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.
AI has become close to bewildering in its promises, met and unmet, its terms and tools, acronyms, “use” case examples of wild successes countered by duds and disappointments. There’s an overall lack of clear pointers for business leaders to shape the direction, priorities and pace of their organization’s AI activities. Over the past two years, we have explored the widening AI space; what stood out in our reviews is that there is today a lack of management perspective on AI.
Faculty Director of the Rethinc. FinTech Lab, Eric Ghysels was featured as the keynote speaker at the 2nd Crypto Asset Lab Conference. The conference, which took place on Tuesday, October 27th, focuses on all aspects of bitcoin and crypto assets, especially those pertaining to investment, banking, finance, monetary economics, and regulation. Topics included cryptocurrency adoption and transition dynamics, digital cash and payment systems, economics and/or game theoretic analysis of cryptocurrency protocols, economic and monetary aspects of cryptocurrencies and the legal, ethical and societal aspects of (decentralized) cryptocurrencies.
We examine firm disclosure choice during the initial public offering (IPO) roadshow presentation to understand the informativeness of a management presentation designed to attract investors. Although firms submit a comprehensive registration filing during the IPO, managers also prepare a roadshow presentation, which is shorter and typically allows managers more autonomy to select the information released and how it is discussed. We find that IPO roadshows have significantly more positive, less negative, and less uncertain language than the SEC filing.
Despite having the deepest and most diverse capital markets in the world, the United States still struggles to provide sufficient capital to many small businesses outside of major commercial centers as well as to women-owned and minority-owned businesses regardless of size or location. This paper reviews the academic literature and provides an analysis of some recent data to gain understanding of the causes of these gaps as well as the solutions for filling the gaps. Results indicate that the Small Business Administration’s SBIC program is an effective mechanism for providing capital to underserved geographies as well as to businesses owned by women and underrepresented minorities.
This study asks whether investors learn differently from gains versus losses. I find experimental evidence that indicates that being in the negative domain leads individuals to form overly pessimistic beliefs about available investment options.
We use panel data on ISO 9000 quality certification in 85 countries between 1993 and 1998 to better understand the cross-national diffusion of an organizational practice. Following neoinstitutional theory, we focus on the coercive, normative, and mimetic effects that result from the exposure of firms in a given country to a powerful source of critical resources, a common pool of relevant technical knowledge, and the experiences of firms located in other countries. We use social network theory to develop a systematic conceptual understanding of how firms located in different countries influence each other's rates of adoption as a result of cohesive and equivalent network relationships.
Using hand-collected data on succession planning disclosures, we study how having a formal succession plan affects the efficiency of CEO turnovers. We find that firms with succession plans have a lower likelihood of forced CEO turnovers and non-CEO executive team resignations.
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.
Formal theory and empirical research are complementary in building and advancing the body of knowledge in accounting in order to understand real-world phenomena. We offer thoughts on opportunities for empiricists and theorists to collaborate, build on each other’s work, and iterate over models and data to make progress.
In Part 1 of this article, economic incentives were estimated for relaxing the requirement that biocrude entering the refinery infrastructure be oxygen (O2)-free. It was concluded that an accurate estimate of these incentives is not possible without a significant amount of additional data. Part 2 examines key issues that must be addressed and the associated data needed for this constraint to be relaxed.
Rumors are ubiquitous in the workplace, particularly regarding organizational changes. These rumors significantly influence worker behavior by introducing uncertainty, and thus, affect productivity and team performance. However, no studies have provided empirical evidence for these impacts due to data limitations on rumors and workers' behaviors in completing tasks.
Real estate private equity (REPE) funds are often differentiated by risk class: Core, Value-Added, or Opportunistic. Fund class is used by investors and managers to allocate funds and to describe investment policies. In this paper, we use REPE fund cash flow data from Burgiss that allow us to calculate a variety of performance metrics.
We examine the trading behavior of particularly intensive traders, those who contribute the most to daily trading volume, and provide new evidence that is consistent with the presence of informational advantages. Using a unique Chinese data set of the most active daily market participants for each stock, we demonstrate that intensive traders’ buying (selling) predicts large positive (negative) abnormal returns, both unconditionally and, in particular, around key, value-relevant announcements.
We study the microstructure of the U.S. housing market using a novel data set comprising housing search and bargaining behavior for millions of interactions between sellers and buyers. We first establish a number of stylized facts, the most prominent being a nearly 50--50 split between houses that sold below final listing price and those that sold above final listing price. Second, we compare observed behavior with predictions from a large theoretical housing literature.
This paper documents a set of stylized facts about leverage and financial fragility in the non-financial corporate sector in emerging markets since the Global Financial Crisis (GFC). Corporate debt vulnerability indicators prior to the Asian Financial Crisis (AFC) attributed to corporate financial roots provide a benchmark for comparison. The firm-level data suggest that emerging markets post-GFC have lower leverage ratios than the five Asian crisis countries (Asian Five) in the run-up to the AFC.
Although the non-financial corporate sector accounts for the lion’s share of the post-Global Financial Crisis surge in emerging-market leverage, there is little systematic research on factors that impact corporate distress risk in emerging markets. Existing bankruptcy risk models developed using US data have low predictive power when applied to emerging market firms. We suggest that these models do not account for emerging market vulnerabilities to global shocks such as advanced economy monetary policy changes, US dollar movements, or shifts in global liquidity and risk-aversion.
This paper presents the development, validation, and implementation of a data-driven optimization model designed to dynamically plan the assignment of anesthesiologists across multiple hospital locations within a large multi-specialty healthcare system. We formulate the problem as a multi-stage robust mixed-integer program incorporating on-call flexibility to address demand uncertainty. The optimized dynamic staffing plan has been successfully implemented in the University of Pittsburgh Medical Center healthcare system, leading to estimated annual cost savings of 12\% compared to current practice, or about \$800,000 annually.
We investigate the spatial dependence between commercial and residential mortgage defaults. A new class of observation-driven frailty factor models is introduced to do so. The idea of dynamic parameters embedded in the class of GAS models is utilized to estimate dynamic models of default risk with potentially multiple factors which are driven by stratified grouping of large panels of mortgage loan records. The score dynamics in the models is driven by so-called generalized residuals, and have therefore a fairly intuitive interpretation of ARMA-like dynamics. The proposed models are computationally easy to implement and therefore attractive in big data applications, something that gives them a considerable advantage in comparison to the typical latent factor frailty models proposed in the literature.
Wall Street Journal Pro columnist Luis Garcia highlighted the newly announced Private Equity Research Consortium and Burgiss data partnership and how it will reshape the debate surrounding private equity.