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Predicting Full Retirement Attainment of NBA Players

Published: April 20, 2024 00:00

The aim of this analysis is to predict whether an NBA player will be active in the league for at least 10 years so as to be qualified for NBA’s full retirement scheme which allows for the maximum benefit payable by law. We collected per game statistics…

Regional Economic Sentiment: Constructing Quantitative Estimates from the Beige Book and Testing Their Ability to Forecast Recessions

Published: April 16, 2024 00:00

We use natural language processing methods to quantify the sentiment expressed in the Federal Reserve's anecdotal summaries of current economic conditions in the national and 12 Federal Reserve District-level economies as published eight times per year in…

The Information Content of Conflict, Social Unrest and Policy Uncertainty Measures for Macroeconomic Forecasting

Published: April 5, 2024 00:00

It is widely accepted that episodes of social unrest, conflict, political tensions and policy uncertainty affect the economy. Nevertheless, the real-time dimension of such relationships is less studied, and it remains unclear how to incorporate them in a…

The Information Content of Conflict, Social Unrest and Policy Uncertainty Measures for Macroeconomic Forecasting

Published: April 5, 2024 00:00

It is widely accepted that episodes of social unrest, conflict, political tensions and policy uncertainty affect the economy. Nevertheless, the real-time dimension of such relationships is less studied, and it remains unclear how to incorporate them in a…

What’s in a headline? News impact on the Brazilian economy

Published: April 2, 2024 00:00

The purpose of this paper is to explore the impact of textual data on the Brazilian economic cycle. Utilizing a dataset of articles from †Valor Econômico†newspaper spanning from July 2011 to December 2022, we employ the topic model Latent Dirichlet…

Old but Gold or New and Shiny? Comparing Tree Ensembles for Ordinal Prediction with a Classic Parametric Approach

Published: March 29, 2024 00:00

There is a long tradition of modeling ordinal response data with parametric models such as the proportional odds model. With the advent of machine learning (ML), however, the classical stream of parametric models has been increasingly challenged by a more…

Application of Deep Learning to Emulate an Agent-Based Model

Published: March 26, 2024 00:00

In light of the dynamic challenges facing agricultural land markets, the conventional analytical frameworks fall short in capturing the intricate interplay of strategic decisions and evolving complexities. This necessitates the development of a novel…