By David Fellows and John Leonardo

Introduction

The Public Expenditure and Financial Accountability (PEFA) programme provides a framework for assessing and reporting the strengths and weaknesses of public financial management (PFM). The current 2016 Framework refines the previous 2011 Framework and is structured under a hierarchy of 6 Pillars, 31 Indicators (PIs) and 94 Dimensions. The PEFA Field Guide explains the components of the 2016 Framework and describes how an assessment team should score each dimension on a scale of A to D, a D score representing the lowest level of performance.

An initial assessment of the latest PEFA reports for countries published under the 2016 Framework suggested that many countries were not getting the PFM basics right. This led to a comparison of recent results with those from earlier PEFA reports prepared under the 2011 Framework to examine performance over time and the lessons for PFM improvement that such a comparison may offer (termed the ‘dual study’). It was decided to focus on dimension scores since the demands of PFM can change markedly depending on the aspects of the subject matter under consideration and the evident variations of score for the same country at dimension level within a range of PIs.

It was decided to confine this initial study to the analysis of D scores at the dimension level given the frequency of D scores, the very poor performance they represent and the importance of raising performance to a higher level. The Field Guide requires a D score when: ‘the feature being measured is present at less than the basic level of performance or is absent altogether, or that there is insufficient information to score the dimension’.

For the purpose of this study, D scores include dimensions marked D*, NR and some NA scores where evidence suggests a breakdown in PFM activity. It seemed evident that these attributions are often applied inconsistently and serve to obscure the extent of the poor performance of some countries by avoiding the use of justifiable D scores. A summary of all scores for the 2016 Framework and the dual study evaluations, as discussed in this report, can be accessed at Annex 1.

2016 Framework analysis

The 2016 Framework analysis consisted of the latest published evaluations for the 63 countries for which there were published reports at the time of this study. The D scores represent 32% of all dimension scores in this data set, 39% amongst low-income countries.

D scores were widely distributed throughout the framework with 45 of the 94 dimensions having an above average number of D scores.

The study also defined and assessed the key factors (termed descriptors) that contributed to PFM performance. The results, summarised at  Annex 2, suggested that most D scores can be explained by the absence of ‘Management Effectiveness’, ‘Integrity’ and in one case of ‘High Level Technical Knowledge’ although poor “System Design” was another potentially important contributing factor.

Annex 3 provides a full list of the 2016 Framework dimensions and D score data together with the descriptors contributing to each dimension.

Dual framework

Following the results of the 2016 Framework D score study it was decided to undertake a review of 45 countries that have undertaken at least one PEFA evaluation under both the 2011 and 2016 frameworks (the earliest and the latest studies we used for countries with more than two studies). This enabled a country’s performance to be compared over a five-year period.

The 2011 and 2016 PEFA frameworks differ in many respects. An equivalence table published by PEFA suggests that the two frameworks can be aligned to 37 “equivalent” dimensions on the basis that the respective dimensions were either “directly comparable” or “indirectly comparable”.

The PEFA equivalence table identifies 28 dimensions (or in some cases subsets) from the 2011 framework as “non-comparable (subject only)” to 2016 counterparts suggesting that the dimension descriptions and scoring routines differ markedly while the general area of relevance to the dimensions are similar. This leaves only 37 pairs of comparable dimensions.

On examination, the study team decided that 26 of the 28 pairs of dimensions judged “non-comparable (subject only)” were in fact very similar to the 2016 counterparts, the main difference being the way in which the later guidance is translated into clear-cut scoring criteria but that a good PEFA evaluator should have made reasonably similar judgements for both frameworks when reviewing all but two of these dimensions.

This exercise, therefore, recognises 63 equivalent dimensions while also providing results for PEFA’s 37 equivalent dimensions. It is suggested that the D score characteristics of both data sets are sufficiently similar to provide a reasonable validation for the larger 63 dimension equivalence thereby extending the usefulness of inter-framework comparisons. Details of the PEFA and PFMConnect equivalence tables are set out at Annex 4. The dual study of 2016 and 2011 Framework with D score data at dimension level is set out at  Annex 5.             

The dual study is highly concerning in terms of the lack of improvement amongst those dimensions receiving D scores. These data are further summarised and commented on below.

