The Macroeconomic Role of Unemployment Compensation

The standard motivation for unemployment compensation is consumption smoothing and most papers in the literature have analyzed trade-offs involving consumption smoothing and moral hazard. This paper shows how such policy can increase output by enhancing the assignment of workers to jobs in the face of firm productivity heterogeneity and skill-biased technological change. It shows that in order to do so policy needs to be a function of the properties of the firm's productivity distribution. The paper undertakes an empiricallygrounded, normative analysis of this issue. The analysis also bears upon the wage distribution, showing how optimal unemployment compensation policy is affected by wages and affects them in turn. A key insight emerging from the analysis is that the degree of firm productivity heterogeneity, in terms of skewness and variance, matters for the design of the time path of unemployment compensation.Productivity, heterogeneity, unemployment compensation policy, technological change, assortative matching

Firm productivity dispersion and the matching role of UI policy

This paper studies optimal UI policy from the perspective of worker assignment to heterogenous jobs in an environment of random matching. Workers react to UI policy through job acceptance decisions; firms react to UI policy through wage posting. There is endogenous assortative matching as a result of the fact that UI policy induces a time profile for reservation wages, shifting the labor force towards the more productive firms. The relation between productivity dispersion and UI policy is mediated by the wage posting policies of firms that take both productivity and policy into account. Optimal UI policy is shown to crucially depend on the properties of the firm productivity distribution, such as its variance and skewness

Interior and edge magnetization in thin exfoliated CrGeTe3 films

CrGeTe3 (CGT) is a semiconducting vdW ferromagnet shown to possess magnetism down to a two-layer thick sample. Although CGT is one of the leading candidates for spintronics devices, a comprehensive analysis of CGT thickness dependent magnetization is currently lacking. In this work, we employ scanning SQUID-on-tip (SOT) microscopy to resolve the magnetic properties of exfoliated CGT flakes at 4.2 K. Combining transport measurements of CGT/NbSe2 samples with SOT images, we present the magnetic texture and hysteretic magnetism of CGT, thereby matching the global behavior of CGT to the domain structure extracted from local SOT magnetic imaging. Using this method, we provide a thickness dependent magnetization state diagram of bare CGT films. No zero-field magnetic memory was found for films thicker than 10 nm and hard ferromagnetism was found below that critical thickness. Using scanning SOT microscopy, we identify a unique edge magnetism, contrasting the results attained in the CGT interior.Comment: Main text: 15 pages, 5 figures. Supplementary information: 9 pages, 10 figures. Supplementary videos:

The macroeconomic role of unemployment compensation

The standard motivation for unemployment compensation is consumption smoothing and most papers in the literature have analyzed trade-offs involving consumption smoothing and moral hazard. This paper shows how such policy can increase output by enhancing the assignment of workers to jobs in the face of firm productivity heterogeneity and skill-biased technological change. It shows that in order to do so policy needs to be a function of the properties of the firm’s productivity distribution. The paper undertakes an empiricallygrounded, normative analysis of this issue. The analysis also bears upon the wage distribution, showing how optimal unemployment compensation policy is affected by wages and affects them in turn. A key insight emerging from the analysis is that the degree of firm productivity heterogeneity, in terms of skewness and variance, matters for the design of the time path of unemployment compensation

Efficient Unemployment Insurance Time Path

The Paper examines the time sequencing of UI benefits in a general equilibrium framework, with random matching and endogenously determined wages. A key feature of the model is that policymakers exploit random matching to produce some assortative matching through UI policy. The Paper considers a mechanism whereby a declining UI time profile makes unemployed workers relatively choosier at the beginning of their unemployment spell. Hence they tend to continue to search unless a sufficiently attractive offer is received. Later on, the reservation wage drops and agents are willing to take less attractive job offers. Firms respond by introducing endogenous market segmentation. In equilibrium more productive firms offer higher wages facing lower vacancy risk, whereas less productive firms offer lower wages and face higher vacancy risk. The role of a declining profile UI regime is to insure enough heterogeneity among workers, so as to obtain enhanced matching with heterogenous firms. The longer the duration, the higher the degree of induced heterogeneity. Such optimal UI policy is shown to crucially depend on the nature of technological dispersion.benefit duration; matching; search; technology dispersion; UI

