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Omer Faruk Akbal
,
Mr. Seung M Choi
,
Mr. Futoshi Narita
, and
Jiaxiong Yao
Quarterly GDP statistics facilitate timely economic assessment, but the availability of such data are limited for more than 60 developing economies, including about 20 countries in sub-Saharan Africa as well as more than two-thirds of fragile and conflict-affected states. To address this limited data availablity, this paper proposes a panel approach that utilizes a statistical relationship estimated from countries where data are available, to estimate quarterly GDP statistics for countries that do not publish such statistics by leveraging the indicators readily available for many countries. This framework demonstrates potential, especially when applied for similar country groups, and could provide valuable real-time insights into economic conditions supported by empirical evidence.
Brandon Buell
,
Reda Cherif
,
Carissa Chen
,
Jiawen Tang
, and
Nils Wendt
The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.
Tim Maurer
and
Arthur Nelson

In February 2016, hackers targeted the central bank of Bangladesh and exploited vulnerabilities in SWIFT, the global financial system’s main electronic payment messaging system, trying to steal $1 billion. While most transactions were blocked, $101 million still disappeared. The heist was a wake-up call for the finance world that systemic cyber risks in the financial system had been severely underestimated.

International Monetary Fund. Statistics Dept.

Abstract

The 2018 Annual Report of the IMF Committee on Balance of Payments Statistics provides an overview of trends in global balance of payments statistics.

Lisbeth Rivas
and
Mr. Joe Crowley
Statistical agencies worldwide are increasingly turning to new data sources, including administrative data, to improve statistical coverage. Administrative data can significantly enhance the quality of national statistics and produce synergies with tax administration and other government agencies, supporting better decision making, policy advice, and economic performance. Compared to economic censuses and business surveys, administrative data are less burdensome to collect and produce more timely, detailed, and accurate data with better coverage. This paper specifically explores the use of value added tax and income tax records to enhance the compilation of national accounts statistics.
International Monetary Fund. Fiscal Affairs Dept.
This Technical Assistance Report discusses the initiation of the stock-taking of the public investment program in Uganda. This stock-taking will provide a basis for better budgeting by providing information on the existing multi-year project commitments, and the incremental recurrent costs for operation and maintenance of the assets delivered. It will also identify a basic information structure for each project and subsequently collect a data baseline, providing a foundation for more robust project monitoring. It will aid the management of the overall project portfolio. By identifying the scale of existing multi-annual commitments, it will avoid adding projects to the investment pipeline, which cannot be financed under the Medium Term Expenditure Framework.