Search Results
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.
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.
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.
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 ...
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 ...
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 ...
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 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 ...
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 ...
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 ...