Africa > Uganda
E-money development has important yet theoretically ambiguous consequences for monetary policy transmission, because nonbank deposit-taking e-money issuers (EMIs) (e.g., mobile network operators) can either complement or substitute banks. Case studies of e-money regulations point to complementarity of EMIs with banks, implying that the development of e-money could deepen financial intermediation and strengthen monetary policy transmission. The issue is further explored with panel data, on both monthly (covering 21 countries) and annual (covering 47 countries) frequencies, over 2001 to 2019. We use a two-way fixed effect estimator to estimate the causal effects of e-money development on monetary policy transmission. We find that e-money development has accompanied stronger monetary policy transmission (measured by the responsiveness of interest rates to the policy rate), growth in bank deposits and credit, and efficiency gains in financial intermediation (measured by the lending-to-deposit rate spread). Evidence is more pronounced in countries where e-money development takes off in a context of limited financial inclusion. This paper highlights the potential benefits of e-money development in strengthening monetary policy transmission, especially in countries with limited financial inclusion.
This paper presents estimates of the carbon emissions of FDI from capital formation funded by FDI and the production of foreign-controlled firms. The carbon intensity of capital formation financed by FDI has trended down, driven by reductions in the carbon intensity of electricity generation. Carbon emissions from the operations of foreign-controlled firms are greater than those from their capital formation. High emission intensities were accompanied by high export intensities in mining, transport, and manufacturing. Home country policies to incentivize firms to meet strict emissions standards in both their domestic and foreign operations could be important to reducing emissions globally.
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.
I develop a model of firm-to-firm search and matching to show that the impact of falling trade costs on firm sourcing decisions and consumer welfare depends on the relative size of search externalities in domestic and international markets. These externalities can be positive if firms share information about potential matches, or negative if the market is congested. Using unique firm-to-firm transaction-level data from Uganda, I document empirical evidence consistent with positive externalities in international markets and negative externalities in domestic markets. I then build a dynamic quantitative version of the model and show that, in Uganda, a 25% reduction in trade costs led to a 3.7% increase in consumer welfare, 12% of which was due to search externalities.
The effects of debt relief on incentives to accumulate debt, consume, and invest are an important concern for donors and recipients. Using a dynamic stochastic general equilibrium model of a small open economy with a minimum consumption requirement and an endogenous relief probability, we show that excessive debt accumulation is consistent with an anticipation of a future debt relief. Simulations of the calibrated model using 1982-2006 Ugandan data suggest that debt-relief episodes are likely to have only a temporary impact on the level of debt in low-income countries, while being associated with more consumption and less invesment. The long-run debt-to-GDP ratio is estimated to be about twice as high with debt relief than without it.