Analyzing more than 300,000 articles across 40 top-tier journals between 2000 and 2022, this study demonstrates that China’s 2006 National Medium-and Long-Term Plan for the Development of Science and Technology catalyzed a surge in publication volume and citations, propelling China past the United States as the world’s leading producer of scientific research.
Analyzing more than 300,000 articles across 40 top-tier journals between 2000 and 2022, this study demonstrates that China’s 2006 National Medium-and Long-Term Plan for the Development of Science and Technology catalyzed a surge in publication volume and citations, propelling China past the United States as the world’s leading producer of scientific research.
Edward Herbst, Scott Konzem, and Cristina ScofieldWe comprehensively document 1,265 Federal Reserve staff alternative scenarios presented to the Federal Open Market Committee in publicly released materials from 1968 to 2020. Scenarios grew in frequency and sophistication, typically spanning a range of outcomes around the baseline.
Dong Hwan Oh and Andrew J. PattonWe propose a new measure of mutual fund manager ability: "efficiency" is the ability to accrue the risk premium associated with a risk factor. The familiar abnormal return, or alpha, is shown to be the sum of two distinct measures of ability: "aggregate efficiency" which is the beta-weighted sum of the fund's (in)efficiencies across risk factors, and "skill," the component that is unrelated to factor exposures. Using a panel of U.S.
Monetary policy asymmetrically affects the response of firms’ employment to an output shock and plays a role in cushioning employment adjustment over the business cycle. Combining annual firm-level data until 2020 with quarterly firm-level data until 2023 and high-frequency monetary policy surprises, we show that for a given change in output, monetary policy influences the extent to which firms hold on to labour, or “labour hoard”.
Monetary policy asymmetrically affects the response of firms’ employment to an output shock and plays a role in cushioning employment adjustment over the business cycle. Combining annual firm-level data until 2020 with quarterly firm-level data until 2023 and high-frequency monetary policy surprises, we show that for a given change in output, monetary policy influences the extent to which firms hold on to labour, or “labour hoard”.
We propose a new model in which relationship-specific effects or shocks are identified in a bipartite network under mild covariance restrictions, generalizing the influential Abowd et al. (1999) framework. For example, separate demand shocks are identified for each bank from which a firm borrows. We show how previous approaches break down when confronted with such heterogeneity, while our novel identification strategy yields a simple estimator that is consistent and asymptotically normal, under weaker network density assumptions than previous approaches.
We examine recent changes in stock market participation using newly available survey data from eleven euro area countries over the period 2020–2024. The evidence points to substantial turnover, with around 10% of non-stockholders entering the market each year, and more than 20% of stockholders exiting. New entrants tend to have lower education, income, financial literacy, and risk tolerance than established investors, indicating a shift in the composition of market participants. We also highlight the growing importance of cryptocurrency investments among retail investors.
We examine recent changes in stock market participation using newly available survey data from eleven euro area countries over the period 2020–2024. The evidence points to substantial turnover, with around 10% of non-stockholders entering the market each year, and more than 20% of stockholders exiting. New entrants tend to have lower education, income, financial literacy, and risk tolerance than established investors, indicating a shift in the composition of market participants. We also highlight the growing importance of cryptocurrency investments among retail investors.
We propose a new model in which relationship-specific effects or shocks are identified in a bipartite network under mild covariance restrictions, generalizing the influential Abowd et al. (1999) framework. For example, separate demand shocks are identified for each bank from which a firm borrows. We show how previous approaches break down when confronted with such heterogeneity, while our novel identification strategy yields a simple estimator that is consistent and asymptotically normal, under weaker network density assumptions than previous approaches.
