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.
Digitalization is accelerating as countries fight against the COVID-19 pandemic. In this context, the impact of mobile phone ownership on welfare (represented by consumption) is estimated for South Africa using rich household survey data in a panel format, the National Income Dynamics Study (NIDS) with 5 waves spanning 2008–17. The literature argues mobile phone ownership facilitates greater and more affordable access to information and generate welfare gains. We attempt to disentangle the two-way relationship between consumption and mobile phone ownership, which is inherently difficult, and add to the literature by investigating distributional effects. Estimated results suggest that consumption of mobile phone owners tends to be 10–20 percent above that of non-owners. Benefits tend to accrue more on individuals with relatively low levels of consumption, potentially as a greater number of new users, likely with higher marginal positive effects on consumption, and a faster rate of user cost reduction help reap greater gains.
We test the existence of the balance sheet channel of monetary policy in a middle-income country. Firm-level data scarcity and quality, in such a context, make the identification of this channel a steep challenge. To circumvent this challenge, we use panel instrumental variables estimation with measurement error to analyze the financial statements of 58 500 Moroccan firms over the period 2010-2016. Our analysis confirms the existence of this channel. It shows that monetary policy has a significant impact on small and medium enterprises’ access to banks’ financing, and that firm-specific variables are key determinants of firms’ financing decisions.
Mr. Mario Catalan, Alexander W. Hoffmaister, and Cicilia Anggadewi Harun
This paper studies the transmission of bank capital shocks to loan supply in Indonesia. A series of theoretically founded dynamic panel data models are estimated and find nonlinear effects of capital on loan growth: the response of weaker banks to changes in their capital positions is larger than that of stronger banks. This non-linearity implies that not only the level of capital but also its distribution across banks in the financial system affects the transmission of shocks to aggregate lending. Likewise, the effects of bank recapitalization on loan growth depend on banks’ starting capital positions and the size of capital injections.
Diebold and Yilmaz (2015) recently introduced variance decomposition networks as tools for quantifying and ranking the systemic risk of individual firms. The nature of these networks and their implied rankings depend on the choice decomposition method. The standard choice is the order invariant generalized forecast error variance decomposition of Pesaran and Shin (1998). The shares of the forecast error variation, however, do not add to unity, making difficult to compare risk ratings and risks contributions at two different points in time. As a solution, this paper suggests using the Lanne-Nyberg (2016) decomposition, which shares the order invariance property. To illustrate the differences between both decomposition methods, I analyzed the global financial system during 2001 – 2016. The analysis shows that different decomposition methods yield substantially different systemic risk and vulnerability rankings. This suggests caution is warranted when using rankings and risk contributions for guiding financial regulation and economic policy.
This paper examines whether a tipping point exists for real GDP growth in Italy above which the ratio of non-performing loans (NPLs) to total loans falls significantly. Estimating a heterogeneous dynamic panel-threshold model with data on 17 Italian regions over the period 1997–2014, we provide evidence for the presence of growth-threshold effects on the NPL ratio in Italy. More specifically, we find that real GDP growth above 1.2 percent, if sustained for a number of years, is associated with a significant decline in the NPLs ratio. Achieving such growth rates requires decisively tackling long-standing structural rigidities and improving the quality of fiscal policy. Given the modest potential growth outlook, however, under which banks are likely to struggle to grow out of their NPL overhang, further policy measures are needed to put the NPL ratio on a firm downward path over the medium term.
Mr. Francesco Grigoli, Mr. Mario Mansilla, and Martín Saldías
We propose a stress testing framework of credit risk, which analyzes macro-financial linkages, generates consistent forecasts of macro-financial variables, and projects non-performing loans (NPL) on the basis of such forecasts. Economic contractions are generally associated with increases in NPL. However, despite the common assumption used in the empirical literature of homogeneous impact across banks, the strength of this relationship is often bank-specific, and imposing homogeneity may lead to over or underestimating the resilience of the financial system to macroeconomic woes. Our approach accounts for banks’ heterogeneous reaction to macro-financial shocks in a dynamic context and potential cross-sectional dependence across banks caused by common shocks. An application to Ecuador suggests that substantial heterogeneity is present and that this should be taken into account when trying to anticipate inflections in the quality of portfolio.
The crisis has highlighted the importance of setting up macro-prudential oversight frameworks, having effective macro-prudential instruments in place to be called upon to mitigate growing financial imbalances as needed. We develop a new approach using the euro area Bank Lending Survey to assess the effectiveness of macro-prudential policies in containing credit growth and house price appreciation in mortgage markets. We find instruments targeting the cost of bank capital most effective in slowing down mortgage credit growth, and that the impact is transmitted mainly through price margins, the same banking channel as monetary policy. Limits on loan-to-value ratios are also effective, especially when monetary policy is excessively loose.