defined targets, that might well reflect incentive misalignment. On the clarity of the output to be delivered, we find the absolute impacts of both dimensions of management practice are far larger for projects with high output clarity. This 5
is again consistent with incentive misalignment: when outputs are well defined _ex post_ , granting bureaucrats discretion over how to implement projects is likely to be more e↵ective since abuse of that discretion will be easier to detect _ex post_ . The negative association of incentives/monitoring with output, conditional on autonomy, is then likely to be greater.

Finally, we discuss three remaining important issues related to management practices in bureaucracies: (i) the interplay between management practices and corruption in service; (ii) alternative methods by which to measure management practices in organizations; and (iii) the external validity of our findings linking management practices and project delivery.

On corruption, a long-standing literature in public administration emphasizes that civil servants might pursue their own self-interest [Wilson 1989]. This more negative view of bureaucrats spurs us to explore how the partial correlations between project completion rates and management practices are mediated through perceptions of corruption. We find that for multiple measures of corruption, there is no evidence that the provision of autonomy to bureaucrats leads to a significantly lower likelihood of project completion. This suggests there are few bureaucrats on the margin of being corrupt, for whom small changes in management practices related to autonomy lead to large changes in corrupt behavior. At the same time, we find some evidence that the negative consequences of corrupt practices are partially o↵set by the provision of incentives or monitoring of bureaucrats.

On measuring management practices, we find that there are di↵erences between top-down and bottom-up views of management. While our core results are robust to these di↵erent measurement approaches, our results highlight that there remains scope for research to understand _why_ bottom-up views of management do not coincide with top-down views, and whether organizational discord measured this way might capture important elements of organizational functioning and be predictive of their performance.

The final issue we turn to is that of the external validity of our findings. To do so it is most natural to compare our findings from Ghana to our earlier work on management practices for middle-tier bureaucrats in the Federal Civil Service of Nigeria [Rasul and Rogger 2018, henceforth RR]. A common set of results emerge across the Ghanaian and Nigeria contexts: (i) the provision of autonomy is robustly positively correlated with project initiation, full completion and completion rates; and (ii) incentives/monitoring of bureaucrats is robustly negatively correlated with project initiation, full completion and completion rates in both settings. Moreover, the estimates show similar e↵ect sizes of both dimensions of management practice on the initiation and full completion margins, in which the two settings are most comparable. While not an exact replication, establishing robust findings across similar contexts underpins the external validity of any given study, and so moves the knowledge frontier closer to establishing stylized facts.

Overall, our results point to new directions for theoretical research to better understand the contracting environment in public bureaucracies [Dixit 2002], and lay out an agenda for future research using field experiments to establish causal impacts of management practices in bureaucra6
cies on public service delivery and state capabilities more broadly. Our findings also suggest that the overwhelming focus of many civil service reform programs on introducing stronger incentives and monitoring may backfire in at least some public sector organizations, and that even countries with low overall levels of bureaucratic e↵ectiveness or state capability may benefit by providing their public servants with greater autonomy in some spheres.

The paper is organized as follows. Section 2 describes the Ghanaian context, data sources and key measures of project completion and management practices. Section 3 presents our empirical method and main results. Section 4 unpacks the drivers behind the robust _negative_ partial correlation we find between project completion rates and management practices related to incentives/monitoring. Section 5 further discusses the interplay between management practices and corruption, alternative approaches to measuring management practices, and the external validity of our findings. Section 6 concludes. The Data Appendix provides details on data sources and further robustness checks.

# **2 Context and Data**

Ghana is a West African state home to 28 million individuals. Its central government bureaucracy is structured along lines reflecting its British colonial origins, where Ministries are the central coordinating authority. We study 45 Ministries and Departments in the Civil Service. These are all located in Accra, but have remit over public projects implemented nationwide.<sup>3</sup> Ministries and Departments are overseen by the Office of the Head of Civil Service (OHCS), that is responsible for personnel management and performance within the civil service. OHCS coordinates and decides on all hiring, promotion, transfer, and (in rare circumstances) firing of bureaucrats across the service. While OHCS develops and promulgates official management regulations and processes, Ministries’ and Agencies’ compliance with these is imperfect, with the result that actual management practices are highly variable across organizations.

Our analysis of bureaucrats focuses on the professional grades of technical and administrative officers within these Ministries and Departments. We therefore exclude grades that cover cleaners, drivers, most secretaries, etc. On average, each organization employs 64 bureaucrats of the type we study (those on professional grades), although there is a considerable degree of variation in their size: the organization at the 25th percentile of employee size employs 33 bureaucrats, while the organization at the 75th percentile employs 72 bureaucrats. We designate bureaucrats as being at either a senior or non-senior level. Seniors are those that classify themselves as a ‘Director (Head of Division) or Acting Director’ or as a ‘Deputy Director or Unit Head (Acting or Substantive)’.

> 3Ghana makes a distinction between the Civil Service and the broader Public Service, which includes dozens of autonomous agencies under the supervision but not direct control of their sector ministries, as well as frontline implementers such as the Police Service, Education Service etc. Our sample is restricted to the Civil Service and excludes non-Civil Service government organizations.

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By this definition, the span of control of senior bureaucrats over non-seniors is around 4 _._ 52, but again there is considerable variation across Ministries.<sup>4</sup> Around 45% of bureaucrats are women, 70% have a university education, and 31% have a postgraduate degree (seniors are more likely to be men, and have a postgraduate degree). As in other state organizations, civil service bureaucrats enjoy stable employment once in service: the average bureaucrat has 14 years in service, with their average tenure in the current organization being just under 9 years. This reflects some of the rigidities in the labor market for bureaucrats: appointments are made centrally by OHCS, bureaucrats enjoy secure tenure and transitions between bureaucracies are infrequent.

Our analysis is based on two data sources. First, we hand-coded quarterly and annual progress reports from Ministries and Departments, covering projects ongoing between January and December 2015. As detailed below, these reports enable us to code the individual projects under the remit of each organization, and the extent to which they are initiated or successfully completed. Second, we surveyed 2971 bureaucrats from all 45 civil service organizations over the period August to October 2015. Our civil servant survey covers 75% of _all_ professional bureaucrats in service, with 20% of interviewees being seniors. As detailed below, civil servants were questioned on topics including their background characteristics and work history in service, job characteristics and responsibilities, engagement with stakeholders outside the civil service, perceptions of corruption in the service, and their views on multiple dimensions of management practices. It is this last survey module from which we derive measures of management practice for each organization.

# **2.1 Coding Projects and Completion**

Worldwide, civil service bureaucracies di↵er greatly in whether and how they collect data on their performance. Unlike data related to the macroeconomy, households, firms, schools or labor markets, central statistical agencies are typically not involved in measuring government e↵ectiveness, and few international standards exist to aid cross country comparisons. To therefore quantify the delivery of public sector projects in our context, we exploit the fact that each Ghanaian civil service organization is required by OHCS to provide quarterly and annual progress reports. Organizations di↵er in their reporting formats and coverage, and some either did not produced reports for this time period or produced them in a format that was infeasible to code. We are thus able to use the progress reports of 30 Ministries and Departments (and our civil servant survey covers 2247 bureaucrats in these 30 organizations). Figure A1 provides a snapshot of a typical progress report and indicates the information coded from it, and the Data Appendix discusses the coding

> 4In Ghana, grades of technical and administrative bureaucrats are officially referred to as ‘senior’ officers while grades covering cleaners, drivers etc. are referred to as ‘junior’ officers, regardless of their tenure or seniority. While we restrict our sample to ‘senior’ officers in the formal terminology, throughout we use the terms senior and non-senior in their more colloquial sense to refer to hierarchical relationships within the professional grades.

8
process in detail.<sup>5</sup> Progress reports cover the _entire_ range of bureaucratic activity. While some of these projects are public-facing, others are purely internal functions or intermediate outputs. We were able to use quarterly and annual progress reports from bureaucracies to identify 3628 projects underway during 2015. The projects undertaken by each organization in a given year are determined through an annual planning and budgeting process jointly determined between: (i) the core executive, mainly the Ministry of Finance and the sector minister representing government priorities; (ii) the organization’s management, based in large part on consultatively developed medium-term plans; and (iii) ongoing donor programs. This schedule of projects is formalized in the organization’s annual budget (approved by Parliament) and annual workplan. The quarterly and annual reports that we use to code project completion thus detail the projects that the organization’s workplan committed the organization to working on during the time period of study.

Progress reports detail targets and achievements for individual projects the organization is charged to deliver. The Appendix describes how we hand-coded and harmonized the information to measure projects and project completion across the Ghanaian civil service. Three key points are of note in relation to this process. First, each quarterly progress report was codified into project line items using a team of trained research assistants and a team of civil servant officers seconded from the Management Services Department (MSD), an organization under OHCS tasked with analyzing and improving management in the civil service. MSD officers are trained in management and productivity analysis and frequently review organizational reports of this nature, making them ideally suited to judging project characteristics and completion.

Second, coders were tasked to record project completion on a 1-5 scoring grid, where a score of one corresponds to, “No action was taken towards achieving the target”, three corresponds to, “Some substantive progress was made towards achieving the target. The output is partially complete and/or important intermediate steps have been completed”, and a score of five corresponds to, “The target for the output has been reached or surpassed.” Projects can be long-term or repeated (e.g. annual, quarterly) projects. There were at least two coders per project. Given the tendency for averaging scores across coders to reduce variation, we use the maximum and minimum scores to code whether projects are fully complete/never initiated respectively (we later show robustness of our main result to alternative algorithms to aggregate scores).

Third, as progress reports are self-compiled by bureaucracies, an obvious concern is that low performing bureaucracies might intentionally manipulate their reports to hide the fact. To check the validity of progress reports, we matched a sub-sample of 14% of projects from progress reports to project audits conducted by external auditors through a separate exercise undertaken by OHCS. Auditors are mostly retired civil servants, overseen by OHCS, and they obtain documentary proof of project completion. For matched projects, 94% of the completion levels we code are corroborated 5 Where an organization produced multiple reports during this time (e.g. a mid-year report and an annual report), we selected the latest report produced during the year to include in our sample.

9
based on the qualitative descriptions of completion in audits.<sup>6</sup>

# **2.2 What Do Bureaucrats Do?**

The data reveals the importance of non-infrastructure projects in the work of bureaucracies. Figure 1A shows the most common project type in Ghanaian central government bureaucracies relates to human resource management (‘monitoring, training and personnel management’). Comprising 29% of all projects, this reinforces the importance of understanding whether the management practices bureaucrats operate under correlate to bureaucratic e↵ectiveness. The Figure also shows that 23% of projects relate to policy advocacy and development, while the two traditional areas of quantitative study, infrastructure and procurement, together comprise around a third of projects.

In Figure 1B, each bar corresponds to a project type, and within-bar colors signify projects conducted by a given organization. This reveals that: (i) the same project type is implemented by multiple organizations; (ii) each organization is tasked to implement multiple project types. Hence a lack of specialization is a fundamental feature of the Ghanaian civil service. Such a lack of specialization was also an inherent feature documented in RR in the context of the Nigerian Civil Service. We thus exploit a research design that measures the partial correlation of management practices with public service delivery _within_ project type, so accounting for unobserved heterogeneity in bureaucracies arising from the composition of projects they are tasked to implement. If project types vary in the optimal set of management practices, this lack of specialization leaves more scope for management practices to matter on the margin (even conditional on project type fixed e↵ects). This situation can persist given the rigidities in the labor market for bureaucrats, which slows down the di↵usion of information on best management practices.

Table 1 and Figure 2 show how bureaucratic output varies by project type. Table 1 reiterates that all project types are implemented by the majority of organizations. On completion rates, the first bar in Figure 2 shows that 21% of projects are never started (i.e. are recorded as a one on the scoring card); 34% are fully completed. The variation on the extensive margin of project completion varies by project type. For example, procurement projects are more than twice as likely not to be initiated as permits and regulation projects. However, there is considerable variation in average completion rates even within project types (Column 5, Table 1).

Figure 3 focuses on the variation in completion rates across civil service organizations. To quantify this variation, we note that the 75th percentile organization has an average completion rate 22% higher than 25th percentile organization. This variation occurs despite the fact that multiple organizations engage in similar project types, they are assigned hires from the same pool of incoming bureaucrats, and they are located close to each other in Accra.<sup>7</sup> Figure 3 further

> 6Among the handful of non-corroborated projects, the lowest “true” completion rate was a 3, indicating that the rare instances of misreporting were relatively minor.

> 7As we use the minimum and maximum of reports for the extensive margin of project output, it is possible that the percentage of initiated projects is below that for completed projects, as occurs in one organization.

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highlights the weak link between the proportion of projects initiated by an organization, and the proportion of projects actually completed. Our empirical analysis considers the impacts of management practices on the initiation, completion and progression of projects.

Table 2 presents descriptive evidence on the public service delivery of the 10 organizations that implement the most projects. This reiterates the lack of specialization in the kinds of projects that each organization is tasked to implement (among these 10 organizations, they are tasked with between 4 and 7 unique project types). The Table also reiterates that there is huge variation across organizations in their measured bureaucratic e↵ectiveness. This all suggests there might be important organizational factors correlating with this variation in e↵ectiveness. Our focus is on one such factor: the management practices civil service bureaucrats operate under.

# **2.3 Measuring Management**

We follow BSVR’s approach to measuring management practices, but first adapt their procedures and survey to the Ghanaian public sector setting. Survey team leaders were recruited from the private sector, with an emphasis on previous experience of survey work in Ghana. We worked closely with the team leaders to give them an appreciation and understanding of the practices and protocols of the public service. We then collaborated with OHCS to recruit junior public officials with pre-existing experience of public sector work to act as our enumerators. The Head of Service ensured their commitment to the survey process by stating the research team would monitor enumerator performance and that these assessments would influence future posting opportunities. We trained the team leaders and public officials jointly, including intensive practice interview sessions, before undertaking the first few interviews together. This approach allowed us to capitalize on both the experience of our private-sector team leaders and the knowledge of our public sector enumerators.

