Statistical challenges for African central banks. Mohamed Taamouti Bank Al-Maghrib, Rabat, Morocco

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1 Statistical challenges for African central banks Mohamed Taamouti Bank Al-Maghrib, Rabat, Morocco Laila Dahbi Bank Al-Maghrib, Rabat, Morocco Preliminary draft Abstract In recent years, central banks had to face one of the major financial and economic crises since the great recession of the thirties of the last century. The heavy consequences of this crisis and the inability of the monetary and economic authorities to prevent it brought to light the issue of the reliability of the forecasting and analysis tools but also the availability of data. The debate that followed resulted in several initiatives launched by central banks and statistical offices starting from diagnosis exercises and ending in several cases with major upgrades of national statistical systems. In emerging and developing economies and in African countries in particular, in addition to the challenge posed by the crisis, many central banks started to align their practices and approaches with international standards, particularly in terms of monetary policy, bank supervision and financial stability. This translated into a major increase in data needs and hence in data collection, processing and utilization. Despite these efforts, many difficulties and challenges persist and are linked to the institutional environment, the structure of the economy often characterized by a large informal sector, the vulnerability of the productive fabric, the weak financial development and the high rates of economic illiteracy. The paper reviews the main developments of African statistical systems as well as major statistical challenges faced by African central banks in conducting monetary policy and monitoring financial stability. Keywords: statistical system; central bank; national statistical office; capacity building. 1. Introduction Nowadays, economic decision-making relies heavily on evidence-based approaches and hence requires the availability of reliable and timely data. The financial crisis of 2008 has revealed multiple data gaps and new needs have emerged since then. In this extent, the statistical community, whether national statistical offices, central banks or other statistics producers have taken several initiatives to overcome the new challenges and improve their production processes for a better and more consistent decision making. At the African level, in addition to the challenges triggered by the financial crisis, national statistical systems still face structural problems related to the institutional environment, the structure of the economy often characterized by a relatively large size of the informal sector, a vulnerable productive fabric and weak financial development. After a brief presentation of the data gaps revealed by the latest financial crisis, this paper reviews the different initiatives engaged by African countries to improve their statistics and discusses some important challenges faced by African central banks in conducting their missions. 2. Statistics production in the aftermath of the financial crisis Statistics production has experienced a significant progress during the past few decades. A simple look at some international databases shows how much data is available for decision-making. Despite this 1

2 progress, the 2008 crisis has revealed that some data gaps remain. Crises have, as a matter of fact, always been a triggering point of statistics production. The crisis in Latin America in the mid-1990s warned the international community of the necessity to improve data availability to be able to react to a financial crisis, which led, among other things, to the set up in 1996 of the Special Data Dissemination Standard (SDDS) and the General Data Dissemination System (GDDS) in The most recent financial crisis has also uncovered some data gaps especially on the financial sector and its key vulnerabilities relevant for financial stability analysis. Thus, reducing these gaps requires the production of a wide range of economic and financial statistics and hence a well-developed statistical infrastructure based on an effective and efficient data collection, compilation and dissemination. For central banks, heavy consumers and producers of statistics, the challenges were even greater. As a matter of fact, the financial crisis has put more pressure on the production of financial statistics, which is in general among responsibilities of central banks. In response to the revealed data gaps, a large number of central banks, particularly in developed countries, implemented numerous initiatives in line with the G20 recommendations. The objective is to better capture the build-up of risks in the financial sector, to improve data on financial linkages both domestically and cross-border and to monitor the vulnerability of the domestic economy to shocks. For instance, at the European level, several initiatives were taken to achieve a better integration of the different sources of information and to improve greater granularity and flexibility in datasets based on micro-databases and registers. It led to the collection of more data consolidated at the level of banking groups and insurance groups and more statistics to monitor unregulated financial institutions and markets. 3. Statistical development in Africa The weaknesses of African statistical systems are structural. As a matter of fact, various assessments of statistical capacity in Africa show that the irregularity or lack of investment in statistical capacity development has made statistical systems weak and under-resourced in several countries. As a consequence, weak, sometimes inexistent, statistical information has always been one of the main reasons of having weak-designed and implemented policies in a number of economies. Difficulties faced by statistical producers in the African continent are linked, particularly, to weak institutional frameworks and in some cases insecurity that had a negative impact on ground data collection. The National Statistical Offices (NSOs), the backbone of statistical production, suffered mainly from lack of autonomy and weak financial and human resources and technical skills. For instance, out of the 54 member countries of the African Union, only 12 are considered to have an autonomous NSO according to Regional Strategic Framework for Statistical Capacity Building in Africa (2010). For the remaining 42 countries, the NSO fall under the jurisdiction of another government ministry. However, recent years have witnessed a substantial increase in demand for statistics and a greater awareness in Africa of the necessity to strengthen National Statistical Systems and deliver relevant, reliable and timely official statistics. In this regard, several projects and programs were launched to develop the statistical capacity and framework of African countries (Figure 1): The Reference Regional Strategic Framework for Statistical Capacity Building in Africa (RRSF, 2006): it aims to strengthen national statistical systems by providing a framework to guide statistical development in the Regional Member Countries of the African Development Bank. It focuses on strategic directions and appropriate implementation instruments to improve the planning, financing, management and coordination of statistical development activities to meet demand for statistics. It is built around three pillars: meeting users needs, improving the management of statistics systems and ensuring the sustainability and irreversibility of statistics development in Africa. The International Comparison Program for Africa (ICP-Africa): launched in 2002, by the African development bank, it is a global statistical initiative aimed at generating purchasing 2