The dual framework study reveals a deteriorating performance with most dimensions exhibiting a greater number of D scores in the later evaluations. Only 13 (35%) of dimensions from the 37 dimensions study and 16 (25%) from the 63 dimensions study experienced reductions in D scores between evaluations.

When the dual evaluations for the same country were compared, see Annex 6, it was noted that most countries recorded a higher proportion of D scores for the same dimension in both evaluations demonstrating a reasonably consistent poor performance. A few countries displayed less consistent results.

Few countries in the 63 dimensions set recorded reductions in the number of D scores in 2016 framework results compared with the 2011 framework results. The top performers where significant PFM reform activities had been undertaken between the dual framework studies included: Philippines, Maldives, Mongolia and Tajikistan.

The results for the proportion of dimensions with above-average D scores that are common to both framework dimensions sets is concerning. Approximately one third of all dimensions had above-average D scores that were common to both frameworks for the same country for both datasets. In addition, over 70% of the above-average dimensions in both datasets were common to both frameworks showing limited improvement in the worst scoring areas over a five-year period.

Dimensions with regular poor performance are widely distributed (titles in red at Annex 6). This suggests pockets of poor management that remain in place without effective challenge and this is consistent with the descriptor analysis.

Conclusions

This study offers a range of findings that pose questions about the approach, effectiveness and sustainability of PFM reforms instituted by national and subnational governments often in collaboration with development agencies. The concerns about management effectiveness and integrity highlighted in this study must be seen to question the most basic aspects of any organisation.

The study focusses on D score analysis, but it could be useful to extend the analysis to C-level scores where the performance of countries still remains below good international standards. This could reveal new characteristics of national PFM performance and extend the range of analytical techniques applied to performance data.

The data analysis evidences the credibility of PFMConnect’s extended 63 dimension equivalence model that offers significant potential for more detailed studies of specific countries or regions.

Further work on descriptors to reveal contributory factors to variations in performance seems worthy of further development.

The failure of some governments to publish PEFA studies in full reinforces concerns about the need for greater attention to integrity. Another improvement that could be readily and widely implemented is legislative scrutiny of audit reports (PI 31).

Recommendations

We recommend that country-specific studies should be undertaken based on PEFA assessment reports (both 2016 Framework studies for the full 94 dimensions and dual studies where the data are available) examining D scores at dimension level to establish potential causes of poor performance and identify ways in which performance may be improved. Issues to consider with respect to areas of poor performance, include:

• The commitment to personnel development and support, including: in-service training, management development, oversight, feedback on performance, and system design.
• The adequacy of transparency and accountability and evidence of corrupt activity.
• The quality of relevant communication and support levels among different departments and units of the finance ministry.
• The reasons for persistently poor or erratic performance and the fit with other findings.
• The observations of managers and staff on reasons for poor performance and barriers to improvement.

We recommend that country studies should be designed as the initial phase of PFM development programmes. In this context, a report by the Swedish International Development Cooperation Agency (SIDA) offers some observations about the conditions for effective PFM reform. These include the importance of change agendas being aligned with Government priorities and the need to treat PFM reform as a learning process with strong emphasis on coordination and systematic evaluation of the activities performed by teams responsible for delivery.

Groups of countries or subnational bodies may wish to collaborate in reform programmes enabling challenges and learning to be shared and systems of mutual support developed. We have previously advocated the use of digital communication as a cost-effective and time-saving way of sharing knowledge and ideas between nations (incl. expert advisors).

Any country, region or development institution wishing to participate in further work in this field is invited to discuss their interest with the authors.

An article based on this study has been published by the IMF’s PFM Blog.

PFMConnect is a public financial management consultancy with a particular interest in the use of digital communication to support learning and sharing expertise amongst the international development community.

David Fellows began his career in UK local government where he became President of the Society of Municipal Treasurers and a pioneer of digital government. He has held appointments in the UK Cabinet Office and the National Treasury of South Africa (david.fellows@pfmconnect.com).

John Leonardo is a PFM expert with extensive worldwide experience. He has undertaken PFM assignments in Africa, Asia, the Caribbean and the Pacific where he undertook PEFA assessments. Both authors are directors of PFMConnect, a public financial management consultancy (john.leonardo@pfmconnect.com).

by David Fellows and Glyn Evans[1]  

The SDGs

The United Nation’s SDGs present an array of complex social, engineering, medical, scientific and managerial challenges for member states set in different contexts and mostly requiring very significant investment, organisational capacity and community involvement. Nations have made commitments to this agenda and it is accepted as guiding the key purposes of international development work worldwide. It is a hugely ambitious enterprise yet we suggest that current development work could be more successful.

