Africa > Nigeria

You are looking at 1 - 10 of 28 items for :

  • Type: Journal Issue x
  • Mathematical and Quantitative Methods x
Clear All Modify Search
Karim Barhoumi, Seung Mo Choi, Tara Iyer, Jiakun Li, Franck Ouattara, Mr. Andrew J Tiffin, and Jiaxiong Yao
The COVID-19 crisis has had a tremendous economic impact for all countries. Yet, assessing the full impact of the crisis has been frequently hampered by the delayed publication of official GDP statistics in several emerging market and developing economies. This paper outlines a machine-learning framework that helps track economic activity in real time for these economies. As illustrative examples, the framework is applied to selected sub-Saharan African economies. The framework is able to provide timely information on economic activity more swiftly than official statistics.
Sebastian Horn and Mr. Futoshi Narita
Over the past two decades, many low-income developing countries have substantially increased openness towards external financing and have received large capital inflows. Using bank-level micro data, this paper finds that capital inflows have been associated with financial deepening through increases in bank loans, deposits, and wholesale funding. Domestic banks increase loans more than foreign banks. There are only modest signs of a build-up in financial vulnerabilities. Causality is examined through an instrumental variable approach and an augmented inverse-probability weighting estimator. These approaches indicate only limited evidence for global push effects, pointing towards the importance of domestic pull factors.
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.
International Monetary Fund. African Dept.
The COVID-19 pandemic is having a severe impact on São Tomé and Príncipe’s economy, exacerbating fiscal and external imbalances. Tourism activities and external remittances dropped sharply, while lockdown measures further deepened the recession. The authorities’ swift actions and unprecedented international financial support are helping the country weather the emergency. The economy began to reopen in the fall, but the outlook for 2021 remains challenging and subject to significant uncertainty.
Hans Weisfeld, Mr. Irineu E de Carvalho Filho, Mr. Fabio Comelli, Rahul Giri, Klaus-Peter Hellwig, Chengyu Huang, Fei Liu, Mrs. Sandra V Lizarazo Ruiz, Alexis Meyer-Cirkel, and Mr. Andrea F Presbitero
In recent years, Fund staff has prepared cross-country analyses of macroeconomic vulnerabilities in low-income countries, focusing on the risk of sharp declines in economic growth and of debt distress. We discuss routes to broadening this focus by adding several macroeconomic and macrofinancial vulnerability concepts. The associated early warning systems draw on advances in predictive modeling.
Hector Perez-Saiz, Mr. Jemma Dridi, Tunc Gursoy, and Mounir Bari
We propose a simple macroeconomic model with input-output sectoral linkages based on Acemoglu et al. (2016) to quantify how changes in aggregate demand due to additional income from household’s remittances propagates through the network of input-output linkages in Sub-Saharan African countries. We first propose two network centrality measures to assess the role of some sectors as key input providers in the economy. Then, we use these measures to quantify the effect of sectoral linkages on sectoral and total output following an increase in remittances inflows. Our empirical results suggest that the effects of remittances on recipient economies increase with the degree of linkages across sectors, which is especially prominent in the case of the financial intermediation sector. Our paper contributes to the emerging macroeconomic literature on the propagation of shocks across sectors and the implications for the whole economy.