National Treasury and Department of Science & Technology Review Of

National Treasury and Department of Science & Technology

National Treasury: GTAC 007-2017 (PN730-j RDI) Review of the funding systems, mechanisms, and instruments adopted by government in funding for research, development and innovation including an international bench-mark analysis

Report 22 February 2018

Date Client 22 February 2018 National Treasury & Department of Science and technology

Disclaimer: All care has been taken in the preparation of this document and the information contained herein has been derived from sources believed to be accurate and reliable. RebelGroup does not assume responsibility for any error, omission or opinion expressed as well as investment or other decisions based on this information. All opinions expressed in this report are the responsibility of RebelGroup and do not necessarily reflect the opinions of the National Treasury, GTAC or the Department of Science and Technology.

Acknowledgments: RebelGroup would like to acknowledge the contribution of the many people who contributed information, time and effort in service of this project. A word of thanks to the following; project steering committee members (including officials from the Department of Science and Technology and staff from the National Intellectual Property Management Office) as well as the staff of Centre for Science, Technology and Innovation Indicators (CeSTII) who provided invaluable support in sourcing necessary data for this exercise. We are particularly thankful to: Mr. Godfrey Mashamba Ms. Mavis Anim Mr. Sandisa Siyengo Dr. Kerry Faul Ms. Natalie Vlotman Dr. Glenda Kruss Ms. Natalie Vlotman Mr. Vinod Singh

Project team: Mr. Andreas Bertoldi Dr. Chux Daniels Mr. Christian Gable Mr. Rodney Kukubo Dr. Sibusiso Sibisi Prof. David Walwyn

Contact:

RebelGroup Contract person: Andreas Bertoldi 2nd Floor, West Wing, 158 Jan Smuts Avenue, Rosebank, 2196, Johannesburg, South Africa Tel. +27 010 591 1232; Mobile. +27 83 289 4135 Email. [email protected]

Table of Contents

1 Approach and Methodology 6 1.1 General Objectives 6 1.2 Specific Objectives 7 1.3 Focus of the Analysis 8 1.4 Report Structure 8

2 Step 1: Institutional Analysis 9 2.1 Definitions and Theory for Research and Development 9 2.1.1 Definitions for types of Research and Development 11 2.1.2 Definitions of a National Systems of Innovation 12 2.1.3 Definitions of Actor Categories 13 2.2 Rationale for the Public-Funding of R&D 13 2.2.1 Market Failures 15 2.2.2 Knowledge Spill-overs 16 2.2.3 Human Resource Development 16 2.2.4 Support for Public Goods and Services 16 2.2.5 Global Competitiveness and Economic Growth 16 2.3 Barriers to Return on Investment in R&D 17 2.4 Policy Environment and Policy Intent for Public-Funded R&D in South Africa18 2.4.1 White Paper on Science and Technology 18 2.4.2 National Research and Development Strategy 19 2.4.3 Strategic Management Model of 2004 20 2.4.4 Policy Intent of the Programme 21 2.5 Institutional Landscape and Situational Analysis 22 2.5.1 Actor Hierarchy: Institutional Linkages between Actors and Funding Flows23 2.5.2 Understanding the Functional levels within the R&D System 25 2.5.3 Governance and Research Functions within the South African R&D System26 2.5.4 Strategic Intelligence 26 2.5.5 Vertical Steering and Contracting 27 2.5.6 Horizontal Coordination 28 2.5.7 Flow of Funds across the Levels 29 2.6 Comparative Examination of SA R&D Landscape to International Examples 31 2.6.1 Open versus Closed Budget Processes of R&D Funding 31 2.6.2 Benchmarking South Africa with Key Performance Indicators 31 2.6.3 Strategic positioning of the government function on Science and Technology 34 2.6.4 Trends and Structural Changes to R&D Funding Mechanisms 34 2.7 Findings from the Institutional Analysis 39 2.7.1 Funding Coordination and findings for Funding Mechanisms 39 2.7.2 Monitoring and Evaluation for the R&D Landscape 40

3 Step 2 and 3: Logical Framework and Indicators for Public-Funded R&D 41 3.1 Theory of Change 41 3.1.1 Inputs 43 3.1.2 Activities 43 3.1.3 Outputs 43 3.1.4 Immediate Outcomes 44 3.1.5 Intermediate Outcomes 44

3.1.6 Long-Term Outcomes and Overall Impact 45 3.2 Indicators 45 3.3 Work Breakdown Structure 46

4 Step 4: Expenditure Analysis of Public-Funded R&D 53 4.1 Purpose of the Expenditure Analysis 53 4.2 Data Analysed 53 4.3 Overall Spending for R&D Programmes 58 4.4 Intramural versus Extramural Expenditure 61 4.5 BAS Data compared to secondary data sources 63 4.6 Performance Expenditure by Socio-Economic Objective 68 4.7 Conclusions 70

5 Step 5 and 6: Costing Model Exercise and Trade-offs 72 5.1 Costing of R&D Outputs 72 5.1.1 Main Cost Components and Relative Costs for R&D Outputs 72 5.1.2 Actual Costs 73 5.2 Methodology for Costing Exercise within the PER 73 5.2.1 Definition of the Key Performance Indicators 74 5.2.2 Publication Equivalents (Scientific Publications) 74 5.2.3 Research Qualifications 75 5.2.4 Patents Granted 75 5.2.5 Intellectual Property Income 75 5.2.6 Technology Packages and Spin Outs 75 5.2.7 Contract Research Income 76 5.2.8 Relative Valuation of the Indicators 76 5.2.9 Model Application 79

6 Conclusions of the PER 81

7 Appendix 1: Glossary 82

8 Appendix 2: References 84

9 Appendix 3: Respondents List (BAS, CeSTII, STA) 87

List of Figures Figure 1: PER Standardised Methodology 7 Figure 2: Impacts of public funding of R&D 14 Figure 3: Evolution of South Africa's R&D policy environment 18 Figure 4: Strategic framework of the NRDS 20 Figure 5: Actor hierarchy as per the PER 24 Figure 6: Functional Levels within the R&D System 25 Figure 7: Illustration of Funding Flows through National Department 30 Figure 8: Major funding flows for R&D from all sources in South Africa, 2014/15 30 Figure 9: Funding flows for STA and programmes 31 Figure 10: Public funding for PRIs and HEIs (2000 to 2010; constant 2005 $) 35 Figure 11: Changes in Policy Mix for innovation policy 38 Figure 12: Major Funding Instruments in the Policy Mix for Innovation (2014) 39 Figure 13: Theory of Change for South African Public-Funded R&D 42 Figure 14: Theory of Change for South African Public-Funded R&D 47 Figure 15: Funding flows for STA and programmes 54 Figure 16: Data Hierarchy and Relationships 55 Figure 17: Estimated Total Government BAS and R&D Expenditure (2013/14 -2015/16) 58 Figure 18: GDP to Government R&D BAS Expenditure (2013/14 -2015/16) 59 Figure 19: R&D BAS Expenditure Top Ten Departments (2013/14 -2015/16) 59 Figure 20: R&D BAS Expenditure Transfers and Intramural (2013/14 -2015/16) 61 Figure 21: Selected Entities Transfers by Source of Department Funds (R&D BAS Expenditure 2013/14 - 2015/16) 62 Figure 22: Selected National Departments Intramural Expenditure (R&D BAS Expenditure 2013/14 - 2015/16) 63 Figure 23: Departments within BAS but without GBAORD figures (BAS and STA Data) 63 Figure 24: Final BAS Expenditure compared to GBAORD (2013/14-2015/16) 64 Figure 25: Intramural R&D BAS Expenditure compared to CeSTII survey data (2013/14-2015/16) 65 Figure 26: R&D BAS and CeSTII R&D Performance Expenditure by Actor (2013/14-2015/16) 66 Figure 27: R&D BAS and CeSTII R&D Performance Expenditure by Actor per Year (2013/14-2015/16) 67 Figure 28: CeSTII R&D performance amounts by actor (2013/14-2015/16 68 Figure 29: Aggregate 2013/14-2015/16 CeSTII R&D performance amounts by actor (limited to source of fund - public funding) 68 Figure 30: CeSTII R&D performance data on Socio-Economic Objectives by Actor (2013/14-2015/16) 69 Figure 31: CeSTII R&D performance data on Socio-Economic Objective (2013/14 -2015/16) 69 Figure 32 CeSTII R&D performance expenditure data based on type of research produced (2013/14 - 2015/16) 70 Figure 33:FTE costs in South Africa 73

List of Tables Table 1: Identifying R&D projects through the 5 core criteria 10 Table 2: Differentiating types of R&D according to sector 11 Table 3: R&D Sector Barriers to Return on Investment 17 Table 4: Oversight and Transaction Activity 29 Table 5 Summary of R&D Benchmark Comparisons by Country (2014) 32 Table 6 Allocation of Public R&D Funds in Benchmark Countries (2014) 33 Table 7 Categorisation of funding for South African Public Research Institutes 35 Table 8 Monitoring and Evaluation Activities in the R&D Sector 40 Table 9: Performance indicators as selected for the NRDS 45 Table 10: Indicator Framework for South African Public-Funded R&D 48 Table 11. Work Breakdown for South African Public-Funded R&D 51 Table 12 Approximate values for the standard components of a R&D project 72 Table 13 Indicators for Costing Model and Equivalent Values 78 Table 14 Assumptions in the Costing Model 79 Table 15 Summary Sheet for Costing Model 80

Abbreviations & Acronyms

BERD Business Expenditure R&D DST Department of Science and Technology DOE Department of Energy ENE Estimates of National Expenditure GBAORD Government budget appropriations or outlays for R&D GDP Gross Domestic Product GERD Gross Expenditure on R&D GovERD Government Expenditure on R&D HERD Higher Education Expenditure on R&D IBA International Benchmarking Analysis IPAP Industrial Policy Action Plan MTEF Medium Term Expenditure Framework NACI National Advisory Council on Innovation NDP National Development Plan NIH National Institutes of Health NIST National Institute of Standards and Technology NRDS National Research and Development Strategy NSI National System of Innovation OECD Organisation for Economic Co-operation and Development PER Performance Expenditure Review PSERD Public Sector Expenditure on R&D R&D Research and Development RDI Research, Development and Innovation S&T Science and Technology SOE State Owned Enterprise TYIP Ten-Year Innovation Plan

Key terminology and definitions for Research, Development and Innovation sector are provided as part of Appendix 1.

1 Approach and Methodology

1.1 General Objectives Government’s understanding of the effectiveness of specific policy initiatives relies on monitoring and evaluation information flows. In principle, this information is the evidence base on which the allocation of resources to programmes and institutions rests. But in practice, the set of monitoring tools for assessing the implementation of policy initiatives has not rendered information that is rich and detailed enough to be useful to managers, and the budget process does not adequately take advantage of planning information, performance monitoring or programme evaluation reports. There is a large gap between policy development and implementation planning. In many instances, costing is not regarded as part of the policy development process. In certain instances, partial costings are done later for purposes of asking National Treasury for funding. However, there is little sense of what the full cost of policy initiatives/ implementation programmes are and whether they are even affordable, or how they can be made to be more affordable. The National Treasury has initiated a number of Performance Expenditure Reviews (PERs) that are intended to provide an improved understanding of:  The costs of activities/services, expenditure patterns and trends over recent years, and what drives changes in costs, as well as the distribution of costs and expenditure across spheres of government and between relevant government agencies, and  The output and impact of this expenditure (and the delivery of services) in supporting government activities or in delivery to the public. In addition, the PERs work aims to identify proposals for:  Improving budget allocations and expenditure,  Improving the linkage between policy goals, programme design, and delivery by identifying and interrogating the chain of causality between them, and  Developing key measures of performance to assist in the monitoring of performance and expenditure in the future, preferably based on existing data and systems. The overall approach to the PER is guided by a specific methodology, which reflects the learnings of the previous PER assignments. The overall PER process is set out in the figure overleaf and comprises seven key steps of analysis.

Figure 1: PER Standardised Methodology

1.2 Specific Objectives The primary purpose of this project is to undertake a performance expenditure analysis of governments funding for Research, Development and Innovation (RDI) in support of a better, evidence-based approach to public funding of RDI in South Africa. The specific objectives of the project are to:  Quantify levels of spending/investment and performance in RDI programmes in SA between 2013/13 to 2015/16  Analyse spending patterns and identify cost drivers across national and provincial governments  Describe approaches to budgeting and funding, as well as the mechanisms and instruments other countries use to secure sufficient public RDI funding  Benchmark SA levels of spending and approaches to budgeting and funding against international norms  Propose an approach to ensuring the efficient allocation of ROI funding to various departments and institutions  Develop a set of practical performance measures for critical aspects of ROI system  Make proposals for implementation in the next MTEF

1.3 Focus of the Analysis The original Terms of Reference for this assignment sought to understand activities and funding flows as they relate to “RDI,” meaning Research, Development, and Innovation. “Research and Development” is well-understood, supported by a body of research and an internationally recognised consensus definition whereas “innovation” is ill-defined with contested interpretations. The project steering committee and research team made the determination that including “innovation” activities and expenditure would make the exercise too broad and dilute the study’s findings. In Section 2 below, the research team has provided more a more detailed description of what is contained within the scope of the assignment using the OECD definition of “Research and Development”. This interpretation has material implications for the expenditure analysis, which needed to be contained given the large number of departments and entities examined. The research team has used a variety of approaches to arrive at a final view of the institutional landscape within the South African R&D System. This included a review of annually published documentation by departments and entities; such as the Annual Performance Plans and the Annual Reports. Utilising the Frascati Manual as a guidance framework, each programme or activity description within these publications were scrutinised to assess the actor’s relevance to the study. This effort also helped to provide a sense of which sub-programmes relate specifically to R&D investment and which might fall under other purposes, such as international travel or accommodation. Still, there are several limitations to this approach as definitions and reporting criteria vary between entities, and there is an opportunity to mis-identify certain categories of activity.

In addition, an extensive analysis of R&D expenditure through the Basic Accounting System (BAS) data provided by National Treasury has been undertaken, which aided in triangulating organisations that are undertaking R&D activities. The exact approach and methodology to the analysis of BAS data are discussed in another section of this report. A final informant to the Institutional Review component of the PER came through the engagement with the Centre for Science, Technology, and Innovation Indicators (CESTii) based at the Human Science Research Council who were able to offer a list of entities and Departments that had contributed to the R&D Survey over the last three years.

1.4 Report Structure This report is organised in line with the key PER Steps and comprises the following sections:  Description and overview of the R&D institutional landscape  A Theory of Change and Indicators for the Publicly-funded R&D Sector  Funding Flows within the Sector  Expenditure Analysis and Review of Data Sources  Costing Model of R&D Outputs  Key Findings and recommendations

This final report is a companion piece to the excel workbooks that serve as deliverables for many of the steps within the PER. It provides for clarity on definitions for the sector, key methodological explanations, and motivations for decisions taken by the research team.

2 Step 1: Institutional Analysis

2.1 Definitions and Theory for Research and Development The internationally accepted guideline on the definition of Research and Development and its measurement is the “Frascati Manual: Guidelines for Collecting and Reporting Data on Research and Experimental Development (OECD 2015), commonly referred to as the “Frascati Manual.” Within this framework Research and Development (R&D) is defined as “creative and systematic work undertaken to increase the inventory of knowledge (which includes the knowledge of humankind, culture and society) in order to devise new applications of available knowledge” (OECD, 2015; OECD, 2002). Note: Key Terms for the Research and Development Sector are derived from the document referenced above and have been included as Appendix 1. R&D activities can be performed by multiple parties or single individual and can be aimed at reaching specific or general objectives. All R&D activities are aimed at new findings based on original concepts and their understanding. Given the above, a few observations in respect of the R&D process can be made:  R&D activity is uncertain about its outcome or the amount of time and resources needed to reach its outcome;  R&D is planned for and budgeted and it is aimed at producing results that could be seamlessly transferable and/or reproducible (OECD, 2015). In principle, there are 5 characteristics that need to be met for the activity to be identified as a R&D activity, namely the following: 1) Creative: R&D projects undertaken should be able to improve on existing knowledge and processes through objective new concepts. Given the above statement, routine changes to products and processes are excluded from R&D and a human input is inherent to the creativity in R&D (OECD, 2015) 2) Uncertain: Each R&D process has varying degrees of uncertainty. At the starting point of any R&D process, the outcome and costs cannot be determined with precise certainty, relative to the primary goal. As R&D is undertaken, there is always consensus reached that a possibility of not achieving the intended results, despite the injection of resources, is a possibility (OECD, 2015). 3) Novel: The creation of new knowledge is an expected objective of an R&D project; however, it is important to note that the potential novelty of R&D projects has to be assessed by comparison with the inventory of knowledge presently in the industry (OECD, 2015). The R&D activity within the project must result in findings that are new to the developer and not already in use in the industry. Excluded from R&D are activities

undertaken to copy, imitate or reverse engineer as a means of gaining knowledge, as this knowledge is not novel (OECD, 2015). 4) Systematic: R&D is conducted in a planned way, with records kept of both the process followed and the outcome. To verify this, purpose of the R&D project and the sources of funding for the R&D performed should be identified. The availability of such records is consistent with an R&D project that is aimed at addressing specific needs and has its own human and financial resources (OECD, 2015). 5) Transferable & reproducible: An R&D project should result in the potential for the transfer of the new knowledge, ensuring its use and allowing other researchers to reproduce the results as part of their own R&D activities (OECD, 2015). This includes R&D that has negative results, in the case that an initial hypothesis fails to be confirmed or a product cannot be developed as originally intended (OECD, 2015). Table 1 provides some general guidelines on how R&D can be identified using the five criteria explained above. Table 1: Identifying R&D projects through the 5 core criteria

Question Comment

The pursuit of original and challenging objectives through the creation of What are the “new knowledge” is a key criterion for R&D. Any use of already available objectives of the knowledge (adaptation, customisation, etc.) which does not entail an project? attempt to expand the state of the art should be excluded (novelty).

In addition to the development of “new knowledge”, an R&D project should What is new have a creative approach, such as devising new applications of existing about this scientific knowledge or new uses of available techniques or technologies project? (creativity).

Methods used in scientific and technological research, as well as in What methods research in the social sciences, humanities and the arts, are accepted if are being used to they address uncertainty about the project’s outcome. The uncertainty carry out the could be about how much time and resources will be needed to achieve the project? planned goal. The choice of method could be part of the project’s creativity and a means of dealing with uncertainty (creativity and uncertainty).

To be generally applicable, the findings of an R&D project have to meet the How generally criterion of being transferable/reproducible, in addition to the other four applicable are the criteria. Transferring the results may for example be demonstrated by findings or results publication in the scientific literature and the use of instruments of of the project? intellectual property protection.

A range of skills is assumed to be required to undertake an R&D project (the R&D personnel issue is discussed in Chapter 5 of this manual). What types of Research personnel in projects are classified as researchers, technicians staff are working and other supporting staff, but only researchers, working as researchers, on the project? are needed to identify an R&D activity which, implicitly, satisfies all five core criteria.