3 power parity estimates that facilitate cross-country comparisons of price levels, and economic aggregates in real terms. Two rounds of data collection were undertaken, in 2005 and 2011, an interim comparison of Household Consumption Expenditure in 2009, leading to comparative output, consumption, income and price level data for 50 African countries. African Charter on Statistics Scope: initiated in 2009, it provides a policy framework for statistical development in the African continent, setting out guiding principles related to professional independence, mandate for data collection and resources, quality and dissemination of statistics, protection of individual data, and to coordination and cooperation. The Charter has only entered into force in 2014 after 16 African Union Member States endorsed it. Strategy for the Harmonization of Statistics in Africa (SHaSA): This strategy was initiated in 2010 to improve the capacity and integration of the African statistical system. It is based on four pillars: i) produce quality statistics for Africa, by expanding the statistical information base, transforming statistics for comparability and harmonizing standards and methods of production, ii) coordinate the production of quality statistics for Africa, iii) build sustainable institutional capacity in the African statistical system, and iv) promote a culture of quality decision-making and improve the communication of statistical information. Africa Data Consensus: a strategy for implementing the data revolution in Africa, adopted in March 2015 that aims to create a new statistical landscape, opening up the field of data production and dissemination to state and non-state actors. Figure 1: Timeline of initiatives to improve statistical capacity in Africa Source: Strength in numbers: Africa s data revolution (2016), Research Team of African foundation Mo Ibrahim Foundation. Despite these several initiatives, improvement in statistics in Africa remains relatively sluggish, the focus was more on elaborating strategies than implementing them. National Strategies for the 3