The need for a powerful learning system

At a general level perhaps the greatest challenge is the creation of a learning system that is powerful enough to develop and distribute relevant knowledge and an understanding of how that knowledge can be best applied in the very different circumstances that exist across the world. As SDG performance criteria are finalised and adopted a report by ESCAP makes it clear just how difficult it is going to be to make a real difference.

We are not suggesting a great deal of organisation to create this necessary learning system. We propose a loose system of networking between experts based on digital communication. This would enable advice to be made available to community-based projects with greater levels of expertise being made available to the development of major programmes and projects. It would also facilitate feedback on project progress and performance. The use of digital technology would also improve the public information base and support public engagement.

Learning system features

The basis of this networking would be a digital communication system that would be largely self-driven by those in the field and a support network that will evolve around them. Key aspects of this digital communication system are illustrated below.

At national and local level:

• Provide feedback on progress made at
  local level within the country
• Request the public to identify key factors to be taken into account
  when designing SDG initiatives
• Seek feedback on the  regulations
  required to support SDG initiatives
• Engage in shared learning (perhaps amongst scattered populations)  between ordinary people who are trying to cope
  with SDG challenges on limited resources

At regional level:

• Undertake shared research programmes
• Share experiences of adapting recognised approaches to particular circumstances
• Improve monitoring techniques
• Share monitoring and advisory services
• Encourage the development of problem-solving support networks
• Undertake peer reviews of projects and governance arrangements

At international level:

• Build worldwide expertise to address fundamental scientific, engineering, economic, social  and implimentation challenges
• Identify and promote successful strategies and initiatives
• Recognise issues for which effective solutions remain elusive
• Create networks capable of addressing significant and urgent challenges
• Develop modeling tools to help design  solutions

Supporting technology would include:

• Websites including chat rooms, website messaging, on-line data monitoring and
  online questionnaires
• Video-conferencing for expert dialogue and advisory
  sessions
• Cloud-stored databases and shared document development
• Email for public interactions( newsletters), dispatch of documents,
  technical & administrative correspondence and technical update circulars
• Learning management systems to support training programmes that
  develop skills and expertise
• Application software to assist the gathering of performance data
  including the collection of data from administrative sources (ESCAP Report ibid:
  page x)
• Text messaging and social media for public dialogue
• Massive open online courses to raise general awareness

In general such a system would require relatively unsophisticated technology dependent only on fairly low level digital communication. Expert dialogue would tend to benefit from good connectivity at reasonable bandwidth to support video conferencing although this is not absolutely essential. Proprietary software is readily available for most of these applications although bespoke monitoring, modelling and assessment tools could be created as the approach gained traction.

Examples from around the world

Our blog ‘An International eCollaboration Route to Public Service Reform’
(also published by the Australian National University’s DEVPOLICYBLOG in July 2017) considers the diverse power of digital communication technologies. Examples of this technology used in ways relevant to this proposition are, as follows:

1. An example of ‘Shared Learning’ is set out in the UNESCO publication Digital Services for Education in Africa. UNICEF has reported that in Vietnam 40% of children in rural areas used the internet for educational purposes, rising to 62% in urban areas.

2. Communities of practice have already been established in Canada  for green climate purposes

3. Social media has been used by PFMConnect for the past three years to raise public awareness on public financial management and governance topics reaching significant numbers of people in more than 50 countries.

Conclusion

This is not a system requiring heavy oversight and regulation. We seek cultural change to the way programmes and projects are developed. A more inclusive approach at expert and community level could be usefully supported by major development agencies and could become a requirement on contractors. For instance, these proposals could help the Green Climate Fund which appears to be heavily engaged in process issues at the expense of shared innovation.

Is it time to experiment with change?

End note

We should be pleased to discuss the ideas in this piece with those who believe that they may have relevance to their situation.

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[1] David Fellows is a specialist in public financial management and digital government reform and is a director of PFMConnect. He is a recipient of the Swedish Prize for Democratic Digital Service Delivery. Glyn Evans is the Vice President of the Major Cities of Europe IT Users Group and former CIO of various major cities.

