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Jel Classification:C1 

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
Systematic Cojumps, Market Component Portfolios and Scheduled Macroeconomic Announcements

This study provides evidence of common bivariate jumps (i.e., systematic cojumps) between the market index and style-sorted portfolios. Systematic cojumps are prevalent in book-to-market portfolios and hence, their risk cannot easily be diversified away by investing in growth or value stocks. Nonetheless, large-cap firms have less exposure to systematic cojumps than small-cap firms. Probit regression reveals that systematic cojump occurrences are significantly associated with worse-than-expected scheduled macroeconomic announcements, especially those pertaining to the Federal Funds target ...
Working Papers , Paper 2017-11

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

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 2020-7

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

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
The Economic Effects of Trade Policy Uncertainty

We study the effects of unexpected changes in trade policy uncertainty (TPU) on the U.S. economy. We construct three measures of TPU based on newspaper coverage, firms' earnings conference calls, and aggregate data on tari rates. We document that increases in TPU reduce investment and activity using both firm-level and aggregate macroeconomic data. We interpret the empirical results through the lens of a two-country general equilibrium model with nominal rigidities and firms' export participation decisions. In the model as in the data, news and increased uncertainty about higher future ...
International Finance Discussion Papers , Paper 1256

Working Paper
Minimum Distance Estimation of Dynamic Models with Errors-In-Variables

Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when external instruments may not be available or are weak. The idea is to exploit the relation between the parameters of the model and the least squares biases. In cases when this mapping is not analytically tractable, a special algorithm is designed to simulate the latent predictors without completely ...
FRB Atlanta Working Paper , Paper 2014-11

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

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

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