dataesr/scientific-paragraphs-categorization huggingface dataset:
The results seem to indicate that losses associated with rare events are relatively small supporting the alternative view that the salient feature of a peso state is a large value of the SDF. 19 To save space, we do not report the betas of the RX factor but they are available upon request. 20 We reach very similar conclusions using factor mimicking portfolios. See  Lustig et al. (2011). 21 We could rely on a simple forecasting model relating M oM t or V alue t to the future one-month return of the currencies. However this may introduce estimation errors in the analysis. 22 Reuters captures data at 4pm UK time while Bloomberg captures them at 5pm UK time. See Thomson  Reuters (2018)  and  Bloomberg (2018)  23 Reuters' spreads may widen in case of spike of volatility but only up to a pre-fixed maximum.
The special issue starts with a paper by Karimov and Konings analysing the profile of the employment shock, using a detailed Belgian dataset which allows to distinguish between start-ups and incumbent firms (grouped by age classes). The paper finds that the employment losses are mainly located with incumbent firms but predicts a more structural, medium term negative effect associated missing generation of start-ups. This provides a more nuanced assessment of the shape of the recovery in particular it contrasts with US evidence on business creation in 2020. The next set of papers discusses the constraints which complicate the policy response and the impact this has on the shape of the recession. The paper by Kollmann identifies the nature of the shock through the lens of a new Keynesian macroeconomic model where policy is constrained by an (expectations driven) liquidity trap.
The abstract is often the only section read by users of biomedical articles. 1 On the basis of the abstract, many readers decide whether they will read the full text. The abstract is also critical to people who do not have access to the full text, owing to pay walls or because the article is written in a language they do not understand. Therefore, abstracts should enable a quick assessment of the study's objectives, purpose, and key design features; present an accurate picture of the validity of the main results; and allow readers to evaluate whether the study can meet their information needs. 2  Informative abstracts are also key to enabling effective literature searches in electronic databases, notably in the context of systematic reviews. 4] [5] [6]  The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement was developed to improve the reporting of systematic reviews, primarily for reviews of interventions.
Compared with throat culture, rapid antigen detection tests (RADTs) offer diagnosis at the point of care. Objectives: To evaluate the diagnostic accuracy of RADTs for diagnosing GAS in children with pharyngitis. Methods: We searched 8 databases (including MEDLINE and Embase) from 1980 through 2015. We included studies that compared RADT for GAS pharyngitis with throat culture on a blood agar plate in a microbiology laboratory in children in ambulatory care. Quality assessment was carried out using QUADAS-2. We used bivariate meta-analysis to estimate summary sensitivity and specificity, and to investigate variability in accuracy across studies. Results: We included 98 unique studies in the review (116 test evaluations; 101 121 participants). The overall methodological quality of included studies was poor, mainly because many studies were at high risk of bias regarding patient selection and the reference standard used.
Explanation The abstract should briefly highlight the main strengths and limitations of the review process and the included evidence. Review limitations might include search restrictions (for example, number of databases, language, dates) and lack of independent study selection and data extraction by more than one person, for example. Limitations of included evidence might include risk of bias (examples 9a-b), unavailability of data (examples 9a-b), variability of accuracy estimates (example 9c), imprecision (for example, due to few studies or small sample sizes; examples 9a-b), or low applicability of study findings (for example, due to patient selection within the included studies; example 9a). Such limitations may lead to summary estimates of accuracy that may not reflect the "true" performance of a test or may limit applicability in real world clinical use.
Adapted with permission of authors fromCohen JF et al. Cochrane Database Syst Rev 2016(7):CD010502. on 31 March 2021 at Barnes Library Medical School. Protected by copyright. http://www. bmj. com/ BMJ: first published as 10. 1136/bmj. n265 on 15 March 2021. Downloaded from to report methods used for comparisons of multiple index tests and reasons for not pooling study results (example A1c).