Question Comment

In selected cases, an “institutional approach” can be used to distinguish How should the between R&D and non-R&D projects. For instance, most projects carried research projects out in research institutes or research universities can be qualified as R&D of research projects. Projects launched in other domains – like business enterprises or institutions be institutions not totally devoted to R&D – should be checked against the five classified? R&D criteria

Source: Adapted from the Frascati Manual (OECD, 2015)

2.1.1 Definitions for types of Research and Development Assuming all the above criteria are met, the term “R&D” spans three types of activities:  Basic research: The Frascati Manual defines basic research as the theoretical or experimental work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any clear application or use (OECD, 2015).  Applied research: Applied research is described as original investigation that is undertaken to acquire new knowledge towards a specific primary objective (OECD, 2015).  Experimental development: Experimental development is the systematic work, drawing on knowledge gained from research and practical experience and producing new products or processed or to improving existing products or processes (OECD, 2015). The table below provides some examples of each research type by sector. Table 2: Differentiating types of R&D according to sector

Sectors R&D Types

Basic research – Examples would include a review of theories on the factors determining regional disparities in economic growth or the development of new risk mitigation approaches.

Applied research - The analysis of a specific regional case for the purpose of developing government policies. Economists investigating the properties of an auction mechanism that could be relevant to auctioning the Economics & telecommunications spectrum. businesses Experimental development - The development of operational models, based upon statistical evidence, to design economic policy tools to allow a region to catch up in terms of growth. The development by a national telecommunications authority of a method for auctioning the telecommunications spectrum. The development of a new method to manage an investment fund is experimental development as long as there is sufficient evidence of novelty.

Basic research: Analysis of the environmental determinants of learning ability. Education The investigation by researchers of the effect of different types of manipulatives on the way first graders learn mathematical strategy by changing manipulatives

Sectors R&D Types and then measuring what students have learned through standardised instruments

Applied research: The comparative evaluation of national education programmes aimed at reducing the learning gap experienced by disadvantaged communities. The study by researchers of the implementation of a specific math curriculum to determine what teachers needed to know to implement the curriculum successfully.

Experimental development: The development of tests for selecting which educational programme should be used for children with specific needs. The development and testing (in a classroom) of software and support tools, based on fieldwork, to improve mathematics cognition for student special education.

Basic research: Researchers seek to understand the fundamental dynamics Social & of spatial interactions. Economic Geography Applied research: A research study analyses the spatial-temporal patterns in the transmission and diffusion of an infectious disease outbreak.

Source: Adapted from the Frascati Manual (OECD, 2015) In the context of R&D processes, basic research does not necessarily evolve or lead to applied research and experimental development. In other words, the definitions do not imply a linear model of innovation. Further clarification of the three types is provided in Appendix 1.

2.1.2 Definitions of a National Systems of Innovation A national system of innovation is defined as a network of actors who function within a particular context of institutions and policies, and together accomplish knowledge creation and technology development, adoption behaviour and performance, and who bring new products, processes and organization structures into economic or social use (Lundvall, 2010; Lundvall, 1992; Freeman, 1987). This definition highlights the four structural components of an innovation system, namely:  Actors: Actors include firms and other organizations (such as universities, industry associations).  Networks: Networks are the result of links established between separate actors to perform a particular task (such as learning, knowledge creation and diffusion, standardization, market formation).  Institutions: Institutions consist of formal rules (e.g. laws and property rights) and informal norms (e.g. tradition and culture) that structure political, economic and social interactions. Institutions have three roles: reducing uncertainty by providing information; managing conflicts and promoting cooperation; and providing incentives for innovation (Bento and Fontes, 2015).  Knowledge/ material artefacts.

Systems of innovation theory introduced the need to look beyond just institutions and to include the concept of linkages, placing a new emphasis on the importance of these interdependencies in achieving technological innovation within national economies. The impact of this new approach was far-reaching and helped to improve both the management and output of such systems at the level of the firm and elsewhere. Since the publication of the White Paper on Science and Technology (DACST, 1996), the national systems approach has become more accepted in South Africa in line with its wide adoption in many countries and international organisations. According to Lundvall (2007), two of the positive impacts have been firstly a reconsideration of policies for international competitiveness (of domestic economies), where the latter is now more focussed on improving output rather than reducing cost (such as through currency devaluation); and secondly a shift in policy circles from linear to interactive thinking of innovation, also referred to as a transition from science and technology policy to innovation policy (Lundvall and Borrás, 2005). The latter is particularly relevant to South Africa, which is struggling to raise or even maintain levels of technological innovation. Researchers from other countries attempting to look at similar constraints within their economies and particularly within different economic sectors have noted that sectors differ in respect of their modes of innovation and hence the types of incentives required for the stimulation of technological innovation. Furthermore firms (and sectors) tend to be either technology users or technology producers, with the latter favouring R&D and the former DUI (Reinstaller and Unterlass, 2008). One of the challenges is to encourage firms generally to adopt both modes since the evidence points to the combination as being optimal for production innovation.

2.1.3 Definitions of Actor Categories Theory in National Systems of Innovation calls for clear segmentation of actors involved in R&D along lines of competency and mandate. Thus, there is a distinction in actor types between the policy-making (ministry), customer (agency) and contracting (project-performing) levels of government, in order to increase transparency and to create markets at the interfaces between the layers. Thus, organisations began to typify into categories; “funders” of R&D and “performers” of R&D. This division of labour has important benefits. It forces greater clarity on objectives and enables competition between research performers at the project level and between alternative agents or agencies at the programme level. This delineation also aides in preventing conflict of interests that can arise in funding of research.

2.2 Rationale for the Public-Funding of R&D Evidence from studies of economic growth has shown that in the medium to long term innovation is a crucial driving force of growth in many developed countries, as well as developing countries (Bilbao‐Osorio and Rodríguez‐Pose, 2004; Rosenberg, 2004). This influence is the consequence of various factors, including the impact of innovation on building and maintaining competitive advantage at firm level, improvements in health and protection of public goods. As a result, RDI has become increasingly important for Government’s around the world, and the use of public resources to fund private R&D has long been considered as legitimate (Carvalho, 2012) . Public- funded research, which consists of R&D funded from the fiscus and conducted by a range of actors

including public research intuitions (PRIs), public research universities, intramural government departments, state owned entities and private firms, plays an important role within the system of innovation and the production of knowledge (OECD, 2017). Such a perspective is supported by multiple South African policy documents (National Planning Commission, 2011; Department of Science and Technology, 2002). For instance, the forward to the South African Survey of Intellectual Property and Technology Transfer at Publicly Funded Research Institutions, written by the Minister of Science and Technology, states that “Innovation is crucial for South Africa’s economic growth and competitiveness. To enhance technological innovation, scientific R&D is necessary. As the enabler, government, playing the role of an “entrepreneurial state”, is thus required to invest significantly in R&D and in the institutional platforms that drive innovation.” (National Intellectual Property Management Office, 2017). R&D can lead to a form of innovation known as radical innovation, where the latter plays a crucial role in a country’s social and economic development and has been recognised as a new and potentially significant driver of improvements in service delivery and poverty alleviation, as well as a mechanism for achieving commercial benefit, economic growth and job creation. R&D also builds and strengthens the absorptive capacity of national systems of innovation; this capacity is essential to the process of incremental innovation, which often relies on technology transfer and diffusion at firm level (Arnold and Bell, 2001). The figure below shows that public funding for R&D generates several intermediate outcomes, ultimately supporting Factor Accumulation and Total Factor Productivity within an economy. Figure 2: Impacts of public funding of R&D

Source: Adapted from Walwyn (2016)

The following enumerates the various reasons for public investment in R&D, including the neo- classical approach of market failures, the Schumpeterian logic of economic competitiveness, the public goods perspective of human resources/environment and R&D in support of public services including health and defence.

2.2.1 Market Failures The principle rationale for the public provision of research funding is often stated as market failure. In the specific context of the innovation process, four typical sources of market failure are identified: indivisibilities linked to increasing returns, lack of appropriability related to externalities, uncertainty inherent in R&D investment, and information asymmetry (Chorafakis, 2013; Arrow, 1962):  Indivisibilities: Indivisibility refers to the necessary economy of scale, and particularly high setup costs, for R&D to be effective. As the production of new technological knowledge is becoming more complex and demanding, indivisibilities tend to increase, and so do the barriers to entry for new firms and the costs of innovation-based competition for incumbent firms. For this reason, firms increasingly resort to the adoption of the open innovation paradigm, and Governments assist with various instruments including the establishment of common infrastructure in order to share the upfront costs.  Inappropriability: Technological knowledge, with the exception of the rather unusual cases where it can be protected using intellectual property provisions, is generally considered to be non-rival and non-excludable i.e. it cannot be made exclusive and exhibits strong spillovers (Bernanke, 2011). As a result, it tends to be generally under-produced by the market. Government intervention through public research funding in this context aims to ensure the sufficient provision of this type of knowledge for the benefit of the innovation system at large (see next section). In the case of rival technological knowledge of the instrumental or organisational type, the problem of inappropriability is partially tackled through the establishment and protection of IPR.  Uncertainty: R&D investments take years to materialise into new products, and often lead to failure. Even when some success is observed, sometimes the actual outcome is a lot different than what was predicted and the returns from those investments are highly uncertain and thus cannot be understood through rational economic theory (Mazzucato, 2013). Given the inherent high level of risk, the market does not provide enough incentives for private investment on R&D, which creates a need for public investment. The private sector is in many ways less entrepreneurial than the public sector, as it shies away from radically new products and processes, leaving the most uncertain investments to be first taken on by the state (Mazzucato, 2013). As a result, Governments mobilise resources, allowing knowledge and innovations to diffuse across sectors and the economy, and businesses to benefit in a way that would not have otherwise have been possible.  Information Asymmetries: Another cause of underinvestment by private sector is the inability to attract external funding due to information asymmetries, especially prominent among SMMEs and start-ups (Mashamba, 2015).

2.2.2 Knowledge Spill-overs As already noted, the full economic benefits of technological innovation are unlikely to fully accrue to its developer or creator, especially if the new knowledge can be replicated or disseminated at low cost (Bernanke, 2011). If many people are able to exploit, or otherwise benefit from, research done by others, then the total or social return to research may be higher on average than the private return to those who bear the costs and risks of innovation, supporting the need for the state to play a major role in create opportunities of knowledge spill-overs through their investment in R&D.

2.2.3 Human Resource Development The process of R&D results in human resource development (HRD) and the creation of new job opportunities as part of the process of the renewal of an economy, where innovative companies produce more and better job opportunities. A crucial mechanism for the transfer of knowledge from public research to firms takes place when this knowledge is embodied in the researcher that carries out the specific research and the scientists migrate into the commercial sector of the innovation system (European Commission, 2017). The benefits are associated not only with applying the latest theoretical knowledge accruing from scientific research, but also scientists transferring elements of problem-solving strategies that are fundamental in basic research. Public support for R&D therefore has a triple function in HRD; it leads to new skills, it retains existing key skills (Carvalho, 2012) and it improves the absorptive capacity of firms.

2.2.4 Support for Public Goods and Services The private sector does not have any immediate or direct incentive to invest in public goods because by its nature, you cannot derive marginal benefits from individual consumption and therefore cannot effectively supply these goods at a profit. The onus is on the Government to invest in the protection and preservation of public goods for the goal profit. Public research is also needed to meet specific needs of national interest, such as defence, and of the population at large, such as health and food safety, and as a result, potentially new and improved products and applications can result from new R&D activities (Griffith et al., 2006).

2.2.5 Global Competitiveness and Economic Growth Another argument sometimes made for expanding government support for R&D is the need to keep pace with technological advances in other countries. R&D has become increasingly international, thanks to improved communication and dissemination of research results, the spread of scientific and engineering talent around the world, and the transfer of technologies through trade, foreign direct investment, and the activities of multinational corporations (European Commission, 2017). In the face of globalisation, the location of R&D activity can matter. To emphasise the above point, advanced technological expertise may help a country reap the financial and employment benefits of leadership in a strategic industry. Public support for R&D is therefore important in order to assist firms in adapting to technological change; exploiting new knowledge; increasing absorptive capacity; supporting the spillovers of R&D activities to other firms and industries; and increasing the interaction between firms, universities and research institutions. Governments must stimulate private R&D not necessarily due to any imbalance between private and social returns in specific industries, but because it is believed to be a major driver of future economic growth based on knowledge and innovation (Carvalho, 2012). This

aspect links closely to the analytical framework of the Cobb-Douglas function and the concept of total factor productivity (TfP).

2.3 Barriers to Return on Investment in R&D Encouraging a conducive enabling environment for Research and Development and ensuring that the sector is structured for optimal performance is no easy exercise. The literature on R&D policy notes a number of pitfalls that can undermine efficacy of R&D as a government supply-side intervention and ultimately the achievement of desired objectives: Table 3: R&D Sector Barriers to Return on Investment

Limitation / Explanation Potential Barrier

Reduces the efficiency and the effectiveness of public investment in R&D if Inadequate firms or other economic actors fail to take up research outputs. The quantity absorptive and quality of human and social capital involved in the innovation process, capacity of R&D as well as the strength, coherence and diversity of economic sectors are fundamental determinants of absorptive capacity.

Inadequate An environment where there is increased funding for activities but no performance additional capacity due to an inflexible labour market simply leads to an capacity increase of R&D costs rather than growth in output.

Fragmentation Much of R&D system efficacy relies on thickness of relationships between and key actors. dysfunctionality

Inefficiencies and Additional layers in the delivery chain and complex processes can lead to transaction costs wasteful expenditure and dilution of impact.

Contexts where there is low competition and less drive for innovation can Demand for lead to little uptake of publicly funded R&D. goods

2.4 Policy Environment and Policy Intent for Public-Funded R&D in South Africa The importance of R&D, in particular R&D policy and supporting instruments for R&D, has evolved in South Africa over the last 25 years, particularly with the adoption of the White Paper on Science and Technology in 1996 (DACST, 1996) and its associated concept of the national system of innovation (NSI), as shown in Figure 3. In this chapter, we present an initial overview of the NSI, then discuss in more detail the National Research and Development Strategy, where the latter is considered as the core policy framework for the analysis of this Performance Expenditure Review on RDI. Figure 3: Evolution of South Africa's R&D policy environment

Adapted from the DST Ministerial Review (2012)

2.4.1 White Paper on Science and Technology Many countries have adopted the policy approach of a national system of innovation, where the latter is defined as “ the network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies” (Freeman, 1987) The primary objective of the NSI was to, “enhance the rate and quality of technology transfer from the science, engineering and technology sector by the provision of quality human resources, effective technology transfer mechanisms, and the creation of more effective and efficient users of technology in the business and government sectors” (Department of Science and Technology, 2012). The adoption of the White Paper on Science and Technology in 1996 led to a new era in S&T policy, in which public funded R&D was meant to, “positively affect the “quality of life of citizens in the areas of environmental sustainability, health care provision, meeting basic needs at community level, reducing cost of infrastructure provision, and providing safety and security to all” (DST, 2012). The adoption of the White Paper led to the establishment of the NRF and NACI in 1998 and the formation of the DST in 2002. Between 1997 and 2001, two sources of public funding for R&D were created: The Innovation Fund and then the Biotechnology Regional Innovation Centres (DST,

2012). The Innovation Fund was aimed at projects of an innovative nature that will generate new knowledge and, projects that will be commercially viable at the end of the three-year contract. Justifications for the integration of the NSI approach contained in the White Paper are described below (Walwyn et al., 2015):  has a focus on innovation, which is doing new things and new ways, as opposed to the production of knowledge  offers a means of identifying what needs to be done without automatically tying the necessary function to any existing institution or organisation  affords an opportunity to think of means for the promotion of coherence and integration among national activities, which are two factors within the South African S&T system.  Note: The government has completed a revised White Paper on Science and Technology in 2017 but this is not yet for public distribution.

2.4.2 National Research and Development Strategy As a response to the increasing concerns of the lack of adoption of the NSI across government departments, the National R&D Strategy (NRDS) was promulgated in 2002 (Department of Science and Technology, 2002). The NRDS had special focus on the key perceived weaknesses of the NSI such as:  insufficient funding arrangements  lack of growth in numbers of high-level S&T personnel  an apparent decline in private sector R&D  absence of new policy on intellectual framework. The NRDS also specified that an annual science budget document would be created from data drawn from departmental budgets, to reflect all government research and development expenditure; this part of the strategy has not been implemented (Walwyn et al., 2015). A highly relevant aspect of the NRDS is the implied logical framework, or what the document itself referred to as the strategic framework, which is shown in the figure below. However, the PER logical framework and Theory of Change focuses explicitly on R&D and Public-funding while the NRDS reaches for a more inclusive view and includes innovation and private-sector driven R&D. Despite these differences, the NRDS serves as useful proxy for determining the “programme logic and design” in the context of this Performance and Expenditure review since the assignment covers no one particular programme within government.

Figure 4: Strategic framework of the NRDS

Adapted from the National Research and Development Strategy 2002 The relationships and causal assumptions have informed the logical frameworks adopted for this Performance and Expenditure Review analysis, as shown in later sections of this document.

2.4.3 Strategic Management Model of 2004 Integral organisational arrangements for government managed research were elaborated in the promulgation of the 2004 Strategic Management Model for South Africa's public S&T system in 2004. The impact of this initiative has not been published, although the model has been implemented. The 2004 Strategic Management Model (2004 SMM), was intended to achieve the following within the National System of Innovation (NSI):  clarify and strengthen the functions of the DST and the relevant line departments to support and undertake R&D  enable the DST to act as a driver or framework for coordinating the National System of Innovation  outline the role of the DST in setting common governance standards and quality assurance mechanisms for each science council, irrespective of their location (through the associated Policy on Governance Standards for Science, Engineering and Technology Institutions)  assign to the DST the annual process of assembling National Science and Technology Expenditure Reports, to be used for the generation of a single government S&T expenditure plan covering and integrating all DST and sectoral R&D plans (through the associated Framework for the Development of a National Science and Technology Expenditure Plan)

 ensure that the DST could assist in the case of national priority programmes with best practice advice on S&T aspects, including developing financial instruments for that purpose. A significant contribution of the 2004 SMM was to describe the nature of the partnerships between the DST and those departments which managed domain-specific research institutions, such as the National Department of Health (managing the Medical Research Council). The NSMM accepted the view that domain-specific research agencies should remain within their respective line departments, and that the function of the DST would be to develop interventions only in the case of market failure, under-subscription or where there are technology gaps of a strategic nature. Examples here include those areas where sector departments are not ready to drive the necessary sector-specific technology programmes due to capacity deficiencies. The annual S&T expenditure plan was intended to guide the clusters and government as a whole on the deployment of resources, while retaining absolute accountability in the relevant departments. The expenditure reports collate expenditure in three different categories across the large number of government departments (23 of the 34 departments) with significant Science and Technology Activities (STAs). The three categories are Scientific and Technological Innovation (STI, about 63%), Scientific and Technological Education and Training (STET, 20%) and Scientific and Technological Services (STS, 17%). The annual reports are obtained through questionnaire- derived information and direct consultations with departments. In summary, the 2004 SMM represented a major intervention in the public component of the NSI, providing clarity on certain definitions and mapping a perhaps optimistic view of the role of the DST in its limited, but now better-defined, domain by advising or cajoling its departmental peers into meeting the demanding requirements set for each of them in creating a well-functioning segment of the NSI.