4 Development of Statistics (NSDS) elaborated by many countries have been found too ambitious and unrealizable in view of the available resources. The World Bank Statistical framework 1 for developing countries shows that overall score for the African countries, despite its improvement in the period between 2008 and 2016, remains among the lowest compared to other regions. In terms of transparency and dissemination, the Informing a Data Revolution (IDR) metabase 2 identified, in 2014, that 4 of the 54 African countries are still not GDDS subscribers, while only 5 are SDDS subscribers. Moreover, it indicates that data accessibility and availability is still an issue in Africa, 15% of NSOs do not have an official website and 63% do not publish data in a machine-readable format. 4. Challenges faced by African central banks in the conduct of their mission Further to the relatively weak development of African statistical systems, the majority of initiatives to improve data and support building statistical framework in African countries focused primarly on social and demographic statistics. A lot of these efforts were devoted to allow the availability of necessary data to monitor the progress in the Millennium Development Goals and more recently Sustainable Development Goals as well as several other regional and international social and health programs. Relatively, little attention was given to economic statistics. For instance, in many lowincome countries in Sub-Saharan Africa, very few economic data are made available to the public on a timely and frequent basis, data like GDP are typically produced annually, unemployment figures, when they are released, it s in general with considerable delay and data related to household wealth and firms balance sheet does barely exist. In this context, central banks that have to take important economic decisions several times a year face much more than other policy makers the weak availability and reliability of economic data. Even if they are often more suitable and relatively better resourced than other governmental institutions to produce macroeconomic statistics, they cannot substitute for all other statistics producers. They have nowadays to produce more detailed and accurate monetary and financial statistics to improve their monetary policy and financial stability decisions. For this purpose, the statistical function within central banks should be given a greater attention. We examined, for the purpose of this study, the organization structure on the website of African central banks and found that, out of 42, only 50% have a statistical department or division, while 24% do not seem to have one. For the remaining banks, either they do not publish clear information about their departments or they do not publish any information at all (around 7%). This finding emphasizes the necessity for African central banks to make more efforts to improve and reinforce their statistics and information system for a better decision-making. a. Consistent inflation measure As all African central banks have price stability as the ultimate objective of monetary policy and in the context of the adoption of inflation targeting by a growing number of central banks, measuring inflation correctly and frequently is vital to achieve their goals and identify appropriate policy responses. Therefore, central banks must have or develop their ability to assess inflation and have data to distinguish between transitory and permanent factors affecting inflation. 1 The World Bank s Statistical Capacity Indicator is a composite score assessing the capacity of a country s statistical system. It is based on a diagnostic framework assessing methodology, data sources, periodicity and timeliness. Countries are scored against 25 criteria in these areas, using publicly available information and/or country input. The overall Statistical Capacity score is then being calculated as a simple average of all three area scores on a scale of Informing a Data Revolution (IDR) which is a metabase that has been developed by PARIS21 using information available from a variety of different data sources regarding the organization, management and performance of national statistical systems in developing countries. 4

5 To measure inflation, all central banks in the African continent use the variation of the Consumer Price Index (CPI). Despite the support of the African Development Bank, through its ICP Africa program, in many African countries market prices are not properly collected to produce representative CPI and many difficulties persist: Retail prices are collected only in major urban cities while rural areas constitute a majority of the population. Compared to other low and middle income countries, the proportion of missing prices or those collected only in main cities is relatively high (Figure 2). Weights used for CPI calculation and the base year are often outdated. Those weights typically come from budget share estimates from household surveys. According to International Labor Organization metadata, in July 2012 CPI basket of 13% of the African population dated from the 1990s or earlier and additional 11% had missing information (Figure 3). The international standard is to update the base year at least every five years. According to IDR metabase, 30% of African countries have a CPI base date prior to 1999 and 63% a base year between 2000 and Figure 2: Collection of retail prices by area Figure 3: Base year of CPI basket Source: ILO, 2013 Source: ILO, 2013 b. Other macroeconomic aggregates measurement and availability In their monitoring of the business cycle and preparation of economic projections, central banks rely on the availability of a whole set of data on a large number of aggregates. Despite a significant progress data availability and reliability, the availability of some of the main aggregates remains well insufficient in many African countries. Gross Domestic Product: According to the IDR metabase, 65% of African countries use the 1993 System of National Accounts (SNA) and only 2 use the 2008 SNA. The frequency of the production of national accounts represents also a substantial challenge for African central banks since monetary policy decisions are often made on quarterly basis while it turns out that 76% of the countries produce GDP estimates on an annual basis and disseminate it with a considerable delay. Another major problem that is specific to developing countries, in general, is the preponderance of the informal sector, which activity is very difficult to measure and value accurately. Moreover, in many African countries, the GDP base year is relatively old, which biases estimates of the relative size of the economy and the pace at which it grows. WDI data indicates that 43% of African countries have a base year prior to The most striking examples are the rebasing of GDP in Ghana and Nigeria. In the case of Ghana, GDP estimate was uplifted by 60% as a result of an update in the base year from 1993 to For Nigeria, the new 5