Over the period to August to November 2015, our enumerators interviewed 2971 bureaucrats employed at 45 organizations. This constitutes 98% of all eligible sta↵in these organizations, with the remainder mostly having been out of the office during the survey period. Interviews were conducted in person, but were double-blind in the sense that interviewers had never worked in the organizations in which they were interviewing and did not know the names of their interviewees, and likewise interviewees did not know the names of their interviewers.

We adapted BSVR’s methodology to cover six dimensions of management practice: roles, flexibility, incentives, monitoring, staffing and targets. Table A1 details each management related question, by topic, as well as the 1-5 scoring grid used by our enumerators for each question. There are 14 questions in total over the six topics.

To provide a sense of the holistic nature of these questions, a question on practices related to bureaucratic flexibility was, “Does your division make e↵orts to adjust to the specific needs and peculiarities of communities, clients, or other stakeholders?”. Following BSVR, enumerators 11
would then probe respondents’ responses and ask for examples, and then score responses on a continuous 1-5 scale, where for indication the scoring grid described a score of one as corresponding to circumstances where, “The division uses the same procedures no matter what. In the face of specific needs or community/ client peculiarities, it does not try to develop a ‘better fit’ but automatically uses the default procedures.”; a score of three corresponded to, “The division makes steps towards responding to specific needs and peculiarities, but stumbles if the specific needs are complex. Often, tailoring of services is often unsuccessful.”; and a score of five corresponded to, “The division always redefines its procedures to respond to the needs of communities/ clients. It does its best to serve each individual need as best as it can.” We elicited information on management practices in _individual_ surveys administered to bureaucrats. The surveys enumerated both those in managerial roles, as well as bureaucrats being managed by seniors. In contrast to much of the earlier work on management, we can therefore reconstruct management practices based on alternative sets of respondents in the organization. The measure of Ghanaian management practices we use for our core analysis averages management scores over the most senior divisional-bureaucrat reports. The median (mean) number of senior managers per organization is 13 (20). This retains the closest similarity to the way in which management practices were elicited in RR. However, we later show robustness to alternative constructs for management practices in organizations, based on all senior bureaucrats in an organization (a top-down view of management), or as elicited from lower-tier bureaucrats being managed (a bottom-up view of management).

The answers to questions on roles and flexibility are then combined to produce a measure of management practices related to autonomy, denoted CS-autonomy. Similarly, the answers to questions on incentives and monitoring scores are combined to produce a CS-incentives/monitoring measure of management practices. The answers to questions on staffing and targeting topics are combined into a CS-other measure of management practices. The scores on each practice are converted into normalized z-scores by taking unweighted means of the underlying z-scores (so are continuous variables with mean zero and variance one by construction), where both are increasing in the notion of ‘better management’. For the CS-autonomy index, we assume greater autonomy corresponds to better management, and for the CS-incentives/monitoring measure we also assume the provision of incentives/monitoring corresponds to better management practices (as suggested to be so in private sector settings [Prendergast 1999]).<sup>8</sup> The CS-autonomy and CS-incentives/monitoring management scores are positively correlated ( _⇢_ = _._ 67) suggesting complementarity of these practices, but this did not have to be so. For example, substitution between practices could occur if bureaucrats have career concerns, and so performance incentives are not required once autonomy is provided. Alternatively, if bureaucrats

> 8These z-scores are constructed using data for all 45 organizations we can construct management practices for based on our civil servant survey. To address concerns over sample selection, we later show robustness of our main finding to redefining the z-scores based only on the 30 organizations for which project completion data exists.

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are intrinsically motivated they might need only to be provided autonomy, and the provision of explicit incentives might crowd out their intrinsic motivation. Importantly, the partial correlations of these two dimensions of management can still be separately estimated from each other and from the CS-other practices index.<sup>9</sup>

# **2.4 Management Practices Across Civil Service Organizations**

Figure 4 shows the across-organization variation in management practices, using our preferred aggregation of survey responses over the most senior divisional-bureaucrats. As with bureaucratic performance on projects, there is high variation in the management practices bureaucrats are subject to across organizations. For practices related to the provision of autonomy, the 75th percentile organization has a CS-autonomy score that is 145% higher than 25th percentile organization. On management practices related to incentives/monitoring, the 75th percentile organization has a CSincentives/monitoring score that is 97% higher than 25th percentile organization. To reiterate, this variation occurs despite the fact that all organizations share the same colonial and post-colonial structures, are governed by the same civil service laws and regulations, are overseen by the same supervising authorities, are assigned new hires from the same pool of incoming bureaucrats each year, and are located proximately to each other in Accra.<sup>10</sup> It is this variation in management practices along the dimensions of the autonomy given to bureaucrats, and the extent to which they are provided incentives or monitoring, that we now link to variation in project completion rates.

9 The CS-autonomy (CS-incentives/monitoring) index has a correlation of _._ 59 ( _._ 70) with CS-other.

> 10To provide practical detail on what drives this variation in management scores, we go back to consider the raw management scores in Table A1. In relation to the component of the autonomy score based on the question, “When senior sta↵in your division are given tasks in their daily work, how much discretion do they have to carry out their assignments? Can you give me an example?”, we note that 45% of organizations score between 3 _._ 75 and 5 (and so are closer to practices where, “Officers in this division have a lot of independence as to how they go about their daily duties”, while the remaining 55% of organizations score below 3 _._ 75 (and so are closer to practices where, “Officers in this division have no real independence to make decisions over how they carry out their daily assignments. Their activities are defined in detail by senior colleagues or organizational guidelines.” Similarly, in relation to the component of incentives/monitoring that asks, “Does your division use performance, targets, or indicators for tracking and rewarding (financially or non-financially) the performance of its officers?”, we note that 52% of organizations score between 1 and 3 _._ 75 (and so are closer to the practice where, “Officers in the division are rewarded (or not rewarded) in the same way irrespective of their performance. The evaluation system awards good performance in principle (financially or non-financially), but awards are not based on clear criteria/processes”, and the remaining 48% of organizations score between 3 _._ 75 and 5 (and so are closer to practices where, “Rewards are given as a consequence of well-defined and monitored individual achievements.”).

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# **3 Empirical Method and Main Results**

## **3.1 Method**

The unit of observation is project _i_ of type _j_ in organization _n_ . We estimate the following OLS specification, _yijn_ = _γ_ 1 _CS_ - _autonomyn_ + _γ_ 2 _CS_ - _incentives/monitoringn_ + _γ_ 3 _CS_ - _othern_ + _β_ 1 _PCijn_ + _β_ 2 _OCn_ + _λj_ + _✏ijn_ (1) where _yijn_ is either an indicator of whether the project is initiated, whether it is fully completed (both extensive margin outcomes), or a continuous measure of the project completion rate (the intensive margin). Management practices are measured using the CS-autonomy, CSincentives/monitoring and CS-other indices, and _PCijn_ and _OCn_ are project and organizational controls.<sup>11</sup> As Figure 1B highlighted, many organizations implement the same project type _j_ , so we can control for project type fixed e↵ects _λj_ in (1), as well as fixed e↵ects for the broad sector the implementing organization operates in.<sup>12</sup> The partial correlations of interest are _γ_ 1 and _γ_ 2, the e↵ect size of a one standard deviation change in management practices along the respective margins of autonomy and incentives/monitoring. To account for unobserved shocks, we cluster standard errors by organization ( _n_ ), the same level of variation as management practices. In the Appendix we show robustness of our main results to alternative levels of clustering.

## **3.2 Main Results**

Table 3 presents our main results. Columns 1 to 4 focus on the outcome of full project completion. A robust set of findings emerge across specifications: (i) management practices providing bureaucrats more autonomy are robustly positively correlated with the likelihood of project completion ( _γ_ b1 _>_ 0); (ii) management practices related to the provision of incentives or monitoring to bureaucrats are robustly _negatively_ correlated with the likelihood of project completion ( _γ_ b2 _<_ 0). The

> 11Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one o↵, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Following BVSR, we condition on ‘noise’ controls related to the management surveys. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer.

> 12Project type fixed e↵ects relate to whether the primary classification of the project is listed as Advocacy and Policy Development, Financial and Budget Management, ICT Management and Research, Monitoring/Training/Personnel Management, Physical Infrastructure, Permits and Regulation, or Procurement. Sector fixed e↵ects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector.

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remaining Columns show similar partial correlations of both dimensions of management practice with project initiation (Column 5) and the continuous measure of project completion rate (Column 6). On magnitudes, taking our preferred specification (1) shown in Column 3, a one standard deviation increase in management practices related to CS-autonomy increases the likelihood a project is initiated by 25%, and it increases the likelihood it is fully completed by 28%; a one standard deviation increase in management practices related to CS-incentives/monitoring decreases the likelihood a project is initiated by 28%, and it decreases the likelihood it is fully completed by 18%. These magnitudes are of economic as well as statistical significance: recall the backdrop here is that 21% of projects are never started and only 34% are fully completed.<sup>13</sup> Our core finding thus confirms the two dimensions of management practice emphasized by the public administration and economics literatures do indeed robustly correlate to e↵ective public service delivery in the Ghanaian context. The positive correlation of CS-autonomy with project completion supports the notion bureaucracies could delegate some decision making to civil servants, relying on their professionalism and resolve to deliver public services. The evidence is less supportive of the notion that when bureaucrats have more agency, they are more likely to pursue their own, potentially corrupt, objectives that diverge from societal interests. We return to the issue below, when we discuss the interplay between management and corruption in service.

The _negative_ partial correlation between project completion rates and management practices related to the provision of incentives and monitoring of bureaucrats, runs counter to a body of evidence from private sector settings. As described earlier, evidence on the impacts of performancerelated incentives in _public_ sector settings is mixed (and often based on frontline workers or streetlevel bureaucrats) [Perry _et al._ 2009, Banerjee _et al._ 2014, Khan _et al._ 2018]. Moreover, Finan _et al._ [2017] review the evidence base on the impacts of monitoring in public organizations, including studies highlighting how this can often lead to gaming/circumventing monitoring systems. Our findings reinforce the evidence base suggesting the possibility that management practices related to incentives and monitoring negatively correlate to outputs of the professional tier of civil service _bureaucrats_ across contexts.

Appendix Table A2 provides a battery of checks on our baseline estimates. These show the results to be robust to alternative codings of completion rates, samples, estimation methods, and fixed e↵ects specifications.<sup>14</sup> Appendix Table A3 further shows the results to be robust to

> 13Given the management practices are positively correlated to each other, this also implies that only controlling for incentives/monitoring leads _γ_ b2 to be biased upwards as CS-autonomy is omitted. Similar biases arise from a traditional public administration perspective that might only focus on the provision of autonomy.

14More precisely, we first redefine project completion rates to be the average of the codings of the two enumerators designated to each progress report. The result in Column 2 shows the baseline results continue to hold even when we reduce the variation in completion rates this way. Column 3 excludes projects implemented by the largest organization in terms of number of projects; Column 4 excludes the five smallest organizations by number of projects. Columns 5 and 6 exclude organizations at the top and bottom of the CS-autonomy and CS-incentives/monitoring management scales respectively. Column 7 uses only the 30 organizations for whom we have coded project completion data for, to define the management z-scores (and so does not define the z-scores based on all 45 organizations for which these scores are available based on our civil servant survey). Column 8 reports the result of estimation 15
alternative clusterings of the standard errors, including robust standard errors, allowing them to be clustered by project type within organization (so at the _jn_ level), by project type within sector, and by sector. In all cases, the coefficients of interest, _γ_ 1 and _γ_ 2, remain precisely estimated and statistically di↵erent from zero at conventional significance levels ( _p < ._ 05 throughout).

# **3.3 IV**

Before digging deeper into what drives the _negative_ partial correlation between project completion rates and incentives/monitoring of bureaucrats, we first present additional evidence that this might represent a causal relationship. A chief concern is that management practices are endogenous to organizational performance, so the negative result could reflect that if an organization has low project completion rates, it increases the provision of incentives/monitoring to its bureaucrats.

We address such reverse causality using an IV strategy that exploits the fact that similar interviews on management practices had previously been undertaken for a subset of the same organizations in 2013, by one of us in a separate and independent study [Williams 2015]. While these interviews were primarily qualitative and on a much smaller scale (based on one or two senior bureaucrats in each organization), they also took a similar semi-structured format and adapted the approach of BSVR, coding the quality of each management practice on a 1-5 scale, with overall organization z-scores compiled in the same way.

Table A4 details the questions on management practices administered in the 2013 interviews. While the same six topic areas were covered as in our 2015 survey, there is a far more limited set of questions on the topic of bureaucrat roles, which meant it was not possible to reconstruct a measure of CS-autonomy from the 2013 data. We therefore focus on exploiting the earlier measure of management practices related to the provision of incentives/monitoring, as measured two years prior to the main management and project completion measures used for the core analysis. We instrument current practices related to incentives/monitoring with the historic practices along the same dimension of management. The exclusion restriction requires that past management practices related to incentives/monitoring only impact current project delivery through their persistent e↵ects on management practices on this dimension.

Table 4 shows the results. Column 1 replicates our baseline OLS specification in the subsample of 18 organizations for which management practices related to incentives/monitoring are available from 2013 (and so can be used for the IV strategy).<sup>15</sup> Our baseline results continue to hold, b b although the e↵ect sizes are smaller than in the full sample ( _γ_ 1 _,OLS_ = _._ 04, _γ_ 2 _,OLS_ = _−._ 09), but are both estimated with similar if not greater precision. Column 2 shows the first stage and demonstrates the strength of the instrument: the first stage F-statistic is over 100. There is high

> a specification analogous to (1) but using a fractional regression to account for the fact that project completion rates lie between zero and one. Finally, in Column 9 we control for project-sector level fixed e↵ects (so allowing for sector specific impacts of project types).