Posted by David Fellows[1]

Introducing the concept of “objective data”

In March 2018, we republished a short note on the use of objective data to combat corruption [2]. The piece highlighted statistical techniques being used in western countries to identify corruption by correlating unorthodox procurement practices with aberrant supplier behaviour established from factually based ‘objective’ administrative data. It was suggested that less complex approaches to the analysis of ‘objective’ data could be used to indicate the need for further forensic examination of officials, suppliers, and politicians. The emphasis was on finding workable approaches for developing countries that were compatible with the available resources.

The term ‘objective’ data refers to factual information derived from official government records. It represents data on transactions, activity schedules, and personal information, recorded through established processes, that give the information credibility. This contrasts with ‘subjective’ data which is often based on opinions or experience that is poorly evidenced and of limited application, as is the case with corruption perception surveys.

Frequent use of objective data

Objective data is checked and compared in dozens of administrative processes which can produce anomalies that may indicate the presence of corruption. For example, invoices are checked against orders and goods received notes or contract certificates, or payroll submissions are checked against timesheets. In addition, national bodies charged with the oversight of public administration – such as supreme audit institutions and public procurement commissions – are routinely engaged in the examination of objective data which can also lead to the identification of corruption.

Such findings are then included in published reports that may be used to identify process deficiencies or potentially to prosecute cases of fraud and corruption. These oversight functions can be particularly effective when they are invested with independence from government, extensive powers of enquiry, transparency of reporting, and due consideration of findings.

Developing objective administrative data systems

Apart from routine scrutiny provided by administrative processes and oversight arrangements, programs of administrative reform provide excellent opportunities for the development of systems that incorporate the automatic validation and cross-referencing of administrative data to help identify patterns of corrupt activity.

Such arrangements are straightforward, well known, and remarkably simple to put into effect but in practice they are rarely complete or well executed. Too often there is a lack of expectation that good administration will have a beneficial effect. This places a premium on those who hold relevant managerial roles, requiring them to value high standards of administrative practice; exercise oversight responsibilities courageously, insightfully and in partnership with others as necessary; and ensure that reform opportunities are used to best effect. Well prepared and committed management is a prerequisite to any well-intentioned anti-corruption initiative.

Objective administrative data applications

Some examples of objective administrative data and its use to combat corruption are included in an Appendix available here.

The use of objective data could also be developed in other ways. For example:

1. Countries could prepare anti-corruption strategies that include the use and development of objective data and staff training. Such strategies should be accompanied by operational guidance. Anti-corruption strategies and related material are often referred to as being part of the standard anti-corruption armoury but are rarely made available. In practice, however, few of these documents have been produced to a reasonable standard anywhere in the developing world, and perhaps it is time to redress this omission.
2. Additionally, collaboration between states, perhaps on a regional basis, could be helpful in developing techniques for interrogating data, preparing anti-corruption strategies, sharing knowledge of corrupt practices, and building operational cooperation between countries
3. Consideration should also be given by multilateral agencies and regional representative bodies to the development of an international systems assessment schema (akin to PEFA methodology[3]) that would indicate the efficacy and shortcomings of individual administrative systems for the purposes of combatting corruption.

This article is written with government administration in mind, but similar considerations apply to local governments and state-owned enterprises.

 

[1] Director, PFMConnect. The author thanks John Leonardo for his helpful comments.

[2] This blog was first published at http://blog-pfm.imf.org/pfmblog/2018/03/how-useful-are-perception-indices-of-corruption-to-developing-countries.html

[3] See https://pefa.org/sites/default/files/PEFA%20Framework_English.pdf

 

In a March 2018 blog PFMConnect co-principal David Fellows discussed the deficiencies surrounding corruption perception indices and outlined how objective data analysis could offer a clearer insight into the systemic nature of corrupt behaviour, thus providing a more precise indication of the corrupt parts of an administration, the number of external parties that are engaged in corruption, and features of the public financial management (PFM) system that need to be strengthened in order to combat corruption.

In a forthcoming blog “Developing Systems to Combat Corruption”, David describes how an objective data system is used in practice and how the concept may be developed. Some further examples of objective data and their use to combat corruption is available here.