6 estimation of GDP in 2014, following the change in base year from 1990 to 2010, revealed that the Nigerian economy was 59,5% larger than previously estimated. Labor market figures: It s very hard to get a legitimate handle on the development of labour market indicators in most of African countries. In fact, when examining the Macroeconomic and Financial Metadata of the IMF and some NSOs websites, it appears that only 25% of African countries 3 produce indicators on labor market on a quarterly basis, 45% on an annual basis while nearly 12% seems not to have a periodicity. Our review showed also that 20% conduct a labor force survey every ten years and only 6% conducted it at an annual basis, while the rest do not have a regular frequency. Trade Statistics: for some African countries, providing timely and comparable merchandise trade statistics has often been difficult because of their lack of regular reporting of consistent and comparable data over time and across countries based on international standards and guidelines. In addition, many countries suffer from inaccuracies of quantities and values of import and export data as well as balance of payments figures. A major reason for this is the poor trade recording system by their Customs Services and a huge proportion of informal border trade transactions that are not sufficiently captured. c. Data availability to assess financial inclusion and monitor financial stability When it comes to data on access to finance, on SMEs financing or on the utilization and quality of financial services and financial infrastructure many challenges remain too. As most of statistics in that regard are rough and irregular estimates, they do not allow for a meaningful assessment of policy implementation. The emergence these last years of financial stability as a mission of central banks translated into new data needs that are more difficult to satisfy. As a matter of fact, monitoring financial stability requires rich information on developments in financial and real estate markets, credit, debt and funding patterns. At the level of African countries, the wide absence of granular data, the inadequacy of data on financial sector accounts, microeconomic data on firms balance sheet, household wealth and the housing market are among the main challenges facing central banks. Furthermore, there is an important gap in coverage of financial statistics that are limited most of the time to the banking sector. There s also a lack of credit registers, which are an important source of information on loans provided to the economy than can be a valuable asset for both monetary policy and financial stability. Information on interconnectedness between international financial institutions, common exposures and exposure concentration will also be needed given the expansion of cross-border banking in Africa. Nearly ten African banks have a presence in at least 10 countries on the continent and one is present in more than 30 countries. To analyze the availability of these types of data at the level of African countries, we examined the number of countries reporting the financial soundness indicators (FSI). It turns out that, although it is increasing, the number of African countries reporting FSI is still limited to 16, which means that FSI aren t available in almost 70% of the African countries. 3 Out of 54 African countries, information was available for 33 countries only. 6

7 Figure 3: Financial soundness indicators: reporting economies Source: IMF s FSI website. 5. Conclusions Despite the progress made by many African countries to develop their statistical systems and strengthen their quality and reliability, many challenges remain. African countries should, indeed, put on more efforts to establish efficient statistical governance that will mainly help them promote the production of economic and social statistics, enhance cooperation between the various producers, harmonize statistical methodologies and improve coherence between official statistics. Furthermore, more regular resources should be allocated to guarantee a large and regular data production. Central banks in particular are among policy makers that suffer the most from the weak availability of statistics. In view of their relatively frequent and heavily data consuming decision-making mainly in monetary policy, they face the lack of reliable economic data on many key indicators upon which they base their decisions. They should first strengthen coordination with other statistics producers to have access to a valuable data. As statistics producer, African central banks should invest in strong framework of data collection in monetary and financial spheres. As credibility is the greatest asset of central banks, they also need to be more transparent about the statistics they produce and disseminate on a regular basis the statistics used in the analytical framework of monetary policy or financial stability. Finally, a greater and better support from international organizations should accelerate the pace of the development of statistical systems in Africa. As a matter of fact, specific technical assistance and welltargeted initiatives for African countries in particular would help them overcome the main challenges in data production and dissemination. 7

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