> 15As we only have 18 organizations in these specifications, we do not control for general and capital controls.

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persistence in management practices related to incentives/monitoring over time: the first stage correlation is _._ 44 ( _p <_ 0 _._ 01). Column 3 then shows the second stage IV estimates, using project completion as the outcome. The IV estimate on CS-incentives/monitoring is larger in absolute b value than the OLS estimate ( _γ_ 2 _,IV_ = _−._ 27), suggesting OLS is upwards biased and attenuated. The remaining Columns show the IV results are also supportive of a causal interpretation in relation to the other outcome margins of bureaucratic e↵ectiveness considered: project initiation (Column 4) and the continuous measure of project completion (Column 5). Contrary to the concern that reverse causality could be driving or exaggerating the negative association between incentives/monitoring and project completion, the IV results suggest that (if anything) the OLS estimates understate the true negative e↵ect.

# **4 Unpacking the Negative E↵ect of Incentives/Monitoring**

Incentive theory provides many explanations why incentives/monitoring might be ine↵ective or backfire in public sector contracting environments [Dixit 2002, Besley and Ghatak 2005, Finan _et al._ 2017]. Our data allows us to study four mechanisms in more detail. First, bureaucrats might need to multi-task in their work environment, where they need to exert some types of e↵ort that can be labelled as ‘processing’, and do not directly increase project completion rates, while also needing to exert more productive types of e↵ort that raise project completion rates. Our management practice measure might then capture an incentive system that places excessive regulatory burden or ‘red tape’ on bureaucrats that has been argued to cause bureaucrats to mis-allocate e↵ort towards processing activities [Kelman 1990, Baker 2002]. Second, incentives/monitoring might crowd out the intrinsic motivation of bureaucrats [Perry and Wise 1990, Benabou and Tirole 2006, Francois and Vlassopoulos 2008, Besley and Ghatak 2018]. Third, our holistic management practices related to incentives/monitoring might pick up _subjective_ performance evaluation (SPE). While SPE has the benefit of being based on a more holistic set of assessments, such subjective assessments also give rise to other biases and dysfunctional responses, especially the desire of agents to engage in influencing activities to curry favor with seniors [Milgrom 1988, Milgrom and Roberts 1988]. If so, the increased use of such mis-targeted incentives or key performance indicators can lead bureaucrats reallocating e↵ort towards non-productive tasks, _reducing_ project completion rates. Fourth, there might be specific project characteristics, such as the clarity of their target, that impact the ability of organizations to put together a well-designed set of incentive/monitoring practices.

## **4.1 Multi-tasking**

Table 5 examines whether bureaucrats might face multi-tasking concerns. We do so by considering two organization-level measures of environments in which bureaucrats will need to exert 17
multiple kinds of e↵ort to push forward projects. We first examine whether the impact of incentives/monitoring practices varies with the ethnic fractionalization of bureaucrats in the organization. Such ethnic di↵erences internal to an organization capture di↵ering policy preferences over how projects should be designed, prioritized, or implemented [Rasul and Rogger 2015]. In such environments, bureaucrats might then need to exert multiple types of e↵ort to negotiate around these concerns and get projects completed. Column 1 shows the marginal impact of incentives/monitoring on project completion rates is indeed even more negative if there is greater ethnic fractionalization of bureaucrats in the organization.<sup>16</sup> On multi-tasking concerns relating to external e↵ort, we next examine whether the negative impact of incentives/monitoring becomes exacerbated in organizations where a greater share of their projects require engagement with stakeholders outside of their organization. This set of stakeholders includes members of civil society, Ministers/Members of parliament, Member(s) of the Metropolitan/Municipal/District Assemblies (MMDAs - local government units), the private sector, traditional authorities, community or religious group(s), and the media. The result in Column 2 shows the marginal impact of incentives/monitoring on project completion rates is even more negative in organizations where there is a greater need to coordinate with such external stakeholders.

Both results suggest that when the environment faced by bureaucrats requires them to exert multiple forms of e↵ort to push forward projects - due either to a greater need to coordinate/negotiate internally or to coordinate with external stakeholders - it becomes harder to design and instigate e↵ective forms of incentives/monitoring. In such multi-tasking environments where not all e↵orts can be measured or monitored to the same extent, organizations tend to have worse outcomes because practices related to incentives/monitoring might be poorly designed and not be holistic enough to encourage all forms of e↵ort required for successful project completion.

# **4.2 Intrinsic Motivation**

A long established literature suggests those that self-select into public service might be relatively more _intrinsically motivated_ than those working in the private sector [Crowley and Smith 2014]. Performance incentives or monitoring might then be detrimental if such practices crowd out such intrinsic motivation. To measure civil servant’s intrinsic motivation, As part of our civil servants survey, we obtained individual measures of the public service motivation (PSM) of bureaucrats, using an abbreviated version of the standard Perry scale [Perry 1996]. This includes four sub-indices related to motivations related to compassion, public interest, policy making and sacrifice. We then examine whether the negative impacts of management practices related to incentives/monitoring

> 16An established macroeconomic literature documents a negative correlation between societal diversity and economy-wide outcomes [Easterly and Levine 1997, Alesina and La Ferrara 2005]. In Kenyan private sector settings, Hjort [2014] and Macchiavello and Morjaria [2015] show ethnic divisions impact productivity due to worker discrimination.

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interplay with these dimensions of intrinsic motivation.<sup>17</sup> The results are shown in Table 6. Column 1 shows the negative impacts of incentives/monitoring are reinforced in organizations whose bureaucrats on average score more highly on the ‘policy making’ dimension of PSM (this sub-index measures intrinsic interest in the structures and procedures of policymaking). Columns 2 and 3 show the negative impact of management practices related to incentives/monitoring is partly ameliorated when bureaucrats in the organization score higher on the PSM dimensions of ‘compassion’ and ‘public interest’. This runs counter to the notion that incentive provision crowds out e↵orts of intrinsically motivated individuals: if anything, as in Ashraf _et al._ [2014], our evidence suggests intrinsically motivated bureaucrats work harder in the face of poorly designed incentives/monitoring practices (so as to ameliorate the negative e↵ects of these practices). However, in neither case does this interaction fully o↵set the negative overall e↵ect of incentives/monitoring except for a small handful of bureaucrats at the extreme top end of the PSM distribution.<sup>18</sup> Finally, Column 4 shows that the ‘self-sacrifice’ dimension of PSM has no interactive e↵ect with management practices.

Taken together our results shed new light on an old issue: the interplay between intrinsic and extrinsic motivation. We show that there are some dimensions of intrinsic motivation that are crowded out by practices related to incentives/monitoring, other dimensions that are crowded in, and others that are independent. We leave a fuller exploration of the nature of this heterogeneity to future research.

# **4.3 Subjective Performance Evaluation**

As described in Section 2, Ghanaian bureaucrats enjoy long tenure. On the one hand, longer serving bureaucrats might learn how best to respond to incentives by exploiting other flexibilities. On the other hand, if bureaucrats are subject to SPE they might learn how best to engage in influencing activities. We investigate this using two measures based on the social connectedness between non-seniors and their managers: (i) the proportion of non-senior bureaucrats in an organization that overlapped in time at university as an undergraduate, with their most senior civil servant; (ii) the proportion of non-senior bureaucrats in an organization in the same ethnic group as their most senior civil servant. As Table 7 shows, along both dimensions, we find the negative impact of incentives/monitoring on project completion becomes significantly worse. This strongly suggests that these management practices might be capturing schemes in place that e↵ectively

> 17In the public administration and economics literatures, the PSM scale developed in Perry [1996] is often found to be positively associated with various measures of individual commitment, pro-social behavior, and performance [Belle 2013, Dal Bo _et al._ 2013, Warren and Chen 2013, Perry 2014].

> 18We have explored whether there are within-sample values of the interactions at which the marginal e↵ect of CS-incentives/monitoring becomes positive. Generally, this is not the case. In the case of PSM-compassion, it is only individuals who score at the 95th percentile of the index or above for which CS-incentives/monitoring would have a positive e↵ect on project completion. For the PSM-public interest measure, the same is true again only individuals who score at the 95th percentile or above.

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allow for subjective performance evaluation or influencing activities to take place between socially tied senior and non-senior bureaucrats [Milgrom 1988, Milgrom and Roberts 1988].

# **4.4 Project Characteristics**

The fourth dimension we examine focuses in on the interplay between project characteristics and management practices. As we exploit di↵erences in individual project characteristics (rather than characteristics of organizations or bureaucrats as in Tables 5 to 7), we present the results splitting the sample by the relevant project characteristic, and so allow the partial correlation between all covariates (including both dimensions of management practice) and project completion to vary with project characteristics. These characteristics are derived from the progress reports of each organization (as detailed in Figure A1 and the Appendix).

We first consider projects for which the quarterly targets set out in progress reports are more or less clear. In Columns 1 and 2 of Table 8 we see that the partial correlation of CS-autonomy to be similar across target clarities but that there is a far more detrimental impact of practices related to incentives/monitoring for projects that have poorly defined targets (i.e. are below the b median clarity). More precisely, _γ_ 2 = _−._ 23 for projects with poorly defined targets, and the point estimate for _γ_ 2 is less than half this magnitude (but still di↵erent from zero) for projects with well defined targets. This is intuitive: for projects with poorly defined targets, the design of incentives and monitoring schemes is harder, all else equal. Hence the more detrimental impacts on projects with poorly defined targets reflects incentive misalignment.

We next consider the clarity of the description of output to be delivered. Columns 3 and 4 show the absolute impacts of both management practices are far larger for projects with high output b b clarity ( _γ_ 1 = _._ 37, _γ_ 2 = _−._ 31), while the impacts are attenuated (but still statistically significant) b b for projects with low output clarity ( _γ_ 1 = _._ 17, _γ_ 2 = _−._ 09). This is again consistent with incentive misalignment: when outputs are well defined _ex post_ , granting bureaucrats discretion over how to implement projects is likely to be more e↵ective since abuse of that discretion will be easier to detect _ex post_ . Hence the negative association of incentives/monitoring with output (conditional on autonomy) is likely to be even greater.<sup>19</sup> 19We have also examined whether the complexity of projects impacts how management practices relate to project completion. Unfortunately, our ability to precisely codify the complexity of projects from the progress reports is far more limited than in RR. As Figure A1 and the Data Appendix make clear, we end up with a crude 0-1 measure of complexity. We find that the partial correlation of CS-autonomy with project completion is the same for more or less technically complex projects. The negative partial correlation of incentives/monitoring and project completion is of similar magnitude across both project types, but is more precisely estimated for more complex projects. Again this is in line with e↵ective incentive/monitoring schemes being harder to design when projects are more complex.

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# **5 Discussion**

We discuss three remaining important issues: (i) on the interplay between management practices and corruption in service; (ii) on alternative approaches to measuring management practices; (iii) on the external validity of our findings.

## **5.1 Corruption**

While the recent economics literature has emphasized the importance of the intrinsic motivation of bureaucrats, a long-standing literature in public administration emphasizes that civil servants might pursue their own self-interest [Wilson 1989]. This more negative view of bureaucrats spur us to explore how the correlations between project completion rates and incentives/monitoring are mediated through perceptions of corruption among civil service organizations. Corruption in public bureaucracies is an issue in Ghana, and in other countries at similar stages of development (although as Figure 2 shows, the fact that 34% of projects are fully completed also suggests corruption is not all-pervasive).<sup>20</sup> We use two approaches to elicit information on perceptions of corruption in service. First, we focus on corruption by senior bureaucrats by measuring the proportion of received corruption rents (kickbacks) that are claimed to have gone to seniors in the organization. Second, we build a measure based on bureaucrats’ reports of the proportion of recent projects and/or programs on which officials report observing others engaging in corrupt practices. We then examine whether the partial correlation of management practices related to autonomy and the provision of incentives/monitoring vary with each measure of corruption.<sup>21</sup> Table 9 shows the results: for neither measure of corruption do we find evidence that the provision of autonomy to bureaucrats interacts with corruption to lead to a significantly lower likelihood of project completion. For the second measure, the negative impact of practices related to incentives/monitoring is ameliorated if there is a greater proportion of recent projects on which officials report observing others engaging in corrupt practices. This suggests that the negative consequences of corrupt practices can be partially o↵set by the provision of incentives/monitoring of bureaucrats.

> 20In 2015 Ghana scored at the 53rd percentile worldwide on the World Governance Indicators’s Control of Corruption measure; Nigeria scored at the 13th percentile [World Bank 2018].

> 21The first measure is based on asking what proportion of unofficial payments are shared with the superior in the hypothetical scenario that, ‘Imagine that a corrupt bureaucrat extracts unofficial payments. Typically in your organization, what proportion of the unofficial payments does s/he share with the following types or groups of people.’ An organization-level average from across all interviews is constructed and for our whole sample, the organization-average was 11%, but wide a relatively wide dispersion reflected in a standard deviation of 8%. The second measure used a similar question structure, but asked officials the proportion of projects on which they ‘observed others breaking service rules for their own benefit’. Officials are more likely to report the corrupt behavior of others, and 16% of officials have observed such acts by others in their organization.

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# **5.2 Alternative Measures of Management Practice**

Our measures of management practice at the organization level are all aggregated from individual responses on management to our civil servant survey. The measure used for our core analysis averages management scores over the most senior divisional-bureaucrat reports. We now consider alternative constructs for management practices, based on all the senior bureaucrats in an organization, or as elicited from non-senior bureaucrats, namely those that are being managed. We can thus compare and contrast top-down versus bottom-up views of management practices, an underexplored element of the BSVR approach to measuring management.