2.4.4 Policy Intent of the Programme The above sections outlined pertinent policy aspects relevant to this analysis. It is no simple matter to define the policy intent comprehensively since there are multiple opinions and views, spread across various documents, some of which are contradictory. Despite such hurdles, the research team has derived a set of broad policy “intents” on the basis of the available policy documents and elements of previous sections of the report. These policy intents summarise the main aims of the South African Research & Development policy landscape. Primary Policy Intent  Maximise the transformative potential of science and innovation to improve economic and social well-being  Strengthen the functioning of the NSI, particularly regulatory, performance, and funding agencies, and the networks between system actors  Increase factor productivity within the economy  Encourage a pervasive culture of innovation  Support growth in the fiscal base to sustain the social wage

Secondary Policy Intent The team has defined “secondary” those objectives that are specifically linked to individualised indicators that serve to support the overall development within the National System of Innovation.  Provide sufficient government budget appropriations or outlays for R&D (GBAORD) to ensure the gross expenditure on R&D (GERD) as a percentage of Gross Domestic Product (GDP) reaches a target level of 2.5% (GERD/GDP is presently at 0.80%, GBAORD at 0.34% of GDP and 44% of GERD).1  Ensure that there are sufficient scholars matriculating with satisfactory marks in science and mathematics. At present, it is reported that the percentage of grade 12 scholars passing NSC with >50% for Mathematics and Physical Science is 11.8% and 9.3% respectively in 2015  Maintain a satisfactory level of science, engineering and technology (SET) enrolments at undergraduate level. At present, this level is 30% of all enrolments  Increase the levels of SET graduations (30% in 2014) to those of the more innovative countries (e.g. 47% for South Korea)  In terms of knowledge production, increase the global share of global share of research publications (present 0.81% in 2014)  Increase the level of doctoral graduations from present levels  Increase the country’s patent output, especially based on the intellectual property arising from public-funded R&D  Increase technology receipts from the present level of 0.033% of GDP  Improve collaboration between research organisations and firms through funding of joint projects  Raise level of high technology exports from present level of 0.1% of world share  Increase labour force participation rates and decrease unemployment rate

2.5 Institutional Landscape and Situational Analysis The R&D landscape within South Africa represents a system of considerable depth and breadth as well as one that contains a multitude of actors. In 2007, the OECD through its review of the South African R&D environment, provided substantial illumination of the institutional landscape within South Africa. Much has changed within the decade since, but the OECD review provided the first illumination of the landscape as one of different “levels” of entities. These levels are relevant from a governance perspective as well as how funds flow through the system and the approach has been adopted for mapping institutions within the context of the PER.

1 Note: the figure of 2.5% has been obtained from the Draft White Paper on Science and Technology; the latter is not yet an adopted policy document and could still be revised. The present target from the NRDS is 1% for GERD/GDP.

2.5.1 Actor Hierarchy: Institutional Linkages between Actors and Funding Flows There is no one consensus view on the R&D system within South Africa. Different reports and institutions have presented a number of representations of the hierarchies in respect of the linkages within the R&D system. For example, the National Research and Development Strategy of 2002 and the OECD review differed in their interpretation of relationships between Parliament and Executive function of government. In this PER, the team has adopted a slightly different mapping approach, one that takes cognisance of some structural aspects pointed out through the OECD report of 2007, but is more geared to the understood present-day realities and relationships between entities. This mapping is presented diagrammatically in the figure below. In many respects, this structure correlates with the flow of funds within the system. In the accompanying set of excel workbooks for this PER, the team has included a review of specific actors and confirm the list of institutions that are most relevant. This review includes the key National Departments, Schedule 2, Schedule 3 entities (as defined by the South African government), as well as Provincial governments and their respective entities. Furthermore, it identifies the programmes within these institutions and entities that align with R&D expenditure and activities, as far as could be discerned from the line item descriptors in texts.

Figure 5: Actor hierarchy as per the PER

Public Funds Level 3 R&D Performance Level Budget National Departments Level 2 Programme SoC’s Level Budget Programmes Funding Agencies Level 3 R&D Performance Level Performance Budget Agencies (incl. HEI)

Provincial Departments Level 4 R&D Performance Expenditure

Programmes Entities

Local Government

Private Sector Firms

Source: Rebel own Analysis

2.5.2 Understanding the Functional levels within the R&D System Essentially, there are four functional levels within the R&D landscape in South Africa. These functional levels, as indicated below in Figure 6, are largely mapped to different types of oversight and areas of responsibility. Grouping activity and funding by levels Error! Reference source not found.provides better clarity in how funds flow through the system and the relationships between actors. Figure 6: Functional Levels within the R&D System

Source: Rebel own Analysis Level 1 is representative of the aggregate transfer of funds from the National Revenue Fund to national departments through the MTEF budget allocation process. This level represents all nominal amounts dedicated to R&D funds within the system. Level 2 would represent the allocation of funds within departments for programmes or ring-fenced transfers to entities specific to funding agencies that would be ascribed to R&D. It is this level that represents “overall” R&D expenditure rather than purely budget allocation. Level 3 is indicative of funds transferred through the Level 2 programmes or funding agencies to entities that actually perform R&D activities. Whereas the final level, Level 4, represents R&D projects and researchers conducting the work. The latter category is not shown in many of the typologies since it forms part of R&D performance.

Each of these levels have their own respective policy and oversight decision points which breakdown roughly as follows:  Level 1 is the highest level. It involves setting overall directions and priorities across the whole national innovation system. Within the South African system this is achieved through advice to government or by more binding means, such as decisions of a cabinet sub-committee.  Level 2 is co-ordination among ministries whose sectoral responsibilities otherwise encourage them to pursue independent policies. In practice, this level of co-ordination may involve administrative aspects, policy issues or both. Sometimes an inter-ministerial group also functions as the Level 1 co-ordination mechanism.  Level 3 is more operational, with an attempt to make a coherent whole of the actions of funding agencies. This level, too, can involve administrative co-ordination as well as more substantive co-ordination of funding activities, such as co-programming.  Level 4 involves co-ordination among the bodies that actually perform research and innovation. Co-ordination at this level tends to be achieved through self-organisation rather than formal mechanisms.

2.5.3 Governance and Research Functions within the South African R&D System From the perspective of key research and innovation governance functions, each level has at least some element of the following seven dimensions (Arnold and Boekholt, 2003):  strategic intelligence  setting directions (policy formulation)  vertical steering  horizontal co-ordination  co-ordinating production among knowledge producers  a referee  enhancing the profile of research and innovation

2.5.4 Strategic Intelligence There are a number of organisations which undertake policy-relevant research on, and analysis of, the national innovation system. Firstly, there are the in-house capabilities of the main policy- making bodies (DST, DTI, the Department of Minerals and Energy, and others that influence innovative activity across the economy and society). Another in-house part lies with the staff of larger STI organisations such as the CSIR and the secretariats of advisory bodies such as the National Advisory Council on Innovation and the Council of Higher Education. Secondly there are important capabilities outside such bodies, mainly in academic organisations. This has three main components. The largest is located in the Human Sciences Research Council and has several segments. Perhaps the core is the Centre for Science and Technology and Innovation Indicators (CeSTII). It is particularly important because it now has responsibility for the national R&D and Innovation Surveys following a disruptive decade-long phase of migration between several different organisations. In 2004 a Memorandum of Agreement between DST and Statistics South Africa

formalised this arrangement as the basis for the official national science and technology statistics. Other segments of HSRC capability in this field are contained in a changing portfolio of substantial research programmes such as the Employment and Economic Policy Research Programme, the Education, Science and Skills Development Research Programme, and the Research Programme on Human Resource Development which undertook the flagship project leading to the excellent collection of studies published as the Human Resources Development Review 2003 (HSRC, 2003). Through a series of projects and commissioned studies over several years, these programmes have fostered a deepening base of expertise both within the staff of HSRC itself and among a wider network of collaborators. A second component consists of small research groups in at least the following universities; the University of Stellenbosch (Centre for Research on Science and Technology), the University of Pretoria (Institute for Technological Innovation), Tshwane University of Technology (Institute for Economic Research on Innovation), the University of Cape Town (Programme for Science Studies in the South), and the University of Limpopo (Social Innovation Centre). These relatively formal groups blur into a third component that consists of individuals and small groups in universities and private consultancies. These play an important role as a wider network that not only contributes to projects undertaken by the other two components, they also undertake an array of studies on specialised aspects of innovative activity in South Africa: work in economics departments on clusters and industrial upgrading and innovation in the automobile industry (the University of KwaZulu-Natal) or on the details of innovative activity in Ekurhurleni (the University of the Witwatersrand). All this activity is an extremely valuable resource. The core survey activities and associated analytical work at CeSTII now appear to be very soundly based, with strong capabilities of international standing at a senior level and a strategy to strengthen middle-level and younger cohorts. Given the importance of these activities as a basis for providing data and intelligence about the innovation system and given the particular significance of accumulated experience at national and international levels in this field, it is important to maintain this stability and to further strengthen these capabilities so that they are not weakened by the normal patterns of personnel mobility.

2.5.5 Vertical Steering and Contracting At the highest level, the Parliamentary Portfolio Committee for Science and Technology (comprising members of Parliament) oversees the activities of the DST. At Level 3, the NRF is the only sizeable agency in the system, in the sense that it deals with multiple programmes. It also has multiple principals. At Levels 3 and 4 the use of research councils (actually, research institutes) is widespread. These typically receive a substantial grant from the responsible ministry and have a mandate both to set priorities for individual projects and to do research. Note: The Medical Research Council spans Levels 3 and 4, not only setting internal priorities and performing research but also acting as a funding agency for external contractors (primarily in the higher education system). This is noted as a deviation from internationally accepted OECD current practice, in which the research and innovation funding function is generally separated from project performance. A major drawback of vertical delineation is that – if implemented in a literal way, so that the policy level makes policy in isolation or only based on the feedback obtained through reporting on existing programmes – the policy level is starved of the information it needs to make good policy.

There are difficult trade-offs to be made in relation to research institutes such as the South African research councils. If the mission of an institute is so important that the state needs to maintain a national capacity in the area, it also needs to ensure that there is an adequate supply of work. Many countries settle on a compromise according to research institutes whose primary customer is the state remain highly funded research performing agencies of government. These are especially likely to operate in areas like marine or environmental research, where a significant part of the institute’s task is to provide the knowledge needed for regulation (e.g. monitoring fish stocks, understanding the relationship between national sources of pollution and climate change). Other institutes, especially industrial ones in the style of CSIR, get less grant funding and are more exposed to research markets. Thus, in OECD countries, the degree to which a three-level structure is used depends partly on the sector. In research and innovation policy areas, where the number of potential project performers is large, “agencification” is frequent. However, in areas such as agriculture, where the state acts as proxy customer for end-users of knowledge who have limited absorptive capacity, and in areas like geology where knowledge production is largely intended to support government and regulation, there is less “agencification”. “Agencification” of the funding function adds little value to research institutes that deal heavily with government missions. These institutes can be managed using a combination of performance contracts, simple performance indicators and careful qualitative oversight. However, when it is necessary to choose between allocating money and work to themselves or to others, “agencification” has two advantages. First, it makes resource allocation more objective and transparent. Second, it makes possible innovation in funding instruments and shifts in the emphasis of funding among different groups. Understandably enough, research institutes that largely set their own priorities tend to become locked into particular patterns of investment, technologies and partnership rather than changing these over time as needs evolve.

2.5.6 Horizontal Coordination Both the DST and the DHET have their own high-level advisory councils. However, there is no high- level body responsible for the direction of the whole of research and innovation policy. There is an independent South African Academy of Sciences, but it does not appear to have a significant influence on government policy. As a result, there is no Level 1 arena for discussing research and innovation policy and setting cross-departmental priorities. Internationally, there is broad agreement that this function is important and many countries look to the Finnish Science and Technology Policy Council as a model. There are specific cultural reasons why this model works so well in Finland, but the role of the Council in representing a combination of the key stakeholders and ministers under the chairmanship of the Prime Minister, setting broad policy directions and ensuring that lower-level actors comply, appears to have been an important enabling factor for Finland’s successful research and innovation policies over the past couple of decades. South Africa does have a general process in place for horizontal co-ordination at Level 2. The South African ministries organise a number of policy clusters in order to deal with problems that affect multiple ministry responsibilities. In addition to the general cluster approach, DST has a number of special responsibilities for horizontal co-ordination. It has a cross-cutting and steering function for areas such as S&T liaison across departmental line functions and sectors; large-scale, broad- scope new S&T platforms and challenges (such as astronomy, human palaeontology and indigenous knowledge); and system-wide oversight functions, including establishing and maintaining a common governance framework, priority setting, and performance and budgetary

monitoring systems. In 2005, DST representatives were appointed to the boards of a number of research councils and the Nuclear Energy Council of South Africa (NECSA). There appear to be no formal horizontal co-ordination mechanisms in place at Levels 3 or 4. The consequences of limited co-ordination may include an unbalanced mix of instruments, gaps and mismatches in terms of resource availability. Table 4: Oversight and Transaction Activity

Level Entity Governance and Type of Transaction Oversight

National Departments Portfolio Committee on MTEF Allocations are (such as Department of Science and made 1 Science and Technology Techonology)

National Department at Director-General and Transfers and Payments Programme level or Executive to Entities 2 Funding Agency (such as TIA or NRF)

Performance Agencies Board and Executive Transfers and Payments or Government to Entities 3 Research Institutes (such as CSIR or SANEDI)

Specific projects where Head of Department R&D Expenditure Takes R&D is performed (such Place 4 as CSIR particular project)

Source: Rebel own Analysis

2.5.7 Flow of Funds across the Levels The table above also provides an elaboration of how funds flow through the levels within the system. It shows distinctly which actors are operating at what level. It is useful to note that as funds flow through each level there is an element of transaction cost that impacts on amount available at the final level for R&D performance. The complexity of these transfers is that often at Level 2 as national departments will conduct transfers across several programmes to one entity. Thus, the budgets at Level 1 and Level 2 go through disaggregation but are then reported at Level 3 in agglomeration. The Figure below illustrates this aspect.

Figure 7: Illustration of Funding Flows through National Department

Moreover, at Level 3 there is multiple channels of flows between performing agencies, departments, and other sources of funds within the system. Each of these issues has to be accounted for in the mapping of funding flows. Figure 8: Major funding flows for R&D from all sources in South Africa, 2014/15

Source: Department of Science and Technology 2017 Finally, it is necessary to consider that the reporting of R&D within the system can create confusion on what is considered R&D. Much of the reporting is subsumed in the definition of Science and

Technology Activities (STA), but the scope of this PER assignment is more appropriate aligned with Government Budget Appropriations or Outlays for Research and Development (GBAORD). One final dimension of complexity is that the common thematic clustering of R&D expenditure is not analysed through Levels but rather by specific purpose. From a portfolio management standpoint this makes strategic sense but requires reconciliation of funding flows through levels to present the whole picture. Figure 9: Funding flows for STA and programmes

Source: Department of Science and Technology. Government Funding for Scientific and Technological Activities. 2015/16

2.6 Comparative Examination of SA R&D Landscape to International Examples As part of the overall scope of the PER, the research team produced an analytical piece of work examining the funding and governance environment for Publicly-Funded R&D for selected countries. That selection consisted of Finland, Tanzania, United Kingdom (UK), and the United States of America (USA) and Brazil. Furthermore, additional research was done in which data from a variety of countries was brought together. This work was issued as a stand-alone report but some of the relevant key findings derived from the analysis are highlighted in this synthesis report.

2.6.1 Open versus Closed Budget Processes of R&D Funding The South African R&D budget process closely resembles the approaches of other open and democratic R&D funding processes around the world. Such open processes have their strengths and weaknesses. These include issues such as: 1) they can become cumbersome and inflexible; 2) time and resource consuming; and 3) the need for inclusiveness and participation, two elements of openness, coupled with long periods of debates and delays could result in “dilution” of the core principles and target objectives, thereby weakening the focus, goal, directionality, and possibly, intended outcomes. Furthermore, given the emerging market context of South Africa, the length of budget processes have a magnifying effect, if the process is not well structured and carefully orchestrated the delay of funding to R&D performers can have significant effect given the lack of reserves.

2.6.2 Benchmarking South Africa with Key Performance Indicators The tables below provide a summary of R&D benchmark comparisons by country. The OECD (2014 or latest available) data available help us examine BERD as a percent of GDP; BERD financed by

direct and tax funding as a percent of total BERD; BERD financed by direct and tax funding a percent of GDP; and, BERD financed by direct and tax funding a percent of total public funding of R&D. In addition, data on GERD a percent of GDP; GERD, publicly financed, a percent of GDP is presented. Further data on public support to business R&D; direct funding of business R&D; GBAORD as a percent of GDP; GBAORD, defence as a percent of total GBAORD; GBAORD, energy, as a percent of total GBAORD; GOVERD, as a percent of GDP; HERD, as a percent of GDP; Tertiary education expenditure, as a percent of GDP; PSERD, as a percent of GDP; and PSERD, financed by industry, a percent of GDP are presented and discussed. There are notable limitations with regard to the data for certain indicators. For instance, data was not available for GBAORD/(Business Funding of R&D, except in the case of energy, representing- business), GOVERD/GBAORD, institutional block funding, percent of total funding to national performers, and project-based funding as a percent of total funding to national performers. Some illustrative data elements are provided. For example, the UK data presents the direct and indirect funding of R&D as a percentage of GDP. Table 5 Summary of R&D Benchmark Comparisons by Country (2014)

South Finland UK USA EU-27 OECD Africa

BERD, as % of GDP (2014; 2.15; 1.23; 1.63; 0.36 1.09; 1.1 -; 1.95 latest available) 2.44 1.24*2 1.63+3

BERD, financed by direct and tax funding, % of total 8.27 3 14.9 14.05 - - BERD

BERD, financed by direct 0.03 0.07 0.16 0.27 - - and tax funding, % of GDP

BERD, financed by direct and tax funding, % of total 15.41 7.76 27.87 28.73 - - public funding of R&D

GERD, as % of GDP 0.76 3.55 1.73 2.79 1.98 2.4

GERD, publicly financed, 0.34 0.95 0.52 0.94 0.68 0.77 % of GDP

Public support to business 29.21 7.00 24.57 33.47 - 17.58 R&D

Direct funding of business 89.98 100.00 53.45 83.85 - 62.52 R&D

GBAORD4, as % GDP 0.54 1.03 0.57 0.79 0.7+ -

GBAORD, defence, % of (7) 2.58 14.63 53.93 5.11 - total GBAORD

2 *Data for EU-28 3 +Data for OECD total 4 Government Budget Appropriations and Outlays for R&D ©2018 RebelGroup South Africa National Treasury: GTAC 33 Review of government funding for research, development and innovation Report

South Finland UK USA EU-27 OECD Africa

GBAORD, energy, % of (?) 9.36 1.19 1.48 4.1 - total GBAORD5

GOVERD, as % of GDP 0.17 0.32 0.14 0.34 0.25* 0.28+

HERD, as % of GDP 0.23 0.77 0.46 0.39 0.47* 0.43+

Tertiary education 0.58 1.94 1.33 2.67 - - expenditure, % of GDP

PSERD6, as % of GDP 0.39 1.09 0.6 0.73 0.72 0.71

PSERD, financed by 0.02 0.07 0.04 0.02 0.03 - industry, % of GDP

Source: OECD Dataset: Science Technology and Industry Outlook 2014 (http://stats.oecd.org/Index.aspx?ThemeTreeId=19&DatasetCode=BENCHMARK_STIO)

Table 6 Allocation of Public R&D Funds in Benchmark Countries (2014) BERD, Basic Institutional BERD, financed financed by HERD, % of research GBAORD, block by government GBAORD, direct and tax public sector expenditures, generic funding, % (direct), % of civil, % of Indicator funding, % of R&D public research, % of of total direct and tax total total public expenditures research, % total civil funding to

funding of GBAORD

funding of (PSERD) of total public GBAORD national

business R&D

R&D R&D performers Country

Chile 88 15.49 89.37 .. 99.97 47.12 23.8

Finland 100 7.76 70.54 .. 97.81 50.38 50.4 United

52.91 27.87 76.28 32.92 83.54 50.88 .. Kingdom United

81.57 28.73 52.9 .. 46.95 15.54 .. States European Union (28 .. .. 66.16 .. 95.17 53.52 .. countries) OECD - ...... 75.33 43.17 .. Total Brazil ...... China (People's 49.84 23.91 31.78 16.6 ...... Republic of) Colombia .. .. 90.76 ...... India .. .. 6.65 ......

