计量经济分析 = Econometric analysis

Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

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Maximizing the spread of influence through a social network

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

The authors examine the effect of consumer reviews on relative sales of books at Amazon.com and Barnesandnoble.com. The authors find that (1) reviews are overwhelmingly positive at both sites, but there are more reviews and longer reviews at Amazon.com; (2) an improvement in a book's reviews leads to an increase in relative sales at that site; (3) for most samples in the study, the impact of one-star reviews is greater than the impact of five-star reviews; and (4) evidence from review-length data suggests that customers read review text rather than relying only on summary statistics.

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The Effect of Word of Mouth on Sales: Online Book Reviews

In traditional models, arbitrage in a given security is performed by a large number of diversified investors taking small positions against its mispricing. In reality, however, arbitrage is conducted by a relatively small number of highly specialized investors who take large positions using other people's money. Such professional arbitrage has a number of interesting implications for security pricing, including the possibility that arbitrage becomes ineffective in extreme circumstances, when prices diverge far from fundamental values. The model also suggests where anomalies in financial markets are likely to appear, and why arbitrage fails to eliminate them.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w5167.pdf?abstractid=225230&mirid=1&type=2

The Limits of Arbitrage

A large literature following Hirsch (2005) has proposed citation-based indexes that could be used to rank academics. This paper examines how well several such indexes match labor market outcomes using data on the citation records of young tenured economists at 25 U.S. departments. Variants of Hirsch’s index that emphasize smaller numbers of highly-cited papers perform better than Hirsch’s original index and have substantial power to explain which economists are tenured at which departments. Adjustment factors for differences across fields and years of experience are presented.

How Does the Market Use Citation Data? The Hirsch Index in Economics

We examine the evolution of economics research using a machine-learning-based classification of publications into fields and styles The changing field distribution of publications would not seem to favor empirical papers But economics' empirical shift is a within-field phenomenon; even fields that traditionally emphasize theory have gotten more empirical Empirical work has also come to be more cited than theoretical work The citation shift is sharpened when citations are weighted by journal importance Regression analyses of citations per paper show empirical publications reaching citation parity with theoretical publications around 2000 Within fields and journals, however, empirical work is now cited more

https://pubs.aeaweb.org/doi/10.1257/aer.p20171117

Economic Research Evolves: Fields and Styles

Over the past decade there has been a decline in the fraction of papers in top economics journals written by economists from the highest-ranked economics departments This paper documents this fact and uses additional data on publications and citations to assess various potential explanations Several observations are consistent with the hypothesis that the Internet improves the ability of high-profile authors to disseminate their research without going through the traditional peer-review process

Is Peer Review in Decline

Data on memory modules sales are used to explore aspects of e-retail demand. Aggregate sales are examined in state-level regressions. Discrete choice techniques are used to examine (incomplete ) hourly sales data from a price comparison site. We find a strong relationship between e-retail sales to a given state and sales tax rates that apply to purchases from offline retailers, suggesting substantial online- offline substitution and the importance of tax avoidance motives. Geography matters in two ways: consumers prefer purchasing from firms in nearby states and appear to have a separate preference for buying from in-state firms. ( JEL D12, H25, H71, L81)

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Tax Sensitivity and Home State Preferences in Internet Purchasing

This paper provides a critical review of models of the spread of the coronavirus (SARS-CoV-2) epidemic that have been influential in recent policy decisions. There is tremendous opportunity for social scientists to advance the relevant literature as new and better data becomes available to bolster economic outcomes and save lives.

https://www.nber.org/system/files/working_papers/w27007/w27007.pdf

Glenn Ellison

Papers

How Does the Market Use Citation Data? The Hirsch Index in Economics

Economic Research Evolves: Fields and Styles

Is Peer Review in Decline

Tax Sensitivity and Home State Preferences in Internet Purchasing

Policy implications of models of the spread of coronavirus: perspectives and opportunities for economists