Funding: No specific funding was received to develop this explanation and elaboration document. JJD is a  UK National Institute for Health Research (NIHR ) senior investigator emeritus. YT is funded by a  UK NIHR  postdoctoral fellowship. JJD and YT are supported by the  NIHR Birmingham Biomedical Research Centre. MDFM is supported by the  Canadian Institute for Health Research  (grant number  375751 ), the  Canadian Agency for Drugs and Technologies in Health (CADTH) , and the  Standards for Reporting of Diagnostic Accuracy Studies Group (STARD). BT is a  Fonds de recherche du Québec -Santé distinguished scholar  and a Tier 1 Canada research chair. BHW is funded by a  UK   MRC clinician scientist fellowship  ( MR/N007999/1 ). DM is supported by a university research chair (uOttawa). The views expressed are those of the author(s) and not necessarily those of the  NHS ,  NIHR , or  Department of Health and Social Care.
This may suggest that the momentum effect is linked to the cryptocurrency size or liquidity. Finally, only one study-by  Yang (2019) -examines patterns of dayto-day return dependence. Interestingly, contrary to our work, the author finds evidence for momentum rather than a reversal effects. Notably, the article is based on a limited dataset of 23 core cryptocurrencies composed of 40 ERC20 tokens. This corresponds to the pattern that the investigations of more constrained asset universes are more likely to report momentum profits.
day Positive and significant returns on the majority of long-short momentum portfolios up to 0. 63% daily. The table summarizes the major studies of the momentum and reversal effects in cryptocurrency markets. 2 If a cryptocurrency is listed on multiple exchanges, the crypto asset prices retrieved from https://coinmarketcap. com are volume-weighted averages of market pair prices from different exchanges. The rationale for using a volumeweighted average is that the high-volume markets tend to be more liquid and less prone to fluctuations. Therefore, the higher percentage of volume that is contributed from the pair, the more influence it has on the average price in our dataset. For additional details, please see https://support. coinmarketcap. com/hc/en-us/sections/360008888252-Metric-Methodologies.
In particular, in their literature survey,  Ma, Anderson, and Marshall (2016)  conclude that Amihud's measure is the best price impact proxy. The measurement of the bid-ask spread is less straightforward. To the best of our knowledge, high-quality and comprehensive data on bid-ask spreads are not publicly available for the universe of cryptocurrencies as broad as ours. Therefore, in line with the argumentation in Novy-Marx and Velikov (2016) that builds on  Roll (1984) , we estimate the bid-ask spread for day t as: BAS = ̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅ ̅ -cov(R t-1 ; R t-2 ) √ (9) where BAS denotes the percentage bid-ask spread, cov denotes the covariance function, and R t-1 and R t-2 are lagged cryptocurrency returns. Similarly, as for other variables, we estimate BAS with trailing 20-weeks of daily data.
The subset 1 (50) on the horizontal axis denotes the portfolio of cryptocurrencies with the smallest (biggest) MV. ILLIQ is estimated using 20 weeks of daily data (divided by 1,000,000). BAS is estimated based on trailing 20 weeks of daily returns (R t ) using the formula BAS = ̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅ -cov(R t , R t-1 ).
This point is important in the framing of the search query (see below), as a particular effort had to be devoted to the selection of words conveying this idea. We reviewed the literature by conducting a systematic database search with a detailed search query. Two academic literature databases were used to ensure extensive literature coverage: Elsevier Scopus and Thomson Reuters Web of Science databases. We searched for publications in English, concentrating on scientific articles, book chapters and conference proceedings. The The query is composed of three main groups. The first reflects the concept of 'climate change'. The second-the largest group-reflects the concept of 'response [to climate change]', with the definition provided above. The third group reflects the concept of 'energy use'.
Study selection The database and grey literature search were done in Paris (France), on May 2nd 2019 and updated with Scopus database on November 11th, 2019. The search returned 10 117 papers in total, and 6684 after removing duplicates. Not all papers were relevant, and we first excluded papers which were obviously out of scope based on their title (1266 papers selected). 8 We then checked for relevance based on the abstracts. This resulted in the selection of 562 papers. For robustness, more than half of the abstracts (randomly chosen) were screened by at least two different researchers (we used Abstrackr online tool (Wallace et al 2012) to carry this out). We excluded 233 publications after the full-text reading and finally found 329 publications being fully relevant at the end of the screening process.