The results are in Table 10, where we focus on project completion. Column 1 repeats the baseline specification from Column 3 in Table 3. Column 2 shows the findings to be robust to constructing management practice scores from all senior bureaucrats in the organization, while Column 3 shows them to be weaker if bottom-up views of management are used based on all non-senior bureaucrats only. Column 4 constructs management scores based on all bureaucrats in each organization, and these closely replicate the baseline findings in Column 1 in terms of the magnitudes of the coefficients of interest ( _γ_ 1, _γ_ 2) and the precision with which they are estimated.

Given these results, we probe further where the top-down and bottom-up views of management diverge. Figure 5 shows the CDF of management scores for CS-autonomy and CSincentives/monitoring elicited from senior and non-senior bureaucrats. We see that non-seniors generally report there being more autonomy than seniors (the average of the CS-autonomy score for non-seniors is _._ 021, while for seniors it is _−._ 003); and they also report their being more incentives/monitoring (the average of the CS-incentives/performance score for non-seniors is _._ 004, while for seniors it is _−._ 018 and seniors often report the lowest scores in this dimension).

We then examine what individual characteristics of non-senior bureaucrats predict the difference between their raw individual management score, along each dimension of autonomy and incentives/monitoring, and the corresponding organizational average derived from seniors. We create a dependent variable of the di↵erence between the individual and senior scores, where the unit of observation is bureaucrat _i_ in organization _n_ . We then regress this di↵erence on: (i) bureaucrat characteristics ( _Xi_ ); and (ii) organization _n_ fixed e↵ects.

These results are shown in Table 11 and highlight that: (i) women bureaucrats report higher autonomy, and a greater use of incentives/monitoring; and (ii) older bureaucrats and those with an undergraduate degree report lower levels of autonomy and incentives/monitoring. We also control for other bureaucrat characteristics such as their tenure, Raven test score of cognition, their aggregate PSM score and the extent to which they share an undergraduate institution or ethnicity with their manager/most senior bureaucrat in their division. These other characteristics do not systematically correlate with di↵erences in management scores with seniors. These findings all hold: (i) controlling for organization fixed e↵ects (Columns 2 and 5); and (ii) limiting attention to those 30 organizations for which we have project completion data for (Columns 3 and 6).

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These results open new avenues for research, highlighting that: (i) in terms of top-down views of management, it might be preferable to use a small number of individual surveys of senior managers to measure management practices if it is more cost e↵ective than the consensual approach followed in RR; and (ii) there remains scope to understand _why_ top-down and bottom-up views of management do not coincide, and whether organizational discord measured this way captures elements of organizational functioning and is predictive of their performance.

# **5.3 External Validity**

The final issue we turn to is that of the external validity of our findings linking management practices that central civil servants are subject to, and the quantity of public services delivered. To do so it is most natural to compare our findings from Ghana to our earlier work linking management practices for middle-tier bureaucrats and public sector output in the Federal Civil Service of Nigeria [Rasul and Rogger 2018]. In the Nigerian context, RR hand-coded independent engineering assessments of project completion rates for 4700 public projects. For each of 63 civil service organizations tasked to implement these projects (including 10 ministries and 53 other Federal civil service organizations), RR conducted a survey among senior bureaucrats to elicit management practices in place for middle-tier bureaucrats, also building on the methods pioneered by BSVR.

The comparison across Ghanaian and Nigeria settings exploits obvious similarities in terms of civil service structures and economic environment. At the same time, the two sets of analysis di↵er in the measurement of key variables. How projects and project completion is measured di↵ers across contexts, and this is necessitated by the fact that civil service bureaucracies worldwide di↵er greatly in whether and how they collect data on their own performance. Second, the precise way in which management practices are measured also di↵ers across settings, although each approach is anchored in the BSVR methods. The Appendix details these key data features from Nigeria.

Table 12 repeats our core results for Ghana and Nigeria. Columns 1 to 3 refer to Ghana; Columns 4 to 6 refer to Nigeria. A common set of results emerge across contexts: (i) CS-autonomy is robustly positively correlated with project initiation, full completion and completion rates; and (ii) CS-incentives/monitoring is robustly negatively correlated with project initiation, full completion and completion rates in both settings. Moreover, the estimates show similar e↵ect sizes of both dimensions of management practice on the initiation and full completion margins, in which the two settings are most comparable.

We have to be cautious in further comparing project types across contexts. As described earlier, the bulk of tasks conducted by the Ghanaian bureaucracy relate to non-physical projects whereas the bulk of projects RR have data on from Nigeria relate to physical infrastructure (boreholes, roads etc.). However, overall the results suggest the impacts of management practices do seem 23
broadly similar for their respective samples.<sup>22</sup> Being able to replicate findings in this nascent literature is valuable because: (i) each individual study is nearly always limited to a small number of bureaucratic organizations, especially when examining middle-tier civil servants working in central ministries; (ii) establishing robust findings across similar contexts underpins the external validity of any given study, and so moves the knowledge frontier closer to establishing stylized facts; (iii) establishing similar findings using alternative methodologies/measurement tools helps researchers collect data more cost-e↵ectively; and (iv) where di↵erences in results have emerged, this helps focus researchers’ future attention on such sources of heterogeneity across contexts.<sup>23</sup>

# **6 Conclusions**

There is growing recognition that bureaucrats and bureaucracies play a key role in determining state capability. This in turn has implications for macroeconomic outcomes and the scaling up of e↵ective microeconomic interventions. Our work highlights the role that management plays in driving pockets of good governance within the structure of political institutions in low-income and relatively weak states [Leonard 2010].

Our findings provide support to the notion that public agencies might delegate some decision making to bureaucrats [Simon 1983]: even countries with low overall levels of bureaucratic e↵ectiveness or state capability may benefit by providing their public servants with greater autonomy in some spheres. The robust _negative_ correlation documented between project completion rates and management practices related to the provision of incentives and monitoring of bureaucrats, is surprising and counter to a large body of evidence from private sector settings. We find that the negative partial correlation of incentives/monitoring is related to bureaucrats engaging in multi-tasking, interactions with their intrinsic motivation, influence activities and other project characteristics such as the clarity of targets and deliverable outputs. As such, our results sound a word of caution to the good governance agenda: the simple import of incentive/monitoring practices from the private sector might backfire in bureaucratic settings.

Our research points to areas for methodological advance for the measurement of management practices in organizations. Going forward, the remains a rich agenda to study the frictions pre-

> 22One project type for which there is reasonable overlap in definition and number across both contexts relates to monitoring/training and personnel management (this is the modal project type in Ghana). For this project type, we find that in Ghana the provision of autonomy to bureaucrats increases project completion and there are weak impacts of management practices related to incentives/monitoring. This is exactly in line with the results from RR [c.f. Figure 1] where for those kind of human resource project conducted by the Nigerian Civil Service, there was no detrimental impact of management practices related to incentives/monitoring.

> 23Many social and natural sciences are actively discussing the replicability of research, although there remains no consensus on the precise meanings of reproducibility, replicability and robustness [Hamermesh 2007, Clemens 2015]. Attention is being placed on scientific replicability in the social sciences, including economics where there has been a long-standing debate on the transparency, reproducibility and credibility of research, heightened by evidence of p-hacking [Christensen and Miguel 2016].

24
venting organizations adopting optimal management practices. These might relate to the lack of specialization in project types assigned to organizations, there being large fixed costs of adopting better practices, frictions in the labor market for bureaucrats that prevent best practice from spreading, a lack of competitive pressure enabling poorly managed organizations to survive, and the fact that bureaucracies are driven by objectives other than maximizing project completion.

While our results across Ghana and Nigerian settings are similar, going forward, it will be important for researchers to understand similarities and di↵erences across such state organizations in order to advance the literature. Bureaucracies di↵er in terms of their selection and retention policies for bureaucrats [Dal Bo _et al._ 2013, Deserranno 2017, Ashraf _et al._ 2018], as well as mechanisms for the public and politicians to hold public sector organizations accountable [Olken 2007, Bjorkman and Svensson 2009].

Building on the literature examining cross-country di↵erences in bureaucratic e↵ectiveness, our analysis pushes forward the frontier to understand within-country variation in e↵ectiveness. Indeed, a nascent body of work has now started to examine the impacts of autonomy and incentives/monitoring in bureaucracies using experimental variation in these practices [Banerjee _et al._ 2014, Bandiera _et al._ 2018].<sup>24</sup> We hope our work further helps establish a picture of what findings on bureaucratic e↵ectiveness replicate over settings and what the sources of within-country heterogeneity driving e↵ectiveness might be.

# **A Data Appendix**

## **A.1 Measuring Bureaucracy Projects and Output**

In Ghana each civil service organization is required to provide quarterly and annual progress reports. These detail targets and achievements for individual projects. The process of measuring projects and output for each organization then comprised two steps. First, extracting the data from organizations’ reports (which di↵ered slightly in their formats) into a standardized template. Second, coding variables based on the standardized data.

Figure A1 shows a snapshot of a typical quarterly progress report. The unit of observation is the project or task, defined as the most disaggregated output reported. For each quarterly progress

> 24Banerjee _et al._ [2014] report on a field experiment with the state police of Rajasthan, where a series of treatments involved middle managers providing more autonomy to frontline police officers. They find such reforms to be poorly implemented and ine↵ective in rasing the e↵ectiveness of policing. This opens up the issue of understanding how exactly to reallocate autonomy within organizations without creating constituencies of individuals that would prefer to sabotage such reforms or see them weakly implemented. This also echoes recent findings from private sector settings: Atkin _et al._ [2017] document that in the context of manufacturing firms in Pakistan, productivity enhancing innovations were blocked by lower-tier workers who stood to loose from the adoption of such techniques. In ongoing work, Bandiera _et al._ [2018] vary the autonomy and incentives/monitoring of purchasing managers in procurement decisions across 500 public bodies in Pakistan. Echoing our results, they find providing such bureaucrats greater autonomy allows them to perform better (they procure lower prices) while incentives have weak or perverse e↵ects (leading them to procure goods at higher prices).

25
report, we codified project line items using a team of trained research assistants and a team of civil servant officers seconded from the Management Services Department in the Civil Service. Each project was thus assigned to an organization (ministry or department) and to a division within that organization. For organizations in which reporting formats did not specify which division was responsible for a particular project, coders were supplied with information about the divisions in the organization and assigned each project to the division that was most likely responsible for it, in consultation with civil servants and/or research assistants who were familiar with the organization. In cases where the two coders assigned a project to di↵erent divisions, a manager made a judgment about which division to assign the project to.

# **A.2 Extracting and Standardizing**

Although organizations’ reports di↵ered in their format and variable coverage, we extracted the following standard variables for each organization (leaving them blank where the variable was missing).

**Output Level 1** The name or short description of the output specifying the action to be taken during the time period, at the most disaggregated or fine-grained level available. For instance, in Figure A1, this is ‘Develop draft competition policy’. This variable defines the unit of observation, and by definition, cannot be missing.

**Output Level 2** The name or short description of the output, aggregated to one level higher than in _Output level 1_ . Many organizations reported outputs that were nested into broader outputs, or whose completion required multiple sequential or simultaneous smaller outputs to be completed. For example, in Figure A1 the _Output level 2_ for ‘Develop draft competition policy’ is ‘Competition Policy Developed and Approved.’ Multiple outputs can thus share the same _Output level 2_ . **Output Level 3** The same as Output level 2, but one level of aggregation higher. As in Figure A1, this level of aggregation was frequently unreported, but was extracted where relevant. **Budget Allocation/Cost** The budgeted cost of the project. This was reported infrequently. **Baseline Completion Level** Where reported, the level of attainment on the output at the start of the time period.

**Actual Output** The actual attainment or work done during the time period. Together with the target level of achievement for the time period (from Output level 1) and (where relevant) the baseline level of completion, this is used to code project completion (as described in more detail below).

**Remarks** Where reported, the organization’s comments about the output. These often explain why the target level of attainment was not achieved during the time period.

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# **A.3 Coding**

After extracting the data, our team of civil servants and project research assistants coded a fixed list of variables for each output (at the most disaggregated level, _Output level 1_ ). As the variables to be coded required coders to interpret and judge the information being reported by each organization, coding was undertaken by two independent coders, with reconciliation led by managers where necessary. Below is a list of all variables coded for each output.

**Output Type (primary)** _Which category best describes this output?_ Coders had to select one of the following: (i) Advocacy, outreach and stakeholder engagement/relations; (ii) Financial & budget management; (iii) ICT management and/or development; (iv) Monitoring, review, & au– dit; (v) Permits and regulation; (vi) Personnel management; (vii) Physical infrastructure office & facilities; (viii) Physical infrastructure – public infrastructure and projects; (ix) Policy development; (x) Procurement; (xi) Research; (xii) Training. **Output Type (secondary)** _If output covers more than one category, select the secondary category here._ Coders had to select one of the same twelve categories as above.

**Period/Regular vs. One-o↵** _Is the output repeated (e.g. weekly, quarterly, annually) or one-o↵ (no planned repetition)? Coders had to_ select one of: (i) Periodic/ regular (e.g. weekly, quarterly, annually); (ii) One-o↵(no planned repetition).

**Output Scope** _How narrowly is the output defined? Does it include multiple tasks, or even multiple outputs?_ Coders had to select one of: (i) Single activity (one step in a larger activity, has no value on its own; e.g. hold a meeting about writing a policy); (ii) Single output (multiple steps, has value on its own; e.g. write a policy); (iii) Bundle of outputs (multiple outputs that each have their own value; e.g. write four policies)].

