Search Results
Working Paper
What Do LLMs Want?
Large language models (LLMs) are now used for economic reasoning, but their implicit "preferences" are poorly understood. We study these preferences by analyzing revealed choices in canonical allocation games and a sequential job-search environment. In dictator-style allocation games, most models favor equal splits, consistent with inequality aversion. Structural estimation of Fehr-Schmidt parameters suggests this aversion exceeds levels typically observed in human experiments. However, LLM preferences prove malleable. Interventions such as prompt framing (e.g., masking social context) and ...
Working Paper
Explaining Machine Learning by Bootstrapping Partial Marginal Effects and Shapley Values
Machine learning and artificial intelligence are often described as “black boxes.” Traditional linear regression is interpreted through its marginal relationships as captured by regression coefficients. We show that the same marginal relationship can be described rigorously for any machine learning model by calculating the slope of the partial dependence functions, which we call the partial marginal effect (PME). We prove that the PME of OLS is analytically equivalent to the OLS regression coefficient. Bootstrapping provides standard errors and confidence intervals around the point ...
Journal Article
Assessing the Risk of Extreme Unemployment Outcomes
Although the unemployment rate is at a historically low level, many policymakers are nevertheless watching projections for the future unemployment rate closely to evaluate the risk of extreme outcomes. We assess the probabilities of extreme outcomes in the near and medium term and find that the risk of unexpectedly high unemployment three years in the future has declined from its Great Recession peak and remained low over the past three years.
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.
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
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.
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.
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
Revamping the Kansas City Financial Stress Index Using the Treasury Repo Rate
The Kansas City Financial Stress Index (KCFSI) uses the London Interbank Offered Rate (LIBOR) to measure money market borrowing conditions. But regulatory changes in the United Kingdom will eliminate LIBOR by 2021. We construct a revised financial stress index with a variable that measures the cost of borrowing collateralized by Treasury securities (the Treasury repo rate) instead of LIBOR. {{p}} This revised measure of the KCFSI is highly correlated with the current KCFSI, suggesting the Treasury repo rate can replace LIBOR.
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.