The data collection mechanisms and the statistical databases

The data collection mechanisms and the statistical databases of ECA Sub-Regional Office of North Africa SRO-NA: The present and the future Introduction SROs by their positioning represent linkages between ECA and its clients, the country members and their respective RECs. SRO-NA as one of ECA arms collaborates with ECA/ ACS and frames its activities of data collection, data dissemination and data use according to this positioning. Recently ECA/ACS installed website statistical database at SRO-NA that reinforced this positioning in addition to its original database.

Continue (introduction) � Moreover, ECA/ACS has entered the stage in which it is due to install a customized version of their main live statistical database at UMA, to meet the special needs of that ECR. With the full implementation of this stage, SRO-NA will completely and efficiently perform its role in linking indirectly ECA with its target member states in quality data collection and data usage through UMA. This report briefly describes the statistical and data management activities of SRO-NA , examines specific data collection issues including challenges, mode and methods of data collection, outlines data manipulation, and explores the vision for a better future.

• . A. The main statistical and data management activities delivered by SRO-NA � i). The status of support to North African countries � Among the main primary functions of SROs is to liaise ECA and the governments at the sub regional level. In this regards the RSOs assist in organizing activities aimed at building institutional capacities as well as to coordinate with ECA to provide advisory services at the request of the country members. � There are seven countries under the umbrella of SRO-NA, namely Algeria, Egypt, Libya, Mauritania, Morocco, Sudan and Tunisia. Egypt, Libya and Sudan mapped under the Anglophone while the rest of the member states are mapped under the Francophone. � SRO-NA in coordination with ECA/ACS, are now engaging to build the statistical infrastructure to UMA, a statistical database platform that customized to meet the special needs of UMA. The platform will not only access quality data at the country level, but in addition will encourage the member states to contribute efficiently in the process of collecting reliable data sets and in producing integrated and harmonized statistical information � Hence the SRO-NA could ultimately support the capacity building at the country level in collaboration with UMA on one hand coordinating with ECA-ACS on the other hand.

A. The main statistical and data management activities delivered by SRO-NA (Continue) � ii) SRO-NA and the scope of its data sets � The Office focuses on a broad coverage of datasets ranging from demographic and social data sets to economic statistic and environment datasets � Specifically, the collected data comprises Trade Statistics with emphasis on intra trade, National Accounts, Public Finance, Prices, Main macroeconomic aggregates, Tourism, Transport , Communications (information society) Money and Banking (monetary indicators), Environment, Agriculture; Energy and Industry ( real sector), Education, Health and Demographic indicators as well as social indicators including employment and MDGs. All these datasets are needed for the Office reporting activities.

A. The main statistical and data management activities delivered by SRO-NA (Continue) � iii) Publications � Annually, we update one page sheet (North Africa in Figures) which covers main demographic indicators, macroeconomic aggregates (GDP, Exchange rate and inflation) Public Finance indicators and Foreign Trade indicators. � The Office also intended to produce an annual pocketbook to be distributed at the ICE meeting, the 2011 booklet will be devoted to extracted MDGs indicators for each of the member states with an estimate figures to North Africa region � Iv) Legal framework in data collection and working groups � In our annual survey questionnaire, usually we request secondary and administrative data from official departments and institutions, For example Ministry of Finance or National Bureau of Statistics, thus it is rather a gentleman agreement than a mandate, although as recommended by the ICE in the 2008 meeting at Rabat the member states to provide relevant data to prepare the annual report on economic and social conditions in North Africa. The survey mainly designed to provide such data for the annual reports � SRO-NA not yet established a formal working group, though the Office has focal point team to coordinate with data management group within ACS. In practice, , only collaborative contacts with the national bureau of statistics, ministries of Finance and central banks at country level mainly to assist in filling the annual questionnaire and UMA as REC as framed with Office Business Plan. ( for example in regional integration, statistical database ) �

B. On Data Collection Issues � i) Addressing the challenges in processing the questionnaire � The following Table provides a list of the member states under the zone of SRO-NA as well as it summarizes the type of data need to be collected from them , the challenges arise and how to address these challenges in the process of data collection

Table (1): Type of data collected and challenges facing SRO-NA Type of Data 1)Macroeconomic aggregates Countries Challenges Algeria No challenge Egypt No serious challenge Why Proposed response to the challenge 2)Trade Statistics ( Esp. intra trade only merchandized published by UNCTAD) 3)National Accounts 4) Public Finance 5) distinction in Investment ( public and private) 6)Agriculture, Energy and industry 7)Tourism ( revenue) 8)Employment statistics 9)Health and education ( rural urban and gender classification) 10)MDGs Libya Challenge The use of fiscal year rather than the calendar year No response to the questionnaire Rare availability of other data sources Technical support including priority in installation of ECA basic statistical database at the National Bureau of statistics and training staff

