Narrow search
Showing 1 - 10 of 613
Cover Image
Risky Oil : It's All in the Tails
Baumeister, Christiane; Huber, Florian; Marcellino, … - National Bureau of Economic Research - 2024
. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that …
Persistent link: https://www.econbiz.de/10014544801
Cover Image
Filtering with Limited Information
Drautzburg, Thorsten; Fernández-Villaverde, Jesús; … - National Bureau of Economic Research - 2024
various simulation studies and an empirical application to a sudden stops model applied to Mexican data …
Persistent link: https://www.econbiz.de/10014635717
Cover Image
Inflation and Real Activity over the Business Cycle
Bianchi, Francesco; Nicolò, Giovanni; Song, Dongho - National Bureau of Economic Research - 2023
We study the relation between inflation and real activity over the business cycle. We employ a Trend-Cycle VAR model to … control for low-frequency movements in inflation, unemployment, and growth that are pervasive in the post-WWII period. We show … that cyclical fluctuations of inflation are related to cyclical movements in real activity and unemployment, in line with …
Persistent link: https://www.econbiz.de/10014247995
Cover Image
Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory
Dominitz, Jeff; Manski, Charles F. - National Bureau of Economic Research - 2024
We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research. SDT provides a formal framework for performing comprehensive OOS evaluation...
Persistent link: https://www.econbiz.de/10014512123
Cover Image
Machine Learning Can Predict Shooting Victimization Well Enough to Help Prevent It
Heller, Sara B.; Jakubowski, Benjamin; Jelveh, Zubin; … - National Bureau of Economic Research - 2022
This paper shows that shootings are predictable enough to be preventable. Using arrest and victimization records for almost 644,000 people from the Chicago Police Department, we train a machine learning model to predict the risk of being shot in the next 18 months. We address central concerns...
Persistent link: https://www.econbiz.de/10013334389
Cover Image
A New Way of Forecasting Recessions
Leamer, Edward E. - National Bureau of Economic Research - 2022
method deals with these intra-correlation issues. The one variable that is causing a recession alarm is inflation. The … control, but the 1970s data suggests it takes a recession to combat high inflation …
Persistent link: https://www.econbiz.de/10013334464
Cover Image
Predicting and Preventing Gun Violence : An Experimental Evaluation of READI Chicago
Bhatt, Monica P.; Heller, Sara B.; Kapustin, Max; … - National Bureau of Economic Research - 2023
Gun violence is the most pressing public safety problem in American cities. We report results from a randomized controlled trial (N=2,456) of a community-researcher partnership--the Rapid Employment and Development Initiative (READI Chicago)--which provided 18 months of a supported job alongside...
Persistent link: https://www.econbiz.de/10013537746
Cover Image
Nowcasting World Trade with Machine Learning : a Three-Step Approach
Chinn, Menzie David; Meunier, Baptiste; Stumpner, Sebastian - National Bureau of Economic Research - 2023
across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we …
Persistent link: https://www.econbiz.de/10014322806
Cover Image
Biased Surveys
Valchev, Rosen; Gemmi, Luca - National Bureau of Economic Research - 2023
We find evidence suggesting that surveys of professional forecasters are biased by strategic incentives. First, we find that individual forecasts overreact to idiosyncratic information but underreact to common information. Second, we show that this bias is not present in forecasts data that is...
Persistent link: https://www.econbiz.de/10014337840
Cover Image
How and When are High-Frequency Stock Returns Predictable?
Aït-Sahalia, Yacine; Fan, Jianqing; Xue, Lirong; Zhou, … - National Bureau of Economic Research - 2022
This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...
Persistent link: https://www.econbiz.de/10013362020