What Do Unions Do for Economic Performance?

Twenty years have passed since Freeman and Medoff's What Do Unions Do? This essay assesses their analysis of how unions in the U.S. private sector affect economic performance - productivity, profitability, investment, and growth. Freeman and Medoff are clearly correct that union productivity effects vary substantially across workplaces. Their conclusion that union effects are on average positive and substantial cannot be sustained, subsequent evidence suggesting an average union productivity effect near zero. Their speculation that productivity effects are larger in more competitive environments appears to hold up, although more evidence is needed. Subsequent literature continues to find unions associated with lower profitability, as noted by Freeman and Medoff. Unions are found to tax returns stemming from market power, but industry concentration is not the source of such returns. Rather, unions capture firm quasi-rents arising from long-lived tangible and intangible capital and from firm-specific advantages. Lower profits and the union tax on asset returns leads to reduced investment and, subsequently, lower employment and productivity growth. There is little evidence that unionization leads to higher rates of business failure. Given the decline in U.S. private sector unionism, I explore avenues through which individual and collective voice might be enhanced, focusing on labor law and workplace governance defaults. Substantial enhancement of voice requires change in the nonunion sector and employer as well as worker initiatives. It is unclear whether labor unions would be revitalized or further marginalized by such an evolution

TOI-431/HIP 26013: A super-Earth and a sub-Neptune transiting a bright, early K dwarf, with a third RV planet

We present the bright (Vmag = 9.12), multiplanet system TOI-431, characterized with photometry and radial velocities (RVs). We estimate the stellar rotation period to be 30.5 ± 0.7 d using archival photometry and RVs. Transiting Exoplanet Survey Satellite (TESS) objects of Interest (TOI)-431 b is a super-Earth with a period of 0.49 d, a radius of 1.28 ± 0.04 R, a mass of 3.07 ± 0.35 M, and a density of 8.0 ± 1.0 g cm-3; TOI-431 d is a sub-Neptune with a period of 12.46 d, a radius of 3.29 ± 0.09 R, a mass of 9.90+1.53-1.49 M, and a density of 1.36 ± 0.25 g cm-3. We find a third planet, TOI-431 c, in the High Accuracy Radial velocity Planet Searcher RV data, but it is not seen to transit in the TESS light curves. It has an Msin i of 2.83+0.41-0.34 M, and a period of 4.85 d. TOI-431 d likely has an extended atmosphere and is one of the most well-suited TESS discoveries for atmospheric characterization, while the super-Earth TOI-431 b may be a stripped core. These planets straddle the radius gap, presenting an interesting case-study for atmospheric evolution, and TOI-431 b is a prime TESS discovery for the study of rocky planet phase curves.Fil: Osborn, Ares. University of Warwick; Reino UnidoFil: Armstrong, David J. University of Warwick; Reino UnidoFil: Cale, Bryson. George Mason University; Estados UnidosFil: Brahm, Rafael. Universidad Adolfo Ibañez; Chile. Instituto de Astrofísica; ChileFil: Wittenmyer, Robert A. University Of Southern Queensland; AustraliaFil: Dai, Fei. Division Of Geological And Planetary Sciences; Estados UnidosFil: Crossfield, Ian J. M. University of Kansas; Estados UnidosFil: Bryant, Edward M. University of Warwick; Reino UnidoFil: Adibekyan, Vardan. Universidad de Porto; PortugalFil: Cloutier, Ryan. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Collins, Karen A. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Delgado Mena, E.. Universidad de Porto; PortugalFil: Fridlund, Malcolm. Leiden University; Países Bajos. Chalmers University of Technology; SueciaFil: Hellier, Coel. Keele University; Reino UnidoFil: Howell, Steve B. NASA Ames Research Center; Estados UnidosFil: King, George W. University of Warwick; Reino UnidoFil: Lillo Box, Jorge. Consejo Superior de Investigaciones Científicas. Centro de Astrobiología; EspañaFil: Otegi, Jon. Universidad de Ginebra; Suiza. Universitat Zurich; SuizaFil: Sousa, S.. Universidad de Porto; PortugalFil: Stassun, Keivan G. Vanderbilt University; Estados UnidosFil: Matthews, Elisabeth C. Universidad de Ginebra; Suiza. Massachusetts Institute of Technology; Estados UnidosFil: Ziegler, Carl. University of Toronto; CanadáFil: Ricker, George. Massachusetts Institute of Technology; Estados UnidosFil: Vanderspek, Roland. Massachusetts Institute of Technology; Estados UnidosFil: Latham, David W. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Seager, S.. Massachusetts Institute of Technology; Estados UnidosFil: Winn, Joshua N.. University of Princeton; Estados UnidosFil: Jenkins, Jon M. NASA Ames Research Center; Estados UnidosFil: Acton, Jack S. University of Leicester; Reino UnidoFil: Addison, Brett C. University Of Southern Queensland; AustraliaFil: Diaz, Rodrigo Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias Físicas. - Universidad Nacional de San Martín. Instituto de Ciencias Físicas; Argentin

