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.
This paper investigates the response of consumer price inflation to changes in domestic fuel prices, looking at the different categories of the overall consumer price index (CPI). We then combine household survey data with the CPI components to construct a CPI index for the poorest and richest income quintiles with the view to assess the distributional impact of the pass-through. To undertake this analysis, the paper provides an update to the Global Monthly Retail Fuel Price Database, expanding the product coverage to premium and regular fuels, the time dimension to December 2020, and the sample to 190 countries. Three key findings stand out. First, the response of inflation to gasoline price shocks is smaller, but more persistent and broad-based in developing economies than in advanced economies. Second, we show that past studies using crude oil prices instead of retail fuel prices to estimate the pass-through to inflation significantly underestimate it. Third, while the purchasing power of all households declines as fuel prices increase, the distributional impact is progressive. But the progressivity phases out within 6 months after the shock in advanced economies, whereas it persists beyond a year in developing countries.
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.
There has been a global push to decrease the cost of remittances since at least 2009, which has culminated with its inclusion in the Sustainable Development Goals in 2015. Despite this effort and the emergence of new business models, remittance costs have been decreasing very slowly, disproving predictions that sharp declines would be just around the corner. In addition, remitting to poorer countries remains very expensive. Oddly, this situation has not been able to elicit academic interest on the drivers of remittance costs. This paper delved deeply into the remittances ecosystem and found a very complex, heterogenous and unequal environment, one in which costs are driven by a myriad of factors and where there are no easy and quick solutions available, which explains the disappointing outcome so far. Nonetheless, it also shows that while policymakers have limited room to act they still have a very important role to play.
The Global Informal Workforce is a fresh look at the informal economy around the world and its impact on the macroeconomy. The book covers interactions between the informal economy, labor and product markets, gender equality, fiscal institutions and outcomes, social protection, and financial inclusion. Informality is a widespread and persistent phenomenon that affects how fast economies can grow, develop, and provide decent economic opportunities for their populations. The COVID-19 pandemic has helped to uncover the vulnerabilities of the informal workforce.
Mr. Amine Mati, Ms. Monique Newiak, and James Wilson
This paper focuses on identifying potential asymmetric responses of non-commodity output growth in times of positive and negative commodity terms-of-trade shocks. Using a sample of 27 oil-exporting countries and a panel VAR method, the study finds: 1) the short-and medium-run response of real non-commodity GDP growth is larger for negative shocks than positive shocks; 2) this asymmetry is more pronounced in countries with weak pre-existing fundamentals–high levels of public debt and low levels of international reserves–which also serve to amplify the volatility of the response; 3) the output response to positive shocks is stronger following a sustained period of CTOT increases, while the impact of negative shocks on output are more damaging when they occur after a period of CTOT decline.
The coronavirus (COVID-19) crisis, which has hit financial systems across Africa, is likely to deteriorate banks’ balance sheets. The largest threat to banks pertains to their loan portfolios, since many borrowers have faced a sharp collapse in their income, and therefore have difficulty repaying their obligations as they come due. This could lead to a sharp increase in nonperforming loans (NPLs) in the short to medium term.
In recent years, we have observed an increase in low-income countries’ (LICs) access to international capital markets, especially after the Global Financial Crisis (GFC). This paper investigates what factors—country-specific macroeconomic fundamentals and/or external variables—have contributed to the surge in external bond issuance by these LICs, which we refer to in our paper as ‘frontier economies’. Using data on public and publicly guaranteed (PPG) external bond issuance, outstanding PPG bond stock, as well as sovereign spreads, we employ panel data analysis to examine factors related to the increase in issuance by these economies as well as the reduction in their spreads over time. Our empirical study shows that both country-specific fundamentals (such as public debt, current account balance, level of reserves, quality of institutions) and external variables (such as US growth and the VIX index) play a role in explaining the increased amount of issuance and the decline in spreads of frontier economies’ sovereign bonds. The impact of some of these variables on issuance appears to reflect a country’s need to issue bonds for external financing (‘the supply side’ of bond issuance), while others appear to correlate more through their impact on investors’ appetite for a country’s debt (‘the demand side’). In addition, the impact of country-specific variables can also be affected by external factors such as global risk appetite. Our analysis of key factors that have contributed to increased market access for frontier economies over the past decade provides important information to gauge the prospects for their continued market access, and for other LICs to join this group by tapping international markets for the first time.
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.