For small businesses, AI promises to handle financial and operational tasks, freeing up workers for other duties and creating new efficiencies. We offer seven focal points for small businesses planning for AI integration.
The paper uses structured machine learning regressions for nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the problem of predicting corporate earnings for a large cross-section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse-group LASSO regularization which can take advantage of the mixed-frequency time series panel data structures.
This paper explores the ups and downs of innovation and productivity growth in the US economy and potential connections to the ups and downs of business dynamism and entrepreneurship over the last few decades.
The advent of artificial intelligence (AI) tools necessitates the development of human skills that allow workers to use these new technologies to create value that AI tools cannot on their own.
This paper surveys the recent advances in machine learning method for economic forecasting. The survey covers the following topics: nowcasting, textual data, panel and tensor data, high-dimensional Granger causality tests, time series cross-validation, classification with economic losses.
UNC-Chapel Hill Professor Kurt Gray discusses how research can help us understand – and navigate – our rapidly changing professional and social lives.
UNC Professor Mohammad Jarrahi and IBM’s Phaedra Boinodiris address concerns about organizational adoption of artificial intelligence and how to include employees in important discussions, such as ethical considerations and potential job-related changes.
Mohammad Hossein Jarrahi of the UNC School of Information and Library Science explores the competitive and cooperative skills that organizations will seek in both their employees and their artificial intelligence systems for Harvard Business Review.
Research from UNC Kenan-Flagler Finance Professor Eric Ghysels attaches explicit costs to a model’s classification errors, in this case concerning pretrial detention decisions, avoiding the one-size-fits-all symmetrical cost function of traditional machine learning.
Generative AI such as ChatGPT holds the potential to alter many kinds of work, but analysis of a new report shows the occupations most likely to be affected are populated by more women than men.