Russia 95.2 54.06 22.41 27.73 47.92 24.85 .. South

100 15.41 57.1 34.19 ...... Africa

5 GBAORD, as % of GDP-energy (representing-business) 6 Public Sector Expenditure on R&D ©2018 RebelGroup South Africa National Treasury: GTAC 34 Review of government funding for research, development and innovation Report

BERD, Basic Institutional BERD, financed financed by HERD, % of research GBAORD, block by government GBAORD, direct and tax public sector expenditures, generic funding, % (direct), % of civil, % of Indicator funding, % of R&D public research, % of of total direct and tax total total public expenditures research, % total civil funding to

funding of GBAORD

funding of (PSERD) of total public GBAORD national

business R&D

R&D R&D performers Source: OECD Dataset: Science Technology and Industry Outlook 2014 (http://stats.oecd.org/Index.aspx?ThemeTreeId=19&DatasetCode=BENCHMARK_STIO)

2.6.3 Strategic positioning of the government function on Science and Technology There is a wealth of information on various countries’ structures and institutional arrangements for the governance and policy formulation of R&D. Yet, there is very little analysis on how the arrangements have proved optimal for outcomes or efficient in the deployment of resources. Researchers have cited this as a key area where literature is desperately needed. Still, there are some specific lessons learned from the international analysis. “Horizontialisaiton” i.e. the ability of governments to coordinate and leverage focus of departments without core science mandate in service of R&D objectives is becoming a key feature in best practice. Mechanisms that allow the Science and Technology function of government to collaborate on other departments’ objectives are critical for horizontalization to occur. This has become a core component of the Flanders National System of Innovation (OECD 2011). There are trends toward ensuring that cross-sectoral, multi-faceted research programmes that are in service of society objectives received dedicated funding streams and not relegated to sectoral ministries. This is to ensure that R&D spend is focused on medium and longer-term objectives rather than less strategically focused in service of short-term budget output requirements (Technopolis Group 2015). Similarly, there is a trend toward consolidation of coordination entities for Science and Technology to promote more unified approaches to budget planning. There is a growing international focus on the importance of an organisational body that can ensure interconnectivity and performance evaluation of R&D expenditure across the entirety of government (Oh and Lee Kyoung-Joo 2013).

2.6.4 Trends and Structural Changes to R&D Funding Mechanisms Public Research Institutions (PRIs) have seen a decline in funding in developed countries while a resurgence in developing countries. Yet, all are undergoing changes including funding mechanisms, structure of innovation networks and governance/operations (OECD,2011). For instance, the profile of funding for PRIs has changed substantially as governments have sought to achieve higher levels of impact and efficiency from public resources. Traditional ‘no strings attached’ block funding has been replaced in part by programme funding and public competitive funds (Lepori et al. 2007) and is subject to institutional performance review (known as performance-based block funding). PRIs are required to submit annual budget plans with specific investment outcomes; the latter are monitored and future funding is adjusted according to the extent to which these targets have been met. Typical performance criteria include the quality and relevance of institutions’ research activities, their pursuit of research excellence, the fulfilment of institutional mandate, and socio-economic impact.

Figure 10: Public funding for PRIs and HEIs (2000 to 2010; constant 2005 $)

Source: OECD. 2011. Public Research Institutions: Mapping Sector Trends. OECD (Paris) In addition to these changes in types of funding, PRIs have been encouraged to access non-public income including funding from industry and international agencies. Industry funding in particular has become more widespread, especially as governments have sought to make PRIs more market- facing and responsiveness to market need, and the consequence of reduced government control. Currently the South African Public Research Institutions derive income from the five main sources as shown in the table below. Accessing private funding has required the introduction of full cost accounting, which is necessary to ensure that private clients are billed at real costs and there is no cross-subsidisation from public funds. This change has prompted other operational reforms, such as the adoption of business-like operational models (also known as the corporatisation of the PRI) and the appointment of a Board of Directors. Furthermore, the advent of NSI-thinking has encouraged PRIs to extend their collaborative R&D, their international projects, the number of staff on joint appointments with HEIs/industry, the use of post-doctoral and PhD students working part-time or on a contract basis at PRIs, the registration of PRI staff for PhD studies, teaching by PRI staff at universities, the introduction of specific funding schemes for joint R&D and the establishment of joint university/PRI research centres. Table 7 Categorisation of funding for South African Public Research Institutes

Typical Type of Funding Definition and Description Percentage of Total Revenue

Core Funding Category A covers public funding for science (Category A) councils allocated in the form of an annual grant and for which the science council has freedom to 40% – 60% decide how it is allocated (between its various research activities) and spent. Such funds are also known as block or grant funding and are broadly

Typical Type of Funding Definition and Description Percentage of Total Revenue intended to facilitate the fulfilment of the organisation’s public mandate (such as undertaking

industrial R&D in the case of the CSIR). Project level allocation of block funding takes place internally without any direct involvement of government. Core funding of institutions is typically determined on a pre-agreed formula reflecting certain structural economic issues such as overall government budgets and inflation, although it is becoming increasingly influenced by performance against a set of institutional KPIs (referred to as performance-based block funding).

Also known as ring-fenced, ear-marked or targeted funding, this category has evolved as an alternative to block funding which gives more control to government and are oriented towards the solution of specific political, social or economic problems or objectives. The funds are awarded through a non- Programmatic competitive process based on existing capability Funding and strategic intent of the agency. Each programme consists of a portfolio of research 10% - 15% (Category B) projects, and the programme duration may be 5 years or longer. The projects of programmes are primarily policy driven and serve a policy goal. The intention of programmes is to facilitate the development of specific competence and outcomes within a performance agency on the basis of secure medium-term funding, usually attached to clear performance criteria.

Category C covers public funding to specific projects attributed to a group or an individual to perform a specific R&D activity (such as the development of a new HIV drug). The funds are Public limited in scope, budget and time, normally on the Competitive basis of the submission of a project proposal Project Funding describing the research activities to be done. 15% - 30% (Category C) These proposals are then reviewed and funding is allocated according to the top-ranked proposals. Success rates for competitive funds vary from 5% to 35% and the standard evaluation criteria are strategic fit (closeness to the objectives of the fund), scientific excellence and relevance.

Categories D, E and F all cover contract R&D Contract Research income from external clients, mostly allocated on a Income from the competitive or semi-competitive basis. Co-funding 5% - 10% Private Sector of projects may take place if there is significant risk (Category D) for the private partner. South African legislation requires that a full cost model is used if the client

Typical Type of Funding Definition and Description Percentage of Total Revenue wishes to own the resultant intellectual property. In cases of co-funding or partial payment, the intellectual property must be shared as specified in a consortium agreement.

Contract Research Income from the Contract research income from the public sector. 30% – 40% Public Sector The same comments apply as for Category D. (Category E)

Also known as third stream funding, Category G covers income from intellectual property deals (royalties, licenses and sale of technology packages) and dividends arising from spin-off companies. Very little published information is available on the average royalty income for PRIs, Royalty, License despite these institutions having actively pursued and Divided such revenue for over twenty years. A brief 1% - 20% Income (Category analysis of the annual reports from several of the F) well-known PRIs (e.g. CSIRO, CSIR India, VTT, DTI, Fraunhofer), indicate that third stream funding is typically between 1% to 4% of total revenue, except for the ‘home runs’ when an institution may earn between up to 20% of revenue (e.g. the windfall royalty to the CSIRO in 2012 arising from its WiFi technology).

Source: RebelGroup Research, 2015 The range of mechanisms used to encourage R&D funding is changing at a rapid pace and is indicative of the sector’s desire to diversify in order to encourage greater responsiveness to socio- economic objectives and encourage private sector participation. A broad description of these changes are provided in the figure below and showcase the diversity of approaches and instruments populating the sector. While there is a global trend towards more competitive funding and contractual arrangements, a small number of countries, particularly in northern Europe, have reversed the trend and increased block funding (OECD, Sept 2016). This is because block funding does allow broader freedom to operate and autonomy.

Figure 11: Changes in Policy Mix for innovation policy

Source: Based on EC/OECD (forthcoming and 2014), International Database on STI Policies (STIP) Questions about the effectiveness of government financing of business R&D are of growing importance to policy makers. With the focus being an attempt to boost business R&D expenditure and improve its contribution to innovation. Seeking out these opportunities government has begun to increasingly focus on the policy mix and funding mechanisms it offers to the business community. Yet, governments are also constrained by fiscal limits for R&D spending. Some have implemented a “no spending” approach by privileging policy tools that do not require additional public spending in the short term, particularly public procurement and tax incentives for R&D and innovation. Much policy attention remains focused on the articulation of direct and indirect support to business innovation, essentially through competitive grants and R&D tax incentives, both instruments being of high relevance in the policy mix overall. But the perceived relevance of R&D tax incentives is related to the fiscal cost they generate and their use remains extremely uneven across countries. Also, special features have been introduced to make schemes more generous and better adapted to SMEs and young firms and countries are trending toward focusing on mechanisms that support technology transfer.

Figure 12: Major Funding Instruments in the Policy Mix for Innovation (2014)

Source: Based on EC/OECD (forthcoming and 2014), International Database on STI Policies (STIP)

2.7 Findings from the Institutional Analysis

2.7.1 Funding Coordination and findings for Funding Mechanisms Our review of the institutional landscape highlights a fairly robust National System of Innovation with strong institutions and structurally similar to most international comparisons. Yet, there are some areas of improvement that could be examined. The review indicates that the coordination within the system is relatively weak due to the structural and institutional barriers. As mentioned in previous sections of this report, at Level 1 there is no primary body with a mandate to direct the whole of research and innovation policy and both DST and the DHET have their own high-level advisory councils. At Level 2, inter-departmental cooperation is largely voluntary and not well mandated. The most recent Ministerial Review expresses concerns that there is no real common agenda or role clarity within the National Systems of Innovation currently. Coordination is a crucial function for the system to operate efficiently and ensure the reduction of overlaps or duplications of activities. Examining international examples shows that South Africa’s challenges in coordinating R&D expenditure are further exacerbated by the relative openness of the system, where individual institutional mandates and a department-led budget setting process yield MTEF proposals in silos rather than strategically packaged. This is at odds with other systems where public funding of R&D is much more directed and less diffuse.

Internationally, there is a rise in more strategic and cross-sectoral collaborative research programmes aimed at medium-term societal development objectives. Countries are encouraging this change by introducing competitive, objective focused funding instruments to ensure R&D expenditure aligns with governmental policy. Overwhelmingly, countries are developing either coordination mechanisms or establish bodies explicitly mandated to conduct legislative and policy guidance for Research and Innovation. Yet, there is no one model that has risen as a clear front-runner, but all have in common the mandate to align R&D spend to policy objectives.

2.7.2 Monitoring and Evaluation for the R&D Landscape The monitoring and evaluation activities within the R&D landscape are just as fragmented as the coordination activities. This is largely because those institutions that do collect data and monitor R&D activity within the sector have a variety of rationales and internal purposes. This is illustrated in the table below. Table 8 Monitoring and Evaluation Activities in the R&D Sector

Entity M&E Responsibility Activities Reporting Events

Collection of information Engagements with Annual STA Survey Department of on expenditure of Departments, Science and Science and Conducting the STA Technology Technology Activities Survey

Collection of data Engages continually Secretariat of an open Centre for related to HEIs with HEIs and data platform for HEI Higher (Research Outputs, generates data for data Education Income, and public access Transformation Expenditure)

Monitoring of specific Engages with Science Annual Reporting on National innovation indicators Councils, HEIs and specific themes Advisory (Commercialisation National Departments Council on activities, Research on Innovation Outputs Innovation Outputs, etc)

Centre for Monitoring of specific Engages in annual Annual R&D Survey Science innovation indicators survey of the National Technology (Commercialisation System of Innovation to and Innovation activities, Research collate R&D outputs Indicators Outputs, etc) and expenditure

National Collection of data Engagement with HEIs Annual reporting on Intellectual regarding Intellectual and Science Councils specific themes, Property Property (License on Research Outputs management of national Management Income, Patent Activity, intellectual property Office etc) database

The above only provides a few highlighted entities and activities, as there are other organisations such as Higher Education South Africa and the Committee of Heads of Organisations of Research and Technology that also monitor specific aspects of the system. The sector also has a number of

database establishment initiatives underway including the Higher Education Information Management System and the Research Information Management System. Despite this magnitude of monitoring and evaluation activity within the system, recent evaluations of the sector have indicated that the various data and information is not collected or collated in a manner sufficient to steer policy. The common critique is that despite the depth and breadth of data collection within the sector, the information has not been translated into learning or applied to inform decision-making within the sector.

3 Step 2 and 3: Logical Framework and Indicators for Public- Funded R&D

3.1 Theory of Change The Theory of Change for this PER is underpinned by the broader objectives illustrated in Figure 1 of this report which is based on global best practice in R&D policy. Public-funding of R&D should seek to improve overall Factor Accumulation and Total Factor Productivity within the economy. Furthermore, the NRDS strategic framework provides an additional foundational pillar, serving to give a more delineated set of desired outcomes. With these two informants in mind, the team has produced a Theory of Change appropriate for the South African Public-Funded R&D “programme” as displayed in the figure below..

FigureResearch 13: Theory& Development of Change for South African Public-Funded R&D

Inputs Activities Outputs Immediate Outcomes Intermediate Outcomes Long-Term Outcomes Impact

abc = Assumptions Programme Development Funding Programmes Research & Development New Knowledge Innovation & Implementation Portfolio

Productivity Funding Identify Need (Research Project-Based & Consultation) Funding Publications

Economic Output Human Resources / Policy & Planning Skills (Framework) # Skilled Human Transfers to Science Councils & PRIs Resources Intellectual Property

Design, Test & Adjust Facilities* Funding for R&D in HEIs New Products & Protection and Social Wellbeing Services Preservation of Public Implementation Goods

Policy Support for Private Sector R&D & Absorptive Capacity Innovation (New Knowledge Support & Promotion Absorption) Commercialised Products & Services Existing Knowledge Support for International S&T Initiatives Qualifications Monitor & Evaluate Supporting Organisations Generalised economic growth

Coherent Economic Policy General economic Effective Inter-Governmental Sufficient funding Sufficient Funding for Commercialisation Ecosystem environment is conductive to Coordination and Planning available Innovation private sector investment

The Theory of Change for R&D comprises the following:

3.1.1 Inputs Through discussion with the Project Steering Committee and review of contemporary literature the following inputs were identified as critical for a well-functioning and productive R&D landscape:  Funding  Human Resources / Skills  Facilities –(Where it is noted that Facilities includes all physical infrastructure, wherever this is located such as HEI, Science Councils, National Facilities, intramural R&D departments, etc.)  Policy  Existing Knowledge Assumptions Some key assumptions that underpin these inputs would include that there is coherent economic policy to give direction to institutions and mandates as well as sufficient funding available to generate sufficient activity within the system.

3.1.2 Activities Activities within the R&D field relate to the procedural steps required for scoping and developing programmes or tailored interventions that aide in the discovery of new knowledge. These include:  Identify Need (Research & Consultation)  Policy and Planning (Framework)  Design, Test, and Adjust  Implementation  Support and Promotion  Monitor & Evaluate

3.1.3 Outputs Unlike other PER’s, this assignment deals with the unique characteristics of the R&D sector which typically has much less-defined outputs than other sectors. Thus, it was decided that in this case the most appropriate outputs would be the programmes and interventions themselves. This is because each of these ultimately drive the creation of new knowledge and yield long-term impacts for a multitude of sectors and industries, increasing Factor Accumulation and Total Factor Productivity within the South African economy. These key outputs would therefore include:  Project-based Funding  Transfers to Science Councils and PRIs  Funding for R&D in HEIs  Support for Private-Sector R&D & Innovation

 Support for International S&T Initiatives Assumptions It is assumed that there is an effective Inter-governmental coordination and planning platform in place to avoid duplication and/or mis-alignment in the scoping of these outputs

3.1.4 Immediate Outcomes Within the context of Research and Development, the immediate outcomes of R&D output can be examined through a number of “lens.” This means that there are three key dimensions along which outcomes can be reported. These include:  A contribution to the body of overall research knowledge in the country, categorised as Basic, Applied, and Experimental (as defined by Frascati).  The contribution to knowledge in specific fields of academic or professional endeavour, including either the Natural Sciences, Technology and Engineering or Social Sciences and Humanities.  The contribution to knowledge as desired by government for specific socio-economic objectives (as identified by Science and Technological Activities Report published by the DST) whether that be Economic Development, Environment, Justice and Protection, etc.  Although somewhat nebulous, it is this generation of new knowledge within the country that is the most immediate outcome of the funding outputs identified within this Theory of Change.

3.1.5 Intermediate Outcomes The assumption is that these immediate outcomes will ultimately result in refined knowledge products and other significant impacts relevant for the National System of Innovation. These intermediate-level outcomes would include specific tangible items like scientific publications, qualifications for researchers, intellectual property (such as patents). Yet, it would also include more intangible outcomes such as the Absorptive capacity, which represents National Innovation System stakeholders’ ability to firm‘s ability to identify, assimilate and exploit knowledge from external environment (Cohen and Levinthal, 1989). These intermediate outcomes are defined as follows:  Research and Development activities, all of which contribute to new knowledge,  Publications  Intellectual Property  New Products and Services  Absorptive Capacity  Qualifications Importantly, it is at this stage in the process that an organic process of innovation takes place as new relationships are formed, intellectual property and other products are commercialised, and new knowledge finds application. It is at this level where opportunities for scalability are found and the activities and efforts dedicated to R&D see the greatest impact potential and return on investment opportunity.

Assumptions For scale of impact and exponential growth to occur, there must be an enabling system in place to nurture this stage of development. It is assumed that sufficient funding for innovation activities and supporting organisations for commercialisation, new company development, etc are in place.

3.1.6 Long-Term Outcomes and Overall Impact Section 3’s rationale for Public-funded R&D identified many long-term outcomes that result from undertaking R&D. Some of these are useful for the Theory of Change as well, but with some modification for the South African context. The proposed list of long-term outcomes includes:  Productivity- R&D represents an investment in changing firms and re-shaping the labour market of a country, its impact on the economy is often measured through Total Factor Productivity.  Commercialised Products and Services – The translation of research outputs and knowledge into competitive market-facing opportunities can generate new economic activity in non-existent sectors, provide livelihoods for individuals, and increase tax revenue for government to utilise in tackling socio-economic objectives.  Skilled Human Resources – The process of R&D generates new job opportunities, up- skilling of individuals, and generation of knowledge transfer from peer to peer. This all yields in a more sophisticated and skilled labour force.  Protection and Preservation of Public Goods and Services - New and improved products and applications can result from R&D activities. These applications could be material to better and more fiscally efficient approaches to goods and services that have to be paid Impact  It is through these four long-term outcomes that the sector has sustainable impact on Social-Well-being and Economic Output.  Assumptions  Similar to the Intermediate Outcomes, there must be a commercialisation and innovation system in place for the translation of R&D outputs to commercial activity. is assumed that sufficient funding for innovation activities and supporting organisations for commercialisation, new company development, etc are in place.

