Search Results
Journal Article
Testing Hybrid Forecasts for Imports and Exports
The quality of economic forecasts tends to deteriorate during times of stress such as the COVID-19 pandemic, raising questions about how to improve forecasts during exceptional times. One method of forecasting that has received less attention is refining model-based forecasts with judgmental adjustment, or hybrid forecasting. Judgmental adjustment is the process of incorporating information from outside a model into a forecast or adjusting a forecast subjectively. Hybrid forecasts could be particularly useful during extraordinary times such as the COVID-19 pandemic, as models that do not ...
Journal Article
China's Post-COVID Recovery: Implications and Risks
China removed most of its COVID-19 restrictions in November 2022 following a year of weak growth. Despite initial uncertainty about sustained COVID-19 outbreaks, the Chinese economy has begun to rebound, driven by domestic consumption. The rebound is likely to boost global growth.
Working Paper
Evaluating Local Language Models: An Application to Bank Earnings Calls
This study evaluates the performance of local large language models (LLMs) in interpreting financial texts, compared with closed-source, cloud-based models. We first introduce new benchmarking tasks for assessing LLM performance in analyzing financial and economic texts and explore the refinements needed to improve its performance. Our benchmarking results suggest local LLMs are a viable tool for general natural language processing analysis of these texts. We then leverage local LLMs to analyze the tone and substance of bank earnings calls in the post-pandemic era, including calls conducted ...
Journal Article
Disruptions to Russian Energy Supply Likely to Weigh on European Output
The Russia-Ukraine war and subsequent oil sanctions from European countries have substantially disrupted the supply of Russian oil and gas. We estimate the effects of these disruptions on European output and find that a decline in the Russian oil and gas supply in 2022 could lead to a sizable drop in European output over 2023–24, though the effect differs across countries and sectors .
Journal Article
To Improve the Accuracy of GDP Growth Forecasts, Add Financial Market Conditions
More timely data on current macroeconomic conditions can reduce uncertainty about forecasts, helping policymakers mitigate the risk of extreme economic outcomes. We find that incorporating financial market conditions along with current macroeconomic conditions improves the forecast accuracy of future GDP growth. Forecasts based only on current macroeconomic conditions eventually converge to those incorporating financial market conditions, lending further support to this approach.
Working Paper
Macroeconomic Indicator Forecasting with Deep Neural Networks
Economic policymaking relies upon accurate forecasts of economic conditions. Current methods for unconditional forecasting are dominated by inherently linear models {{p}} that exhibit model dependence and have high data demands. {{p}} We explore deep neural networks as an {{p}} opportunity to improve upon forecast accuracy with limited data and while remaining agnostic as to {{p}} functional form. We focus on predicting civilian unemployment using models based on four different neural network architectures. Each of these models outperforms bench- mark models at short time horizons. One model, ...
Journal Article
How Much Would China’s GDP Respond to a Slowdown in Housing Activity?
We analyze China's interindustry connections and show that China?s housing activity has become increasingly important to its GDP growth. Our results suggest that a 10 percent decline in final demand for real estate and housing-related construction would lead to a decline in total output of 2.2 percent, an effect more than two times larger than it would have been 10 years ago.
Working Paper
Assessing Macroeconomic Tail Risks in a Data-Rich Environment
We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts ...
Journal Article
Did Importers Try to Front-Run Recent Tariffs on China?
Because tariffs are a tax on foreign goods, tariffs are thought to reduce imports. However, imports may actually increase after a tariff is announced if importers can stock inventories ahead of the tariff’s implementation. We find that after the announcement of additional tariffs on China in May 2024, imports from China increased by 15 percent for EV batteries, which are difficult to substitute.