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.
This paper uses transaction-level import data at the shipment level to examine how multinational companies importing to the US have restructured their supply chains during the COVID-19 pandemic. We find that companies sourced from fewer locations, reduced the share of imports from China, and increased the share of imports from other Asian countries, such as India and Vietnam, and North American countries, such as Canada and Mexico. For managers, our results imply that a one-size-fits-all mentality regarding supply chain disruption responses is not appropriate, and companies’ disruption-response strategies need to be tailored to individual supply chains’ circumstances.
We study the performance and information acquisition behavior of mutual funds for both their long and short positions. We show that managers acquire relatively more information about their shorts because the benefit of acquiring information about shorts is larger.
We describe an experimental curriculum innovation that creates a safe space for students to engage in courageous conversations—to openly share diverse thoughts and opinions as well as vigorously debate politically charged issues of critical business importance.
Customer review manipulation is a common strategy employed by sellers of online marketplaces to combat competitors. The impact of this deceptive behavior on the competitive pricing of online marketplaces is intricate. First, buying fake reviews incurs additional costs and alters customer demand in competitive settings by misrepresenting product information. Second, the pricing is determined through internal competitions, where sellers compete with each other within an online marketplace. This is because the winner's price is the default price displayed to customers, representing the price of the online marketplace. Meanwhile, online marketplaces also effectively manage prices in order to stay competitive in external competition against multi-channel retailers, further complicating this problem. To unravel this influence mechanism, we build instrumented econometric models and develop a game-theoretic model to empirically and theoretically analyze this influence mechanism in the context of internal and external competitions, respectively.
Prior research suggests that female negotiators often obtain worse outcomes than male negotiators. The current research examines whether this pattern extends to the large subset of men and women who identify as gays and lesbians. In particular, we interweave scholarship on gender stereotypes with work on intersectionality and MOSAIC theory to develop a theoretical model that anticipates how male and female negotiators will be treated at the bargaining table based on whether they are perceived to be heterosexual or homosexual.
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.
This work examines the effects on worker psychological well-being and productivity of highly publicized negative identity-related societal events, such as the 2020 murder of George Floyd, mass shootings like the 2016 Pulse nightclub shooting that targeted LGBTQ+ individuals, and the 2021 Atlanta area Spa shootings that targeted individuals of Asian descent.
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.
Pay transparency policies are increasingly popular among governments in the United States and around the world.
COVID-19 exacerbated existing shortages in the labor market, causing business leaders to revise corporate strategies designed to recruit and retain the workforce needed to compete in at the state, national, and global level. We must recognize and support the critical role our community colleges serve in meeting employers’ post-pandemic workforce demands if we are to close the skills gap in the current labor market.
Immigration is one of the most contentious policy issues, and Congress has for decades failed to make any significant legislative progress. The result is an incoherent policy landscape and serious operational challenges on the ground. At the same time, immigration and immigrant integration are critical to U.S. workforce growth, government fiscal solvency, and innovation. I discuss key findings from the economics literature and their implications for where to focus immigration reform efforts.
In 2022, in-migration slowed, and out-migration accelerated, reducing the role of net migration in North Carolina statewide population growth, according to recently released Census data. For the Tarheel state, we document changes in gross and net migration flows between 2021 and 2022, highlight possible drivers, and offer anecdotal evidence as to why the revealed changes may foreshadow a longer- term shift in migration’s role in statewide population change.
Effective policymakers must balance the demands of formulating a corporate tax system that spurs economic activity while promoting a “level playing field” across firms. However, tax systems have become more complex over time, increasing firms’ difficulty in understanding and complying with tax regulations. We explore the role of corporate tax system complexity in both objectives, using an international sample and measuring tax system complexity based on the average time firms spend to comply with the country’s tax regulations. Examining both capital and labor investment, we document two key findings. First, firm-level investment is less sensitive to changes in corporate income tax rates when tax system complexity is higher, suggesting that such complexity can undermine the ability of tax policy to stimulate investment. Second, the impact of complexity on the sensitivity of investment to the tax rate varies significantly across firms, with domestic-owned, smaller, and private firms being more negatively affected by tax system complexity.
We examine how tax-induced organizational complexity (“TIOC”), which we define as the organizational complexity that would not exist in a zero-tax world, is associated with executive performance measurement. While these structures can facilitate lower tax burdens, firms need to design their performance measurement systems to encourage executives to manage the associated complexity to avoid potential negative consequences. Using firms’ subsidiary structures in tax havens and other low tax countries to measure TIOC, we document several main findings.
This paper defines risk-on risk-off (RORO), an elusive terminology in pervasive use, as the variation in global investor risk aversion. Our high-frequency RORO index captures time-varying investor risk appetite across multiple dimensions: advanced economy credit risk, equity market volatility, funding conditions, and currency dynamics. The index exhibits risk-off skewness and pronounced fat tails, suggesting its amplifying potential for extreme, destabilizing events. Compared with the conventional VIX measure, the RORO index reflects the multifaceted nature of risk, underscoring the diverse provenance of investor risk sentiment. Practical applications of the RORO index highlight its significance for international portfolio reallocation and return predictability.
Banks face corporate and regulatory governance pressures. A critical tool of regulatory governance is direct monitoring by bank supervisors. Supervisors assess banks using a multi-dimensional rating scheme, including a rating of top management teams (M-rating). We examine implications of M-ratings from the distinct, but complementary perspectives of managerial capital and managerial discipline.
Prior work on supervisor bottom-line mentality (SBLM) has suggested it represents a static, unbending focus, with supervisors so focused on the bottom line that they discount ethical considerations. We propose that SBLM varies, within-person, given various factors in a supervisor's work life that pull and push their attention to and away from the bottom line across their workweeks. We theorize that the varying nature of SBLM elicits anxiety in employees that is exhausting because, on the days supervisors give greater emphasis to the bottom line, employees must abandon the comfort of their routines to produce bottom-line results. Ultimately, this experience motivates employee unethical behavior (i.e., coworker undermining). We also predict that, by providing employees support and guidance, supervisors’ steadfast commitment to ethics (i.e., between-person ethical leadership perceptions) influences the degree to which exhausted employees undermine their coworkers.
Prior research suggests that female negotiators often obtain worse outcomes than male negotiators. The current research examines whether this pattern extends to the large subset of men and women who identify as gays and lesbians. In particular, we interweave scholarship on gender stereotypes with work on intersectionality and MOSAIC theory to develop a theoretical model that anticipates how male and female negotiators will be treated at the bargaining table based on whether they are perceived to be heterosexual or homosexual. This model predicts that homosexual women, like heterosexual men, will receive more beneficial negotiation offers and outcomes than heterosexual women and homosexual men.
Quantum computers are not yet up to the task of providing computational advantages for practical stochastic diffusion models commonly used by financial analysts. In this paper we introduce a class of stochastic processes that are both realistic in terms of mimicking financial market risks as well as more amenable to potential quantum computational advantages.