**Technical Complexity** _Does the output require specific technical or scientific knowledge, beyond the level most civil servants would have?_ Coders had to select one of: (i) No technical knowledge required (any senior civil servant could do this); (ii) Technical knowledge is required (special education or training needed).

**Coordination Required** _Does the division have to coordinate or interact with other actors in order to achieve the output?_ Coders could select any of the following that applied: (i) Requires action from other divisions in the organization; (ii) Requires action from other government organizations; (iii) Requires action from stakeholders outside government.

**Target Clarity** _How precise, specific, and measurable is the target?_ Coders had to answer on a 1-5 scale (where integers and half values were both permitted) using the following scoring guidelines. Score 1: Target is undefined or so vague it is impossible to assess what completion would mean; Score 3: Target is defined, but with some ambiguity; Score 5: There is no ambiguity over – the target it is precisely quantified or described.

**Output Clarity** _How precise, specific, and measurable is what the division actually achieved?_ Coders had to answer on a 1-5 scale (where integers and half values were permitted) using the

27
following scoring guidelines. Score 1: Output information is absent or so vague it is impossible to assess completion; Score 3: Output information is given but there is some ambiguity over whether the target was met; Score 5: Output information is clear and unambiguous.

**Completion Status** _How did actual achievement compare to the target?_ Coders had to answer on a 1-5 scale (where integers and half values were permitted) using the following scoring guidelines. Score 1: No action was taken towards achieving the target; Score 3: Some substantive progress was made towards achieving the target. The output is partially complete and/or important intermediate steps have been completed; Score 5: The target for the output has been reached or surpassed.

**Completion Remarks** _Were any challenges/ obstacles mentioned? Coders could select all that applied from the following:_ (i) awaiting action from another division, organization or stakeholder; (ii) 2 = Procurement/sourcing delay or problem; (iii) Sequencing issue (can’t start until another output has been completed); (iv) Lack of technical knowledge to complete activity; (v) Delayed/ non-release of funds; (vi) Unexpected event; (vii) Activity not due.

There are at least two coders per project. Given the tendency for averaging scores to reduce the measured variation, we use the maximum and minimum scores to code whether projects are fully complete/never initiated respectively. We show robustness of our main result to alternative methods by which to combine codings.

# **A.3.1 Nigeria: Measuring Projects and Project Completion**

The output data for the RR study based on the Federal Civil Service in Nigeria exploited the following historical event. In 2006/7 the Nigerian Government undertook the Overview of Public Expenditure in NEEDS (the ‘OPEN initiative’), in which it traced, by project, the use and impact of a representative sample of 10% of federal social sector expenditures approved in 2006/7. Under the OPEN initiative, expert teams visited projects to record their implementation. This monitoring process was independent of civil servants: projects were evaluated by teams of independent engineers and civil society.<sup>25</sup> Monitoring teams visited project sites 18 months after projects were approved. The projects studied in RR had 12 month completion schedules. RR hand-coded the material from all projects recorded in OPEN initiative reports from 63 federal civil service organizations, covering 4721 projects. 11 project types are covered (road, borehole, training etc.) with boreholes being the modal project type, and 75% of projects relating to small-scale infrastructure.

> 25A system of checks and balances were further put in place to underpin the credibility of the initiative. First, a centralized team of technocrats monitored the evaluation teams, providing them with training and opportunities for standardization of their methods. Second, evaluators were asked to provide material/photographic/video evidence to support their reports. Third, random checks were performed on evaluated sites.

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## **A.3.2 Nigeria: Measuring Management Practices**

In the Nigerian context, RR also followed BSVR’s approach to measuring management practices, adapting their survey tool to the Nigerian public sector setting. Management practices were elicited from senior management in each organization. While each manager filled in their own questionnaire, enumerators looked for a consensus and recorded that in their own questionnaire. This is the information used to construct management practice indices for each organization. Enumerators held double blind interviews in the 63 organizations with project completion data. The management survey covered nine topics: roles, flexibility, incentives, monitoring, culture, targeting, facilities, skills and staffing. RR combined answers to the roles and flexibility questions to construct an index of management practices capturing bureaucrats’ autonomy (CS-autonomy). RR combined answers on the incentives and monitoring topic areas to construct an index capturing the incentives/monitoring management practices bureaucrats operate under (CS-incentives/monitoring). RR combined answers on all remaining topics to construct an ‘other’ management practices index (CS-other). The responses to each practice were converted into normalized z-scores by taking unweighted means of the underlying z-scores (so are continuous variables with mean zero and variance one by construction), where, as in Ghana, both are increasing in the commonly understood notion of ‘better management’.

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# ~~<mark>©</mark>~~
# **Figure 2: Bureaucratic Performance by Project Types**

<!-- Start of picture text --> 0.80<br>0.70<br>0.60<br>0.50<br>0.40<br>0.30<br>0.20<br>0.10<br>0.00<br>(3) Proportion Never Started (Min Report) (4) Proportion Fully Completed (Max Report)<br><!-- End of picture text -->

**Figure 3: Bureaucratic Performance by Organization**

<!-- Start of picture text --> 0 10 20 30<br>Organisation ranking by proportion of projects initiated<br>Proportion started Proportion completed<br>Mean Completion Proportion: 0.38<br>1<br>.8<br>.6<br>.4<br>Proportion of projects<br>.2<br>0<br><!-- End of picture text -->

**Notes:** Multiple coders assessed a project such that here we take the minimum assessment of initiation and the maximum assessment of completion. The 'Mean Completion Proportion' is an average of the organizational averages of proportion completed.
# **Figure 4: Variation in Management Practices Across Bureaucracies**

## **A. CS-Autonomy Score**

<!-- Start of picture text --> 0 10 20 30<br>Autonomy ranking of organisation<br>2<br>1<br>0<br>Raw management score<br>-1<br>-2<br><!-- End of picture text -->

## **B. CS-Incentives/Monitoring Score**

<!-- Start of picture text --> 0 10 20 30<br>Incentives ranking of organisation<br>2<br>1<br>0<br>Raw management score<br>-1<br>-2<br><!-- End of picture text -->

**Notes:** CS-Autonomy (CS-Incentives) is an aggregate index of management questions relating to roles and flexibility (monitoring and incentives). Responses by senior bureaucrats are averaged across all sub-topics and converted into z-scores before averaged into a single index of management.
# **Figure 5: Management Practices Score by Senior and Non-Senior Bureaucrats**

<!-- Start of picture text --> A. CS-Autonomy Score<br>Senior<br>Non-senior<br>-2 -1 0 1 2<br>Management Score<br>B. CS-Incentives/Monitoring Score<br>g g<br>Senior<br>Non-senior<br>-4 -2 0 2<br>Management Score<br>1<br>.8<br>.6<br>.4<br>Cumulative probability<br>.2<br>0<br>1<br>.8<br>.6<br>.4<br>Cumulative probability<br>.2<br>0<br><!-- End of picture text -->

**Notes:** CS-Autonomy (CS-Incentives) is an aggregate index of management questions relating to roles and flexibility (monitoring and incentives). Responses by senior/non-senior bureaucrats are averaged across all sub-topics and converted into z-scores before averaged into a single index of management. Officials are designated senior based on whether they classify themselves as a 'Director (Head of Division) or Acting Director' or as a 'Deputy Director or Unit Head (Acting or Substantive)'.
# **Table 1: Variation in Bureaucratic Performance by Project Types**

|**Project Type**|**(1) Number of**<br>**Projects**<br>**[Proportion]**|**(2) Number of**<br>**Implementing**<br>**Organizations**|**(3) Proportion**<br>**Never Started**<br>**(Min Report)**|**(4) Proportion**<br>**Fully Completed**<br>**(Max Report)**|**(5) Average**<br>**Completion Rate**<br>**[CV]**|
|---|---|---|---|---|---|
|**All Project Types**|3,628 [1.00]|30|0.21|0.34|3.23 [0.38]|
|**Physical Infrastructure**|1,010 [0.27]|23|0.17|0.28|3.20 [0.36]|
|**All non-Physical Infrastructure Projects**|2,610 [0.73]|30|0.23|0.37|3.24 [0.39]|
|**Advocacy and Policy Development**|833 [0.23]|29|0.23|0.34|3.20 [0.38]|
|**Financial & Budget Management**|137 [0.04]|19|0.27|0.44|3.29 [0.44]|
|**ICT Management and Research**|265 [0.07]|24|0.18|0.35|3.23 [0.38]|
|**Monitoring, Training and Personnel**<br>**Management**|1,044 [0.29]|30|0.23|0.40|3.30 [0.38]|
|**Permits and Regulation**|141 [0.04]|20|0.14|0.32|3.28 [0.31]|
|**Procurement**|190 [0.05]|22|0.31|0.36|3.02 [0.46]|

**Notes:** The “project type” classification refers to the primary classification for each project. Other project classifications exist. The 'Average Completion Rate' is a categorical variable taking the value 1 if the project was not started and 5 if it was fully completed. It is accompanied in Column 5 by the coefficient of variation. The 'Proportion Never Started' and 'Proportion Fully Completed' columns are based on dummies that take the corresponding values of the completion status variable. The corresponding columns with minimum and maximum reports take the lowest and highest reports by project assessors respectively. Figures are rounded to two decimal places where relevant.
# **Table 2: Variation in Bureaucratic Performance by Largest Civil Service Organizations**

|**Civil Service Organization**|**(1) Number of**<br>**Projects**|**(2) Number of**<br>**Unique Project**<br>**Types**|**(3) Proportion**<br>**Never Started**|**(4) Proportion**<br>**Fully Completed**<br>**(Max Report)**|**(5) Average**<br>**Completion Rate**<br>**[CV]**|
|---|---|---|---|---|---|
|**All Organizations (Average)**|117|5.60|0.21|0.34|3.23 [0.38]|
|**Ministry of Trade and Industry**|495|7|0.26|0.27|2.97 [0.4]|
|**Ministry of Finance**|374|7|0.37|0.26|2.75 [0.5]|
|**Department of Feeder Roads**|315|6|0.20|0.32|3.2 [0.42]|
|**Ministry of Energy and Petroleum**|285|7|0.31|0.29|2.99 [0.44]|
|**Ministry of Gender, Children and Social Protection**|274|7|0.16|0.43|3.51 [0.32]|
|**Controller and Accountant-General's Department**|254|7|0.27|0.54|3.49 [0.42]|
|**Environmental Protection Agency**|193|6|0.28|0.17|2.86 [0.4]|
|**Department of Urban Roads**|188|4|0.15|0.21|3.11 [0.34]|
|**Ministry of Environment, Science, Technology, and**<br>**Innovation**|172|6|0.10|0.34|3.45 [0.23]|
|**Office of the Head of Civil Service**|158|7|0.11|0.49|3.87 [0.24]|

**Notes** : The sample covers the ten largest civil service organizations for which we had data on activities ranked by number of projects from our overall sample of projects. The “project type” classification refers to the primary classification for each project. Other project classifications exist. The 'Average Completion Rate' is a categorical variable taking the value 1 if the project was not started and 5 if it was fully completed. It is accompanied in Column 5 by the coefficient of variation. The 'Proportion Never Started' and 'Proportion Fully Completed' columns are based on dummies that take the corresponding values of the completion status variable. The corresponding columns with minimum and maximum reports take the lowest and highest reports by project assessors respectively. Figures are rounded to two decimal places where relevant.
# **Table 3: Management of Bureaucrats and Public Service Delivery**

## **Dependent Variable Cols 1-4: Completion Binary [yes=1] Dependent Variable Col 5: Initiation Binary [yes=1] Dependent Variable Col 6: Completion Index Standard Errors: Clustered by Organization OLS Estimates**

||**(1) Noise**|**(2) Noise and**<br>**General**|**(3) Baseline**|**(4) Fixed**<br>**Effects**|**(5) Binary**<br>**Initiation**|**(6) Completion**<br>**Status**|
|---|---|---|---|---|---|---|
|**CS-Autonomy**|0.00|0.28***|0.28***|0.23***|0.25***|0.18***|
||(0.01)|(0.04)|(0.04)|(0.03)|(0.04)|(0.03)|
|**CS-Incentives/Monitoring**|0.01|-0.17***|-0.18***|-0.11**|-0.28***|-0.16***|
||(0.05)|(0.04)|(0.05)|(0.06)|(0.04)|(0.03)|
|**CS-Other**|0.02|-0.08***|-0.07***|-0.09***|-0.09***|-0.04***|
||(0.03)|(0.01)|(0.02)|(0.02)|(0.02)|(0.01)|
|**Noise Controls**|Yes|Yes|Yes|Yes|Yes|Yes|
|**General and Capital Controls**|No|Yes|Yes|Yes|Yes|Yes|
|**Project Controls**|No|No|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type|Project Type,<br>Sector|Project Type,<br>Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|3620 (30)|3620 (30)|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. In Columns 1 through 4, the dependent variable is a dummy variable that takes the value 1 if the project is fully completed and 0 otherwise. In Column 5, the dependent variable is a dummy variable that takes the value 1 if the project is initiated and 0 otherwise. In Column 6, the dependent variable is an index of project completion (that is a continuous measure between zero and one). Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 4: IV**

