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					Towards a common goal: integration of national statistics

NSS Newsletter
April 2006 Number 2 The National Statistics System in South Africa Volume 5,

Gauteng formally joins the process of integrating national statistics

Statistician-General Pali Lehohla signs a Memorandum of Understanding (MOU) with Mr Mogopodi Mokoena, DirectorGeneral in the Office of the Premier, Gauteng Province, in order for the province to become a formal partner in the NSS

Colleagues, We are in the process of reorganising this newsletter to fit in with the development of a new identity for the NSS. The identity seeks to align the NSS programme both with that of the Stats SA, the implementing agency, and of the Government-wide Monitoring and Evaluation (GWM&E) system being put in place to track and assess the performance of development programmes, and to inform planning and decisionmaking. Publication might therefore become somewhat irregular if only for a short period.

In this edition we cover the joining of the NSS by the Gauteng Province and aspects of governance of the NSS. Governance is an issue which needs plenty of reflection and debate. We therefore invite you to participate in this debate. Yours in partnership, J Akiiki Kahimbaara, NSSD Anisha Maharaj, NSSD

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Gauteng joins the NSS
On 4 April 2006, the Director-General in the Office of the Premier of Gauteng Province, Mr Mogopodi Mokoena, together with the

Apart from committing Gauteng administrative structures to the generation of sustainable official statistics, the ceremony was significant for providing a direction in the governance structure of the NSS at sub-national level.

The Executive Mayor of Sedibeng, Mr Mlungisi Hlongwane, witnessing the MOU between Stats SA and the Gauteng Premier’s Office. Clockwise from left: Mr Hlongwane, Ms Lulama Duma (Chief of Staff, Office of the DG, Gauteng), Director-General Mogupudi Mokoena (Office of the Premier, Gauteng) and Statistician –General Pali Lehohla.

Statistician-General, Mr Pali Lehohla, signed a Memorandum of Understanding in order for the province formally to join the NSS. Gauteng is the second Provincial Government to become a partner in NSS. The first province was KwaZuluNatal. The objective of the MOU is to commit the signatories to work towards the sustainable production of official statistics to inform the GWM&E by populating the relevant indicators in the Compendium of Indicators that has been spearheaded by PCAS. This is an aspect of integrating national statistics and increasing the scope of official statistics in the country. The Gauteng Province saw the signing of the MOU as the first step in partnering with other stakeholders in enhancing service delivery. That the signing ceremony was so well attended attests to the importance of the MOU. The ceremony was also attended by the Executive Mayor of the Sedibeng District Municipality, Mr Mlungisi Hlongwane. The mayor and the Chief of Staff in the Director-General’s Office, Ms Lulama Duma, witnessed the MOU.

Participation in the NSS of local government (municipalities) will be through the Premiers’ offices. Thus instead of having the many MOUs signed with each municipal administration in the country, as has so far been feared might be the case, only nine MOUs will be signed – with Premiers’ offices. Interaction with municipalities will be at the level of service level agreements. The MOU sets out the terms of collaboration between Stats SA and the Gauteng government ensuring that interventions will make difference in people’s lives. A major strategic goal of the Gauteng Provincial Government is to be able to measure its own performance. The DirectorGeneral in the Office of the Premier, Mr Mogopodi Mokoena, remarked that this strategic partnership will go a long way in improving the quality of statistics while at the same time enhancing the monitoring processes of the Premier’s office. We now have five formal partners in the NSS - . Policy Co-ordination and Advisory Services