Databases and data management We imported all bibliographic data and publication metadata directly from SCOPUS and Web of Science. We then attributed a unique ID for each article and built a SQLite database with different tables: • A table containing the ID and bibliographic data of all the 6684 publications identified in our search and retained after removing duplicates, as well as their final status after screening. • A table containing 6106 pieces of information gathered from the 304 publications reviewed (as one publication often studies multiple places, scenarios, projections, etc. ). Each observation is linked to its publication by the unique ID.
Acknowledgments This study received funding from the  French Agence Nationale de la Rercherche  through the projects  VITE  ( ANR-14-CE22-0013-03 ) and  DRAGON  ( ANR-14-ORAR-0005 ). We also thank the  French ANR Convergence Institute   CLAND  project for support. This paper wouldn't have been possible without the help of  Patrice Dumas ,  David Makowski ,  Samuel Morin ,  Vivien Fisch  and  Thierry Brunelle.
In this paper, we build a new test of RE. Our test only requires having access to the marginal distributions of subjective beliefs and realizations, and, as such, can be applied quite broadly. In particular, this test can be used in a data combination context, where individual realizations and subjective beliefs are observed in two different datasets that cannot be matched. Such situations are common in practice (see, e. g. ,  Delavande (2008) , Arcidiacono, Hotz, and Kang (2012), Arcidiacono, Hotz, Maurel, and Romano (2014),  Stinebrickner and Stinebrickner (2014a) , Gennaioli, Ma, and Shleifer (2016),  Kuchler and Zafar (2019) ,  Boneva and Rauh (2018) , Biroli, Boneva, Raja, and Rauh (forthcoming)). Besides, even in surveys for which an explicit aim is to measure subjective expectations, such as the Michigan Survey of Consumers or the Survey of Consumer Expectations of the New York Fed, expectations and realizations can typically only be matched for a subset of the respondents.
g. ,  Lovell (1986) ,  Gourieroux and Pradel (1986) ,  Ivaldi (1992) , for seminal contributions). On the empirical side, we contribute to a rapidly growing literature on the use of subjective expectations data in economics (see, e. g. ,  Manski (2004) ,  Delavande (2008) , Van der Klaauw and Wolpin (2008), Van der Klaauw (2012),  Arcidiacono et al. (2014) , de Paula, Shapira, and Todd (2014),  Stinebrickner and Stinebrickner (2014b) ,  Wiswall and Zafar (2015) ). In this paper, we show how to incorporate all of the relevant information from subjective beliefs combined with realized data to test for rational expectations. The remainder of the paper is organized as follows. In Section 2, we present the general set-up and the main theoretical equivalences underlying our RE test. In Section 3, we introduce the corresponding statistical tests and study their asymptotic properties.
Section 4 illustrates the finite sample properties of our tests through Monte Carlo simulations. Section 5 applies our framework to expectations about future earnings. Finally, Section 6 concludes. The Appendix gathers the proofs of the equivalence results. We consider in the Online Supplementary Material (D'Haultfoeuille, Gaillac, and Maurel (2021)) various theoretical extensions, additional simulation results, additional material on the application, and all the remaining proofs. Finally, the companion R package RationalExp, described in the user guide (D'Haultfoeuille, Gaillac, and Maurel (2018a)), performs the test of RE.
Data Using the tests developed in Section 3, we now investigate whether household heads form rational expectations on their future earnings. We use for this purpose data from the Survey of Consumer Expectations (SCE), a monthly household survey that has been conducted by the Federal Reserve Bank of New York since 2012 (see Armantier, Topa, Van der Klaauw, and Zafar (2017), for a detailed description of the survey, and Kuchler and Zafar (2019); Conlon, Philossoph, Wiswall, and Zafar (2018); Fuster, Kaplan, and Zafar (forthcoming) for recent articles using the SCE). The SCE is conducted with the primary goal of eliciting consumer expectations about inflation, household finance, labor market, as well as housing market. It is a rotating internet-based panel of about 1200 household heads, in which respondents participate for up to 12 months.
We combine this data with current earnings (Y ) declared in July 2015 and November 2015 by the respondents who are working full-time or part-time at the time of the survey. 11 This leaves us with a final sample of 2993 observations, which is composed of 1565 earnings expectation observations, and 1428 realized earnings observations. 51% (1536) of these observations correspond to the subsample of respondents who are reinterviewed at least once. We refer to Table  1  for additional details on our sample.
Implementation of the test We summarize how we implemented the test in practice, either on the overall sample or on each subsample corresponding to the binary covariates in Table  1. For each case, we start by winsorizing the distribution of realized earnings (Y ) and earnings beliefs (ψ) at the 95% level. 12 Then we perform the test without covariates, where we allow for multiplicative aggregate shock, and thus test H 0S , with q(y; c) = y/c. 13 Then we use the function test of our companion R package RationalExp. 14 We choose the same values for the tuning parameters b 0 = 0 3 and κ = 0 001 as in the Monte Carlo simulations in Section 4. We also set p = 0 05, = 0 05, and η = 10 -6. Following  Andrews and Shi (2017) , the interval Y is approximated by a grid of length 100 from min i=1 n Y i to max i=1 n Y i.
Model ACC2 ACC2 represents four domains of the global earth system: i) physical climate system, ii) carbon cycle system, iii) atmospheric chemistry system, and iv) economy system. The first three domains are described in the next paragraph and the last one in the paragraph that follows. We keep the model description succinct here, only describing the aspects most pertinent to our present analysis. The current model was developed from earlier simple climate models  (59, 60)  and produces an equivalent output with the one used in ref. (23). The model is written by the General Algebraic Modeling System (GAMS) language. The physical climate system is represented by an energy balance model coupled with a heat diffusion model  (22, 61). Radiative forcing agents considered in the model include CO 2, CH4, N2O, SF6, 29 species of halocarbons, tropospheric and stratospheric O 3, and stratospheric water vapor.
e. zero emissions from fossil fuel CO 2). These constraints allow larger changes in the abatement level than those found in the 450 ppm CO 2eq scenarios in the AR5 database (Supplementary Figs. 12 to 14 of ref  (23) ). The maximum abatement levels for CO 2 (fossil fuel origin), CH 4, and N2O are assumed at 112%, 70%, and 50%, respectively. The abatement potential for CO2 can exceed 100% primarily because the IAM, on which our CO 2 MAC curve is based, considers bioenergy combined with carbon capture and storage as an option in the mitigation portfolio  (44). Our approach is kept simple and works under the assumption that CO 2 and non-CO2 mitigation measures are interchangeable, which is partially true given the necessity to finance mitigation actions but may also break down for measures involving co-reduction of GHGs.
Acknowledgments The authors are grateful for comments and suggestions from  Seita Emori ,  Jan Fuglestvedt ,  Brian O'Neill ,  Hideo Shiogama ,  Kayo Tanaka ,  Junichi Tsutsui , and  Tokuta Yokohata , which were useful for this study. " Cost-effective implementation of the Paris Agreement using flexible greenhouse gas metrics "  Katsumasa Tanaka ,  Olivier Boucher ,  Philippe Ciais ,  Daniel Johansson ,  Johannes Morfeldt  arXiv: 2006. 01901v2 ( 26 November 2020 ).
Funding This work benefited from State assistance managed by the  National Research Agency in France  under the " Programme d'Investissements d'Avenir"  under the reference " ANR-19-MPGA-0008 ". K. T. was supported by a  Make Our Planet Great Again (MOPGA) Short-Stay  grant in France (N° dossier:  927201A ). O. B. acknowledges support from the  Ministère de la transition écologique et solidaire (MTES) of France through the "Convention relative à l'attribution d'un appui financier au bénéfice des services climatiques. ".
