The tremendous growth in cryptocurrency trading has included frequent pump-and-dump (P&D) schemes. The resulting volatility has raised both excitement and concern about exploitation and fraud. Unlike the stock market, where P&D schemes can last for months, in the cryptocurrency market the price and volume inflations last just minutes, making it is almost impossible for those not in the pump group to participate. P&Ds are organized through pump groups who communicate through heavily encrypted message platforms. Investors learn about the groups through ads on social media. Our research examines 500 cryptocurrency P&D schemes to better understand their timing, characteristics and impact. As cryptocurrency exchanges think about regulating P&Ds, our researchers seek to understand who is currently benefiting and what these “cryptobloggers” do to the health of the cryptocurrency market.
We document what fraction of the housing stock in US cities is affordable to different family types. Rather than looking at what fraction of their income people actually pay in rent in each city, which reflects a mix of households’ ability to pay and supply conditions, we look at the extent to which the housing stock is affordable using discrete housing expenditure share cutoffs and the distribution of rents in the American Community Survey from each city.
We present a classical enhancement to improve the accuracy of the Hybrid variant (Hybrid HHL) of the quantum algorithm for solving linear systems of equations proposed by Harrow, Hassidim, and Lloyd (HHL). We achieve this by using higher precision quantum estimates of the eigenvalues relevant to the linear system, and a new classical step to guide the eigenvalue inversion part of Hybrid HHL.
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.
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.
The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics and proponents of partial least squares path modeling (PLS-PM).
The current research explores the relationship between living abroad and self-concept clarity. We conducted six studies (N = 1,874) using different populations (online panels and MBA students), mixed methods (correlational and experimental), and complementary measures of self-concept clarity (self-report and self-other congruence through 360-degree ratings).
In this paper, we compare several approaches of producing multi-period-ahead forecasts within the GARCH and RV families – iterated, direct, and scaled short-horizon forecasts. We also consider the newer class of mixed data sampling (MIDAS) methods.
We examine whether the contribution of firm-level accounting earnings to the informativeness of the aggregate is tilted towards earnings with specific financial reporting characteristics. Specifically, we investigate whether considering the smoothness of firm-level earnings increases the informativeness of aggregate earnings for future real GDP, and if so, whether macroeconomic forecasters use this information efficiently. Using recently-developed mixed data sampling methods, we find that the aggregate is tilted towards firms with smoother earnings and that this composition of aggregate earnings outperforms traditional weighting schemes.
We study how an improvement in contracting institutions due to the 1999 U.S.-China bilateral agreement affects U.S. firms’ innovation. We show that U.S. firms operating in China decrease their process innovations—innovations that improve firms’ own production methods—following the agreement.
Simulation-based estimation methods have become more widely used in recent years. We propose a set of tests for structural change in models estimated via simulated method of moments (see Duffe and Singleton (Econometrica 61 (1993) 929).
Time series regression analysis relies on the heteroskedasticity- and auto-correlation-consistent (HAC) estimation of the asymptotic variance to conduct proper inference. This paper develops such inferential methods for high-dimensional time series regressions.
Collective action is critical for successful market formation. However, relatively little is known about how and under what conditions actors overcome collective action problems to successfully form new markets. Using the benefits of simulation methods, we uncover how collective action problems result from actor resource allocation decisions interacting with each other and how the severity of these problems depends on central market- and actor-related characteristics.
Following state-level legal changes that increase labor dismissal costs, firms increase their innovation in new processes that facilitate the adoption of cost-saving production methods, especially in industries with a large share of labor costs in total costs. Firms with high innovation ability exhibit larger increases in process innovation and capital-labor ratios, an effect driven by both increases in capital investment and decreases in employment. By facilitating the adjustment of the input mix when conditions in input markets change, innovation ability allows firms to mitigate value losses and is a key driver of their performance.
In this paper, we develop new methods for analyzing high-dimensional tensor datasets. A tensor factor model describes a high-dimensional dataset as a sum of a low-rank component and an idiosyncratic noise, generalizing traditional factor models for panel data. We propose an estimation algorithm, called tensor principal component analysis (PCA), which generalizes the traditional PCA applicable to panel data.
Technology acquisitions are increasingly prevalent, but their failure rate is notoriously high. Although extant research suggests that collaboration may improve acquisition success, relatively little is known about how firms cultivate collaboration during postmerger integration (PMI) of technology acquisitions. Using inductive multiple-case methods, we address this gap.
Conventional wisdom touts tax breaks and other economic incentives as the key to attracting out-of-state business. But do educational policies play an even bigger role? In a recent article in The New Republic, Brent Lane, economic strategist for the Kenan Institute of Private Enterprise, says a well-educated workforce is essential, and not just for winning business bids.
The extent to which federal investment in research crowds out or decreases incentives for investment from other funding sources remains an open question. Scholarship on research funding has focused on the relationship between federal and industry or, more comprehensively, non-federal funding without disentangling the other sources of research support that include nonprofit organizations and state and local governments. This paper extends our understanding of academic research support by considering the relationships between federal and non-federal funding sources provided by the National Science Foundation Higher Education Research and Development Survey.
As Global Entrepreneurship Week begins, Professor Ted Zoller, faculty director of the Kenan Institute-affiliated UNC Entrepreneurship Center, discusses what UNC Kenan-Flagler Business School is doing to drive innovation in entrepreneurship education and prepare the next generation of entrepreneurs for success.