BATScan: A radar classification tool reveals large‐scale bat migration patterns

Abstract Bat movement and behaviour are still mostly understudied over large scales. High‐altitude, nocturnal activity makes visual identification of bats from the ground virtually impossible, dramatically hindering our ability to study their movement ecology. Despite the wide use of radar in aeroecology, its application to study specific taxa is limited due to incomplete target classification abilities. BATScan is a bat classifier for vertical‐looking radar data, which enables identifying bats and characterizing their unique aeroecology. We constructed the classifier using data from 10 radar deployments, covering a wide range of habitats on a central bird migration flyway over a 7‐year period, comprising ~18 million observations. We analysed animal migration above the Hula Valley, home to over 30 species of bats spanning a range of 5–150 g in size and exhibiting a variety of ecological characteristics. We distinguished bat‐labelled radar echoes for training according to phenology, morphology and movement ecology of bats, birds and insects. Several non‐bat datasets were constructed and joined to train classifiers under increasing levels of difficulty. Class imbalance in the resulting training data was handled using a generative adversarial network for up‐sampling the much smaller bat dataset. The resulting classification tool reached a high level of accuracy and precision, and was further scrutinized with an extensive set of ecological validations. Bats perform seasonal migrations over long distances, but little is known about the spatial and temporal characteristics of this movement, and the ability to study it at a large scale has so far been limited. We present the Israeli BATScan dataset, containing over 60,000 bat observations spanning the entire country and representing multiple habitats. Using this data, we produce an unprecedented large scale, highly detailed documentation of the yearly movements of bats on a major migration flyway, and distinguish this pattern from bird migration over space and time. So far, radar aeroecology dealt primarily with birds, increasingly with insects, and only rarely with bats. We present BATScan, a classification tool that can incorporate bats into the framework of radar aeroecology to finally enable a comprehensive description of animal aeroecology

Fetal and Perinatal Outcome Following First and Second Trimester COVID-19 Infection: Evidence from a Prospective Cohort Study

A novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus causing coronavirus disease 2019 (COVID-19) disease, which emerged as a global pandemic. Data regarding the implications of COVID-19 disease at early gestation on fetal and obstetric outcomes is scarce. Thus, our aim was to investigate the effect of first and second trimester maternal COVID-19 disease on fetal and perinatal outcomes. This was a prospective cohort study of pregnant women with a laboratory-proven SARS-COV-2 infection contracted prior to 26 weeks gestation. Women were followed at a single tertiary medical center by serial sonographic examinations every 4–6 weeks to assess fetal well-being, growth, placental function, anatomic evaluation and signs of fetal infection. Amniocentesis was offered to assess amniotic fluid SARS-COV-2-PCR (polymerase chain reaction) and fetal brain magnetic resonance imaging (MRI) was offered at 30–32 weeks gestation. Demographic, obstetric and neonatal data were collected from history intake, medical charts or by telephone survey. Perinatal outcomes were compared between women infected at first vs. second trimester. 55 women with documented COVID-19 disease at early gestation were included and followed at our center. The mean maternal age was 29.6 ± 6.2 years and the mean gestational age at viral infection was 14.2 ± 6.7 weeks with 28 (51%) women infected at the first trimester and 27 (49%) at the second trimester. All patients but one experienced asymptomatic to mild symptoms. Of 22 patients who underwent amniocentesis, none had evidence of vertical transmission. None of the fetuses exhibited signs of central nervous system (CNS) disease, growth restriction and placental dysfunction on serial ultrasound examinations and fetal MRI. Pregnancies resulted in perinatal survival of 100% to date with mean gestational age at delivery of 38.6 ± 3.0 weeks and preterm birth <37 weeks rate of 3.4%. The mean birthweight was 3260 ± 411 g with no cases of small for gestational age infants. The obstetric and neonatal outcomes were similar among first vs. second trimester infection groups. We conclude SARS-CoV-2 infection at early gestation was not associated with vertical transmission and resulted in favorable obstetric and neonatal outcomes