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(PCAS in the Presidency); the Department of Education; the Department of Science and Technology; CSIR; KwaZulu-Natal Province; and Gauteng Province. A number of departments are awaiting the signing of MOUs when their principals are available. is then assessed against all the relevant indicators and ranked on a four-point scale for its suitability to become an official statistic or an acceptable statistic, or if it is only a poor statistic or a questionable statistic. The results from all the SASQAF indicators are then combined to determine whether the candidate statistic is ready to be an official statistic, or if it is acceptable, poor or questionable. It is not sufficient to produce only an absolute measure for each SASQAF indicator, of course – it is essential that these be accompanied by metadata, describing how the candidate statistic measured up to each SASQAF indicator. SASQAF will first be tested internally in Stats SA, and the Data Management and Information Delivery (DMID) project and the Methodology and Standards Component are running the process of determining how SASQAF will be applied to each of the surveys executed by Stats SA. SASQAF will then be tested with our partners in the NSS on selected data sets. To date, SASQAF has focused on official statistics produced from Stats SA surveys and censuses, and we are now looking at what indicators need to be added to SASQAF to deal with other official statistics, particularly those derived from administrative data. An example of a source of administrative data is the registration of births and deaths available at Home Affairs. SASQAF should also cater for other products, such as statistical indicators (particularly for the Millennium Development Goals), registers and the questions used in survey questionnaires. SASQAF is currently a draft document. For more information on SAQAF or to become involved in its development and testing, please contact us at the NSSD. Cross-sectional publications at Stats SA Donald Masasanya, Manager, Publishing, Printing and Distribution, Statistics South Africa The Publishing component at Statistics South Africa is responsible for the compilation of three cross-sectional publications, namely, Stats in Brief, The Bulletin of Statistics and South African Statistics. Stats SA produces on average 20 statistical releases per month that are subjectspecific. The cross-sectional publications are therefore compiled to provide the general user with a broader view of the country’s statistics by

Partners Corner
South African Statistical Quality Assessment Standards Framework (SASQAF) – Marius Cronje, Manager, Data Management and Information Delivery Project, Statistics South Africa, and Antony Cooper, Operating Unit Fellow, CSIR Δ

Antony Cooper is an expert on standards from CSIR, supporting Stats SA with development of standards

Work on the South African Statistical Quality Assessment Framework (SASQAF) continues. SASQAF provides the framework for regulating statistical series as official statistics in accordance with the requirements of the Statistics Act (No. 6 of 1999). SASQAF provides a comprehensive set of indicators for assessing the eight quality dimensions for official statistics: relevance, accuracy, timeliness, accessibility, interpretability, coherence, methodological soundness, and integrity. SASQAF also includes prerequisites for these dimensions, covering the legal and institutional environments, privacy, confidentiality and the resources available to produce official statistics. Each candidate for becoming an official statistic
Δ

Editors’ note: One of the major contributions to the NSS by Stats SA is the development and coordination of standards; hence the development of SASQAF.

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each of these publications, aimed at a specific audience and released at different time intervals. have been produced for over twenty (20) years; their level of use; their usefulness and shortcomings; and the layout formats most preferred by users. The outcome A large proportion of users of The Bulletin of Statistics and The Bulletin of Statistics use these publications on a weekly and monthly basis to find the latest statistical information they use for policy-making and decision-making. Responses on Stats in Brief indicated that the publication is popular with users, receiving the highest number of respondents corresponding with its wide distribution.
Donald Masasanya

What are these publications? Stats in Brief is an annual publication presenting statistical information from Stats SA and other sources in a handy pocket size booklet. It is aimed at a general readership which includes students, educators and learners at schools, tourists and general members of the public. It covers annual data sourced from Stats SA publications released a year prior to the date of publication. South African Statistics is an annual single volume, displaying comprehensive time series statistical information on important facets of South African life. This publication includes historical tables in which data are presented from as early as 1920, to the period before the publication date. It is used as a reference source for research purposes and is used mainly by researchers, academics and policymakers. The Bulletin of Statistics is a quarterly reference source which provides statistics in the form of short-term statistics on a month-by-month, quarter-by-quarter and year-by-year basis. It contains annual figures for the two-year period prior to the year of publication, and monthly and/or quarterly figures for the second of these two years, as well as monthly figures, if available, of the year immediately prior to the publication date. It is also targeted at researchers, academics and policy makers. Why the cross-sectional survey? In line with the vision of Stats SA to be the preferred supplier of quality statistics, the survey was aimed at reviewing these publications in order to establish: their relevance, since they

Although a large proportion of respondents have access to the web, about half the respondents of all three publications still prefer accessing the data on hard copy and the need to continue presenting data in this format is still valid. This is in addition to the provisions made within the organisation to make electronic data available on request in the format most preferred by users to supplement the publishing of all publications at release time on StatsOnLine, the Stats SA website. Concerns on the type of data presented in the three publications have been raised, largely in response to data that is not collected directly by Stats SA. The bulk of the data used to compile the three publications is sourced from published statistical releases and reports from Stats SA. There was a need expressed by respondents to provide more data on education and health. The National Statistics System division (NSSD), whose brief, amongst other things, is to coordinate the production of official statistics, has been consulted and would be assisting in informing the content of these publications through their consultative approach in designating statistics produced by other organs of state as official. Through this collaboration and the involvement of other organs of government through the NSS, we hope to improve on the content we currently provide in the three publications.