Table (1): Type of data collected and challenges facing SRO-NA ( continue) Type of Data 1)Macroeconomic aggregates Countries Mauritania Challenges Challenge Morocco No challenge Sudan Challenge 2)Trade Statistics ( Esp. intra trade only merchandized published by UNCTAD) 3)National Accounts Why No response to the questionnaire The alternative data sources are not exhaustive Proposed response to the challenge Technical support including priority in installation of ECA basic statistical database To coordinate the scattered data at various departments 4) Public Finance 5) distinction in Investment ( public and private) 6)Agriculture, Energy and industry 7)Tourism ( revenue) 8)Employment statistics 9)Health and education ( rural urban and gender classification) 10)MDGs Tunisia No Challenge No response to the questionnaire. The alternative data sources are not exhaustive Technical support, including priority in installation of ECA basic statistical database to coordinate the scattered data at various departments

B. On Data Collection Issues Continue) � ii) Favorable responses � As countries vary in their statistical capacities, accordingly the response to SRO-NA survey varies. Some countries have already built an update websites that provide both statistical data and other data resources. On the other hand, some countries need technical assistance both instructional and human resources to build their statistical capacities � Iii) Type of data sources and the mode of data collection in the field � Usually the data is housed in different departments, for example in the Central Bank, in the Ministry of Finance, Ministry of social affairs, the National Office of statistics , just to mention a few. We channel the survey through the Ministry of Foreign Affairs requesting its distribution, with a further copy to the focal point for the follow up. Therefore most of the data reported is administrative data already provided by the officials in their respective offices

B. On Data Collection Issues (Continue) � Iv) Methods of Data collection � a)Data’s missions and incentives to focal points � Currently, payment to the focal points is not yet introduced for their follow up activities at the country level. The only incentive is a word of thanks. However the office sends missions on data collection usually is to collect published reports not accessible to the Office that complement and/or validate the data collected through the questionnaire. Such reports normally contain both quantitative as well as qualitative data. Moreover, the deliberations with the country’s officials, usually result in collecting a further sets of data that may not be at the stage of dissemination � We have an annual questionnaire designed to collect data on the annual report of the economic and social conditions in North Africa as well as other related activities as mapped in the office business plan and work program.

B. On Data Collection Issues (Continue) � The questionnaire addresses each country in its own. Most of the tables are common to all the countries, unified nature, in the sense that the same question is asked to each country, though requested data that pertaining to a given country is also considered, particularly with regards to measures, policies and programs adopted or implemented. � Since we are dealing with only seven countries the exercise so far is feasible and quite practical. The format, also consider the official language of the given country (in our case an Arabic version to Libya, English version to Egypt and Sudan, French version for the remaining four member states; Algeria, Mauritania, Morocco and Tunisia)

B. On Data Collection Issues (Continue) � b) Accessibility of other websites � Although the office retrieves data from other data sources, For example, UNSD, ECA/ACS, Other UN Agencies, World Bank, IMF, governmental websites (central banks, Ministries of Finance etc. )Just to mention the most common visited sites, however most of these resources sharing one drawback which is either providing projection for the desired year or it is lacking data cell to that desired year. � On the other hand such data sources are quite useful to verify and validate some of the historical data, when there is no consistency with them and the data collected through the questionnaire. Moreover such sources help in designing the annual survey by shaping the tables that contain the requested data. Therefore, currently we view such data sources as complementary rather than a substitute to data missions

C. Revision , Estimation and dissemination of data � i) The practice is to assign first priority to official data provided by each country, when we edit the annual reports even when discrepancies occur between the country data and other sources of data. � ii) For disseminated data by another agent, e. g. (the IMF missions reports approved officially by the country), and if a dispersion with another set of data produced by the country occurs, then the revision is judged by the available historical data as well as through examination of the consistency of this data with other complementary and validating data that are consistent in the two sets of data, using simple imputation techniques � Iii) The annual survey updates annual aggregates according to theme of the year and other activities spelled in the office’s PIP.

