We study the role of information in asset pricing models with long-run cash flow risk. When investors can distinguish short- from long-run consumption risks (full information), the model generates a sizable equity risk premium only if the equity term structure slopes up, contrary to the data.
How will the hurricanes affect economic data for October? Kenan Institute Research Fellow Greg Brown will look at the data during the institute’s monthly virtual briefing at 9 AM EDT Friday, November 1.
The aim of this all-day workshop is to familiarize you with the Microsoft Azure public cloud and some of its Big Data and Machine Learning technologies. By the time you leave the workshop, you should know the following: (1) how to navigate Azure and how to spin up new resources to do your work; (2) know different data collection & sanitation techniques and technologies; (3) have a feel for implementation of machine learning platforms that will facilitate your research aspirations.
Using machine learning techniques, we uncover an important number of dealers in the U.S. municipal bond market who focus on geographically adjacent states, a characteristic distinct from dealer centrality. These “specialized” dealers enjoy larger market shares in states with greater local ownership and in local bonds with more complex features. We also find that trades intermediated by these specialized dealers have significantly larger markups than those intermediated by national dealers.
“Look for your North Star.” “Chase success rather than run from failure.” “Success typically includes failure.” These are just a few of the drops of wisdom that Kenan Scholars program mentors shared at the year’s first mentor panel discussion.
The widespread adoption of technological advances has made the move to working from home during the COVID-19 pandemic a success. In this Kenan Insight, we look at why the switch was such a win, its impact on worker productivity, and what it means in the long term for workers, office spaces and cities.
As governments try to keep up with broadening economies and address new areas, such as climate change, data protection and artificial intelligence, the regulatory pace is increasing. This expansion creates new costs and requires increased business resiliency.
In this paper we present a framework for linking smart products (with embedded real-time diagnostics and prognostics based health management capabilities) to a service provisioning system to create a system of ―self-aware product-centric systems. The framework includes a powerful ―learning engine capable of monitoring, analyzing and interpreting patterns of system/product behavior in real-time. The learning engine provides the capability of information feedback for real-time, ―in-the-loop control. This concept enables the service-provisioning network to provide customer services such as product health management at reduced maintenance costs, improved responsiveness to customer needs during use, and generally more efficient operations.
The COVID-19 pandemic has generated a significant shift in how and where we work, play and live. In this Kenan Insight, we explore which changes will be temporary and which are here to stay.
This study examines the antecedents and consequences of knowledge sharing and monitoring based governance strategies on emissions reduction. We theorize, and empirically test, the impact of supply base diversity in industry and geographic locations on the governance strategy choices. We find that sector and regional diversity both have a significant impact on emissions reduction strategies, yet their direct and interactive impacts are different. Regarding consequences, we find that engaging suppliers is associated with GHG emissions reduction for both buyers and suppliers.
The mounting health and economic toll of the COVID-19 pandemic raises many questions about how this unprecedented event will affect the U.S. economy. In this Kenan Insight, we explore how people’s expectations about their own financial situation may hold some answers as to how the larger economy will perform.
New business formation plays a crucial role in predicting economic activity in North Carolina. Research shows that business starts positively impact county GDP growth and job creation, with larger effects in highly populated counties. The impact is smaller but still significant in less populated counties. Employment growth also varies by sector—new businesses in goods-producing industries create jobs after a delay, while service-sector businesses contribute to job growth more quickly. This research was done in collaboration with the North Carolina Secretary of State’s Office and the North Carolina Collaboratory.
We consider an electric utility company that serves retail electricity customers over a discrete-time horizon. In each period, the company observes the customers' consumption as well as high-dimensional features on customer characteristics and exogenous factors. A distinctive element of our work is that these features exhibit three types of heterogeneity—over time, customers, or both. Based on the consumption and feature observations, the company can dynamically adjust the retail electricity price at the customer level.
The conference is designed to share timely research in entrepreneurship, innovation and regional economic development that is developing new and original data sources.
Inspired by recent discussions of the systematic costs that external rankings impose on academic institutions, and the undeniable shifts in the landscape of institutional data, a concerted and pragmatic re-evaluation of ranking efforts has begun. In this study, multiple administrators and researchers representing both public and private institutions across the United States weigh in on these issues.
Flight delays have been a growing issue and they have reached an all-time high in recent years, with the airlines' on-time performance at its worst level in 2007 since 1995.
Recent studies emphasize that survey-based inflation risk measures are informative about future inflation and thus useful for monetary authorities. However, these data are typically available at a quarterly frequency whereas monetary policy decisions require a more frequent monitoring of such risks.
COVID-19 and the subsequent rise in work-from-home policies by firms have changed the landscape of skilled labor in the United States. The Survey of Working Arrangements and Attitudes finds that 15% of employees are working from home full time, as of September 2022. This dramatic increase in remote work has led to an equally dramatic physical migration of workers across the U.S. Census data shows a sharp decline in populations of the largest U.S. cities and increases among midsize cities and smaller metro areas. For example, from 2020 to 2021, the counties of Manhattan (New York County) and San Francisco both saw a decline in their population of 25- to 54-year-olds by nearly 10%.
In addition to academic presentations, the Conference on Market-Based Solutions for Reducing Wealth Inequality took participants out of the classroom and into the community for a walking tour and on-site discussions in nearby Durham, N.C.