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Jel Classification:C1 

Working Paper
Risks and Uncertainty in Monetary Policy

Central banks monitor macroeconomic risk through two traditions: scenario analysis, regularly used since the mid-1990s, and distributional forecasting, practiced since the late 1960s. The two are complementary but separate: scenarios provide narratives without probabilities, while predictive distributions provide probabilities with limited economic interpretation. Treating baseline forecasts and scenarios as conditional predictive densities, and distributional forecasts as reference predictive distributions, places both within a common framework and clarifies their roles. The Scenario ...
Finance and Economics Discussion Series , Paper 2026-061

Working Paper
Global Macro-Financial Cycles and Spillovers

We develop a new dynamic factor model to jointly characterize global macroeconomic and financial cycles and the spillovers between them. The model decomposes macroeconomic cycles into the part driven by global and country-specific macro factors and the part driven by spillovers from financial variables. We consider cycles in macroeconomic aggregates (output, consumption and investment) and financial variables (equity and house prices and interest rates). The global macro factor plays a major role in explaining G-7 business cycles, but there are also sizeable spillovers from equity and house ...
Working Papers , Paper 2512

Discussion Paper
What Do Climate Risk Indices Measure?

As interest in understanding the economic impacts of climate change grows, the climate economics and finance literature has developed a number of indices to quantify climate risks. Various approaches have been employed, utilizing firm-level emissions data, financial market data (from equity and derivatives markets), or textual data. Focusing on the latter approach, we conduct descriptive analyses of six text-based climate risk indices from published or well-cited papers. In this blog post, we highlight the differences and commonalities across these indices.
Liberty Street Economics , Paper 20241007

Journal Article
Measuring and Managing COVID-19 Model Risk

One of the many lessons learned from the financial crisis is the increased awareness of model risk. In this article, I apply the best practices of model risk management found in SR 11-7 (which offers regulatory guidance on the best practices for managing model risk) to COVID-19 models. In particular, I investigate the Institute of Health Metrics and Evaluation's (IHME) model to see if it has been effectively challenged with a critical assessment of its conceptual soundness, ongoing monitoring, and outcomes analysis.
Policy Hub , Volume 2020 , Issue 7 , Pages 12

Working Paper
Measuring Geopolitical Risk

We present a news-based measure of adverse geopolitical events and associated risks. The geopolitical risk (GPR) index spikes around the two world wars, at the beginning of the Korean War, during the Cuban Missile Crisis, and after 9/11. Higher geopolitical risk foreshadows lower investment and employment and is associated with higher disaster probability and larger downside risks. The adverse consequences of the GPR index are driven by both the threat and the realization of adverse geopolitical events. We complement our aggregate measures with industry- and firm-level indicators of ...
International Finance Discussion Papers , Paper 1222r1

Working Paper
Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. Our estimated time-varying-parameters SIRD model ...
Working Papers , Paper 21-18

Working Paper
Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach

This paper focuses on forecasting quarterly energy prices of commodities, such as oil, gas and coal, using the Global VAR dataset proposed by Mohaddes and Raissi (2018). This dataset includes a number of potentially informative quarterly macroeconomic variables for the 33 largest economies, overall accounting for more than 80% of the global GDP. To deal with the information in this large database, we apply a dynamic factor model based on a penalized maximum likelihood approach that allows us to shrink parameters to zero and to estimate sparse factor loadings. The estimated latent factors show ...
Globalization Institute Working Papers , Paper 376

Working Paper
Measuring Geopolitical Risk

We present a monthly indicator of geopolitical risk based on a tally of newspaper articles covering geopolitical tensions, and examine its evolution and effects since 1985. The geopolitical risk (GPR) index spikes around the Gulf War, after 9/11, during the 2003 Iraq invasion, during the 2014 Russia-Ukraine crisis, and after the Paris terrorist attacks. High geopolitical risk leads to a decline in real activity, lower stock returns, and movements in capital flows away from emerging economies and towards advanced economies. When we decompose the index into threats and acts components, the ...
International Finance Discussion Papers , Paper 1222

Discussion Paper
Measuring and Managing COVID-19 Model Risk

One of the many lessons learned from the financial crisis is the increased awareness of model risk. In this article, I apply the best practices of model risk management found in SR 11-7 (which offers regulatory guidance on the best practices for managing model risk) to COVID-19 models. In particular, I investigate the Institute of Health Metrics and Evaluation's (IHME) model to see if it has been effectively challenged with a critical assessment of its conceptual soundness, ongoing monitoring, and outcomes analysis.
Policy Hub , Paper 2020-07

Working Paper
A new monthly indicator of global real economic activity

In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely the Kilian?s index of global real economic activity and the index of OECD World industrial production. We develop an econometric approach based on desirable econometric properties in relation to the quarterly measure of World or global gross domestic product to evaluate and to choose across different alternatives. The method is designed to evaluate short-term, long-term and ...
Globalization Institute Working Papers , Paper 244

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