Our empirical approach focused on social capital, instead of income or wealth, provides an innovative way to apprehend and to study in its entirety and nationwide how ''the powerful upper tail" functions. Drawing on this unique dataset of 1000 hyper-elites, we show to what extent position of power is associated to four key elite network dimensions: size, quality, diversity of contacts and strength of ties. More specifically, the quality and diversity of ties are among the most relevant determinants of access to positions of power. Our analysis sheds light on the hyper-elite strategy of network building to ''keep themselves to themselves" and on the importance attached to casts and other inherited positions. It explains the limited social mobility and the huge gap between the elites and the majority of the population, which are among the causes of Madagascar's recession.
Capturing the hyper-elites through their social capital Social networks have long been a topic of interest for sociologists and more recently for economists, given their key role in the labour market. However, quantitative research remains thin on the ground as to the characteristics and role of social networks for elites, mainly because of a lack of data. In this paper, we use the first individual database from a unique representative statistical survey of a country's elite members  (ELIMAD 2012 (ELIMAD -2014)). This dataset provides previously unavailable rich and exceptionally detailed information on the elite's positions and social network. Elites were asked to give all the elite positions they had held during their lifetime and extensive information on their elite connections. Our statistical approach focused on social capital (instead of financial capital) can constitute a credible option to capture in its entirety and nationwide the ''powerful upper tail" (of distribution of power), a complementary or alternative approach to strategies based on national account or tax records  (Piketty, 2005; Anand and Segal, 2017).
The survey and the data: ELIMAD a unique dataset With a sample size of 1000 elite members, ELIMAD is a representative comprehensive survey designed to capture the powerful ''upper tail" in Madagascar. It is the first of its kind to our knowledge. The top elites are interviewed on three areas: their background and trajectory (both personal and family) via a biographical approach, their social networks (scope, structure and characteristics), and their values (cultural and in terms of development). It poses a triple methodological challenge: definition and scope of the universe to be studied (who are the elites?), representativeness of the sample selected (how to put together a comprehensive list of the elites for the sample frame to minimize sample errors?), and reliability of the information collected (how to guarantee honest, and systematic, answers to minimize measurement errors and non-responses?).
Acknowledgments The fieldwork was funded by  IRD  and  AFD. The authors gratefully acknowledge the team from  Coef Ressources  for their technical contribution and the coordination of the survey in the field. We further thank  Jean-Michel Wachsberger ,  François Combarnous ,  Marc Raffinot ,  Jean-Philippe Berrou ,  Catherine Araujo  and  Marcel Fafchamps , and seminar and conference participants at  DIAL Development Conference (Paris), CERDI Development doctoral day, IEDES-Paris I Atelier croisé D&S Dial Mobilités, GREThA-IDEA International Conference on Economic Development (Bordeaux)  for useful comments on previous versions of this paper. The usual disclaimer applies.
Data on commuting Ideally we would have based our analysis on a mobility survey related to overall daily mobility of the whole population (both households and their individual members), as measured for instance in conventional household travel surveys (HTS). However, the sampling of the HTS in Lyon covers mainly the dense urban area and is parsimonious in low density outskirts. This is why we rely upon another survey focused on (work) commuting only which has the advantage of a much higher sampling rate and more variability in the representation of various locations in the urban region. Therefore we use an extract from the French national census about the population holding a job  (INSEE MOBPRO 2013). This institutional source has a high sampling rate (around 27%) and provides dozens of individual information including the usual home-work transportation mode.
Through this coding variables' values are "coarsened" (i. e. grouped) so that they have the same meaning according to the researcher assumptions. This is the case for instance for age or household size. Some variables are already coarsened and taken as they are, like gender, or may be recoded like qualification level which is coarsened along main diploma stages. Again we have to make a compromise with the availability of variables in the MOBPRO database. We capture lifecycle stage through individual's age (discretized in classes) and household size. Income is unfortunately not available, so we approximate it through the housing tenure status (owner, social housing tenant, other tenant) and the qualification level (the highest diploma obtained by the individual). Person origin is measured through the status of immigrant or not.