Governance of the NSS
As the Statistician-General rolls out the NSS outside the boundaries of Stats SA, definition of an effective governance structure becomes a priority. This is as it should be as Stats SA is a partner in the NSS albeit its having been given

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the mandate to drive the development and implementation of the process. In this edition we explore one of the elements of a proposed governance structure – statistical units in departments. Production of national statistics is based on the first principle of the NSS - that the various organs of state will themselves be directly producing statistics within the contexts of their mandates. In this respect Stats SA will be responsible for producing statistics primarily for measuring outcomes of policies, programmes and projects; for developing and coordinating standards; and for organising for building capacity in departments. At the moment there is very little statistical capacity in most departments; and demand on Statistics South Africa to provide such services has become increasingly overwhelming, given the capacity constraints in the department. It is thus very important for statistics units to be deliberately established in departments, and for departments to plan for training programmes in statistical literacy. Departmental Statistical Units will perform three main functions: (1) to guide and manage the production and dissemination of statistics in their respective departments; (2) to implement SASQAF in their respective departments; and (3) to work jointly with Stats SA to improve the quality of the statistics of their departments. There are three models to choose from in establishing statistics units in departments. Model One is the line function model whereby statisticians are appointed by the departments and the unit is treated as a line function unit like any other component in the department. This is a laissez faire model. Model Two is a Statistics South Africa cadre of statisticians appointed by and accountable to Stats SA; they are seconded to departments; and they report to the Stats SA on subject-matter issues and to the head of the department in which they are posted on line function issues. In practice they would technically belong to Stats SA, on which they would depend for their remuneration and career path. Model Three is a national cadre of statisticians whereby the statistical staff would not be members of Stats SA, but would be members of a national statistical service of which the Statistician-General would be the professional head by being in charge of professional standards and conduct. In this respect the statisticians would meet set standards against which they would be certified. In this instance every statistician in the NSS would be bound by the same standards and protocols which the Statistician-General would enforce. Departmental statisticians would be directly recruited and would belong to their departments, but the Statistician-General would retain professional standards both over the statisticians and the departments (Strode 2005). There are advantages and disadvantages to each model. The line function model is easier on management issues but is most likely to have a negative impact on integrity and timeliness of data. The staff would expectedly be loyal to the head of their department and are likely to go along with the head’s decisions on the quality of data and their release. If the data do not tell a particularly good story the chances that they may be manipulated and delayed for release are quite high. Even when the data are of poor quality, the department may well not be disposed to exposing its weaknesses. On the other hand, Statistics South Africa cadre of statisticians seconded to different departments is relatively difficult to coordinate. They may also find it difficult to be effective as they might not be fully accepted and integrated into the departments. They may be seen as policing the departments. However, they would be an effective means to ensure integrity and timeliness as they are accountable to Stats SA where there already are systems in place to ensure compliance with the two quality dimensions. The third model, a national cadre of statisticians, would have Stats SA possibly losing some of its staff to other departments, although a deliberate statistical capacity building programme would be a mitigating factor. However, the model would have the advantage of staff belonging to departments and thus being effective. And because of their professional accountability to the Statistician-General, they would facilitate integrity and timeliness. The current statistical environment tends to encourage a national cadre of statisticians. In this context the concept of “statistician” widely refers to individuals with the necessary skills to produce the desired statistical products. Such skills range from compiling administrative records and registers, through classifications and executing surveys, to management of large datasets, analysis and report writing. The head of the departmental statistical unit would be a departmental statistician that would be

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accountable to the Statistician-General on professional matters and be responsible for implementing SASQAF and the various provisions of the Terms of Engagement. Let’s get suggestions on the proposal. Contact: Queries, comments or suggestions may be directed to Khuli Kunene, e-mail address: khulik@statssa.gov.za

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