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International Monetary Fund. African Dept.
This Selected Issues Paper analyzes potential macro-financial risks from cross-sectoral exposures in Uganda by leveraging on the Balance Sheet Approach framework. It presents evidence on the macro-financial linkages in Uganda using the Network Map and Financial Input-Output approaches. On the one hand, the Network Map analysis shows the cross-sectoral exposures in which potential build-up of macro-financial vulnerabilities may arise. On the other hand, the Financial Input-Output tool simulates relevant scenarios in the context of Ugandan economy such as currency depreciation and increases in government interest payments on debt held by banks. The purpose of the scenario exercises is to strengthen the monitoring of the developments in key economic sectors in Uganda. While the banking sector, which dominates the Ugandan financial system, remains fundamentally sound, there are pockets of vulnerabilities resulting from the growing sovereign-bank nexus and cross-border exposures of the Near Field Communication technology sector which require close vigilance.
International Monetary Fund. African Dept.
This Selected Issues paper examines tax policy and administrative changes in Eastern African Community (EAC) countries with a view to benchmark Kenya’s experience and draw lessons for future tax reforms. Using granular data from a new IMF database on tax measures announced during 1988–2022, it concludes that EAC policymakers frequently changed their tax system and administrations by announcing tax packages that typically consisted of measures to narrow the tax base and strengthen tax administrative practices. Kenya appeared to be one of the EAC countries that most frequently announced and introduced such changes, which might have played a significant role in explaining the reduction in the tax-to-gross domestic product ratio experienced by the country since 2014. The conclusions of this note are subject to caveats, as the frequency of tax measures is not an indicator of the actual revenue impact of such measures. Looking at the frequency of changes, however, can help identify reform episodes providing a sense of their duration and comprehensiveness.
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.