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Working Paper
On the Testability of the Anchor-Words Assumption in Topic Models
Freyaldenhoven, Simon; Ke, Shikun; Li, Dingyi; Olea, Jose Luis Montiel (2025-03-19)
What does the Fed talk about in its monetary policy discussions? We introduce a new statistical methodology to analyze text documents, and we use that methodology to recover the topics discussed during FOMC meetings. Topic models are a simple and popular tool for the statistical analysis of textual data. Their identification and estimation are typically enabled by assuming the existence of anchor words; that is, words that are exclusive to specific topics. In this paper we show that the existence of anchor words is statistically testable: There exists a hypothesis test with correct size that ...
Working Papers , Paper 25-14

Working Paper
Artificial Intelligence Methods for Evaluating Global Trade Flows
Monken, Anderson; Gopinath, Munisamy; Batarseh, Feras A. (2020-08-20)
International trade policies remain in the spotlight given the recent rethink on the benefits of globalization by major economies. Since trade critically affects employment, production, prices and wages, understanding and predicting future patterns of trade is a high-priority for decision making within and across countries. While traditional economic models aim to be reliable predictors, we consider the possibility that Artificial Intelligence (AI) techniques allow for better predictions and associations to inform policy decisions. Moreover, we outline contextual AI methods to decipher trade ...
International Finance Discussion Papers , Paper 1296

Working Paper
Forecasting Consumption Spending Using Credit Bureau Data
Croushore, Dean; Wilshusen, Stephanie M. (2020-06-04)
This paper considers whether the inclusion of information contained in consumer credit reports might improve the predictive accuracy of forecasting models for consumption spending. To investigate the usefulness of aggregate consumer credit information in forecasting consumption spending, this paper sets up a baseline forecasting model. Based on this model, a simulated real-time, out-of-sample exercise is conducted to forecast one-quarter ahead consumption spending. The exercise is run again after the addition of credit bureau variables to the model. Finally, a comparison is made to test ...
Working Papers , Paper 20-22

Working Paper
Common Factors, Trends, and Cycles in Large Datasets
Barigozzi, Matteo; Luciani, Matteo (2017-11-13)
This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic properties of the estimator are discussed. Then, we show how to separate trends and cycles in the factors by mean of eigenanalysis of the estimated non-stationary factors. Finally, we employ our methodology on a panel of US quarterly macroeconomic indicators to estimate aggregate real output, or Gross ...
Finance and Economics Discussion Series , Paper 2017-111

Working Paper
The Effects of the War on Ukraine on Global Corporate Investment
Caldara, Dario; McHenry, Mike; Iacoviello, Matteo; Schott, Immo (2026-03-03)
We study the investment effects of the Russia-Ukraine war using a novel, text-based measure of firm-level exposure derived from earnings call transcripts. Combining this measure with financial statement data for over 6,500 firms across 50 countries, we show that exposure to the conflict led to sizable and persistent declines in corporate investment. Firms that discussed the war in early 2022 invested significantly less than otherwise similar firms. The results hold across multiple empirical strategies and highlight the role of geopolitical risk in shaping firm behavior during global crises.
International Finance Discussion Papers , Paper 1432

Discussion Paper
Reintroducing the New York Fed Staff Nowcast
O’Keeffe, Hannah; Sbordone, Argia M.; Baker, Katie; Almuzara, Martín (2023-09-08)
“Nowcasts” of GDP growth are designed to track the economy in real time by incorporating information from an array of indicators as they are released. In April 2016, the New York Fed’s Research Group launched the New York Fed Staff Nowcast, a dynamic factor model that generated estimates of current quarter GDP growth at a weekly frequency. The onset of the COVID-19 pandemic sparked widespread economic disruptions—and unprecedented fluctuations in the economic data that flow into the Staff Nowcast. This posed significant challenges to the model, leading to the suspension of publication ...
Liberty Street Economics , Paper 20230908

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks
Chudik, Alexander; Sharifvaghefi, Mahrad; Pesaran, M. Hashem (2021-04-17)
This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signal variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of ...
Globalization Institute Working Papers , Paper 394

Working Paper
Forecasting with Sufficient Dimension Reductions
Barbarino, Alessandro; Bura, Efstathia (2015-09-14)
Factor models have been successfully employed in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. When the objective is to forecast a target variable y with a large set of predictors x, the construction of the summary of the xs should be driven by how informative on y it is. Most existing methods first reduce the predictors and then forecast y in independent phases of the modeling process. In this paper we present an alternative and potentially more attractive alternative: summarizing x as it relates to y, so ...
Finance and Economics Discussion Series , Paper 2015-74

Working Paper
Trends and cycles in small open economies: making the case for a general equilibrium approach
Chen, Kan; Crucini, Mario J. (2016-08-12)
Economic research into the causes of business cycles in small open economies is almost always undertaken using a partial equilibrium model. This approach is characterized by two key assumptions. The first is that the world interest rate is unaffected by economic developments in the small open economy, an exogeneity assumption. The second assumption is that this exogenous interest rate combined with domestic productivity is sufficient to describe equilibrium choices. We demonstrate the failure of the second assumption by contrasting general and partial equilibrium approaches to the study of a ...
Globalization Institute Working Papers , Paper 279

Working Paper
Business Exit During the COVID-19 Pandemic: Non-Traditional Measures in Historical Context
Flaaen, Aaron; Kurz, Christopher J.; Decker, Ryan A.; Crane, Leland D.; Hamins-Puertolas, Adrian (2020-10-22)
Given lags in official data releases, economists have studied "alternative data" measures of business exit resulting from the COVID-19 pandemic. Such measures are difficult to understand without historical context, so we review official data on business exit in recent decades. Business exit is common in the U.S., with about 7.5 percent of firms exiting annually in recent years, and is countercyclical (particularly recently). Both the high level and the cyclicality of exit are driven by very small firms. We explore a range of alternative measures and indicators of business exit, including ...
Finance and Economics Discussion Series , Paper 2020-089

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