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Journal Article
Tracking U.S. GDP in Real Time
Bae, Jaeheung; Doh, Taeyoung (2019-07)
Measuring the current state of the U.S. economy in real time is an important but challenging task for monetary policymakers. The most comprehensive measure of the state of the economy?real gross domestic product?is available at a relatively low frequency (quarterly) and with a significant delay (one month). To obtain more timely assessments of the state of the economy, the Federal Reserve Bank of Kansas City has developed a GDP tracking model that combines new econometric methods with two conventional approaches to estimating GDP. {{p}} Taeyoung Doh and Jaeheung Bae review the Kansas City Fed ...
Economic Review , Issue Q III , Pages 5-19

Working Paper
Reasons Behind Words: OPEC Narratives and the Oil Market
Brunetti, Celso; Joëts, Marc; Mignon, Valérie (2024-02-02)
We analyze the content of the Organization of the Petroleum Exporting Countries (OPEC) communications and whether it provides information to the crude oil market. To this end, we derive an empirical strategy which allows us to measure OPEC's public signal and test whether market participants find it credible. Using Structural Topic Models, we analyze OPEC narratives and identify several topics related to fundamental factors, such as demand, supply, and speculative activity in the crude oil market. Importantly, we find that OPEC communication reduces oil price volatility and prompts market ...
Finance and Economics Discussion Series , Paper 2024-003

Working Paper
BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R
Feldkircher, Martin; Huber, Florian; Böck, Maximilian (2020-08-20)
This document introduces the R library BGVAR to estimate Bayesian global vector autoregressions (GVAR) with shrinkage priors and stochastic volatility. The Bayesian treatment of GVARs allows us to include large information sets by mitigating issues related to overfitting. This improves inference and often leads to better out-of-sample forecasts. Computational efficiency is achieved by using C++ to considerably speed up time-consuming functions. To maximize usability, the package includes numerous functions for carrying out structural inference and forecasting. These include generalized and ...
Globalization Institute Working Papers , Paper 395

Working Paper
A Note on the Finite Sample Bias in Time Series Cross-Validation
Lusompa, Amaze (2025-11-24)
It is well known that model selection via cross validation can be biased for time series models. However, many researchers have argued that this bias does not apply when using cross-validation with vector autoregressions (VAR) or with time series models whose errors follow a martingale-like structure. I show that even under these circumstances, performing cross-validation on time series data will still generate bias in general.
Research Working Paper , Paper RWP 25-17

Working Paper
A Flexible Finite-Horizon Identification of Technology Shocks
Owyang, Michael T.; Roush, Jennifer E.; Francis, Neville (2005)
Recent empirical studies using in finite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long-run restrictions in Monte Carlo experiments. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long, but finite horizon. In small samples, our identification outperforms its in finite ...
International Finance Discussion Papers , Paper 832

Working Paper
Estimating Impulse Response Functions When the Shock Series Is Observed
Choi, Chi-Young; Chudik, Alexander (2019-03-04)
We compare the finite sample performance of a variety of consistent approaches to estimating Impulse Response Functions (IRFs) in a linear setup when the shock of interest is observed. Although there is no uniformly superior approach, iterated approaches turn out to perform well in terms of root mean-squared error (RMSE) in diverse environments and sample sizes. For smaller sample sizes, parsimonious specifications are preferred over full specifications with all ?relevant? variables.
Globalization Institute Working Papers , Paper 353

Working Paper
Monetary Policy Spillovers, Capital Controls and Exchange Rate Flexibility, and the Financial Channel of Exchange Rates
Zhu, Feng; Georgiadis, Georgios (2019-05-05)
We assess the empirical validity of the trilemma (or impossible trinity) in the 2000s for a large sample of advanced and emerging market economies. To do so, we estimate Taylor-rule type monetary policy reaction functions, relating the local policy rate to real-time forecasts of domestic fundamentals, global variables, as well as the base-country policy rate. In the regressions, we explore variations in the sensitivity of local to base-country policy rates across different degrees of exchange rate flexibility and capital controls. We find that the data are in general consistent with the ...
Globalization Institute Working Papers , Paper 363

Working Paper
Estimating the Missing Intercept
Matthes, Christian; Nagasaka, Naoya; Schwartzman, Felipe (2025-10-03)
Cross-sectional data have proven to be increasingly useful for macroeconomic research. However, their use often leads to the 'missing intercept' problem in which aggregate general equilibrium effects and policy responses are absorbed into fixed effects. We present a statistical approach to jointly estimate aggregate and idiosyncratic effects within a panel framework, leveraging identification strategies coming from both cross-sectional or time-series settings. We then apply our methodology to study government spending multipliers (Nakamura and Steinsson, 2014) and wealth effects from stock ...
Working Paper , Paper 25-12

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