## **Dependent Variable Cols 1, 3: Completion Binary [yes=1] Dependent Variable Col 2: CS-Monitoring/Incentives Management Index, 2015 Dependent Variable Col 4: Initiation Binary [yes=1] Dependent Variable Col 5: Completion Index Standard Errors: Robust**

||**OLS**|**First Stage**|**IV:**|**Second Stag**|**e**|
|---|---|---|---|---|---|
||**(1) Baseline [IV**<br>**Sample]**|**(2) Monitoring**|**(3) Project**<br>**Completion**|**(4) Binary**<br>**Initiation**|**(5) Completion**<br>**Status**|
|**CS-Autonomy**|0.04**||0.11**|0.14***|0.35***|
||(0.02)||(0.05)|(0.02)|(0.10)|
|**CS-Incentives/Monitoring**|-0.09***|0.44***|-0.27**|-0.38***|-0.95***|
||(0.02)|(0.04)|(0.11)|(0.06)|(0.21)|
|**CS-Other**|-0.06*||-0.03|0.01|-0.04|
||(0.03)||(0.03)|(0.02)|(0.07)|
|**First Stage F Statistic**||107||||
|**Noise Controls**|Yes|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type, Sector|Project Type,<br>Sector|Project Type,<br>Sector|
|**Observations (clusters)**|2,463 (18)|2463|2,463|2,463|2,463|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Robust standard errors are in parentheses, and are clustered by organization in Column 1. All columns report OLS estimates. In Columns 1 and 3, the dependent variable is a dummy variable that takes the value 1 if the project is fully completed and 0 otherwise. In Column 2, the dependent variable is the monitoring management index defined using baseline data. In Column 4, the dependent variable is a dummy variable that takes the value 1 if the project is initiated and 0 otherwise. In Column 5, the dependent variable is an index of project completion (that is a continuous measure between zero and one). Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 5: Multi-tasking**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization Interactions in Deviation from Mean OLS Estimates**

|**OLS Estimates**|**Internal**<br>**(1) Ethnic**<br>**Fractionalization**|**External**<br>**(2) Stakeholder**<br>**Engagement**|
|---|---|---|
|**CS-Autonomy**|0.31***|0.28***|
||(0.04)|(0.04)|
|**CS-Incentives/Monitoring**|-0.18***|-0.18***|
||(0.04)|(0.05)|
|**CS-Other**|-0.08***|-0.07***|
||(0.02)|(0.02)|
|**CS-Incentives/Monitoring x Ethnic Fractionalization**|-0.05*<br>(0.03)||
|**Ethnic Fractionalization**|0.06*<br>(0.03)||
|**CS-Incentives/Monitoring x Stakeholder Engagement**||-0.06**<br>(0.02)|
|**Stakeholder Engagement**||0.05**<br>(0.02)|
|**Noise, General and Capital Controls**|Yes|Yes|
|**Project Controls**|Yes|Yes|
|**Fixed Effects**|Project Type, Sector|Project Type, Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable in all columns is a dummy variable that takes the value 1 if the project is completed and 0 otherwise. The variable with which management scores are interacted is z- score defined across the 30 organizations we study. In Column 1, 'Ethnic Fractionalization' is the organization-level Herfindahl index that is equal to 1 minus the sum of squares of ethnicity proportions in an organization. In Column 2, 'Stakeholder Engagement' is the proportion of projects officials at an organization report that they interact with stakeholders outside of their organization. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one-off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to the government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 6: Intrinsic Motivation of Bureaucrats**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization Interactions in Deviation from Mean OLS Estimates**

||**(1) PSM: Policy**<br>**Making**|**(2) PSM:**<br>**Compassion**|**(3) PSM: Public**<br>**Interest**|**(4) PSM: Self-**<br>**Sacrifice**|
|---|---|---|---|---|
|**CS-Autonomy**|0.28***|0.34***|0.34***|0.28***|
||(0.04)|(0.04)|(0.06)|(0.06)|
|**CS-Incentives/Monitoring**|-0.14***|-0.19***|-0.20***|-0.16***|
||(0.05)|(0.04)|(0.05)|(0.05)|
|**CS-Other**|-0.09***|-0.11***|-0.11***|-0.08***|
||(0.03)|(0.01)|(0.03)|(0.03)|
|**CS-Incentives/Monitoring x PSM - Policy Making**|-0.05**<br>(0.02)||||
|**PSM - Policy Making**|0.02||||
||(0.02)||||
|**CS-Incentives/Monitoring x PSM - Compassion**||0.08***<br>(0.02)|||
|**PSM - Compassion**||-0.08***<br>(0.01)|||
|**CS-Incentives/Monitoring x PSM - Public Interest**|||0.12***<br>(0.04)||
|**PSM - Public Interest**|||-0.09***<br>(0.03)||
|**CS-Incentives/Monitoring x PSM - Sacrifice**||||0.04<br>(0.04)|
|**PSM - Sacrifice**||||-0.04***<br>(0.01)|
|**Noise, General and Capital Controls**|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable in all columns is a dummy variable that takes the value 1 if the project is completed and 0 otherwise. The variable with which management scores are interacted is z-score defined across the 30 organizations we study. In Columns 1 through 4, the variables represent organization averages of aggregate Perry Public Service Motivation scores on the sub-categories of attraction to policy making, compassion for underprivileged people, commitment to the public interest, and self-sacrifice respectively. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 7: Subjective Performance Evaluation**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization Interactions in Deviation from Mean OLS Estimates**

||**(1) Shared**<br>**University Time**|**(2) Same Ethnicity**|
|---|---|---|
|**CS-Autonomy**|0.28***|0.28***|
||(0.03)|(0.03)|
|**CS-Incentives/Monitoring**|-0.22***|-0.10***|
||(0.04)|(0.04)|
|**CS-Other**|-0.06***|-0.09***|
||(0.01)|(0.03)|
|**CS-Incentives/Monitoring x Shared University Time**|-0.11***<br>(0.02)||
|**Proportion of Officials In Organization Who Share Time In**|0.10***||
|**Undergraduate With Senior Unit Civil Servant**|(0.02)||
|**CS-Incentives/Monitoring x Same Ethnicity**||-0.10***<br>(0.03)|
|**Proportion of Officials In Organization Who Are the Same**<br>**Ethnicity As The Senior Unit Civil Servant**||0.10***<br>(0.02)|
|**Noise, General and Capital Controls**|Yes|Yes|
|**Project Controls**|Yes|Yes|
|**Fixed Effects**|Project Type, Sector|Project Type, Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable in all columns is a dummy variable that takes the value 1 if the project is completed and 0 otherwise. The variable with which management scores are interacted is z-score defined across the 30 organizations we study. In Column 1, 'Shared University' refers to the proportion of officials in an organization who share an undergraduate university with the senior civil servant in the unit. In Column 2, 'Same Ethnicity' refers to the proportion of officials in an organization who share an ethnicity with the senior civil servant in the unit. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organizationlevel controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 8: Project Characteristics**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization OLS Estimates**

||**Target**|**Clarity**|**Output**|**Clarity**|
|---|---|---|---|---|
||**(1) Below**<br>**median**|**(2) Above**<br>**median**|**(3) Below**<br>**median**|**(4) Above**<br>**median**|
|**CS-Autonomy**|0.30***|0.25***|0.17***|0.37***|
||(0.03)|(0.05)|(0.03)|(0.06)|
|**CS-Incentives/Monitoring**|-0.23***|-0.10**|-0.09**|-0.31***|
||(0.03)|(0.04)|(0.03)|(0.09)|
|**CS-Other**|-0.01|-0.11**|-0.01|-0.16***|
||(0.01)|(0.04)|(0.02)|(0.03)|
|**Noise Controls**|Yes|Yes|Yes|Yes|
|**General and Capital Controls**|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|
|**Observations (clusters)**|1851 (29)|1769 (29)|2177 (29)|1443 (27)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable is a dummy variable that takes the value 1 if the project is fully completed and 0 otherwise. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 9: Corruption**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization Interactions in Deviation from Mean OLS Estimates**

||**(1) Superior**<br>**Shares In**<br>**Corruption**|**(2) Proportion of Projects that**<br>**Bureaucrats Report Observing**<br>**Corrupt Practices On**|
|---|---|---|
|**CS-Autonomy**|0.28***|0.33***|
||(0.06)|(0.04)|
|**CS-Incentives/Monitoring**|-0.13**|-0.20***|
||(0.07)|(0.07)|
|**CS-Other**|-0.07***|-0.14***|
||(0.02)|(0.03)|
|**CS-Autonomy x Superior Shares In Corruption**|-0.01<br>(0.03)||
|**CS-Incentives/Monitoring x Superior Shares In Corruption**|0.02<br>(0.05)||
|**Average Proportion of Corruption Rents Received By Superior**|0.05**<br>(0.02)||
|**CS-Autonomy x Proportion of Projects that Bureaucrats Report O**<br>**Practices On**|**bserving Corrupt**|0.00<br>(0.02)|
|**CS-Incentives/Monitoring x Proportion of Projects that Bureaucra**|**ts Report**|0.11**|
|**Observing Corrupt Practices On**||(0.04)|
|**Proportion of Projects that Bureaucrats Report Observing**||0.04|
|**Corrupt Practices On**||(0.03)|
|**Noise, General and Capital Controls**|Yes|Yes|
|**Project Controls**|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type, Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable in all columns is a dummy variable that takes the value 1 if the project is completed and 0 otherwise.The variable with which management scores are interacted is z-score defined across the 30 organizations we study. In Column 1, 'Superior Shares in Corruption' represents the average proportion of corruption rents received by a unit superior within an organization. In Column 2, 'Other Breaking' refers to the proportion of recent projects and/or programmes on which officials report observing others engaging in corrupt practices. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. In both countries, general controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 10: Different Measures of Management Practices and Public Service Delivery**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Project Type Within Organization OLS Estimates**

||**(1) All Senior**<br>**Bureaucrats**|**(2) Most Senior**<br>**Bureaucrat**|**(3) Non-senior**<br>**bureaucrats**|**(4) All Respondents**|
|---|---|---|---|---|
|**CS-Autonomy**|0.28***|0.31***|0.12***|0.30***|
||(0.04)|(0.04)|(0.05)|(0.07)|
|**CS-Incentives/Monitoring**|-0.18***|-0.14***|-0.02|-0.17**|
||(0.05)|(0.04)|(0.04)|(0.07)|
|**CS-Other**|-0.07***|-0.08**|-0.04|-0.01|
||(0.02)|(0.03)|(0.04)|(0.06)|
|**Noise, General and Capital Controls**|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type, Sector|Project Type, Sector|Project Type, Sector|Project Type, Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by project type within organization throughout. All columns report OLS estimates. The dependent variable in all columns is a dummy variable that takes the value 1 if the project is completed and 0 otherwise. All senior bureaucrats referes to that set of individuals who identify themselves as Director (Head of Division) or Acting Director, or Deputy Director or Unit Head (Acting or Substantive). The most senior bureaucrat refers to the official of the highest grade that we interviewed within a division. Non-senior bureaucrats are those officials who do not identify themselves as senior bureaucrats. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organisation or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table 11: Different Measures of Management Practices and Public Service Delivery**

## **Dependent Variable: Difference between bureaucrat and organizational management scores Standard Errors: Clustered by Organization**

|**OLS Estimates**|**(1) Baseline**|**(2) Organization**<br>**Fixed Effects**<br>**Autonomy**|**(3) Output**<br>**Organizations**|**(4) Baseline**<br>**In**|**(5) Organization**<br>**Fixed Effects**<br>**centives/Monito**|**(6) Output**<br>**Organizations**<br>**ring**|
|---|---|---|---|---|---|---|
|**Gender [female=1]**|.089**|.121***|.094**|.120***|.140***|.143***|
||(.036)|(.039)|(.044)|(.042)|(.043)|(.047)|
|**Age**|-.006**|-.004**|-.002|-.009***|-.008***|-.007*|
||(.002)|(.002)|(.002)|(.003)|(.003)|(.004)|
|**Undergraduate Education**|-.143***|-.139***|-.100**|-.166***|-.196***|-.211***|
||(.048)|(.044)|(.044)|(.051)|(.048)|(.051)|
|**Other Bureacrat Controls**|Yes|Yes|Yes|Yes|Yes|Yes|
|**Fixed Effects**|None|Organization|Organization|None|Organization|Organization|
|**Observations (clusters)**|1359 (45)|1359 (45)|1039 (30)|1361 (45)|1361 (45)|1041 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. The dependent variable in Columns 1 to 3 (4 to 6) is the difference in CS-Autonomy (CS-Incentives/Monitoring) index score between the individual public official and the aggregate score for her organisation. Other Bureaucrat Controls relate to the tenure of the official in the organization, their cognitive score on the Raven cognition test, their aggregate score on the Perry Public Service Motivation index and the extent to which they share an undergraduate institution or ethnicity with their manager/the most senior bureaucrat in their division. Figures are rounded to two decimal places.
# **Table 12: External Validity**