<i>TESS</i> Spots a Compact System of Super-Earths around the Naked-eye Star HR 858

Transiting Exoplanet Survey Satellite (TESS) observations have revealed a compact multiplanet system around the sixth-magnitude star HR 858 (TIC 178155732, TOI 396), located 32 pc away. Three planets, each about twice the size of Earth, transit this slightly evolved, late F-type star, which is also a member of a visual binary. Two of the planets may be in mean motion resonance. We analyze the TESS observations, using novel methods to model and remove instrumental systematic errors, and combine these data with follow-up observations taken from a suite of ground-based telescopes to characterize the planetary system. The HR 858 planets are enticing targets for precise radial velocity observations, secondary eclipse spectroscopy, and measurements of the Rossiter–McLaughlin effect

A Three Species Model to Simulate Application of Hyperbaric Oxygen Therapy to Chronic Wounds

Chronic wounds are a significant socioeconomic problem for governments worldwide. Approximately 15% of people who suffer from diabetes will experience a lower-limb ulcer at some stage of their lives, and 24% of these wounds will ultimately result in amputation of the lower limb. Hyperbaric Oxygen Therapy (HBOT) has been shown to aid the healing of chronic wounds; however, the causal reasons for the improved healing remain unclear and hence current HBOT protocols remain empirical. Here we develop a three-species mathematical model of wound healing that is used to simulate the application of hyperbaric oxygen therapy in the treatment of wounds. Based on our modelling, we predict that intermittent HBOT will assist chronic wound healing while normobaric oxygen is ineffective in treating such wounds. Furthermore, treatment should continue until healing is complete, and HBOT will not stimulate healing under all circumstances, leading us to conclude that finding the right protocol for an individual patient is crucial if HBOT is to be effective. We provide constraints that depend on the model parameters for the range of HBOT protocols that will stimulate healing. More specifically, we predict that patients with a poor arterial supply of oxygen, high consumption of oxygen by the wound tissue, chronically hypoxic wounds, and/or a dysfunctional endothelial cell response to oxygen are at risk of nonresponsiveness to HBOT. The work of this paper can, in some way, highlight which patients are most likely to respond well to HBOT (for example, those with a good arterial supply), and thus has the potential to assist in improving both the success rate and hence the cost-effectiveness of this therapy

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4---the next-generation ground-based cosmic microwave background (CMB) experiment---is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semi-analytic projection tool, targeted explicitly towards optimizing constraints on the tensor-to-scalar ratio, $r$, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2--3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments given a desired scientific goal. To form a closed-loop process, we couple this semi-analytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for $r > 0.003$ at greater than $5\sigma$, or, in the absence of a detection, of reaching an upper limit of $r < 0.001$ at $95\%$ CL.Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note: text overlap with arXiv:1907.0447

Three new brown dwarfs and a massive hot Jupiter revealed by TESS around early-type stars

Context. The detection and characterization of exoplanets and brown dwarfs around massive AF-type stars is essential to investigate and constrain the impact of stellar mass on planet properties. However, such targets are still poorly explored in radial velocity (RV) surveys because they only feature a small number of stellar lines and those are usually broadened and blended by stellar rotation as well as stellar jitter. As a result, the available information about the formation and evolution of planets and brown dwarfs around hot stars is limited. Aims. We aim to increase the sample and precisely measure the masses and eccentricities of giant planets and brown dwarfs transiting early-type stars detected by the Transiting Exoplanet Survey Satellite (TESS). Methods. We followed bright (V 6200 K that host giant companions (R > 7 R⊕) using ground-based photometric observations as well as high precision radial velocity measurements from the CORALIE, CHIRON, TRES, FEROS, and MINERVA-Australis spectrographs. Results. In the context of the search for exoplanets and brown dwarfs around early-type stars, we present the discovery of three brown dwarf companions, TOI-629b, TOI-1982b, and TOI-2543b, and one massive planet, TOI-1107b. From the joint analysis of TESS and ground-based photometry in combination with high precision radial velocity measurements, we find the brown dwarfs have masses between 66 and 68 MJup, periods between 7.54 and 17.17 days, and radii between 0.95 and 1.11 RJup. The hot Jupiter TOI-1107b has an orbital period of 4.08 days, a radius of 1.30 RJup, and a mass of 3.35 MJup. As a by-product of this program, we identified four low-mass eclipsing components (TOI-288b, TOI-446b, TOI-478b, and TOI-764b). Conclusions. Both TOI-1107b and TOI-1982b present an anomalously inflated radius with respect to the age of these systems. TOI-629 is among the hottest stars with a known transiting brown dwarf. TOI-629b and TOI-1982b are among the most eccentric brown dwarfs. The massive planet and the three brown dwarfs add to the growing population of well-characterized giant planets and brown dwarfs transiting AF-type stars and they reduce the apparent paucity

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages