Working Papers

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2024

May 17, 2024

New Perspectives on Quantitative Easing and Central Bank Capital Policies

Description: Central banks have come under increasing criticism for large balance sheet losses associated with quantitative easing (QE), and some observers have also argued that QE helped fuel the post-COVID-19 inflation boom. In this paper, we reconsider the conditions under which QE may be warranted considering the recent high inflation experience. We emphasize that the merits of QE should be evaluated based on the macroeconomic stimulus it provides and its effects on the consolidated fiscal position, and not simply on central bank profits or losses. Using an open economy DSGE model with segmented asset markets, we show how QE can provide a sizeable boost to output and inflation in a deep recession and improve the consolidated fiscal position—even if the central bank experiences considerable losses. However, the commitment-based features of QE and the possibility that upside inflation risks are bigger than recognized pre-pandemic call for more caution in using QE closer to full employment. We then consider how central banks might modify their policies for allocating profits to the government in light of large-scale losses. In short, we suggest that a more forward-looking and risk-based approach may be desirable in helping protect central bank financial autonomy and ultimately independence.

May 17, 2024

Sovereign Environmental, Social, and Governance (ESG) Investing: Chasing Elusive Sustainability

Description: This paper evaluates the progression of the sovereign ESG landscape since the initial comprehensive assessment of the sector in 2021 in “Demystifying Sovereign ESG” by conducting a comparative analysis of the current sovereign ESG methodologies of commercial ESG providers. The 2021 study articulated the distinct nature of the sovereign ESG segment from corporate ESG and documented fundamental shortcomings in sovereign ESG methodologies, such as the “ingrained income bias”, lack of consensus on environmental performance, and conflation of risk and sustainability objectives. While sovereign ESG methodologies have evolved since 2021, the significant correlation across providers of aggregate, S, and G scores persist. In response to market demand there has been a notable shift towards greater focus on the E pillar against growing heterogeneity on climate and environmental considerations across ESG providers. The findings underscore the disparity between perceptions and realities in implementing a sustainability strategy within the sovereign debt asset class. This necessitates a reevaluation of sovereign ESG scoring methodologies towards outcome-based metrics and urges a globally coordinated effort to establish robust sustainability measurement frameworks.

May 10, 2024

Forecasting Tail Risk via Neural Networks with Asymptotic Expansions

Description: We propose a new machine-learning-based approach for forecasting Value-at-Risk (VaR) named CoFiE-NN where a neural network (NN) is combined with Cornish-Fisher expansions (CoFiE). CoFiE-NN can capture non-linear dynamics of high-order statistical moments thanks to the flexibility of a NN while maintaining interpretability of the outputs by using CoFiE which is a well-known statistical formula. First, we explain CoFiE-NN. Second, we compare the forecasting performance of CoFiE-NN with three conventional models using both Monte Carlo simulation and real data. To do so, we employ Long Short-Term Memory (LSTM) as our main specification of the NN. We then apply the CoFiE-NN for different asset classes, with a focus on foreign exchange markets. We report that CoFiE-NN outperfoms the conventional EGARCH-t model and the Extreme Value Theory model in several statistical criteria for both the simulated data and the real data. Finally, we introduce a new empirical proxy for tail risk named tail risk ratio under CoFiE-NN. We discover that the only 20 percent of tail risk dynamics across 22 currencies is explained by one common factor. This is contrasting to the fact that 60 percent of volatility dynamics across the same currencies is explained by one common factor.

May 10, 2024

Conflicts and Growth: The R&D Channel

Description: Violent conflicts are typically associated with a long-lasting drag on economic output, yet establishing causality based on macro-data remains as a challenge. This study attempts to build causality in the conflict-growth nexus by exploiting within-country variation across industries’ technological intensity. It identifies a channel through which conflicts can impact growth, i.e., by hindering R&D activities. The analysis is based on industry-level data from two-digit manufacturing industries for a large sample of countries over the last four decades. The results show that conflicts lead to a decline in labor productivity growth, particularly in industries with higher technological intensity. The estimated magnitude of the differential effect of conflicts on labor productivity growth in high-tech industries is large. Moreover, the additional labor productivity loss in those industries in the years of conflicts does not seem to be offset in the post-conflict period neither. The findings offer insight into the observed patterns of durable declines in income in the aftermath of conflicts, considering the role of technological progress and innovation in long-term economic growth.

May 10, 2024

Intra-African Migration: Exploring the Role of Human Development, Institutions, and Climate Shocks

Description: We examine push and pull factors, including demographic, geography, culture, economic and human development, politics and climate, and uncover the key determinants shaping migration patterns within Africa. Our findings emphasize the significance of political (instability, ethnic tensions) and socio-demographic (human development, common language, population size and structure) factors, climate shocks, along with economic motivations, in driving intra-African migration. Understanding these multifaceted factors is vital for policymakers in formulating effective strategies to leverage human capital mobility to promote sustainable development in the region.

May 3, 2024

Challenges Facing SSNs in Emerging and Developing Economies:

Description: We show how the standard social welfare framework can be used to assess the performance of social safety nets (SSNs) in terms of targeting efficiency and budget effort. We apply this framework to the World Bank’s ASPIRE database and find that the variation in poverty alleviation achieved by SSNs in emerging markets and developing economies (EMDEs) is driven mainly by variation in budget effort. Increasing transfer spending is therefore key to strengthening SSNs in EMDEs. However, the inability of many EMDEs to finely target transfers to poor households means the required spending increases are prohibitive over the short term, especially in low-income countries. This emphasizes the importance of enhancing targeting efficiency and we discuss how the use of proxy-means testing can contribute to this emphasizing the importance of careful design to manage the horizontal inequity inherent in such an approach to targeting.

May 3, 2024

Strengthening Social Protection to Pave the Way for Technological Innovation: Evidence from the U.S.

Description: This paper investigates the impact of automation on the U.S. labor market from 2000 to 2007, specifically examining whether more generous social protection programs can mitigate negative effects. Following Acemoglu and Restrepo (2020), the study finds that areas with higher robot adoption reduced employment and wages, in particular for workers without collegue degree. Notably, the paper exploits differences in social protection generosity across states and finds that areas with more generous unemployment insurance (UI) alleviated the negative effects on wages, especially for less-skilled workers. The results suggest that UI allowed displaced workers to find better matches The findings emphasize the importance of robust social protection policies in addressing the challenges posed by automation, contributing valuable insights for policymakers.

May 3, 2024

The Impact of Reduced Commuting on Labor Supply and Household Welfare: A Post-Pandemic Analysis

Description: This paper examines the impact of changes in commuting time on welfare and labor supply in the aftermath of the COVID-19 pandemic. Utilizing data from the American Time Use Survey, we observe a shift in commuting time and working hours across occupations with varying ability of telework after the pandemic. We develop a household model of labor supply that accounts for commuting time, and we characterize how changes in commuting time impact individuals' and spouses' labor supply. We calibrate the model to the data. Our findings reveal that the observed post-pandemic decline in commuting time yields significant welfare gains: between 1.5 to 4.5 percent of consumption equivalents for households where at least one spouse experiences reduced commuting.

May 3, 2024

Monetary Policy Transmission in Emerging Markets: Proverbial Concerns, Novel Evidence

Description: Doubts persist about the effectiveness of monetary transmission in emerging markets, but the empirical evidence is scarce due to challenges in identifying monetary policy shocks. In this paper, we construct new monetary policy shocks using novel analysts’ forecasts of policy rate decisions. Crucial for identification, analysts can update forecasts up to the policy meeting, allowing them to incorporate any relevant data release. Using these shocks, we show that monetary transmission in emerging markets operates similarly to advanced economies. Monetary tightening leads to a persistent increase in bond yields, a contraction in real activity, and a delayed reduction in inflation. Furthermore, monetary policy impacts leveraged firms more strongly.

April 26, 2024

Central Banks Casting a Global Financial Safety Net: What Drives the Supply of Bilateral Swaps?

Description: The expansion of bilateral swap arrangements (BSAs) since the Global Financial Crisis has led to a substantial reconfiguration of the Global Financial Safety Net (GFSN). This paper examines the drivers of BSA supply using a novel dataset on all publicly documented BSAs. It finds that countries with well-developed financial markets and institutions and high trade openness are more likely to backstop other economies by establishing BSAs. In addition, their choice of BSA counterparts is driven by strong investment and trade exposures to these countries, with variation in the relative importance of these factors across major BSA providers. The paper shows that geopolitical considerations often affect such decisions, as BSAs are less likely to be established between geopolitically distant countries and more likely between countries in the same regional economic bloc.

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