Long depicted as a global melting pot, the United States is home to a collection of sharply divergent geographies, regions and cultures. An overlooked measure of our diversity, however, is economic. While national statistics tell a story of averages, they fail to account for the true drivers of economic expansion and contraction. It is only upon examining America’s microeconomies – our cities, towns, suburbs and rural communities – that we can begin to appreciate the myriad and complex determinants of broader U.S., and sometimes even global, economic trends.
Firms are increasingly launching initiatives with explicit social mandates. Often the business case for these initiatives is justified through one critical aspect of human capital management: employee retention. Although prior empirical studies have demonstrated a link between such corporate social initiatives and intermediate employee-related outcomes like motivation and identification with the firm, the relationship between employee participation in these initiatives and retention outcomes has not been investigated.
Prior studies attribute analysts' forecast superiority over time-series forecasting models to their access to a large set of firm, industry, and macroeconomic information (an information advantage), which they use to update their forecasts on a daily, weekly or monthly basis (a timing advantage).
This paper evaluates the role of various volatility specifications, such as multiple stochastic volatility (SV) factors and jump components, in appropriate modeling of equity return distributions.
There are few topics in business more current, more covered or more controversial than corporate environmental, social and governance (ESG) responsibilities. Proponents claim a business’s adoption of such principles yields outcomes that benefit all parties, driving win-win scenarios for internal and external stakeholders alike. But critics dismiss ESG implementation as a performative PR ploy, and argue that considering such non-pecuniary factors in corporate decision-making is unsustainable. Our (independent, nonpartisan) findings indicate both sides of the debate are missing the mark – and in hopes of advancing more productive conversations, we introduce below a research-based model for examining the trade-offs of ESG adoption for businesses large and small.
We introduce a new, market-based and forward-looking measure of political risk derived from the yield spread between a country's US dollar debt and an equivalent US Treasury bond. We explain the variation in these sovereign spreads with four factors: global economic conditions, country-specific economic factors, liquidity of the country's bond, and political risk. We then extract the part of the sovereign spread that is due to political risk, making use of political risk ratings. In addition, we provide new evidence that these political risk ratings are predictive, on average, of future risk realizations using data on political risk claims as well as a novel textual-based database of risk realizations.
Much is known about the importance of learning and some of the distinct learning processes that organizations use (e.g., trial-and-error learning, vicarious learning, experimental learning, and improvisational learning). Yet surprisingly little is known about whether these processes combine over time in ordered ways, because most research on learning explores one particular process. Using theory elaboration and theory-building methods and data on the accumulated country entries of entrepreneurial firms, we address this gap. Our core contribution is an emergent theoretical framework that develops the concept of learning sequences. We find that learning sequences exist and are influenced by initial conditions.
This study explores how firms learn heuristics from negative outcomes. Prior literature has suggested that learning is strongly affected by whether attributions for negative outcomes are internal or external. Our data complement this view by revealing a new and different pattern. Specifically, they show that learning heuristics appears more dependent on whether attributions are convergent or divergent across hierarchical levels.
Financial regulators and investors have expressed concerns about high pay inequality within firms. Using a proprietary data set of public and private firms, this paper shows that firms with higher pay inequality—relative wage differentials between top- and bottom-level jobs—are larger and have higher valuations and stronger operating performance. Moreover, firms with higher pay inequality exhibit larger equity returns and greater earnings surprises, suggesting that pay inequality is not fully priced by the market. Our results support the notion that differences in pay inequality across firms are a reflection of differences in managerial talent.
We examine data on capital-gains-tax-related information search to determine when and how taxpayers acquire information. We find seasonal increases in information search around tax deadlines, suggesting that taxpayers seek information to comply with tax law.
We revisit the relation between stock market volatility and macroeconomic activity using a new class of component models that distinguish short run from secular movements. We study long historical data series of aggregate stock market volatility, starting in the 19th century, as in Schwert (1989).
We examine the effects of mixed sampling frequencies and temporal aggregation on the size of commonly used tests for cointegration, and we find that these effects may be severe.
This paper examines the impact of NPD make/buy choices on product quality using data from the automobile industry. While the business press laments that NPD outsourcing compromises product quality, there is no systematic evidence to support or refute this assertion.
Corporate executives have begun to glimpse the strategic value of incorporating artificial intelligence as an “employee” within their organization. In this Kenan Insight, we explore a framework that outlines the critical elements for harnessing the potential of human-AI working relationships.
North Carolina is one of the major migration destinations in the U.S. A newly created dashboard that uses 2015-2016 Internal Revenue Service (IRS) county-to-county migration data provides key insights into both the origins and economic characteristics of recent newcomers to the Tar Heel State.
A panel of experts convened by UNC Kenan-Flagler Business School and its affiliated Kenan Institute of Private Enterprise will be offering a press briefing via webinar on re-starting the economy following the COVID-19 pandemic. Join Tuesday, June 16, at 11 a.m. EDT.
The Fed is threading a shrinking needle in its attempts to engineer a soft landing for the U.S. economy. Join Professor Greg Brown for a briefing built on the latest employment data and financial market signals, followed by his answers to questions from the audience.
Counterfeiting is a severe problem with significant economic impact that can negatively affect a manufacturer's profit and brand. However, blockchain-based solutions can help customers make informed purchasing decisions.
Consumers will long associate the early months of the COVID-19 pandemic with seemingly apocalyptic searches for toilet paper, hand sanitizer and PPE. But even now, amid continued surges of the Delta variant, many global supply chains continue to experience disruptions at record rates. This week’s Kenan Insight invites our experts to weigh in on the immediate impact of these disruptions for business and society, the longer term effects across industries and the roles government and emerging tech should be playing to drive solutions.
Kenan Institute Chief Economist Gerald Cohen discusses the power of productivity and what that means for the U.S. economy.