Testing William Baumol’s “Toward a Newer Economics: The Future Lies Ahead!â€

20 years ago, William Baumol provided an interesting wish list that outlined his hopes for the future of economics over the next hundred years. Impatiently, this paper puts his wish list to the test by comparing the characteristics of publications that appeared in the American Economic Review before Baumol’s contribution in 1991 (1984 to 1988) and those published 20 years later (2004 to 2008), and by looking at the Job Openings for Economists between 1991 and 2009. Focusing on issues such as the role of mathematics, the short-run orientation of macroeconomics, the emphasis of economic history versus the history of economic ideas, as well as a more concrete menu of wishes for applied economics, we observe that this was not just a wish list, but is in many ways a list that offers an accurate picture of what has changed over time and what has happened in recent years.American Economic Review, William Baumol, Mathematics, Macroeconomics, Applied Economics, Job Openings

A Century of American Economic Review

Using information collected from American Economic Review publications of the last 100 years, we try to provide answers to various questions: Which are the top AER publishing institutions and countries? Which are the top AER papers based on citation success? How frequently is someone able to publish in AER? How equally is citation success distributed? Who are the top AER publishing authors? What is the level of cooperation among the authors? What drives the alphabetical name ordering? What are the individual characteristics of the AER authors, editors, editorial board members, and referees? How frequently do women publish in AER? What is the relationship between academic age, publication performance, and citation success? What are the paper characteristics? What influences the level of technique used in articles? Do connections have an influence on citation success? Who receives awards? Can awards increase the probability of publishing in AER at a later stage?American Economic Review, Publishing Economics, Rankings, Cooperation, Authors, Editors, Board Members, Referees, Connections, Awards, Paper Characteristics, Economic History, History of Economic Thought

A Century of American Economic Review

Using information collected from American Economic Review publications of the last 100 years, we try to provide answers to various questions: Which are the top AER publishing institutions and countries? Which are the top AER papers based on citation success? How frequently is someone able to publish in AER? How equally is citation success distributed? Who are the top AER publishing authors? What is the level of cooperation among the authors? What drives the alphabetical name ordering? What are the individual characteristics of the AER authors, editors, editorial board members, and referees? How frequently do women publish in AER? What is the relationship between academic age, publication performance, and citation success? What are the paper characteristics? What influences the level of technique used in articles? Do connections have an influence on citation success? Who receives awards? Can awards increase the probability of publishing in AER at a later stage?American Economic Review, publishing economics, rankings, cooperation,authors, editors, board members, referees, connections, awards, paper characteristics, economic history, history of economic thoug

Extraordinary Wealth, Globalization, and Corruption

The billionaires of the world attract significant attention from the media and the public. The popular press is full of books selling formulas on how to become rich. Surprisingly, only a limited number of studies have explored empirically the determinants of extraordinary wealth. Using a large data set we explore whether globalization and corruption affect extreme wealth accumulation. We find evidence that an increase in globalization increases super-richness. In addition, we also find that an increase in corruption leads to an increase in the creation of super fortune. This supports the argument that in kleptocracies large sums are transferred into the hands of a small group of individuals.Globalization, Extraordinary Wealth, Corruption, Superstars

Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance

In this paper, we consider the coherent theory of (epistemic) uncertainty of Walley, in which beliefs are represented through sets of probability distributions, and we focus on the problem of modeling prior ignorance about a categorical random variable. In this setting, it is a known result that a state of prior ignorance is not compatible with learning. To overcome this problem, another state of beliefs, called \emph{near-ignorance}, has been proposed. Near-ignorance resembles ignorance very closely, by satisfying some principles that can arguably be regarded as necessary in a state of ignorance, and allows learning to take place. What this paper does, is to provide new and substantial evidence that also near-ignorance cannot be really regarded as a way out of the problem of starting statistical inference in conditions of very weak beliefs. The key to this result is focusing on a setting characterized by a variable of interest that is \emph{latent}. We argue that such a setting is by far the most common case in practice, and we provide, for the case of categorical latent variables (and general \emph{manifest} variables) a condition that, if satisfied, prevents learning to take place under prior near-ignorance. This condition is shown to be easily satisfied even in the most common statistical problems. We regard these results as a strong form of evidence against the possibility to adopt a condition of prior near-ignorance in real statistical problems.Comment: 27 LaTeX page

Learning about a Categorical Latent Variable under Prior Near-Ignorance

It is well known that complete prior ignorance is not compatible with learning, at least in a coherent theory of (epistemic) uncertainty. What is less widely known, is that there is a state similar to full ignorance, that Walley calls near-ignorance, that permits learning to take place. In this paper we provide new and substantial evidence that also near-ignorance cannot be really regarded as a way out of the problem of starting statistical inference in conditions of very weak beliefs. The key to this result is focusing on a setting characterized by a variable of interest that is latent. We argue that such a setting is by far the most common case in practice, and we show, for the case of categorical latent variables (and general manifest variables) that there is a sufficient condition that, if satisfied, prevents learning to take place under prior near-ignorance. This condition is shown to be easily satisfied in the most common statistical problems.Comment: 15 LaTeX page