## **Standard Errors: Clustered by Project Type Within Organization OLS Estimates**

|||**2 Fll**<br>**Ghana**|**3 Cli**||**5 Fll**<br>**Nigeria**|**6 Cli**|
|---|---|---|---|---|---|---|
||**(1) Initiation**|**() u**<br>**Completion**|**() ompeton**<br>**Rate**|**(4) Initiation**|**() u**<br>**Completion**|**() ompeton**<br>**Rate**|
|**CS-Autonomy**|0.13***|0.23***|0.12***|0.15***|0.16***|0.18***|
||(0.05)|(0.03)|(0.02)|(0.03)|(0.02)|(0.03)|
|**CS-Incentives/Monitoring**|-0.16***|-0.11**|-0.10***|-0.16***|-0.10***|-0.14***|
||(0.06)|(0.06)|(0.04)|(0.02)|(0.02)|(0.02)|
|**CS-Other**|-0.07***|-0.09***|-0.04**|0.06**|0.06**|0.08***|
||(0.02)|(0.02)|(0.01)|(0.03)|(0.03)|(0.02)|
|**Noise, General and Capital Controls**|Yes|Yes|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type|Project Type|Project Type|Project Type|Project Type|Project Type|
|**Observations (clusters)**|3620 (30)|3620 (30)|3620 (30)|4721 (201)|4721 (201)|4721 (201)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by project type within organization throughout. All columns report OLS estimates. The dependent variable in Columns 1 and 4 is a dummy variable that takes the value 1 if the project is initiated and 0 otherwise. The dependent variable in Columns 2 and 5 is a dummy variable that takes the value 1 if the project is completed and 0 otherwise. The dependent variable in Columns 3 and 6 is an index of project completion (that is a continuous measure between zero and one). In Nigeria, Project Type fixed effects relate to whether the primary classification of the project is as a financial, training, advocacy, procurement, research, electrification, borehole, dam, building, canal or road project. In Ghana, Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. In Ghana, sector fixed effects are also included, and relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. In Nigeria, project controls comprise project-level controls for the project budget, whether the project is new or a rehabilitation, and an assessment of its aggregate complexity by Nigerian engineers. In Ghana, project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. In Nigeria, capital controls comprise organization-level controls for the logs of number of employees, total budget, and capital budget. In Ghana, capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. In both countries, general controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. In Nigeria, noise controls are four interviewer dummies, indicators of the seniority, gender, and tenure of the managers who responded, the day of the week the interview was conducted, the time of day the interview was conducted, a dummy variable indicating whether the interview was conducted during Ramadan, the duration of the interview, and an indicator of the reliability of the information as coded by the interviewer. In Ghana, noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table A1: Defining Management Practices Using the CS Indices**

|**Management Practice**|**Topic**|**Question**|**Score 1**|**Score 3**|**Score 5**|
|---|---|---|---|---|---|
|**CS-Autonomy**|**Roles**|Can most senior staff in your<br>division make substantive<br>contributions to the policy<br>formulation and implementation<br>process?|Senior staff do not have<br>channels to make substantive<br>contributions to organisational<br>policies, nor to the<br>management of their<br>implementation.|Substantive contributions can<br>be made in staff meetings by<br>all senior staff but there are no<br>individual channels for ideas to<br>flow up the organisation.|It is integral to the<br>organisation’s culture that any<br>member of senior staff can<br>substantively contribute to the<br>policies of the organisation or<br>their implementation.|
|||When senior staff in your<br>division are given tasks in their<br>daily work, how much<br>discretion do they have to carry<br>out their assignments? Can<br>you give me an example?|Officers in this division have no<br>real independence to make<br>decisions over how they carry<br>out their daily assignments.<br>Their activities are defined in<br>detail by senior colleagues or<br>organisational guidelines.|Officers in this division have<br>some independence as to how<br>they work, but strong guidance<br>from senior colleagues, or from<br>rules and regulations.|Officers in this division have a<br>lot of independence as to how<br>they go about their daily duties.|
|||Is the burden of achieving your<br>division’s targets evenly<br>distributed across its different<br>officers, or do some individuals<br>consistently shoulder a greater<br>burden than others?|A small minority of staff<br>undertake the vast majority of<br>substantive work within the<br>division.|A majority of staff make<br>valuable inputs, but it is by no<br>means everyone who pulls<br>their weight.|Each member of the division<br>provides an equally valuable<br>contribution, working where<br>they can provide their highest<br>value.|
|||Would you say that senior staff<br>try to use the right staff for the<br>right job?|Often tasks are not staffed by<br>the appropriate staff. Staff are<br>allocated to tasks either<br>randomly, or for reasons that<br>are not associated with<br>productivity.|Most jobs have the right staff<br>on them, but there are<br>organisational constraints that<br>limit the extent to which<br>effective matching happens.|The right staff are always used<br>for a task.|
||**Flexibility**|Does your division make efforts<br>to adjust to the specific needs<br>and peculiarities of<br>communities, clients, or other<br>stakeholders?|The division uses the same<br>procedures no matter what. In<br>the face of specific needs or<br>community/ client peculiarities,<br>it does not try to develop a<br>‘better fit’ but automatically<br>uses the default procedures.|The division makes steps<br>towards responding to specific<br>needs and peculiarities, but<br>stumbles if the specific needs<br>are complex. Often, tailoring of<br>services is often unsuccessful.|<br>The division always redefines<br>its procedures to respond to<br>the needs of communities/<br>clients. It does its best to serve<br>each individual need as best as<br>it can.|
|||How flexible would you say<br>your division is in terms of<br>responding to new and<br>improved work practices?|There is no effort to incorporate<br>new ideas or practices. When<br>practice improvements do<br>happen, there is no effort to<br>disseminate them through the<br>division.|<br>New ideas or practices are<br>sometimes adopted but in an<br>ad hoc way. These are<br>sometimes shared informally or<br>in a limited way, but the division<br>does not actively encourage<br>this or monitor their adoption.|<br> <br>Seeking out and adopting<br>improved work practices is an<br>integral part of the division’s<br>work. Improvements are<br>systematically disseminated<br>throughout the division and<br>their adoption is monitored.|
# **Table A1 Continued: Defining Management Practices Using the CS Indices**

|**Management Practice**|**Topic**|**Question**|**Score 1**|**Score 3**|**Score 5**|
|---|---|---|---|---|---|
|**CS-Incentives/Monitoring**|**Performance**<br>**Incentives**|Given past experience, how<br>would under-performance be<br>tolerated in your division?<br>Given past experience, are<br>members of [respondent’s<br>organisation] disciplined for<br>breaking the rules of the civil<br>service?|Poor performance is not<br>addressed or is inconsistently<br>addressed. Poor performers<br>rarely suffer consequences or<br>are removed from their<br>positions.<br>Breaking the rules of the civil<br>service does not carry any<br>consequences in this division.<br>Guilty parties do not receive<br>the stipulated punishment.|Poor performance is<br>addressed, but on an ad hoc<br>basis. Use of intermediate<br>interventions, such as training,<br>is inconsistent. Poor<br>performers are sometimes<br>removed from their positions<br>under conditions of repeated<br>poor performance.<br>An officer may break the rules<br>infrequently and not be<br>punished. An officer who<br>regularly breaks the rules may<br>be disciplined, but there would<br>be no other specific actions<br>beyond this. The underlying<br>drivers of the behaviour can<br>persist indefinitely.|Repeated poor performance is<br>systematically addressed,<br>beginning with targeted<br>intermediate interventions.<br>Persistently poor performers<br>are moved to less critical roles<br>or out of the organisation.<br>Any officer who breaks the<br>rules of the civil service is<br>punished; the underlying driver<br>is identified and rectified. On-<br>going efforts are made to<br>ensure the issue does not<br>arise again.|
|||Does your division use<br>performance, targets, or<br>indicators for tracking and<br>rewarding (financially or non-<br>financially) the performance of<br>its officers?|Officers in the division are<br>rewarded (or not rewarded) in<br>the same way irrespective of<br>their performance.|The evaluation system awards<br>good performance in principle<br>(financially or non-financially),<br>but awards are not based on<br>clear criteria/processes.|The evaluation system<br>rewards individuals (financially<br>or non-financially) based on<br>performance. Rewards are<br>given as a consequence of<br>well-defined and monitored<br>individual achievements.|
||**Monitoring**|In what kind of ways does your<br>division track how well it is<br>delivering services? Can you<br>give me an example?|<br>Measures tracked are not<br>appropriate or do not indicate<br>directly if overall objectives are<br>being met. Tracking is an ad<br>hoc process and most<br>processes aren’t tracked at all.<br>Tracking is dominated by the<br>head of the division.|Performance indicators have<br>been specified but may not be<br>relevant to the division’s<br>objectives. The division has<br>inclusive staff meetings where<br>staff discuss how they are<br>doing as division.|Performance is continuously<br>tracked, both formally with key<br>performance indicators and<br>informally, using appropriate<br>indicators and including many<br>of the divisional staff.|
# **Table A1 Continued: Defining Management Practices Using the CS Indices**

|**Management Practice**|**Topic**|**Question**|**Score 1**|**Score 3**|**Score 5**|
|---|---|---|---|---|---|
|**CS-Other**|**Staffing**|Do you think about attracting<br>talented people to your<br>division and then doing your<br>best to keep them? For<br>example, by ensuring they are<br>happy and engaged with their<br>work.|Attracting, retaining and<br>developing talent throughout<br>the division is not a priority or<br>is not possible given service<br>rules.|Having top talent throughout<br>the division is seen to be a key<br>way to effectively deliver on<br>the organisations mandate but<br>there is no strategy to identify,<br>attract or train such talent.|The division actively identifies<br>and acts to attract talented<br>people who will enrich the<br>division. They then develop<br>those individuals for the<br>benefit of the division and try<br>to retain their services.|
|||If two senior level staff joined<br>your division five years ago<br>and one was much better at<br>their work than the other,<br>would he/she be promoted<br>through the service faster?|The division promotes people<br>by tenure only, and thus<br>performance does not play a<br>role in promotion.|There is some scope for high<br>performers to move up through<br>the service faster than non-<br>performers in this division, but<br>the process is gradual and<br>vulnerable to inefficiencies.|<br>The division would certainly<br>promote the high-performer<br>faster, and would rapidly move<br>them to a senior position to<br>capitalise on their skills.|
||**Targeting**|Does your division have a<br>clear set of targets derived<br>from the organization’s goals<br>and objectives? Are they used<br>to determine your work<br>schedule?|<br>The division’s targets are very<br>loosely defined or not defined<br>at all; if they exist, they are<br>rarely used to determine our<br>work schedule and our<br>activities are based on ad hoc<br>directives from senior<br>management.|Targets are defined for the<br>division and its individual<br>officers (managers and staff).<br>However, their use is relatively<br>ad hoc and many of the<br>division’s activities do not<br>relate to those targets.|Targets are defined for the<br>division and individuals<br>(managers and staff) and they<br>provide a clear guide to the<br>division and its staff as to what<br>the division should do. They<br>are frequently discussed and<br>used to benchmark<br>performance.|
|||When you arrive at work each<br>day, do you and your<br>colleagues know what their<br>individual roles and<br>responsibilities are in<br>achieving the organisation’s<br>goals?|No. There is a general level of<br>confusion as to what the<br>organisation is trying to<br>achieve on a daily basis and<br>what individual’s roles are<br>towards those goals.|To some extent, or at least on<br>some days. The<br>organisation’s main goals and<br>individual’s roles to achieve<br>them are relatively clear, but it<br>is sometimes difficult to see<br>how current activities are<br>moving us towards those.|Yes. It is always clear to the<br>body of staff what the<br>organisation is aiming to<br>achieve with the days activities<br>and what individual’s roles and<br>responsibilities are towards<br>that.|
# **Table A2: Robustness**

## **Dependent Variable: Completion Binary [yes=1] in Columns 1 and 3 through 9; Completion Index in Column 2 Standard Errors: Clustered by Organization OLS Estimates**

||**(1) Baseline**|**(2) Average**<br>**Completion**<br>**Rate**|**(3) Excl. Org.**<br>**With Most**<br>**Projects**|**(4) Excl. Five**<br>**Orgs. With**<br>**Smallest No. of**<br>**Projects**|**(5) Excl. Orgs. Below**<br>**5% or Above 95%**<br>**of CS-Autonomy**<br>**Scale**|**(6) Excl. Orgs.**<br>**Below 5%**<br>**or Above 95% of**<br>**CS-Inc./Monit.**<br>**Scale**|**(7) Defining**<br>**Management**<br>**Scores Using**<br>**Orgs with**<br>**Project Data**|**(8) Fractional**<br>**regression**|**(9) Alternative**<br>**Fixed Effects**|
|---|---|---|---|---|---|---|---|---|---|
|**CS-Autonomy**|0.28***|0.12***|0.24***|0.30***|0.35***|0.30***|0.26***|1.25***|0.26***|
||(0.04)|(0.03)|(0.04)|(0.04)|(0.02)|(0.04)|(0.04)|(0.19)|(0.04)|
|**CS-Incentives/Monitoring**|-0.18***|-0.11***|-0.19***|-0.23***|-0.21***|-0.21***|-0.14***|-0.80***|-0.16***|
||(0.05)|(0.03)|(0.05)|(0.05)|(0.03)|(0.05)|(0.04)|(0.22)|(0.04)|
|**CS-Other**|-0.07***|-0.03**|-0.08***|-0.06***|-0.06***|-0.07***|-0.06***|-0.35***|-0.08***|
||(0.02)|(0.01)|(0.02)|(0.02)|(0.01)|(0.02)|(0.02)|(0.09)|(0.02)|
|**Noise Controls**|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|**General and Capital Controls**|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type, Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type,<br>Sector|Project Type<br>Within Sector|
|**Observations (clusters)**|3620 (30)|3620 (30)|3125 (29)|3593 (26)|3379 (27)|3585 (29)|3620 (30)|3620 (30)|3620 (30)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization throughout. All columns report OLS estimates. Column 8 reports estimates from a fractional regression model. In Columns 1 and 3 through 9, the dependent variable is a dummy variable that takes the value 1 if the project is fully completed and 0 otherwise. In Column 2, the dependent variable is an index of project completion (that is a continuous measure between zero and one). Column 3 excludes projects implemented by the largest organization in terms of number of projects. Column 4 removes the 5 smallest organizations by number of projects. Columns 5 and 6 exclude organizations at the top and bottom of the CS-autonomy and CS-incentives/monitoring management scales respectively. Column 7 uses the 30 focal organisations to define the management z- scores. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table A3: Differential Clustering**

## **Dependent Variable: Completion Binary [yes=1] Standard Errors: Clustered by Organization OLS Estimates**

||**(1) Baseline:**<br>**Organization**|**(2) Robust**|**(3) Project Type**<br>**Within Organization**|**(4) Project Type**<br>**Within Sector**|**(5) Sector**|
|---|---|---|---|---|---|
|**CS-Autonomy**|0.28***|0.28***|0.28***|0.28***|0.28***|
||(0.04)|(0.05)|(0.05)|(0.06)|(0.05)|
|**CS-Incentives/Monitoring**|-0.18***|-0.18***|-0.18***|-0.18**|-0.18***|
||(0.05)|(0.05)|(0.07)|(0.07)|(0.06)|
|**CS-Other**|-0.07***|-0.07***|-0.07**|-0.07**|-0.07***|
||(0.02)|(0.02)|(0.04)|(0.04)|(0.02)|
|**Noise, General and Capital Controls**|Yes|Yes|Yes|Yes|Yes|
|**Project Controls**|Yes|Yes|Yes|Yes|Yes|
|**Fixed Effects**|Project Type,<br>Sector|Project Type,<br>Sector|Project Type, Sector|Project Type,<br>Sector|Project Type,<br>Sector|
|**Observations (clusters)**|3620 (30)|3620|3620 (167)|3620 (41)|3620 (6)|

**Notes:** *** denotes significance at 1%, ** at 5%, and * at 10% level. Standard errors are in parentheses, and are clustered by organization in Column 1, by project type within organization in Column 3, by project type within sector in Column 4, and by sector type in Column 5. In Column 2, robust standard errors are reported. All columns report OLS estimates.The dependent variable is a dummy variable that takes the value 1 if the project is fully completed and 0 otherwise. Project Type fixed effects relate to whether the primary classification of the project is 'Advocacy and Policy Development', 'Financial & Budget Management', 'ICT Management and Research', 'Monitoring, Training and Personnel Management', 'Physical infrastructure', 'Permits and Regulation' or 'Procurement'. Sector fixed effects relate to whether the project is in the administration, environment, finance, infrastructure, security/diplomacy/justice or social sector. Project controls comprise project-level controls for whether the project is regularly implemented by the organization or a one off, whether the project is a bundle of interconnected outputs, and whether the division has to coordinate with actors external to government to implement the project. Capital controls comprise a count of the number of interviews undertaken, which is a close approximation of the total number of employees. General controls comprise organization-level controls for the share of the workforce with degrees, the share of the workforce with postgraduate qualifications, and the span of control. Noise controls are averages of indicators of the seniority, gender, and tenure of all respondents, the average time of day the interview was conducted and of the reliability of the information as coded by the interviewer. Figures are rounded to two decimal places.
# **Table A4: Ghana 2013 Management Survey**

|**Management Practice**|**Topic**|**Ghana 2013 questions**|**Score 1 (2013)**|**Score 3 (2013)**|**Score 5 (2013)**|
|---|---|---|---|---|---|
|**CS-Autonomy**|**Roles**|Examines how well procedures<br>for routine work are structured|<br>Procedures for undertaking<br>routine operations are<br>undefined or are rarely<br>followed in practice. The<br>organization relies almost<br>entirely on top-down<br>assignment to get work done,<br>so execution depends on the<br>individuals involved. Main<br>rationale for current practice is<br>“that’s the way it’s always been<br>done”.|Procedures for routine<br>operations are defined and<br>generally followed, but may be<br>inefficient or arbitrary. Where<br>responsibility for work is<br>assigned to individuals, follow-<br>up and checks sometimes<br>occur but are inconsistent.<br>There is some consideration of<br>how best to undertake day-to-<br>day operations but this is<br>mainly on an_ad hoc_ basis.|Routine operations procedures<br>have been consciously<br>structured to improve quality<br>and efficiency, and staff<br>consistently implement these<br>procedures.|
||**Flexibility**|Examines processes for and<br>attitudes towards continuous<br>improvement<br>Examines whether practice<br>improvements are effectively<br>disseminated throughout the<br>organization|Problems are only detected<br>after they have affected work.<br>No process improvements are<br>usually made when problems<br>occur. Frontline staff do not<br>contribute to improving<br>processes.<br>There is no effort to<br>incorporate new ideas or<br>practices. When practice<br>improvements do happen,<br>there is no effort to<br>disseminate them through the<br>organization.|Problems are sometimes<br>detected before they have<br>negative impacts, but there is<br>no structured, proactive<br>process to do so.<br>Improvements are made on an<br>_ad hoc_ basis, but depend<br>entirely on individuals taking<br>initiative. Resolution of<br>problems involves some, but<br>not all, of the appropriate<br>individuals and staff groups, or<br>includes non-relevant<br>individuals or groups.<br>New ideas or practices are<br>sometimes adopted but in an<br>_ad hoc_ way. These are<br>sometimes shared informally<br>or in a limited way, but the<br>organization does not actively<br>encourage this or monitor their<br>adoption.|Exposing problems in a<br>structured way is integral to<br>individuals’ responsibilities and<br>resolution occurs as a part of<br>normal business procedures<br>rather than by extraordinary<br>individual effort or_ad hoc_<br>teams. Resolution of problems<br>involves all appropriate<br>individuals and staff groups.<br>Seeking out and adopting<br>practice improvements is an<br>integral part of the<br>organization’s regular work.<br>Improvements are<br>systematically disseminated<br>throughout the organization<br>and monitored for adoption.|
# **Table A4 Continued: Ghana 2013 Management Survey**

|**Management Practice**|**Topic**|**Ghana 2013 questions**|**Score 1 (2013)**|**Score 3 (2013)**|**Score 5 (2013)**|
|---|---|---|---|---|---|
|**CS-Incentives/Monitoring**|**Performance**<br>**Incentives**|Examines whether the<br>organization is able to deal<br>with underperformers|Poor performance is not<br>addressed or is inconsistently<br>addressed. Poor performers<br>rarely suffer consequences or<br>are removed from their<br>positions.|Poor performance is<br>addressed, but on an ad hoc<br>basis. Use of intermediate<br>interventions, such as training<br>is inconsistent. Poor<br>performers are sometimes<br>removed from their positions<br>under conditions of repeated<br>poor performance.|,<br>Repeated poor performance is<br>systematically addressed,<br>beginning with targeted<br>intermediate interventions.<br>Persistently poor performers<br>are moved to less critical roles<br>or out of the organization.|
|||Examines how well the<br>organization follows up on and<br>enacts plans to fix identified<br>problems (department/<br>process-level)|<br>Failure to achieve agreed<br>objectives does not carry any<br>consequences. Responsibility<br>for following up is poorly<br>defined.|Responsibility for follow-up<br>may be allocated, but there<br>would be no other specific<br>actions beyond this. Failure to<br>achieve agreed results is<br>tolerated for a period before<br>action is taken and sanctions<br>are rare. Difficult problems ca<br>persist indefinitely.|n<br>Responsibility for follow-up is<br>clearly defined and<br>accompanied by other<br>complementary steps. Failure<br>to achieve agreed objectives<br>is quickly addressed and may<br>lead to sanctions. Ongoing<br>efforts are made to fix even<br>difficult problems.|
|||Examines whether good<br>performance is rewarded<br>proportionately and influences<br>career progression|<br>People are rewarded in the<br>same way irrespective of their<br>performance. Promotions are<br>solely based on tenure.|There is an evaluation system<br>which in principle awards goo<br>performance (financially or<br>non-financially), but awards<br>are not based on clear criteria<br>processes. Performance can<br>sometimes influence career<br>progression.|d<br>/<br>There is an evaluation system<br>which rewards individuals<br>(financially or non-financially)<br>based on performance.<br>Rewards are given as a<br>consequence of well-defined<br>and monitored individual<br>achievements. Performance is<br>a key criterion for promotion<br>decisions.|
||**Monitoring**|Examines whether<br>organizational performance is<br>tracked using meaningful<br>metrics and with appropriate<br>regularity|Measures tracked are not<br>appropriate or do not indicate<br>directly if overall objectives<br>are being met. Tracking is an<br>_ad hoc_ process and most<br>processes aren’t tracked at all.|<br>Performance indicators have<br>been specified but may not be<br>relevant to the organization’s<br>objectives. Some important<br>performance indicators are<br>tracked formally.|Performance is continuously<br>tracked, both formally and<br>informally, using appropriate<br>indicators.|
|||Examines whether<br>organizational performance is<br>meaningfully reviewed with<br>appropriate frequency and<br>communicated to staff|Performance is reviewed<br>infrequently or in an un-<br>meaningful way (e.g. only<br>success or failure is noted).<br>The right information for a<br>constructive discussion is<br>often not present.<br>Conversations are ‘one-way’,<br>focus overly on data that is not<br>meaningful, and exclude most<br>staff. The purpose of the<br>review is not explicitly stated.<br>Next steps are not clearly<br>defined.|<br>Performance is reviewed<br>periodically with appropriate<br>data, and both successes and<br>failures identified. Objectives<br>of meetings are clear to all<br>participating, but results are<br>communicated only to senior<br>staff and conversations often<br>do not drive to the root causes<br>of problems. Next steps are<br>mentioned but not well<br>defined.|<br>Performance is continually<br>reviewed, based on the<br>indicators tracked, with a<br>focus on problem solving and<br>addressing root causes.<br>Purpose and follow-up steps<br>are clear to all. Meetings are<br>an opportunity for constructive<br>feedback and coaching.<br>Results are communicated to<br>all staff.|
**Score 1 (2013)**

**Score 3 (2013)**

**Score 5 (2013)**

**Topic Ghana 2013 questions**

# **Table A4 Continued: Ghana 2013 Management Survey**

**Management Practice**

|**CS-Other**<br>**Staffing**|Examines the emphasis put on<br>attracting talented applicants<br>and applicants with particular<br>skills|The organization does not go<br>out of its way to recruit talented<br>applicants or applicants with<br>particular skills, so hiring is<br>driven entirely by staff numbers<br>and availability of funds.<br>Training opportunities are not<br>actively sought, and when<br>available are not allocated<br>based on capacity and/ or<br>need.|The organization occasionally<br>tries to recruit applicants with<br>particular skills, but<br>identification of needed skills is<br>not systematic and recruitment<br>is only occasionally based on<br>identified skill needs. The<br>organization rarely goes out of<br>its way to recruit talented<br>applicants. Training<br>opportunities are occasionally<br>sought, but driven mostly by<br>availability.|The organization actively<br>recruits talented applicants and<br>applicants with needed skills,<br>based on regular assessments<br>of skill needs. Training<br>opportunities are sought and<br>allocated to the staff who can<br>most benefit from them.|
|---|---|---|---|---|
|**Targeting**|Examines whether the<br>organization defines an<br>appropriate range of<br>meaningful objectives and/ or<br>targets to operationalize its<br>goals|Objectives and targets are<br>vague, only externally imposed,<br>or non-existent. The only<br>targets are lists of activities<br>drawn up as part of the budget<br>process.|<br>Some relevant objectives and<br>targets are defined, but these<br>mainly consist of lists of<br>activities and related outputs.<br>These may be loosely linked to<br>outcome targets.|A balanced range of objectives<br>and targets is defined for the<br>organization, including process<br>targets and other performance-<br>related targets.|
||Examines how well the<br>organization allocates tasks<br>and defines individual<br>objectives|Objectives are undefined or<br>very vague. Staff are expected<br>simply to “do what they’re told”.<br>Tasks are allocated to<br>individuals on an_ad hoc_ basis,<br>with little or no consideration of<br>individual competences or<br>workloads. Staff are often<br>unsure what they should be<br>doing.|Objectives may be formally<br>defined but are vague or<br>inconsistently applied. Staff<br>have a general sense what<br>they are responsible for, but<br>completion of most tasks relies<br>mainly on the giving/ following<br>of direct orders. There is some<br>consideration of which tasks<br>should be allocated to certain<br>individuals, but this is partial,<br>inconsistent, or based only on<br>an officer’s formal position.|Individuals understand clearly<br>what they are responsible for<br>and what they should be doing<br>at all times. Objectives are<br>meaningful and are defined<br>through a two-way process.<br>Tasks are allocated based on<br>identified competences.|
||Examines how easily<br>understandable objectives/<br>targets are and how well they<br>cascade down the organization|Goals do not cascade down the<br>organization, are unclear, and<br>are not clearly understood.<br>Beyond just following orders,<br>individuals do not know how<br>their work is related to overall<br>performance.|<br>Goals do cascade, but only to<br>some staff and/ or division<br>heads. Individuals have only a<br>general sense of how their<br>work contributes to<br>performance and meeting<br>overall objectives.|Goals increase in specificity as<br>they cascade, ultimately<br>defining individual expectations<br>for all staff groups. Individuals<br>understand clearly how their<br>work contributes to overall<br>performance.|
# MINISTRY OF TRADE AND INDUSTRY — DRAFT 2015, SECOND QUARTER PROGRESS REPORT

|]<br><br><br>|||||
|---|---|---|---|---|
|PROGRAMMED<br>|<br>"aerveres”||BUDGET<br>perrormance|EXPECTED<br>|ourpurjimpact|**|**||
|<br>ADM|<br>IN|<br>IST|<br>RAT|ION|
|1. Develop Draft Competition||Draft Competition Policy<br>developed|Evaluation of technical<br>proposalscompleted. Two] <br>rms have been<br>shortlisted.<br>e two firms have been<br>invited to present financial<br>7<br>|Procurement process is<br>| still on-goingand expected<br>to be completed by end of<br>Quarter 3.<br>CL|
|2. Organize stakeholder<br>meeting to validate draft<br>Competition Policy||Stakeholder meeting held|Yet<br>to<br>be co||
|3. Prepare CabinetMemo<br>andsubmitCompetition<br>Policy toCabinet for<br>approval||Competition Policy<br>submitted toCabinet|Work on the bill is still<br>frozendue to on-going<br>work on the policy||
|1. Review the Draft<br>CompetitionBilltakinginto||The draft bill reviewed|Yet to be done|Work on the bill will begin<br>afterhenanyhasbeen|