Showing 1 - 10 of 390
Benchmark finance and macroeconomic models appear to deliver conflicting estimates of the natural rate and bond risk premia. This natural rate puzzle applies not only in the U.S. but across many advanced economies. We use a unified no-arbitrage macro- finance model with two trend factors to...
Persistent link: https://www.econbiz.de/10014421212
We propose a new tool to filter non-linear dynamic models that does not require the researcher to specify the model fully and can be implemented without solving the model. If two conditions are satisfied, we can use a flexible statistical model and a known measurement equation to back out the...
Persistent link: https://www.econbiz.de/10014635717
Although decades of empirical research has demonstrated that criminal behavior responds to incentives, non … incentives. However, scientific research should not be driven by personal beliefs. Whether or not economic conditions matter or …, the original findings of Mocan and Gittings (2003) are robust, providing evidence that people indeed react to incentives …
Persistent link: https://www.econbiz.de/10012466030
Neural networks offer a promising tool for the analysis of nonlinear economies. In this paper, we derive conditions for the global stability of nonlinear rational expectations equilibria under neural network learning. We demonstrate the applicability of the conditions in analytical and numerical...
Persistent link: https://www.econbiz.de/10015056130
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
The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the...
Persistent link: https://www.econbiz.de/10014544801
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
This paper proposes a new way of displaying and analyzing macroeconomic time series to form recession forecasts. The proposed data displays contain the last three years of each expansion. These allow observers to see for themselves what is different about the last year before recession. Based on...
Persistent link: https://www.econbiz.de/10013334464
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
We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, gradient linear boosting). While much less used in the literature, the latter are found to outperform...
Persistent link: https://www.econbiz.de/10014322806