Press Release No. 15/576

Press Release: Improving Short-Term Macroeconomic Data for Southern Africa Policymakers

December 18, 2015

AFRITAC South held two workshops at the facilities of the Africa Training Institute in Mauritius on high frequency indicators and on quarterly national accounts statistics, respectively, on December 7–18, 2015,

The workshops brought together national accounts compilers and macroeconomic data users from government institutions from Southern Africa. It was a unique opportunity for interagency dialogue as producers of statistics improved their understanding of users’ needs while officials from central banks and treasuries better understood the challenges of collecting and compiling high frequency macroeconomic indicators.

Dr. Lehohla, Statistician General of Statistics South Africa, highlighted the challenges of measuring rapid changes in the economy and pointed to the importance of improving data sources for the compilation of national accounts statistics. Mr. Bahadoor, Acting Director of Statistics Mauritius, added that users’ demand for these statistics has increased since the 2008 global financial crisis which had illustrated the size of data gaps. Ms. Appadu, Head of National Accounts at Statistics Mauritius, reinforced the importance of early detection of economic movements.

The seminars focused on specific data sources, compilation procedures, benchmarking and reconciliation of high frequency with lower frequency data, price and volume measures, seasonal adjustments, and dissemination as well as revision policies. IMF experts shared their expertise and country experience of implementing internationally agreed statistical standards. Participants also shared their experience of implementing international standards in the context of limited resources and scarce data sources. They identified key capacity development requirements and ways to resolve data compilation challenges.

AFRITAC South will continue to provide technical assistance and hands-on training and facilitate specialized peer-learning for the adoption of internationally recognized statistical standards.