3.2 Indicators The Theory of Change for the PER, aligns to some degree with the key indicators for the National Research and Development Strategy of 2002, some of which are listed in the table below. Given data collection issues, over the years there has been a struggle to populate all the indicators consistently. Given this hurdle, a revised list of indicators, based on the same broad categories, has since been adopted by the National Advisory Council on Innovation, the values for which are published annually (National Advisory Council on Innovation, 2016).

Table 9: Performance indicators as selected for the NRDS

Value (2015/ 16 Broad Category Indicators Data) Quality of Life Technology Achievement Index N/A

Growth and Wealth Creation Technology-based growth N/A

Science, Engineering and Researchers per thousand of workforce 48,000 (Total) Technology Human Capital SET demography N/A Patents 161

Technical Progress High-tech start-ups N/A (improvement and innovation) Business innovation investment N/A Key technology missions N/A Technology/trade mix N/A Business Performance Proportion of high-tech firms N/A Sectoral performance N/A Technology balance of payments N/A Imported Know-How Imported high-tech equipment N/A Imported ICT N/A Publications 12,000 Global share of publications 0.81%

Current R&D Capacity R&D intensity (investment) 0.77% Future R&D Capacity University enrolments (SET proportion) 29.6% S&T post-graduate degrees 2,258 Matriculates with Maths and Science 25,000

Source: National Advisory Council on Innovation (2016) Given the diversity of indicators identified both by the NRDS and NACI, only those most relevant have been selected as part of this PER as well as some others tailored specifically to the Theory of Change produced for the exercise. Much of these indicators relate explicitly back to the “secondary” policy intents identified for the programme in Section 4 above. Table 8 on the subsequent page shows the consolidated list of indicators as proposed. This table includes indication of whether or not the item is currently measured and if so the baseline measure. It also provides motivation for the indicator and assumptions where necessary.

3.3 Work Breakdown Structure In conducting the analysis of institutions and their roles, the research team has generated a breakdown of work and role allocation within the R&D system. This breakdown is focuses on four key functions:

 Strategic Planning: Where the actor works to provide strategic guidance on the functioning of the system, interaction of stakeholders, and planning on budget-setting processes.  Procure R&D: The task of utilising resources to ensure R&D outputs are obtained for programmatic or specific objectives. This is largely a project management function and includes work activities such as; project planning, development, financing, and approvals process.  Enabling Investment: The provision of necessary infrastructure for the performance of R&D activities which largely takes the form of either facilities or equipment.

 Undertake R&D: The function of conducting actual R&D activities. This is aligned to the three defined categories of research- Basic, Applied, and Experimental.  Manage R&D Portfolio: An administrative and oversight role, where the actor ensures the successful operations of the R&D portfolio. This can happen at three levels, institutional, programmatic, or project.

It is important to note that the “Manage R&D” element of the Work Breakdown structure would operate as a feedback loop and underpin the other activities as shown diagrammatically in the figure below. The full Work Breakdown Structure is presented in tables on subsequent pages.

Figure 14: Theory of Change for South African Public-Funded R&D

Table 10: Indicator Framework for South African Public-Funded R&D

Level Summary Indicator(s) Currently Baseline Source of data Frequency and Means Assumptions measured Measurement of verification (most current value) INPUTS Funding Budgets for R&D Yes None ENE (NT) Annual; ENE / Budget Coherent Economic Policy Reviews GBAORD/GDP Yes 0.34% R&D Survey (2014-15) Annual; R&D Survey

Human Resources / Skills Number and demographics of support staff (general Partial None Annual Reports Annual Reports and technical) Total headcounts (Public Sector) Yes 41712 R&D Survey (2014-15) Annual

University enrolments (SET proportion) Yes 30% NACI Indicators Report Annual; NACI Indicators (2016) Report (DHET Higher Education Information Management System) Number and demographics of researchers on staff Yes 30,000 Centre for Higher Annual Reports Education Transformation (2016) Matriculants with Maths and Science Yes 11% R&D Survey (2014-15) Annual; R&D Survey

Facilities Investment in R&D Infrastructure (total value) Yes 3.117 Billion Rand R&D Survey (2014-15) Annual; R&D Survey

Percentage capital expenditure as per total R&D Yes 10% R&D Survey (2014-15) Annual; R&D Survey expenditure (should reach 10%) Policy R&D relevance per National Department policy No None Departmental Annual Alignment within Annual documentation Performance Plans Performance Plans; Annual Quantity and quality of networks Extent of collaboration amongst institutions (no of Yes NACI "Inter- NACI Indicators Report Annual; NACI Indicators Assumption is that the publications relationships) and depth of such collaboration sectional co- (2016) Report measured through the NACI (quality) authorship matrix" "intersectoral co-authorship" tracking is a useful proxy for measurement.

ACTIVITIES Identify Need (Research & Consultation) N/A Policy & Planning (Framework) Design, Test & Adjust Implementation Support & Promotion Monitor & Evaluate

OUTPUTS R&D Investment (Government funding of R&D) Amount Transferred Yes 12.9 Billion R&D survey (2014-15) Annual; R&D Survey

Transfers to Science Councils & PRIs Amount Transferred Yes 4.32 Billion R&D survey (2014-15) Annual; R&D Survey Funding for R&D in HEIs Amount Transferred Yes 6.32 Billion R&D survey (2014-15) Annual; R&D Survey Support for Private Sector R&D & Innovation Amount Transferred Yes 690 Million R&D survey (2014-15) Annual; R&D Survey Support for International S&T Initiatives Amount Transferred Yes Not Agglomerated DST Annual Report Annual: DST Annual at this point Report

IMMEDIATE OUTCOMES Research & Development Portfolio Amount of funding available to perform R&D Partial BAS data Annual (Transaction Costs as per Level 1) Needs adjustments to BAS coding to Amount of funding available to perform R&D Partial BAS data Annual be completed (Transaction Costs as per Level 2)

Amount of funding available to perform R&D Yes R&D Survey (2014-15) Annual (Transaction Costs as per Level 3) Varies by Actor; See Expenditure Amount of funding available to perform R&D Yes Dashboard R&D Survey (2014-15) Annual (Transaction Costs as per Level 4)

INTERMEDIATE OUTCOMES Publications No. of accredited publications, commissioned Yes See Costing Model NACI; R&D Survey Annual reports (DST/HSRC)

Intellectual Property No. of patent applications, patents granted Yes See Costing Model NACI; R&D Survey Annual (DST/HSRC) Absorptive Capacity (New Knowledge Scale of adoption of policy & practice for better No None Departmental Annual Annual Absorption) governance of resources, environment, service Performance Plans; delivery Entity Annual Reports New Products & Services Prototypes, demonstrators, technical R&D based Partial Se Costing Model NIPMO Databases services for "Spin-offs" Qualifications No. and demographics of Masters & PhD graduates Yes See Costing Model R&D Survey Annual (DST/HSRC)/ Centre for Higher Education Transformation

LONG-TERM OUTCOMES Productivity Total Factor Productivity Yes Calculated quaterly StatsSA Quarterly

Skilled Human Resources Percent of Researchers in R&D fields as part of No Not fully StatsSA Annual Must be sum of Science Councils, overall Labour Force Higher Education Institutes and Government Research Institutes Protection and Preservation of Public Goods Proxy indicator-Human Development Index Yes 0.66 Parlimentary Annual Legislation agenda Commercialised Products & Services No of IP-based licenses granted, social and Yes Various figures High-level through commercial entrepreneurs supported NACI Report

IMPACT Economic Output (Wealth Creation) Not covered

Poverty alleviation, job creation, industry growth

Social Wellbeing

Table 11. Work Breakdown for South African Public-Funded R&D

A. Strategic Planning Implement Process / Develop Administer Inter- Manage Regulatory State Monitor & Stakeholder Activities Policy & R&D R&D Planning Government Oversight Institutions Framework Institutional Review Engagement Strategy Programmes Relations Capacity A.1 A.2 A.3 A.4 A.5 A.6 A.7 A.8 A.9 A.10 Actor Develop Legislation & Department Programme State Owned Performance Organisation National R&D Implement Administration & Statutory & of Science Planning, Promotion of Communication Entities and Monitoring, Management & Strategy, White Regulations Oversight Informal and Budgeting & STI & Coordination Science Reporting & Administration Paper on STI (e.g. R&D Tax (National level) Channels Implementation Councils Evaluation Technology Allowance, IPR- PFRD etc.) Sector Specific Develop Programme State Owned Performance Organisation Statutory & National R&D Strategies Legislation & Planning, Promotion of Communication Entities and Monitoring, Management & Informal Departments (e.g. IPAP; ICT Implement Budgeting & STI & Coordination Science Reporting & Administration Channels R&D …) Regulations Implementation Councils Evaluation Organisation Programme Performance Intramural Organisation Statutory & Specific R&D Planning, Communication Monitoring, R&D Management & Informal Strategies or Budgeting & & Coordination Reporting & Departments Administration Channels Plans Implementation Evaluation Organisation Programme Performance Organisation Statutory & Funding Specific R&D Planning, Communication Monitoring, Management & Informal Agencies Strategies or Budgeting & & Coordination Reporting & Administration Channels Plans Implementation Evaluation Performance Organisation Programme Performance Organisation Statutory & Agencies Specific R&D Planning, Monitoring, Management & Informal (Science Strategies or Budgeting & Reporting & Administration Channels Councils) Plans Implementation Evaluation Provincial Organisation Programme Performance Organisation Provincial & Statutory & and Specific R&D Planning, Monitoring, Management & Municipal Informal Municipal Strategies or Budgeting & Reporting & Administration Entities Channels Departments Plans Implementation Evaluation Organisation Private Organisation Specific R&D Sector Management & Strategies or Institutions Administration Plans

B. Procure R&D C. Enabling Investment D. Undertake R&D E. Manage R&D Portfolio

Process / Strategic Project Project Project Project Applied Experimental Institution Portfolio Project Activities Facilities Equipment Basic Planning Financing Approval Development Research Development Management Management Management Research

B.1 B.2 B.3 B.4 C.1 C.2 D.1 D.2 D.3 E.1 E.2 E.3 Actor

Department Financial Allocations to Scope of of Science packaging, Funding Institution Portfolio Project Knowledge As required and modelling and Agencies and Management Management Management Development Technology procurement Projects

Allocations to National Funding Institution Departments Agencies and Management Projects Financial Intramural Scope of packaging, Strategic Basic Applied Experimental Institution Portfolio Project R&D Knowledge As required Construction Purchases modelling and Research Research Development Management Management Management Departments Development procurement Financial Funding packaging, Allocations to Institution Portfolio Project Agencies modelling and Projects Management Management Management procurement Performance Financial Scope of Agencies packaging, Strategic Basic Applied Experimental Institution Portfolio Project Knowledge As required Construction Purchases (Science modelling and Research Research Development Management Management Management Development Councils) procurement Provincial Allocations to and Funding Institution Municipal Agencies and Management Departments Projects Private Applied Experimental Project Sector Construction Purchases Research Development Management Institutions

4 Step 4: Expenditure Analysis of Public-Funded R&D

4.1 Purpose of the Expenditure Analysis The purpose of the Expenditure Analysis is to analyse how public funds for R&D are directed and utilised within the National System of Innovation. This analysis seeks to examine available data in order to:

 Quantify the spending/investment and performance in R&D programmes in South Africa between 2013/14 and 2015/16  Review spending patterns and cost drivers within R&D across national and provincial governments The data collection, collation and consolidation for the Expenditure Review Step of the PER have now been completed.

4.2 Data Analysed This analysis utilises three different data sets, namely:  Basic Accounting System Data  Scientific and Technological Activities Survey (undertaken by the DST)  Research and Development Survey (undertaken by Centre for Science, Technology and Innovation Indicators) The three different data sources represent different perspectives of the publicly-funded R&D funds and flows within the National System of Innovation. The primary source of data for this exercise was government’s Basic Accounting System (BAS) accounts. To perform the expenditure analysis, National Treasury provided BAS data for all national and provincial departments for 3 financial periods (20013/14; 2014/15 and 2015/16). This tool is the main source of information for the preparation of management reports and departmental financial statements. It is not specifically an instrument for R&D expenditure but forms the foundation of the analysis. The BAS data does not lend itself to “R&D” as a categorisation, there was an attempt to remedy the limitation by adding a field within the BAS for the 2015/16 financial year. The take-up and utilisation of this field has been extremely limited and what has been reported is often erroneous. Given this challenge, the research team has taken efforts to make specific adjustments to the BAS data to ensure alignment with R&D definitions and categorisation. The other two sources of information used as secondary data, the STA Survey and the R&D Survey, relate more explicitly to R&D expenditure. The government, through the Department of Science and Technology, coordinates the Scientific and Technological Activities (STA) survey on an annual basis. This information requests each National Department to provide both projected budget allocations over the Medium-term Expenditure Framework (MTEF) and actual previous year’s expenditure with regard to STA activities. This survey is primarily used to provide government and other stakeholders with a comprehensive and forward-looking view on government’s investment on Science and Technology. Within the survey, reporting is disaggregated into different categories of activities as demonstrated in the figure below. The most critical for this analysis is the Government Budget Appropriation or Outlays for Research and Development (GBAORD) element. GBAORD

represents budget and expenditure from government to itself, other government entities, or private sector for the performance of R&D. This category would also include both “intramural,” R&D activity performed within one’s own organisation, or “extramural,” which is R&D activity outsourced to external parties. Figure 15: Funding flows for STA and programmes

Source: Department of Science and Technology. Government Funding for Scientific and Technological Activities. 2015/16 The STA survey provides a clear accounting of National Department budget and expenditure on R&D. It there provides a reasonable basis of comparison for BAS expenditure. However, the limitations of the survey are three-fold. First, the survey relies upon self-reporting by departments and there is a significant risk that interpretations and approaches to R&D vary. Secondly, the survey provides no insight on provinces as they are not targeted. Finally, within reporting of extramural R&D, the detail of transfers to external entities is given little focus. This lack of information limits the usefulness of the survey in tracking publicly-funded R&D activity throughout the National System of Innovation as most of the government R&D spend relates to extramural activity. The third data set, the R&D survey undertaken by Centre for Science, Technology, Innovation Indicators (CeSTII), is more targeted to R&D activities within the system as a whole. Unlike the STA Survey, the CeSTII data is explicitly focused on performance expenditure amounts and targets all departments, entities, and institutions within the system. The “performance” focus of the survey means that it only examines direct expenditure on R&D performance activities, after all cost factors (such as transaction costs) are excluded. This provides a very different piece of information than GBAORD figures. The primary limitation of the data, however, is that the survey is voluntary and lacks full responsiveness by actors within the system. Another consideration is that CeSTII has established relationships with respondents and ensured certain data will not be disclosed. These agreements meant that certain categories of data could not be given in a disaggregated format. As the figure below shows, the data sets lend themselves quite explicitly to certain aspects of the system. BAS data highlights R&D budget and expenditure largely at the national level, with the STA survey providing GBAORD figures for similar focus while the R&D survey focuses more on the Performance Agency level.

Figure 16: Data Hierarchy and Relationships

As each data set captures certain aspects of R&D funding within the National System of Innovation, they can provide highlights of funding flows between levels but no one source provides a holistic picture. This is due to the fact they all serve very different functional purposes. The approach to each data set was dictated by its fundamental structure and limitations. The National Government BAS excel workbooks were split according to the 2015/16 budget votes for the three financial periods under study to allow for expenditure analysis at the departmental level. At the Provincial level, two kinds of sorting were performed, firstly, the BAS excel data was grouped by provinces to allow for provincial level expenditure analysis. Secondly, the BAS data was grouped by provincial departments, to allow for departmental expenditure analysis within a specific province. BAS consists of various columns (fields) that can be understood to be classifications that each explain an aspect of a row (a line entry that represents a single department transaction). Each classification is further disaggregated according to “levels”, the higher number of levels, the more disaggregated that aspect of a transaction is. Across departments, the amount of detail or “levels” used to explain a transaction varies, this is particularly evident in a majority of Provincial Department’s BAS data, where the use of levels to better explain a line item is underutilised. Each expenditure analysis component of the PER is unique in the sense that some of the classification columns would only be relevant for a given PER assignment. Understanding the relationship between all classification columns and line entries across multiple departments helped deal with the issue of relevancy. With respect to this PER assignment, the following classification columns were found to be most relevant:  Responsibility classification – identifies the particular unit of the organisation, and includes responsibility manager and a group of employees responsible for certain activities.  Item classification – identifies the goods, services and other payments to be made in achieving the objective of a department.  Objective classification - reflects a department’s programme and sub-programme structure in as much detail as required both for reporting and management purposes.

 Infrastructure classification – at the highest level, this classification distinguishes between expenditure and non-expenditure transactions. It is then sub classified into infrastructure and non-infrastructure categories  Project classification - a collection of tasks usually of a multi-disciplinary nature to achieve a certain goal Identification of R&D activities in BAS Given the vast amount of line items in over 500 BAS excel workbooks, and the fact that certain classifications, such as responsibilities, are not standardised across departments, the most efficient and effective means to filter through the transactions was performing a key word search on the BAS data. Using MS Excels search function, the following key words were used to filter through the transactions: “research”; “R&D”; “research and development”, and “innovation”. As a result of the above key word search filtering process, insight was gained at a departmental level around which programs show elements of R&D funding and performance at a higher level. In the context of BAS, R&D funding within a program is simply observed by the amount of money that a Department transfers to another entity where they use a portion or the entirety of those funds for R&D related activities. R&D performance within a program is where a Department undertakes its own R&D related activities as part of that programmes budget. Initial analysis of BAS R&D activity using pivot tables With R&D funding and performance at the programme level in mind, an initial stage of Pivot tables were created for each department/budget vote based on the key word search. Creating Pivot Tables at this early stage provided initial understanding of the funding flows within each R&D related programme, however, BAS is a system of codes and does not offer much detail for the line items and the programmes to which they belong. To remedy the above, additional sources were used to make better sense of the pivot tables created and BAS data in general. Annual Reports and Estimates of National Expenditure were used for national departments, while Provincial Budget Speeches and Provincial Estimates of National Expenditure were used. At a provincial level, it was a lot more difficult to qualify the data because supporting documents were not as detailed as the national departments. The Estimates of National Expenditure for national departments were particularly useful in complementing the results of the key word search on BAS. The Estimates of National Expenditures of each department also identified certain programmes and sub programmes that the key word search did not identify. Departmental/Provincial Estimate of National Expenditure allowed one to better understand each program and their relation to R&D activities by providing a description of outputs – such as number of research papers and internal publications produced each year. and performance targets. The Pivot tables generated through the key word search and recon with external sources then allowed for the understanding of flows from funding internally (departmental programmes) and externally (higher education institutes, SoEs, government research institutes, science councils and other public bodies) in the form of transfers and subsidies. A total figure for Estimated BAS R&D Expenditure was then calculated for each department based on the pivot tables and consisted of R&D transfers to entities and R&D in-house activities (good and services, purchases of capital assets and compensation of employees within a R&D related programme). BAS R&D Expenditure could be analysed across four expenditure types: 1) Transfers – transfers that include all unrequited payments made by the government unit to another entity under programmed flagged as R&D related. 2) Compensation of employees – all payments made to employees of department relating to an R&D related programme.

3) Goods and services – payments of all goods and services to be used by that department for R&D related activities, excluding purchases for capital assets 4) Purchases of capital assets - payments for capital assets in R&D related programmes. These are goods that are expected to be used during more than one reporting period and from which future economic benefits or service potential is expected to flow. Following the first complete analysis of the national and provincial BAS data across the three financial periods, it was evident that further refinement was needed. The departmental amounts for estimated R&D in BAS were generally a lot higher than the figures for GBAORD. This was largely due to the fact that in BAS, there is no way of further disaggregating a transfer to an entity. This a problem because only a portion of a transfer from a department to an entity would be used for R&D related activities, therefore including an entire transfer in some cases inflates the results. This was particularly evident for the Department of Higher Education and Training’s transfers to Higher Education Institutes by way of block grants. Block grants are not specifically for R&D; however, universities may use a portion of that grant for R&D related activities. The process of adjusting departmental BAS amounts involved a thorough review of each entities annual performance plan and annual reports to formulate assumptions on what percentage of transfers to entities constitute R&D activities. Following the thorough analysis of departments and entities, the adjusted estimated BAS R&D departmental depicted a more realistic representation national and provincial funding and performance, as well as the major entities involved in the system.

4.3 Overall Spending for R&D Programmes Using BAS, the total expenditure for R&D programmes within South Africa is estimated at R36,6 billion over the 2013/14-2015/16 MTEF. Figure 17: Estimated Total Government BAS and R&D Expenditure (2013/14 -2015/16)

The figure above shows that from the perspective of BAS, the national R&D expenditure is growing on a year on year basis while its percentage of total BAS has fallen by close to one third of a percent. This suggests a diminishing focus on R&D expenditure from a government perspective. The figure also serves to highlights that provincial expenditure on R&D is merely a fraction of national R&D expenditure (sitting at R504 million in 2015/16) but continues to grow at a significant pace.

Figure 18: GDP to Government R&D BAS Expenditure (2013/14 -2015/16)

The figure above demonstrates R&D expenditure as estimated through the BAS analysis as a percent of total Gross Domestic Product. The percentage continues to rise, reaching 0.44 percent by 2015/16. There are some policy documents that suggest South Africa should reach for a gross expenditure on R&D (GERD) target, which is a measure of gross expenditure (all actors) on R&D divided by total GDP, target level of 2.5%. This expenditure analysis shows that government currently stands at a contribution of 17% towards that target. Other sources of information state that that GERD/GDP is presently at 0.80%, and government would thereby represent 50% of total. Figure 19: R&D BAS Expenditure Top Ten Departments (2013/14 -2015/16)

The BAS data has been useful in identifying which departments are funding R&D activities, as there were 25 National Departments, 37 Provincial Departments, and 102 Entities (inclusive of HEIs and Science Councils) that returned results, showcasing the breadth of the system. The analysis of BAS also allows for an analysis of which departments are the top expenders for R&D. As shown in the figure above, when aggregated for the period of study, the top expender on R&D is the Department of Science and Technology. According to BAS, the department’s average annual spend on R&D over the three years of the study is about R4.05 billion, or about 33% of the total of R12.2 billion. Unsurprisingly, Department of Higher Education and Training, followed in second place, representing approximately 24% and containing the block grant to Higher Education Institutions. These findings are logical given both departments’ mandates. Totals fall significantly for third place, held by the Department of Agriculture, Forestry, and Fisheries, but still represent a sizeable amount of approximately R3 billion (2013/14-2015/16). The Department of Health and Department of Energy rank third and fourth at approximately R2.9 billion and R2.3 billion for the three-year period respectively. The figure above also shows that there has been some variability in funding levels over the analysis period, but largely the rankings remain static, with little change of who features in the top ten. The two significant exceptions are that Department of Health has more than doubled in expenditure for 2015/16 as compared to 2014/15 and that Department of Basic Education returned no data for 2013/14. Departments of Energy, Trade & Industry, and Environmental Affairs all experienced declines in 2015/16. For the DTI, such a change is likely attributable to the move of the CSIR a few years ago from the DTI to the DST. The most surprising expender, based on the GBAORD data, is the Department of Basic Education at approximately R523 million for the three-year period. It is likely that this is an overestimate and may help account for a portion of the net overall difference between BAS adjusted and GBAORD of R1 billion. It is noted that GBAORD is a budget figure and hence its agreement with an actual funding figure may not be accurate. It is also surprising to see the relative low ranking for Department of Health according to the BAS analysis. It is possible that this is due to the fact the Medical Research Council is a relatively small Science Council which is indicative of a smaller transfer amount in comparison to other science councils.

4.4 Intramural versus Extramural Expenditure The majority of the R&D expenditure found within the BAS system is transferred to entities rather than retained for intramural expenditure. Transfers to entities from National Departments represents roughly 92% of expenditure over the three-year period. Figure 20: R&D BAS Expenditure Transfers and Intramural (2013/14 -2015/16)

The above highlights the dependence of National Departments on extramural efforts in driving R&D performance within the system. It also underscores the complexity of analysing R&D expenditure from the BAS perspective given the amount transferred out of the government accounts. Within the analysis period transfers went to 102 entities within the National System of Innovation. These included all Science Councils and Higher Education Institutions, but also, a number of organisations with a variety of mandates. For the purposes of this analysis, these “other” are categorised into two groupings; Government Research Institutes and Other Public Bodies. This categorisation is largely derived from the methodology CeSTII takes in performing the R&D survey but where they limit one category to “museums” this PER analysis expands that category to capture a broader range of organisations. The number of transfers is further complicated by the structural interaction between actors. There is not a one to one relationship in the system, transfers can take place between multiple departments to single entities. The figure below, which is just a selection of entities, illustrates this principle. When funds are transferred into an entity they enter that respective organisation’s own financial reporting and administrative system. This issue makes tracking BAS expenditure to the level of specific research outputs at the performance level virtually impossible.

Figure 21: Selected Entities Transfers by Source of Department Funds (R&D BAS Expenditure 2013/14 - 2015/16)

An interesting aspect of the BAS data is how the top ten changes significantly when focused purely on intramural spend. According to BAS, there were 11 National Departments with intramural R&D expenditure totalling R1.76 Billion for the three-year period. It is from this perspective that Health and dTI feature more prominently in the rankings and many new Departments make an appearance. Unlike the data on extramural transfer funds, intramural BAS data can be divided into three categories of expenditure, goods and services, purchase of capital assets, and compensation of employees. The figure below shows that much of the total expenditure, 70%, is on goods and services, which might indicate simply another route of transfer for intramural. Purchase of capital assets represented the smallest portion of total, at 12%. Only Department of Health and Department of Trade and Industry had significant expenditure in the purchase of capital assets, other departments had some expenditure, but none spent over R1 million within the category. Several departments expended funds on compensation of employees but surprisingly this is not consistent across each year of the study period. Possibly this means once-off contracts rather than dedicated staff for intramural R&D.

Figure 22: Selected National Departments Intramural Expenditure (R&D BAS Expenditure 2013/14 - 2015/16)

4.5 BAS Data compared to secondary data sources The BAS data has also helped identify potential R&D expenders that were non-responsive to the STA survey and therefore have provided no GBAORD figures. The figure below highlights those Departments that did not provide GBAORD figures within the STA survey but were found within BAS to have expenditure tagged as R&D. As a total, this represents R 560 million for the period of study. Figure 23: Departments within BAS but without GBAORD figures (BAS and STA Data)

What can be determined via a comparison of BAS data and GBAORD (STA survy data) at the level of national department is that there is relatively good agreement between the two as shown in the ©2018 RebelGroup South Africa National Treasury: GTAC 64 Review of government funding for research, development and innovation Report

figure below. This has one exception, the Department of Basic Education for which the GBAORD figure is anomalous and requires further investigation. The process of making adjustments to the BAS data greatly aided in reaching this agreement and explanations of steps taken are provided for in Appendix 2 of this report. The level of agreement between the two datasets suggest that the sector is well served by the STA survey in its function of estimating the overall R&D budget envelope. Figure 24: Final BAS Expenditure compared to GBAORD (2013/14-2015/16)

The agreement between the GBAORD figures within the STA survey and the BAS data suggests the methodological approach to the BAS information has been fruitful in identifying R&D allocations within the government accounts. Yet, the STA Survey itself has limitations in tracking the relationship between the budget amounts and actual performance of R&D. GBAORD and performance data cannot be compared since the former does not record expenditure at the level of performance.

Figure 25: Intramural R&D BAS Expenditure compared to CeSTII survey data (2013/14-2015/16)

The figure above shows that when compared against Intramural BAS expenditure for national departments, the CeSTII R&D performance figure within the same category aligns with reasonable agreement. Still, even within this category there is not complete parity. While some of this can be attributed to transaction costs and the difference between budget and expenditure, it is possible that a “lag” factor, where performance happens in later period than budgeting takes place, is partially to blame. Nevertheless, highlighting this particular case, where the research team expected to find strong agreement but still faced issues, shows that the analysis based on the available data is more of an art than science. For example, examining other categories of expenditures and perspectives on the data presents a more mixed picture. Approaching the data from the perspective of “actor” yields notable results. From the basis of CeSTII’s approach and data collection activities for the R&D survey with some modification the research team proposes that there are seven different “actor” types within the system; National Departments, Provincial Departments, Government Research Institutes, Higher Education Institutions, Other Public Bodies, Science Councils, and State-owned Enterprises. The figure below illustrates that actors vary greatly with regard to performance (R&D survey) as compared to BAS expenditure. In looking at three-year aggregates, most have less performance expenditure than BAS R&D amounts.

Figure 26: R&D BAS and CeSTII R&D Performance Expenditure by Actor (2013/14-2015/16)

Science Councils have nearly a one to one ratio between the BAS expenditure and the R&D performance data. National Departments and State-owned Enterprises show less performance than their budget but within expected margins given amounts. The more alarming categories are Government Research Institutes and Other Public Bodies. The former has a performance total of 40% of that actor’s BAS R&D expenditure and the later sits at a mere 4%. It is likely these differentials relate to two issues, transaction costs and under reporting within the R&D survey. It is possible that such low performance figures as related to BAS expenditure amounts presents a significant concern regarding particular actors’ effectiveness but this will have to be corroborated through the costing model exercise. An additional explanation might be the multi-variate nature of funding and expenditure between the various entities in the system. All precautions have been taken against this possibility, such as ensuring performance data is isolated by source of fund for all actors. Examining each year individually does not yield any greater clarity except to highlight that the gap between BAS R&D expenditure and performance expenditure narrowed in the 2014/15 year for Government Research Institutes due to greater performance totals, only to drop again in 2015/16

while the BAS R&D expenditure figure increased. It is entirely possible that the rise in performance expenditure is directly related to better responsiveness in the R&D survey, highlighting the limitations of using R&D survey data. Figure 27: R&D BAS and CeSTII R&D Performance Expenditure by Actor per Year (2013/14-2015/16)

Given the nature of BAS coding, it has been difficult to develop a set of normalised transaction costs. It might be possible to recode BAS but a significant proportion of these transaction costs would still remain inscrutable given the majority of R&D related expenditure continues to pass through as transfers to entities. Conducting the BAS analysis in parallel with CeSTII data has been particularly useful in highlighting certain aspects of State-owned Enterprises, an actor category that has had little intel to date. From an adjusted BAS perspective, the SoEs represent a total of 9% for the three-year period. The figure below highlights that State-owned Enterprises are the third largest performer of R&D behind Science Councils and Higher Education Institutes. This figure changes quite dramatically when the SoE expenditure figure is broken down into source of funds and isolated to public funding, which moves SoEs down the rankings behind the Government Research Institutes. Nevertheless, the SoEs remain key actors in the R&D system from an expenditure and performance perspective.

Figure 28: CeSTII R&D performance amounts by actor (2013/14-2015/16

Figure 29: Aggregate 2013/14-2015/16 CeSTII R&D performance amounts by actor (limited to source of fund - public funding)

4.6 Performance Expenditure by Socio-Economic Objective One other aspect of the analysis was to examine R&D performance by Socio-economic objective. Again, as this analysis was performance expenditure focused, it relied on the CeSTII data as this analysis is not possible through BAS or STA survey information. The findings suggest that the R&D system is not significantly responsive to policy changes or movement of national priorities. This is

deduced by examining the relative apportionment of R&D expenditure against the socio-economic objectives provided in the figures below.

Figure 30: CeSTII R&D performance data on Socio-Economic Objectives by Actor (2013/14-2015/16)

Figure 31: CeSTII R&D performance data on Socio-Economic Objective (2013/14 -2015/16)

Figure 32 CeSTII R&D performance expenditure data based on type of research produced (2013/14 - 2015/16)

The above figures show that from 2013/2014 to 2015/16 these amounts, while marginally increasing each year, remain largely static in not only objective focus, but relative contribution by actor. Such limited movement suggests that policy currently has little impact on the direction of R&D expenditure. It is possible this relates to institutional structure, and the window of analysis is not sufficient to analyse the responsiveness. One critical note is the significant rise in performance expenditure for the environmental socio-economic objective from the Science Councils. From 2013/14 to 2015/16 that figure rose dramatically from R46 million to R455 million.

4.7 Conclusions The analysis of the various data sets has revealed more about the nature of data collection in the R&D sector rather than specific insights into departments, entities, or institutes. The analysis of these data sources and the limitations they present illuminate some of the challenges in presenting data for the sector. Still, there is a level of agreement between the three sources of data used in the expenditure analysis, this is a significant observation considering that they are essentially used for different purposes. However, some notable findings from the analysis include:

 Public Funded R&D needs to be increased significantly if the country is to reach the GERD target of 1.5% of GDP.  Departmental expenditure for R&D has not had significant changes in three-years; this suggests an almost static R&D funding environment.  There is a significant amount of labelled R&D expenditure in BAS that is not reflected within the STA report GBAORD figures, this suggests under-reporting.

 A significant amount of labelled R&D expenditure in BAS is not reflected as expenditure in CeSTII R&D survey showing a significant gap in BAS and R&D performance.  The Other Public Bodies category’s R&D performance figure is only 4% of the BAS R&D expenditure, a notable difference

5 Step 5 and 6: Costing Model Exercise and Trade-offs

5.1 Costing of R&D Outputs

5.1.1 Main Cost Components and Relative Costs for R&D Outputs Research and development (R&D), an activity which takes place mainly within research organisations and whose primary purpose is the development of new knowledge, has a variable cost structure depending on the knowledge domain, the type of research, local labour market conditions, and the cost structure or sector of the parent organisation. For instance, particle physics research requires large and expensive infrastructure, such as particle accelerators, and as a result, capital equipment will be an overwhelming contributor to the total cost of R&D. On the other hand, social science research requires limited infrastructure and its main cost driver is the cost of skilled labour. In this section, a brief overview of R&D cost drivers is briefly presented. There are the standard cost components which are common to all the contexts as previously, namely direct labour, direct or attributable materials, analytical services or other non-core inputs, overheads and capital expenditure. Values for these standard components as a proportion of total costs and as a function of various knowledge domains are shown in Table 3. Table 12 Approximate values for the standard components of a R&D project

Natural Life Social Component Average Sciences Sciences Sciences

Direct Labour 27% 26% 27% 30%

Direct Materials 6% 5% 11% 3%

Analytical or Other Non-Core 6% 5% 5% 3% Services

Overheads 51% 45% 46% 63%

Capital Expenditure 10% 18% 11% 3%

Total 100% 100% 100% 100%

Roll-Up Factor 368% 380% 370% 339%

Source: Adapted from Walwyn (2016) In all cases, overheads are the single largest cost contributor, although this is not unusual in any knowledge-intensive organisation. Direct labour costs are the next most important contributor and are the source of all income earned, since it is the time of researchers on specific projects which forms the basis for costing and billing on a R&D project. In the natural sciences, capital costs can be 15% to 20% of the total project cost, but this figure is almost negligible in the social sciences, where the capital requirements may be restricted to a few computers. In the life sciences, physical infrastructure is also significant but direct materials are much higher than other fields due to the need for the purchase of expensive raw materials.

The roll-up factors for each knowledge domain are also shown in this table. Assuming that the labour costs are in absolute terms almost equivalent, it is apparent from this table that research costs in the natural and life sciences are about 40% to 60% more expensive than the analogous costs in the social sciences, mainly due to lower expenditure on materials and capital equipment.

5.1.2 Actual Costs R&D projects are typically costed using the approach of the annual cost of a full-time equivalent (FTE) researcher (which may or may not include any technical support staff), the expected duration of the project and the direct cost of any materials, if these are considered to be significantly higher than cost of the standard consumables as required by the project. The FTE cost is obtained crudely from the total R&D department or organisation cost divided by the number of active researchers. Approximate values for FTE costs in South Africa as a function of sector are shown in Figure 1 (Walwyn and Cloete, 2016). It is apparent that FTE costs are much higher in the business sector (private forms and state-owned entities) and the science councils, relative to the universities. The reason for this difference is not that academic salaries lag their science council and private sector counterparts (!), but that much of the research in the universities is performed by PhD students and post-doctoral employees, who are paid at significantly lower levels through a grant system. For instance, as high as 80% of university FTE researchers may be doctoral students with relatively reduced costs. Another reason for the difference may also be the way in which universities account for R&D costs, with full-cost accounting being inconsistently applied. Figure 33:FTE costs in South Africa

Apart from the sectoral differences, actual costs also vary as a function of knowledge domain as already mentioned and shown in Table 3.

5.2 Methodology for Costing Exercise within the PER The previous section provides a breakdown of the cost components of R&D projects but cannot be used to build a costing model for the assignment. Producing a costing model for this Performance and Expenditure Output is hampered by the fundamental disconnect between the manner in

which expenditure of government departments is captured in the Basic Accounting System and how research outputs are reported. In part, this issue relates to the broader challenge of measuring performance within the R&D sector generally as inputs to the system do not necessarily translate directly to outputs given that R&D specifically seeks out novel and uncertain territories which can often yield little results. Nevertheless, a specific approach has been devised in an attempt to monetize specific indicators. These indicators, taken together, and examined against the total budget envelope for funding of R&D, can reveal the level of efficiency within the system. Moreover, this type of analysis can show each indicator category’s relative contribution to this efficiency. The following sections highlight the selected indicators, their rationale for selection, and the method used to derive a monetary value.

5.2.1 Definition of the Key Performance Indicators Six performance indicators are utilised to act as proxies for overall output within the R&D System. Note: These indicators differ from those selected in the initial Logical Framework component of this PER. The reason for the deviation is that for a costing model to be constructed, there needed to be a selection of indicators which could be monetised with a defensible methodology. Moreover, as mentioned in the above sections of this report, data collection for R&D indicators is severely limited and where it does occur, not often isolatable by actor. These were chosen for their ability to be linked back to the actor categories and BAS data. However, the team proposes the indicators selected cover the breadth of activity in the R&D sector and offer a relatively holistic picture.

5.2.2 Publication Equivalents (Scientific Publications) Most frameworks already use publications as an output measure but vary according to how such outputs are counted. The team has adopted the approach of South Africa’s Department of Education (Ministry of Education, 2003) is used as follows: 1. publication of an article in an accredited journal counts as unit one in the case that all the authors derive from a single institution. In the event that the authors derive from separate institutions, the equivalent is split between the institutions in proportion to their representation on the author list. In the event of a joint publication with external authors, no correction is necessary where books count for a maximum of 5 units, with 60 pages per unit; the same rules on authorship apply; conference proceedings count as 0.5 units per proceeding with the same rules on authorship. However, the proceedings must relate to the dissemination of original research and new developments within specific disciplines, sub-disciplines or field of study. The articles accepted for publication in the proceedings must be peer reviewed, the proceedings must have an ISBN number and the target audience of the proceedings must be specialists in the relevant field. Where proceedings are published in an approved journal, the output must be treated as a journal article and where monographs and industry standards count as a single unit where these are peer- reviewed and published as part of a industry standard. The units are counted for the particular calendar year being evaluated and only those publications which have actually been published in that year qualify; simply being ‘accepted for publication’ is not considered as adequate. Data sources to include the 2016 South African Science, Technology and Innovation Indicators Report compiled by the National Advisory Council on Innovation.

5.2.3 Research Qualifications The number of research qualification units is calculated from the sum of all the PhD/doctorate degrees plus one third times the research masters degrees which have been conferred by the institution during the year of evaluation. The scale factor of 33% for masters degrees is based on the relative economic value of such a qualification, calculated using the net present value of future earnings relative to those of a PhD-qualified person. Non-research degrees, short courses or diplomas do not qualify. Data sources for these figures include information from the Centre for Higher Education Transformation’s South African Higher Education Open Data platform.

5.2.4 Patents Granted The counting of patents is not straightforward since patent filing proceeds through many stages, beginning with the initial disclosure and ending with the granting of a national filing. In this analysis only patents which have been granted a World Intellectual Property Organisation (WIPO) publication number, a PCT application number, and have received a positive examination response, usually in the form of a ‘International Preliminary Examination Report on Patentability’ (IPRP) can be counted. In general, one patent with a positive IPRP report or a national filing is counted as one patent unit. The following additional guidelines are proposed:  there is no subdivision of the patent count per author as for publications, except in the case of multiple institutions listed as inventors on the same patent, in which case the count must be divided by the number of institutions  several patents all covering the same invention cannot be counted more than once. For instance, the same patent registered in a number of countries, all with examination offices, will only count as one. It is our understanding that patent counts provided in the 2016 South African Science, Technology and Innovation Indicators Report by the National Advisory Council on Innovation and the South African National Survey of Intellectual Property and Technology Transfer at Publicly Funded Research Institutions 2017 Report compiled by the National Intellectual Property Management Office conform to these parameters.

5.2.5 Intellectual Property Income Income obtained from royalties and any other form of license fees (including items such as milestone payments) or fees derived from the sale of any intellectual property or asset are counted in the financial year during which this royalty was obtained. The amount declared should be equivalent to the audited figure as stated in the end-of-year financial statements for the institution, if such information is disclosed. Figures for Intellectual Property Income are provided in the National Survey of Intellectual Property and Technology Transfer at Publicly Funded Research Institutions 2017 Report compiled by the National Intellectual Property Management Office.

5.2.6 Technology Packages and Spin Outs This indicator is used to represent a range of non-explicit research outputs which are often not formally registered, including the development of a new product or service such as a software product, a set of analytical methods, and a novel process to manufacture a chemical or biological product. In general a technology package is defined as ‘the output of a research and development

project which has demonstrated that a particular technology can be operationally exploited to enhance capability, manufacture a product or deliver a service in a previously unknown manner’. The output is often presented in the form of a package that can be applied with no further development in order to make a product or deliver a service. The package can be sold to a client or transferred to a spin-out company, where it will be implemented in a manufacturing or business/ community environment. Given the extremely wide variety of possible packages, and the varying levels of impact, a single value cannot be assigned to this category; instead it scale factors have been applied, and for the purposes of simplicity in this exercise, only spin-off companies have been counted. This is due to the fact that most institutions do not report values for technology packages which have been developed through their research programmes. However, many institutions do report on the number of spin-out companies which can be used as an approximation for this output. Most spin-outs take with them a technology which can be directly applied to the delivery of a service or the manufacture of a product (or set of products). In other words, a spin-out company can be considered as the transfer of a technology package and the number of spin-out companies is a useful approximation to the number of packages. The National Survey of Intellectual Property and Technology Transfer at Publicly Funded Research Institutions 2017 Report compiled by the National Intellectual Property Management Office reports on spin-off companies. Most usefully, it disaggregates spin-offs to those publicly funded and those not.

5.2.7 Contract Research Income Income from contract research, as declared in an audited annual financial report, has become an essential component of the income for many HEIs; without this income many institutions would have to shrink or in some cases altogether disappear. Policy makers have been enthusiastic about this trend and have used contract income as an indication of the academic standing of their national institutions. However, a great deal of care should be taken in the use of external income as a performance indicator. The experience in South Africa has been that an over-emphasis on this indicator, and a failure to distinguish research income from consulting or income from knowledge services, can result in the erosion of the research base of an institution (Walwyn, 2006). For this reason, it is recommended that only contract research income is used, where research includes all the Frascati categories of research and development (Frascati, 2002). The South African Higher Education Open Data produced by Centre for Higher Education Transformation is used to derive Contract Research Income value. Several assumptions must be applied however to isolate the figure. These assumptions include;  A percentage applied to source of funds reported  Assumptions made about that percentage given each institution’s research output

5.2.8 Relative Valuation of the Indicators The next element in the exercise is that these indicators must now be valued against a common parameter in order to allow a total score to be calculated. The underlying approach in this exercise is to estimate the economic equivalence for each output. Many evaluation frameworks do not attempt to combine multiple indicators into a single value, but choose instead to use techniques such as spider diagrams (King, 2004), these approaches rest on an assumption that each indicator has a similar weighting. Clearly this is not the case; a research publication has a different weighting

to a patent or a technology package. In order to overcome the problem of non-weighted methods, the relative weightings for the six indicators have been derived as follows:  Scientific publications: the economic value of a single publication in the scientific peer- reviewed literature can be estimated from a number of different perspectives. One approach is based on estimating the efficiency improvement of the output as a proxy. It has been estimated that publications in the open literature lead to a 10% efficiency improvement in research and development (Houghton, 2006). Using data for the USA, which had a total research expenditure in 2003 of $289.7 billion (OECD, 2007a) and a publication rate of about 206 000 articles per year (National Science Board, 2006), the average value per article (equivalent in this case to a net saving or an opportunity cost) is about $141 000.  Research qualifications: the economic value of a research qualification (such as a PhD) is calculated from the difference between the net present value of the salary that is earned on average by a graduate holding a four year degree (in this case a chemistry graduate), and the equivalent net present value of a PhD graduate (in this case, with a doctorate in chemistry) Based on an annual salary difference over the first 25 years of employment of 20% (this difference was obtained from salary information extracted off the web site of the American Chemical Society (www.acs.org). Applying this information to the South African context we can see that a starting salary for a Chemical Engineer is USD 24,766.00 (www.payscale.com) salary per annum, a salary growth of 10% per annum for the first ten years, thereafter 5%, and a discount rate of 4.5%, the NPV of a PhD ( vs a BSc) is $ $353,532.00. This is assumed to be at the higher end of the spectrum for degrees. An assumption is then applied to argue that inclusive of the humanities, this figure would drop roughly by 45%. Thus a more conservative value of $194,442.60 of has been applied for this analysis.  Patents granted: the average value of an approved patent or the subsequent country filing is not easy to estimate due to the extreme variability in patent applications and the value derived from them. An initial estimate can be obtained by assuming that average patent value is at least equal to the cost of producing a patent (in other words, the patent system does not destroy value). Based on data for the USA, the cost per disclosure, patent application and granted patent (US) is calculated as $2.5 million, $4 million and $11 million of R&D expenditure respectively (Milken, 2006). Similar figures are also reported by the Association of University Technology Managers in their annual survey (AUTM, 2007). These values need to be adjusted for the estimated proportion of R&D expenditure which can be assigned to developing a patent (mostly only the categories of applied research and experimental development). For USA higher education institutions, this value is 26% of the total expenditure (National Science Board, 2006). In other words, the cost (and by a rather poor assumption, the value of an approved patent is $2.86 million.  Intellectual property (IP) income: licensing income is used directly since it is already expressed as a monetary value per annum. It can be argued that this income is already included in the valuation of the patent; however not all patents are licensed and not all licensed patents earn royalty or license fees. As a result, a combination of the two measures is appropriate.  Spin-off Companies: this is the most difficult part of the framework to evaluate. Technology packages cover a huge range in terms of size and scope and assigning a single value to this category of S&T output is almost impossible. In the ideal situation, the optimal approach to the valuation of technology demonstrators is to use the risk-adjusted net present value (NPV) of the future cash flows projected to arise from the final ©2018 RebelGroup South Africa National Treasury: GTAC 78 Review of government funding for research, development and innovation Report

commercialization of the technology (Boer, 2003). However, in many cases it is difficult to calculate such a value without making many vague assumptions about key values required by the evaluation. In the absence of these values, or at least a certain level of confidence in their accuracy, it is possible to value technology packages using the arbitrage argument as follows. A company or organisation that wishes to acquire a new technology faces two options, either to purchase the technology or to develop it through an R&D programme. The assumption is that under the conditions of a highly efficient market for technology, the two options should be equal; in other words the company should be required to invest no more in purchasing the technology than what it would spend to develop the same technology itself. Using certain scale factors, and estimating an average cost of development, It can be shown that the net present value of such a life cycle is equal to about 35% of the peak sales revenue (PSR), which should at least match the R&D investment and is referred to as the ‘affordable cost of research’. Peak average sales revenues are highly dependent on the type of product and its market, but through dividing products into categories and applying the scale factors we can estimate he actual value of a single unit in this category. This can be calculated using an estimated NPV for a platform product, which is calculated as $ 29.8 million based on the assumptions listed above for an average product life cycle.  Contract research income: the equivalent value from contract research is derived by considering the standard headline earnings as a percentage of total revenue for commercial contract research organisations. Such entities typically report their earnings as between 5 – 15% of turnover (for instance, see SAIC at www.saic.com (operating income in 2006 of $497 million on revenue of $7.8 billion) and Icon at www.iconclinical.com (operating income in 2006 of $37 million on revenue of $327 million). Additionally, certain assumptions have been applied to assume that a portion of operational income would contribute to researcher’s salaries. A value of 60% is used in this framework. A summary of the equivalent values is given in the table below; in all cases the performance indicators are equated to a value expressed in millions of USA dollars. In order to convert to South African currency, the values given in the table are multiplied by the current conversion rate and expressed in terms of purchasing power parity Table 13 Indicators for Costing Model and Equivalent Values

Item Units Equivalent Value

Scientific Publications Million $/ publication equivalent 0,141

Research Degrees Conferred Million $/degree units 0,194

Patents Granted Million $/patent 2,23

Intellectual Property Income Million $/ million $ income 1

Spin-Off Companies Million $/package unit 29,8

Contract research Income Million $/million $ income 0,1

Source: Adapted from Walwyn (2016)

5.2.9 Model Application The Costing Model allows for the derivation of the comparative efficiency of public-funded R&D in South Africa against other countries as well as a comparison of output efficiency by actor type against their BAS recorded R&D expenditure. This was completed through a collection of recorded research outputs disaggregated by actor type. Consultations included a list of individuals included in the appendix and several assumptions had to be made about certain indicators. The below table highlights assumptions made per Indicator. Table 14 Assumptions in the Costing Model

Indicator Key Assumptions an Limitations Discussions with those knowledable in the field have highlighted that the majority of scientific publications are produced at Higher Education Institutes Scientific and Science Councils. However, to approach the issue methodically a Scopus Publications web search was conducted with reported data organised by institution. One caveat is that the database does not include institutions with less than 100 publications; which could overlook a number of smaller institutions.

Research The assumption was made that for most actor categories there would be no Degrees reported figures because research degrees conferred must originate from Conferred Higher Education institutes, even those housed by Science Councils.

Based of NIPMOs database, the figures were limited to Science Councils and Patents HEIs. Assumptions for Gov Research Institutes and SoEs based on Granted discussions with those knowledgable in the field. Lack of 2015 figures were compensated for with an escalation based on previous years’ trend. Intellectual property income figures utilised NIPMO’s database. Where figures Intellectual could not be found nor any reasonable trend could be extrapolated (SoEs, Gov Property Research Institutes) a zero assumed. The categories of Other Public Bodies, Income National Government, Provincial Government assumed at zero given limitations of the IPR Act. Limitations to datasets meant that only years of 2012-2014 can be reported with any accuracy. Given limitations of Companies Act 4 categories excluded Spin-Off (National Government, Provincial Government, Other Public Bodies, Companies Government Research Institutions) SoEs are reported at zero given lack of available data. Most of the figures are derived from CeSTII R&D survey data and thus not Contract available for 2012 and 2011. For the HEIs, a methodology was derived in research consultation with CHET where a relative weighting is applied given source of Income fund data and research output productivity by institution. The costing model relies on expenditure data provided for this PER and thus only has three-years of data available (2013/14-2015/16). Research output reporting does not align with the government fiscal calendar but rather the actual calendar year. Moreover, the reporting of outputs tends to lag by a year. The research team is therefore only able to produce a model for 2014/15 and 2013/14. Also, the team notes that the Science Council and State-owned Enterprise figures are quite low. This is largely due to some key missing data elements, such as Spin-offs for Science Councils and IP revenue for the SoES.

The results of the model are presented in the table below.

Table 15 Summary Sheet for Costing Model

Research Degrees Total Patents Return on BAS Total Public R&D Performance Return on Number of Scientific Conferred (Consists of Granted (National Intellectual Property Contract Research Investment (of Indicator Spin-offs Created Totals Expenditure on R&D Expenditure by Actor Investment (of Publications Doctorate and 33% of Phase Patent Income Income R&D per Actor (ZAR) (ZAR) BAS) Masters) Applications) Performance)

Equivalent Value 0.141 0.194 2.23 1 30 0.1 n/a

2014/15 2014/15 2014/15 Higher Education Institute ZAR 2,540,666,479 ZAR 1,084,997,768 ZAR 155,514,848 ZAR 12,588,730 ZAR 302,808,000 ZAR 921,324,256 ZAR 5,017,900,081.06 ZAR 3,090,000,000 ZAR 3,490,000,000 162% 144% Science Council ZAR 171,689,383 ZAR 0 ZAR 71,618,680 ZAR 20,097,068 ZAR 0 ZAR 868,168,704 ZAR 1,131,573,835.50 ZAR 4,857,000,000 ZAR 4,304,000,000 23% 26% National Department ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 2,141,128 ZAR 2,141,127.84 ZAR 740,000,000 ZAR 421,000,000 0% 1% Provincial Department ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR - ZAR 426,000,000 ZAR 390,000,000 0% 0% Other Public Bodies ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 610,020 ZAR 610,020.48 ZAR 629,000,000 ZAR 26,000,000 0% 2% Government Research Institute ZAR 119,548,598 ZAR 0 ZAR 9,330,891 ZAR 0 ZAR 0 ZAR 5,713,712 ZAR 134,593,200.96 ZAR 1,914,000,000 ZAR 972,000,000 7% 14% State Owned Enterprise ZAR 0 ZAR 0 ZAR 24,882,376 ZAR 0 ZAR 0 ZAR 217,027,999 ZAR 241,910,374.88 ZAR 1,322,000,000 ZAR 542,000,000 18% 45%

Total Monetised Research ZAR 2,831,904,461 ZAR 1,084,997,768 ZAR 261,346,795 ZAR 32,685,797 ZAR 302,808,000 ZAR 2,014,985,820 ZAR 6,528,728,641 ZAR 12,978,000,000 ZAR 10,145,000,000 Output (2014/15) in USD

2013/14 2013/14 2013/14 Higher Education Institutes ZAR 2,187,584,093 ZAR 1,000,084,899 ZAR 186,208,568 ZAR 17,360,368 ZAR 110,112,000 ZAR 734,879,830 ZAR 4,236,229,758.18 ZAR 2,663,000,000 ZAR 3,175,000,000 159% 133% Science Councils ZAR 162,115,145 ZAR 0 ZAR 102,312,400 ZAR 24,360,938 ZAR 27,528,000 ZAR 933,405,660 ZAR 1,249,722,143.27 ZAR 4,646,000,000 ZAR 3,401,000,000 27% 37% National Department ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR - ZAR 466,000,000 ZAR 244,000,000 0% 0% Provincial Department ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR - ZAR 314,000,000 ZAR 390,000,000 0% 0% Other Public Bodies ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 0 ZAR 714,076 ZAR 714,076.32 ZAR 456,000,000 ZAR 24,000,000 0% 3% Government Research InstitutionsZAR 92,895,989 ZAR 0 ZAR 9,883,378 ZAR 0 ZAR 0 ZAR 9,297,307 ZAR 112,076,673.36 ZAR 1,914,000,000 ZAR 723,000,000 6% 16% State-Owned Enterprise ZAR 0 ZAR 0 ZAR 26,355,674 ZAR 0 ZAR 0 ZAR 207,678,389 ZAR 234,034,063.52 ZAR 1,124,000,000 ZAR 511,000,000 21% 46%

Total Monetised Research ZAR 2,442,595,226 ZAR 1,000,084,899 ZAR 324,760,020 ZAR 41,721,307 ZAR 137,640,000 ZAR 1,885,975,262 ZAR 5,832,776,715 ZAR 11,583,000,000 ZAR 8,468,000,000 Output (2013/14) in USD

6 Conclusions of the PER

The challenges faced by the research team in analysing the flow of funds in the extremely complex R&D system through existing data collection instruments is indicative of the fact that there are number of challenges with respect to the development of a robust R&D monitoring and evaluation system. Despite the gaps in the data sources and limitations of both the R&D and STA survey, there is clear indication that R&D activities permeate most of government departments, entities, and institutions. This suggests that the sector needs some design principles for effective monitoring and evaluation and a manner by which each and every department could report on their R&D intensity. One finding from conducting the analysis is that recoding BAS would be of limited value. Most entities do not report into BAS. Thus, for an accurate accounting there would have to be a request, on a case by case basis, for each entity’s management accounts – bearing in mind that each entity has its own unique reporting/accounting system. There is also a political issue to consider – currently there are no formal requirement for entities to operate in the manner of government departments. Many are governed by legislation such as the Companies Act with their own executive authority and board. One approach would be to change the funding conditions (working through multiple national departments) – in lieu of a block grant, transfers to entities become more conditional, placing certain requirements from expenditure and reporting perspective to allow better tracking of flows of money out of departments and in to entities. Such an action would have to be weighed against negative externalities in that it might improve analysis, but not necessarily add much value to the current system and further burden administrative processes. Another finding is that the list of respondents to the R&D survey is far shorter than the list of those departments and entities within BAS that have indicated some form of budget or expenditure for R&D. This raises the possibility that modifying the approach to the R&D survey would go far in providing more data for analysis. The survey is already well institutionalised; however, the limited response rate and overall usefulness is impacting its effectiveness. The R&D survey needs to be more formalised and given more support to its robustness. Increasing the number of responses will definitely improve the data available, further linking the R&D survey to BAS. Making the survey more compulsory through the Treasury is definitely an option, however this must be handled carefully. If Treasury makes the R&D survey compulsory for national departments, it is likely departments will also look to share some of the burden with the entities on the receiving end of transfers. Currently entities are only included at the level of performance, a limitation of the survey, expansion to capture their R&D funding would also be a key addition to the survey in matching and analytic purposes by measuring both budget and expenditure.

7 Appendix 1: Glossary

All terms derived from OECD (2015), “Glossary of terms”, in Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, OECD Publishing, Paris.

Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view. Business enterprise expenditure on R&D (BERD) represents the component of GERD incurred by units belonging to the Business enterprise sector. It is the measure of intramural R&D expenditures within the Business enterprise sector during a specific reference period. Capital R&D expenditures are the annual gross amount paid for the acquisition of fixed assets that are used repeatedly or continuously in the performance of R&D for more than one year. They should be reported in full for the period when they took place, whether acquired or developed in house, and should not be registered as an element of depreciation. Experimental development (research) is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes. Extramural R&D is any R&D performed outside of the statistical unit about which information is being reported; its “funds for extramural R&D” should include only internal funds (not from external sources) provided to an outside unit for R&D performance including both where there is an expected compensatory delivery of R&D (exchange or purchase) and where no compensatory delivery is expected (transfer or grant). It may also be noted that such funds for extramural R&D often will include payments for costs other than for R&D, such as cost elements covering depreciation costs, performer profit, delivery charges, etc. Full-time equivalent (FTE) of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group. Government budget allocations for R&D (GBAORD) encompass all spending allocations met from sources of government revenue foreseen within the budget, such as taxation. Spending allocations by extra-budgetary government entities are only within the scope to the extent that their funds are allocated through the budgetary process. Likewise, R&D financing by public corporations is outside the scope of GBAORD statistics, as it is based on funds raised within the market and outside the budgetary process. Government expenditure on R&D (GOVERD) represents the component of GERD incurred by units belonging to the Government sector. It is the measure of expenditures on intramural R&D within the Government sector during a specific reference period. Gross domestic expenditure on R&D (GERD) is total intramural expenditure on R&D performed in the national territory during a specific reference period. Higher education expenditure on R&D (HERD) represents the component of GERD incurred by units belonging to the Higher education sector. It is the measure of intramural R&D expenditures within the Higher education sector during a specific period.

Intramural R&D expenditures are all current expenditures plus gross fixed capital expenditures for R&D performed within a statistical unit during a specific reference period, whatever the source of funds. Intramural R&D expenditure is synonymous with the performance of R&D within a statistical unit. The aggregation of intramural R&D for all units within a sector is synonymous with the performance of R&D within a sector of the economy; the summation of intramural R&D for all sectors is synonymous with the performance of R&D for the entire economy (GERD). Outlays (used interchangeably with expenditures in terms of spending) represent the amounts for checks issued and cash payments made during a given period, regardless of when the funds were appropriated or obligated (when referring to government funds). Performers of R&D consist of statistical units that undertake (i.e. perform) R&D: Business enterprise, Government, Higher education and Private non-profit. R&D coefficients are a tool for calculating / estimating the shares of personnel and expenditure data attributable to R&D. They are especially used for distributing total resources among research, teaching and other activities (including administration) in the Higher education sector. They can be used for the total expenditure or for parts of it, like public general university funds (GUF) or for personnel only. Scientific and technological activities (STA) can be defined as all systematic activities which are closely concerned with the generation, advancement, dissemination and application of scientific and technical knowledge in all fields of science and technology, that is, the natural sciences, engineering and technology, the medical and agricultural sciences (NS), as well as the social sciences and humanities (SSH). The activities that should be covered in the statistical practice may be divided into three broad groups: research and experimental development; S&T education and training at broadly the third level; and scientific and technological services. Socio-economic objectives (SEO) classification is used to distribute GBAORD. The criteria for classification should be the purpose of the R&D programme or project, i.e. its primary objective. The allocation of R&D budgets to socio-economic objectives should be at the level that most accurately reflects the funder’s objective(s). Source of R&D funds is the unit that provides the funds for R&D performance. Sources may be internal or external to the reporting unit. In surveys and data presentation, external sources are grouped by main sector and relevant subsectors. In broad terms, there are five main sources for R&D funding: Business enterprise, Government, Higher education, Private non-profit and the Rest of the world.

8 Appendix 2: References

Association of University Technology Managers (2007) AUTM US Licensing Survey. Volumes 1 and 2 . Association of University Technology Managers, Northbrook, Illinois, USA (available from http://www.autm.net/index.cfm). Arnold, E. & Bell, M. 2001. Some new ideas about research for development. Partnerships at the leading edge: a Danish vision for knowledge, research and development, pp 279-319. Arnold, E. & Boekholt, P. 2003. Research and innovation governance in eight countries; a meta-analysis. Technopolis (Amsterdam). Arrow, K. 1962. Economic welfare and the allocation of resources for invention. In: Rosenberg, N. (Ed.) The rate and direction of inventive activity: economic and social factors. Princeton: Princeton University Press, Ch 6, pp 609 - 626. Bento, N. & Fontes, M. 2015. The construction of a new technological innovation system in a follower country: Wind energy in Portugal. Technological Forecasting and Social Change, 99, pp 197-210. doi: http://dx.doi.org/10.1016/j.techfore.2015.06.037 Bernanke, B. S. 2011. Promoting Research and Development The Goverment's Role. Issues in Science and Technology, 27(4), pp 37-41. Bilbao‐ Osorio, B. & Rodríguez‐ Pose, A. 2004. From R&D to innovation and economic growth in the EU. Growth and Change, 35(4), pp 434-455. Boer, F Peter (2003) Risk-Adjusted Valuation of R&D Projects. R e s e a r c h T e c h n olo g y Management , September-October, pp 50 – 58. Carvalho, L. 2012. Why are Tax Incentives Increasingly Used to Promote Private R&D? In: Papanikos, G. T. (Ed.) Economic Essays. Athens: Athens Institute for Education and Research, Ch 10, pp 113-130. Chorafakis, G. 2013. Public financing of research; taxonomy of public research-funding apparatuses. Programme on Innovation, Higher Education and Research for Development, OECD (Paris). DACST. 1996. White Paper on Science and Technology. Department of Arts, Culture, Science and Technology, (Pretoria). Department of Science and Technology. 2002. South Africa’s National Research and Development Strategy. Department of Science and Technology, (Pretoria). Department of Science and Technology. 2017. South African National Survey of Research and Experimental Development: Statistical Report 2014/15. (Pretoria). Department of Science and Technology. 2012. Ministerial Review Committee on Science, Technology and Innovation Landscape in South Africa: Final Report. Department of Science and Technology (Pretoria). European Commission. 2017. Open innovation, open science, open to the world - a vision for Europe. European Commission (Brussels). Freeman, C. 1987. Technology policy and economic performance: lessons from Japan. pp. Griffith, R., Harrison, R. & Van Reenen, J. 2006. How special is the special relationship? Using the impact of U.S. R&D spillovers on U.K. firms as a test of technology sourcing. American Economic Review, 96(5), pp 1859-1875. Hartmann, George C (2003) Linking R&D Spending To Revenue Growth. Research Technology Management , 46 (1), pp 39 – 46. Houghton, J and P Sheehan (2006) The economic impact of enhanced access to research findings . CSES Working Paper No 23, Melbourne. King, D (2004) The Scientific Impact of Nations. Nature , 430, pp 311 – 316. Lepori, B., Van den Besselaar, P., Dinges, M., Potì, B., Reale, E., Slipersæter, S., Thèves, J. & Van der Meulen, B. 2007. Comparing the evolution of national research policies: what patterns of change? Science and Public Policy, 34(6), pp 372-388.

Lundvall, B.-A. 1992. National innovation system: towards a theory of innovation and interactive learning, London: Pinter. Lundvall, B.-Å. 2010. National systems of innovation: Toward a theory of innovation and interactive learning, Anthem Press. Lundvall, B.-A. & Borrás, S. 2005. Science, technology and innovation policy. The Oxford handbook of innovation, pp 599-631. Lundvall, B. Å. 2007. National innovation systems—analytical concept and development tool. Industry and innovation, 14(1), pp 95-119. Mashamba, G. 2015. Status update on processing of applications for R&D tax incentive. Department of Science and Technology (Pretoria). Mazzucato, M. 2013. The Entrepreneurial State: Debunking Public vs. Private Sector Myths. London: Anthem Press. National Advisory Council on Innovation. 2016. South African Science, Technology and Innovation Indicators 2015. National Advisory Council on Innovation (Pretoria). National Intellectual Property Management Office. 2017. South African Survey of Intellectual Property and Technology Transfer at Publicly Funded Research Institutions. Department of Science and Technology (Pretoria). National Planning Commission. 2011. National Development Plan 2030: Our Future - Make it Work. The Presidency, Republic of South Africa (Pretoria). OECD. 2002. Frascati Manual. Proposed Standard Practice for Surveys on Research and Experimental Development. OECD (Paris). OECD. 2007. Review of South Africa’s Innovation Policy. Organisation for Economic Cooperation and Development (Paris). OECD Reviews of Regional Innovation. Multi-Level Governance of Basque Country STI Policy. OECD. 2011. OECD. 2011. Public Research Institutions: Mapping Sector Trends. OECD (Paris) OECD Dataset: Science Technology and Industry Outlook 2014 OECD. 2015. Frascati Manual. Guidelines for Collecting and Reporting Data on Research and Experimental Development; The Measurement of Scientific, Technological and Innovation Activities. OECD (Paris). OECD Science, Technology and Innovation Outlook 2016. 14 September 2016 Oh, Sea-Hong; Lee Kyoung-Joo. Governance system of governmental R&D programs: Formation and transformation of the Framework Act on Science and Technology in Korea. Science and Public Policy. August 2013. R&D Evaluation Methodology and Funding Principles. Technopolis Group. March 2015 Reinstaller, A. & Unterlass, F. 2008. Sectoral innovation watch synthesis report: what is the right strategy for more innovation in Europe?: drivers and challenges for innovation performancve at the sector level, Office for Official Publications of the European Communities. Rosenberg, N. 2004. Innovation and economic growth. OECD (Paris). Walwyn, D. 2016. Synthesis Report: Review of the White Paper on Science and Technology and High Level Framing for a New Decadal Plan. National Advisory Council on Innovation (Pretoria). Walwyn, D (2007) An Analysis of the Performance Management of South African Higher Education Institutions. Article submitted to the R&D Management, November 2007 Walwyn, D (2007) A New Framework for the Performance Management of Research in Higher Education Institutions Walwyn, D. R., Bertoldi, A., Kaplan, D., Maharajh, R., Manzini, S. & Motala, E. 2015. Review of the White Paper on Science and Technology. National Advisory Council on Innovation (Pretoria). Walwyn, D. & Cloete, L. 2016. Universities are becoming major players in the national system of innovation. South African Journal of Science, 112(7-8), pp 1-8.

9 Appendix 3: Respondents List (BAS, CeSTII, STA)

BAS GBAORD STA CesTII National Department Agriculture, Forestry & Fisheries yes yes yes no Arts and Culture yes yes yes no Basic Education yes yes yes yes Cooperative Governance no yes yes yes Correctional Services no yes yes no Council for Higher Education (CHE) no no no yes Defence yes yes yes no DPME no no no yes Economic Development no no no no Energy yes yes yes no Environmental Affairs yes yes yes yes Government Communication and no no no no Information System (GCIS) Health yes yes yes no Higher Education and Training yes yes yes yes Home Affairs no yes yes yes Human Settlements yes no no no Independent Police Investigative no no no no Directorate International Relations and no no no no Cooperation Justice and Constitutional yes no no yes Development Labour yes no yes no Military Veterans no no no no Mineral Resources yes yes yes no Natonal Planning Commission no no no no Secretariat National Prosecuting Authority of SA no no no no (NPA) National Treasury yes yes yes no National Youth Development Agency no no no no Office of the Chief Justice no no no no Parliament no no no no Planning Monitoring and Evaluation no no no no Presidency no no no yes Public Enterprises no no yes yes Public Service and Administration yes no yes no Public Service Commission no no no no Public Works no no no yes Rural Development and Land Reform yes yes yes no Science and Technology yes yes yes no

Small Business Development no no no no Social Development yes yes yes yes SA Police Service no no yes no State Security Agency no no no no Sport and Recreation South Africa no yes yes no Statistics South Africa yes yes yes no Telecommunications and Postal yes no yes no Services (previously Communications) Tourism yes no yes no Trade and Industry yes yes yes no Traditional Affairs no yes yes no Transport yes yes yes yes Water and Sanitation yes yes yes no Women yes no no no

Provincial Department BAS GBAORD STA CesTII Eastern Cape Department of no no no yes Education Eastern Cape Human Settlements yes no no no Eastern Cape Rural Development yes no no no and Agrarian Reform Free State Department of Agriculture yes no no yes Free State Cooperative Governance yes no no no and Traditional Affairs Free State Department of yes no no yes Environmental & Economic Affairs Free State: Education yes no no no Free State Department of Health no no no yes Free State: Office of the Premier yes no no no Free State: Police, Roads and yes no no no Transport Free State: Provincial Treasury yes no no no Free State: Public Works and yes no no yes Infrastructure Gauteng: Agriculture and Rural yes no no no Development Gauteng Department of Sports, no no no yes Recreation, Arts and Culture Gauteng: Economic Development yes no no no Gauteng: Human Settlements yes no no no Kwazulu Natal Department of yes no no yes Economic Development & Tourism KwaZulu-Natal: Office of the Premier yes no no no Kwazulu Natal Department of yes no no yes Provincial Treasury KwaZulu-Natal: Public Works yes no no no KwaZulu-Natal: Social Development yes no no no KwaZulu-Natal: Sports and yes no no no Recreation KwaZulu-Natal: Transport yes no no no Mpumalanga Department of Agriculture, Conservation & yes no no yes Environment

Mpumalanga Department of Social yes no no yes Services Mpumalanga: Economic Development, Environment and yes no no no Tourism Mpumalanga: Human Settlements yes no no no Northern Cape Department of yes no no yes Agriculture & Land Reform Western Cape Department of Cultural no no no yes Affairs and Sport Eastern Cape Department of no no no yes Economic Development Eastern Cape Department of Health no no no yes Eastern Cape Department of no no no yes Transport Eastern Cape Department of no no no yes Treasury Gauteng Department of Education no no no yes Gauteng Department of Social no no no yes Development Kwazulu Natal Social Development no no no yes Kwazulu Natal Department of yes no no yes Agriculture & Environmental Affairs Kwazulu Natal Department of Health no no no yes Kwazulu Natal Department of yes no no yes Treasury Limpopo Department of Agriculture yes no no yes North West Department of Rural and yes no no yes Agricultural Development North West: Econ Develop, Conservation, Environment And yes no no no Tourism Northern Cape Co-operative Governance, Human Settlements and no no no yes Trad Aff Northern Cape: Economic yes no no no Development and Tourism Northern Cape Department of Environmental and Nature yes no no yes Conservation Northern Cape Department of Social yes no no yes Development Northern Cape Health no no no yes Northern Cape: Transport, Safety and yes no no no Liaison Western Cape Cultural Affairs and no no no yes Sport Western Cape Department of yes no no yes Agriculture Western Cape Department of Health no no no yes Western Cape Nature Conservation no no no yes Western Cape Department of Social yes no no yes Development Western Cape: Economical yes no no no Development and Tourism

Government Research Institute BAS GBAORD STA CesTII KwaZulu - Natal Sharks Board no no no yes SA Weather Services yes no no yes Development Bank of South Africa yes no no yes Dohne Agriculture Development no no no yes Institute

National Energy Regulator of South no no no yes Africa National Film and Video Foundation no no no yes National Health Laboratory Services yes no no yes (NHLS) National Metrology Institute of South yes no no yes Africa (NMISA) National School of Government no no no yes National Student Financial Aid no no no yes Scheme (NSFAS) South African Law Reform no no no yes Commission South African National Parks yes no no yes South African Human Rights no no no yes Commission South African National Biodiversity yes no no yes Institute South African Qualifications Authority no no no yes South African National Space Agency yes no no yes (SANSA) Technology Innovation Agency yes no no no SA National Energy Development yes no no no Inst Financial Fiscal Commision yes no no no Economic Research Southern Africa yes no no no Water Research Commission yes no no no Agricultural Biotechnology Industrial yes no no no Aurum Institute For Health Research yes no no no SA Research & Innovation yes no no no Management Association (Sarima) Seda Ess Oils Business Incubator yes no no no (Seobi) South Africa Institute Of Physics yes no no no SIMODISA Association yes no no no Fnd Research Industrial yes no no no Development (Fridge) Protechnik Laboratories yes no no no

Higher Education Institutes BAS GBAORD STA CesTII Cape Peninsula University of yes no no yes Technology University of Cape Town yes no no yes Central University of Technology yes no no yes Durban University of Technology yes no no yes University of Fort Hare yes no no yes University of the Free State yes no no yes University of Johannesburg yes no no yes University of KwaZulu-Natal yes no no yes University of Limpopo yes no no yes Mangosuthu University of Technology yes no no yes Nelson Mandela Metropolitan yes no no yes University North-West University yes no no yes University of Pretoria yes no no yes

Rhodes University yes no no yes University of South Africa yes no no yes Sefako Makgatho Health Sciences yes no no yes University (SMU) Tshwane University of Technology yes no no yes Vaal University of Technology yes no no yes University of Venda yes no no yes Walter Sisulu University yes no no yes University of the Western Cape yes no no yes University of the Witwatersrand yes no no yes University of Zululand yes no no yes

Science Council BAS GBAORD STA CesTII Agricultural Research Council yes no no yes Council for GeoSciences yes no no yes Medical Research Council yes no no yes National Research Foundation yes no no yes Africa Institute of South Africa no no no yes Council for Scientific and Industrial yes no no yes Research Human Sciences Research Council yes no no yes MINTEK yes no no yes

Other Public Bodies (including BAS GBAORD STA CesTII Museums) Afrikaans Language Museum yes no no yes Albany Museum yes no no yes Bayworld Museum no no no yes Ditsong National Museum of Natural no no no yes History (former Transvaal Museum) Iziko Museums of Cape Town - yes no no yes Natural History Division Natal Museum yes no no yes Afrikaanse Taalmuseum en no no no yes monument Albany Museum no no no yes Amathole Museum no no no yes Bayworld Museum no no no yes Ditsong National Museum of Natural no no no yes History East London Museum no no no yes Fransie Pienaar Museum no no no yes Iziko Museum: National and Social yes no no yes History Kwazulu - Natal Museum yes no no yes McGregor Museum no no no yes Nelson Mandela Metropolitan Art yes no no yes Museum South African Reserve Bank no no no yes SA Bureau of Standards yes no no no

SA National Energy Development yes no no no Institute Onderstepoort Biological Prod yes no no no Die Afrikaanse Taalmuseum yes no no no Freedom Park Trust yes no no no Luthuli Museum yes no no no Nat Museum Blft yes no no no National Research Foundation (NRF) yes no no no Robben Island Museum yes no no no The Nat English Literary Museum yes no no no Voortrekker Museum yes no no no War Museum Boer Republic yes no no no William Humphreys Art Gallery yes no no no Engelenburg House Art Col yes no no no Productivity SA yes no no no National School of yes no no yes Government (previously Palama) CPSI yes no no no Council For Nuclear Safety yes no no no Assaf yes no no no Bakgatla Sports, Arts & Culture yes no no no Biosafety SA yes no no no Black Sc Tech & Engineering Prof yes no no no Centre For Aids Prog Of Res In S yes no no no Centre For Proteomic & Genomic R yes no no no Da Vinci TT100 Awards Programme yes no no no Forestry South Africa yes no no no Fresh Produce Exporters Forum yes no no no Grain South Africa yes no no no Indigenous Knowledge Of Sa Trust yes no no no Institute Of Natural Resources yes no no no Int Centre F Genetic Engi(Icgeb) yes no no no National Science & Technol Forum yes no no no Resonance Bazar yes no no no S A Maritime Safety Authority yes no no no South Africa San Institute yes no no no The Composites Group (Pty) Ltd yes no no no Trade & Industrial Policy Strate yes no no no World Meteorological Organisatio yes no no no Young Water Professionals (Wisa) yes no no no Exprt Credt Insurnce Corp Of Sa yes no no no Nat Credit Regulator yes no no no Nat Consumer Commission yes no no no Commission for Gender Equality yes no no no yes no no no

State Owned Enterprise BAS GBAORD STA CesTII Armaments Corporation Of SA yes no no no SA Nuclear Energy Corp Ltd yes no no no Pelchem (Pty) Ltd yes no no no