C. Revision , Estimation and dissemination of data ( continue) � Iv)However on request of ICE meeting extra independent questionnaires may be designed and send to the member states. (E. g. in 2011 we prepared a questionnaire on monitoring agricultural policies and food security) for 2012 ICE meeting. � v) On the activity of update of the Office database from other data sources for instance websites, we retrieve the desired data cells in a non systematic pattern depending on time availability. � With regards to modeled data and data dissemination � a) We use actual data as well as estimated data generated by other agencies, as our questionnaire accommodates cells for instance actual 2010, estimated for 2011 and projection for 2012. We leave this exercise of providing estimate and projection to the country as data provider. After the ICE meeting we insert only actual data at the office database

C. Revision , Estimation and dissemination of data ( continue) � b)We have not yet generate data using a software, however if the country failed to provide estimate and/or projection , we retrieve such data from other published sources including other UN agencies, International Organizations such as the World Bank and IMF and refers to the sour/s in the published reports. � c) However it is the home work of the Office to calculate weighted aggregates including projection from the data set of the seven country members to arrive to figures that represent the whole of North Africa

D. Data collection initiatives: The Way ahead for live and main reference statistical database � a)Collaboration advisory services and learned lessons: � i)Currently we are collaborating with ECA/ACS in an ongoing project of data collection (The data management platform) on which the piloting phase has already been completed, during which this platform was installed at the Office premises. � ii) ECA/ACS is now working to customize an Arabic version of this platform to meet the special needs of UMA and due to install it at UMA premises. �iii) The office will contribute in training the staff at UMA on how to administer and use this Arabic version of this platform to store, retrieve and disseminate statistical data that cover a wide range of indicators including (Demographic economic statistic, social and MDGs indicators)

D. Data collection initiatives: The Way ahead for live and main reference statistical database ( continue) � iv)It is quite evident the office will be part in a sustainable project that in the long run will coordinate the data collection activities at the country level, directly or indirectly through UMA � v) In the last four years, the questionnaire used to label all the countries within the same table and then send this version of tables to the country members. This design may send a confusing message to the respondent, as whether the requirement is to fill the whole table or only that pertaining to the given country. The risk of human error is also high under this design, as the tables are filled manually. � vi) Since last year each country addressed in its own with improving response rate from 17% to 54%. �

D. Data collection initiatives: The Way ahead for live and main reference statistical database ( continue) � vii)With the installation of ECA/ACS statistical platform which is accessible through the internet, the future of data collection and data dissemination seems to be quite promising in its sustainability and in its accessibility to wide spectrum of data users and broad involvement of data producers � viii) Examples of good practice the construction of some websites that provide recent data at the country level at UN agencies or accessible website constructed at country level for instance, in Egypt or Morocco and now the ongoing ECA/ACS internet data management database platform � b) With regards to the current and future situation of data collection mechanism in Africa the following drawbacks and constraints need to be addressed:

D. Data collection initiatives: The Way ahead for live and main reference statistical database ( continue) � i)Duplication of effort and lack of continental coordination are among the main drawbacks and obstacles that jeopardizing the efficient production of high quality statistical products. � ii) Lack of harmonized data also constrains and hinders comparability. The ECA/ACS is now addressing these and other related constrains. With regard to marketing Africa statistical products, the provision of SNA 2008 at the country level in collaboration with all stakeholders ( both as an infrastructure as well ECA assisting in the technical training), obviously will accelerate the process of Africa statistical capacity building despite the wide capacity gaps between the member states. � Apart from the cost of duplication of efforts both financial and time, the risk of hidden political factor is always exists and to minimize biasness or equivalently to maximize reliability or transparency, may require to lunch a systematic campaigns on statistical literacy. As it is helpful and in the interest of o the policy makers to base the decisions on reliable data regardless the indication of the reality in this regards:

D. Data collection initiatives: The Way ahead for live and main reference statistical database ( continue) � a)The degree of statistical awareness may be among the main hidden constraints in establishing such a mechanism for data collection and statistical production. The root of this constraint may go deeply to the education system and curricula design. A revisit to the education is vital and has to start at an early stage (primary education). The statistical associations have a role to play with the officials in campaigning against statistical illiteracy. � b) Financial resources (budgeting) is disparately needed for building the statistical infrastructure and to equipped the personnel with the latest innovation in the field � c) There is strong correlation between reliable data and transparency in producing quality statistics

Conclusion � 1. It is evident that the statistical and data management activities of SRO-NA flow smoothly with the view that African countries should develop a regional data collection mechanism/s. � 2. Therefore, it is a vital need to design a continental strategy for data collection that involves all stakeholders as both users and producers of such data. � 3. Indeed the ongoing project on data management platform initiated by ECA/ACS, will not only provide a continental coordinating framework that avoid the duplication of effort , but , the successful implementation of this project would associate with a substantial likelihood to provide a quality data that is timely and reliable data as it involve all the stakeholders in the process of data collection at both input and output dimensions � 4. The linking role of SROs and RECs may allow them to significantly contribute in the design and implementation of this strategy that will ultimately lead to the collection of integrated and harmonized data sets and the production of statistical products that can be marketed at the global level.

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