Analysis of Routine and Integrative Data from Clostridioides difficile Infection Diagnosis and the Consequent Observations

Abstract: Background: Clostridioides difficile Infection (CDI) is an acute disease that needs a fast proper treatment. Unfortunately, the diagnosis, and above all the understanding of the results, remain arduous. Objective: This study analyzed routine and integrative results of all fecal samples from patients over time. Our aim was to understand the dynamics of CDI infection and the meaning of \u201cdifficult to interpret\u201d results, to make physicians better understand the various tools they can use. Methods: We evaluated routine results obtained from 815 diarrheal stools with Enzyme Immunoassay (EIA) that detects C. difficile Glutamate Dehydrogenase (GDH) antigen and toxin B. We also reanalyzed a part of samples using integrative tests: a Real-time polymerase chain reaction (RT-PCR) for C. difficile toxin B gene (tcdB) and the automated immunoassay VIDAS C. difficile system for GDH and toxins A/B. Results: EIA GDH positivity increased through multiple testing over time, with a P value <0.001, depicting a sort of bacterial growth curve. Eighty-five percent of GDH positive/toxin B negative, i.e., discrepant, samples PCR were tcdB positive, 61.5% of discrepant tcdB positive samples were VIDAS toxins A/B positive, and 44.4% of GDH EIA negative stools were VIDAS GDH positive. Conclusion: The results confirmed the low sensitivity of the EIA system for C. difficile GDH and toxins, questioned the use of the latter for concluding any CDI diagnostic algorithm, and led us to indicate the algorithm beginning with tcdB molecular research, and continuing in positive cases with VIDAS CD GDH method, as the most effective for CDI

Convolutional Neural Network-Based Automatic Analysis of Chest Radiographs for the Detection of COVID-19 Pneumonia: A Prioritizing Tool in the Emergency Department, Phase I Study and Preliminary “Real Life” Results

The aim of our study is the development of an automatic tool for the prioritization of COVID-19 diagnostic workflow in the emergency department by analyzing chest X-rays (CXRs). The Convolutional Neural Network (CNN)-based method we propose has been tested retrospectively on a single-center set of 542 CXRs evaluated by experienced radiologists. The SARS-CoV-2 positive dataset (n = 234) consists of CXRs collected between March and April 2020, with the COVID-19 infection being confirmed by an RT-PCR test within 24 h. The SARS-CoV-2 negative dataset (n = 308) includes CXRs from 2019, therefore prior to the pandemic. For each image, the CNN computes COVID-19 risk indicators, identifying COVID-19 cases and prioritizing the urgent ones. After installing the software into the hospital RIS, a preliminary comparison between local daily COVID-19 cases and predicted risk indicators for 2918 CXRs in the same period was performed. Significant improvements were obtained for both prioritization and identification using the proposed method. Mean Average Precision (MAP) increased (p < 1.21 × 10(−21) from 43.79% with random sorting to 71.75% with our method. CNN sensitivity was 78.23%, higher than radiologists’ 61.1%; specificity was 64.20%. In the real-life setting, this method had a correlation of 0.873. The proposed CNN-based system effectively prioritizes CXRs according to COVID-19 risk in an experimental setting; preliminary real-life results revealed high concordance with local pandemic incidence

Reversible Tuning of Superconductivity in Ion-Gated NbN Ultrathin Films by Self-Encapsulation with a High-κ Dielectric Layer

Ionic gating is a powerful technique for tuning the physical properties of a material via electric field-induced charge doping, but is prone to introduce extrinsic disorder and undesired electrochemical modifications in the gated material beyond pure electrostatics. Conversely, reversible, volatile, and electrostatic modulation is pivotal in the reliable design and operation of novel device concepts enabled by the ultrahigh induced charge densities attainable via ionic gating. Here we demonstrate a simple and effective method to achieve reversible and volatile gating of surface-sensitive ultrathin niobium nitride films via controlled oxidation of their surface. The resulting niobium oxide encapsulation layer exhibits a capacitance comparable to that of nonencapsulated ionic transistors, withstands gate voltages beyond the electrochemical stability window of the gate electrolyte, and enables a fully reversible tunability of both the normal-state resistivity and the superconducting transition temperature of the encapsulated films. Our approach should be transferable to other materials and device geometries where more standard encapsulation techniques are not readily applicable

Event-based surveillance during EXPO Milan 2015. Rationale, tools, procedures, and initial results

More than 21 million participants attended EXPO Milan from May to October 2015, making it one of the largest protracted mass gathering events in Europe. Given the expected national and international population movement and health security issues associated with this event, Italy fully implemented, for the first time, an event-based surveillance (EBS) system focusing on naturally occurring infectious diseases and the monitoring of biological agents with potential for intentional release. The system started its pilot phase in March 2015 and was fully operational between April and November 2015. In order to set the specific objectives of the EBS system, and its complementary role to indicator-based surveillance, we defined a list of priority diseases and conditions. This list was designed on the basis of the probability and possible public health impact of infectious disease transmission, existing statutory surveillance systems in place, and any surveillance enhancements during the mass gathering event. This article reports the methodology used to design the EBS system for EXPO Milan and the results of 8 months of surveillance