dataesr/scientific-paragraphs-categorization huggingface dataset:
Secondary clinical analyses will be conducted according to the intention-to-treat principle: all randomized patients will be analysed in the group to which they were initially randomized, and all of their data will be used regardless of eventual treatment changes during the study. As economic analysis is not based on statistical tests, no adjustment of the α-level is needed to deal with multiple comparisons. In all analyses, p < 0. 05 will be taken to indicate statistical significance. A statistical team will analyse all data independently of the investigator. The economic analysis will also be conducted according to the intention-to-treat principle. First, the point estimate of the incremental cost/utility ratio and its bootstrap 95% CI will be calculated. We will then estimate the incremental net monetary benefit (INMB) adjusted for potential confounding factors (adherence to statins at baseline, treatment duration, and particular statin dosage) using multiple linear regression models.
The Data Safety Monitoring Board (DSMB) of the study will meet when 50% of the patients reach 12 and 24 months of follow up. We did not anticipate criteria by which the trial may be stopped, but the advice of the DSMB could be solicited in the case of unexpected safety issues or new information. In addition, all CV events will be validated by an external adjudication committee, which includes a cardiologist, a neurologist, and an internal and a geriatric medical specialist. The Sponsor's security and vigilance unit must communicate serious unexpected adverse reactions (SUSA Rs) and new information in the research in a timely manner in accordance with current regulations: -To the French National Agency for the Safety of Medicines and Health Products, (Agence Nationale de Sécurité du Médicament et des Produits de Santé (ANSM)).
This will be closely monitored through the data from the SNDS. In addition, this is why the total mortality rate was chosen as our primary endpoint. Second, patients with previous dementia cannot be included in the trial, so our results will not be generalizable to this population. Third, although our sample is quite large, we cannot exclude a tendency from the investigators to recruit people with very few CV risk factors rather than patients with advanced disease and poor outcomes. Particularly, the inclusion of patients with diabetes mellitus will be monitored. Finally, patients treated with statins are being included in the SITE trial regardless of the specific type of statin. Therefore, we will not be able to examine specific treatments or dosages. However, we believe that the SITE study will be one of the first to show that a strategy of treatment cessation is costeffective and does not adversely affect the prognosis of people over 75 years of age who are treated with statins.
Price elasticities There is no systematic, global disaggregated dataset of price elasticities, similar to the problem for income elasticities. Muhammed et al. (2011)  and  Seale and Regmi (2006)  estimated own-price elasticities simultaneously with income elasticities, using ICP data. Table  4  gives their uncompensated own-price elasticities, which show that the richer the country, the smaller the reaction to price changes. Food is the most inelastic commodity group across all countries and years but, in general, the own-price elasticities fall with rising income. Note that medical care remains very price elastic in low-income countries, that is, it has features of a luxury good, indicating access barriers for poorer people. When econometric estimates of price elasticities are not available, they could be derived through simple calibration.
Muhammad et al. (2011)  give an overview about different ways to calculate either the uncompensated or the compensated price elasticity from income elasticity and data on consumption expenditures. These calculations often make use of the dependency between price and income elasticities in the linear expenditure system developed by  Frisch (1959)  (see section 3). The uncompensated own-price elasticities in the GTAP model for example are calculated based on GTAP data with the estimated income elasticities discussed above, average budget shares and the Frisch index (see  Hertel and van der Mensbrugghe (2016)  for the formula; see section 3 and also in the Appendix, eq. 6b, for more information on the Frisch index). Together with the estimated income elasticities, these calculated price elasticities are then used to calibrated the CDE demand system of the standard GTAP model.
To do this, the estimated expansion parameters provided in the GTAP database are first regressed against GDP per capita, using a spline regression. The expansion parameters are then adjusted in the baseline such that they converge to their fitted values. Similarly, the MAGNET model, which also uses a CDE demand system, also allows for adjustments of CDE parameters to avoid unrealistically high levels of food consumption  (Woltjer et al. , 2014). Let us summarize the advantages of making the exogenous adjustments. One can use simple homothetic functions such as the CES and make adjustments to get expected baseline shares, and this would be reasonable for simulations involving small shocks to income. The non-homothetic LES system involves slightly more complex adjustments to get desired baseline shares but allows for a richer set of income elasticities.
e. an AIDADS with CES sub-nests. The parameters of the CDE are taken from the GTAP data base and the LES income elasticities are calibrated from the CDE parameters. In these alternative cases we calibrated the TFP parameters so that they all reach the same global GDP. Table  5  below reports differences in output quantities and prices at the global level compared to the default G-RDEM configuration. As could be expected, the differences for the LES functional form are the largest ones. The LES also generates a considerably higher demand for agri-food products and lower demand for certain types of services, especially recreational 7 Details can be found in  Britz and Escobar (2020). activities and dwellings. Prices of services are generally lower, reflecting the larger change in endogenous TFP growth that is needed to match the GDP projections from SSP2.
An alternative to allocating an exogenous share of GDP to government demand is to set the deficit exogenously and then the size of the government will be given by the endogenous tax revenues. The composition of final demand for government is not modelled as elaborately as private consumption. Leontief, Cobb-Douglas or CES formulations are common choices and no model that we are aware of adjusts demand system parameters (Figure  10 ). In the GTAP dataset used by most global models, government purchases are predominantly from the "Public Administration, Defense, Education, Health" sector  (Aguiar et al. , 2016) , which accounts for 94% of all government purchases in the GTAP 9 data for 2011. The commodity composition is thus driven by the production function of that sector. The latest available release of GTAP 10 (  Aguiar et al.
In other words, the expected impact on fertility are uncertain but our levels represent a potential range of impact. The attributes and their levels are summarized in Table  1. [Table  1  here] The choice experiment consisted of 12 choice tasks, i. e, 12 scenarios in which respondents had to choose between two options with ash recycling and one option to stay in the current situation (status quo). We used the Ngene software to generate a D-efficient design. On the basis of results from a pilot test (114 respondents), an experimental design with an informative Bayesian update to improve design efficiency was constructed using NGENE software  (Scarpa et al. , 2007). The originality of this experiment lies in the fact that we carried out three treatments in terms of the presentation of the choice tasks, in addition to a control group (an example is provided with Fig.
Data Before carrying out our survey, we tested our questionnaire on a focus group of 13 individuals in October 2017. While our survey also includes the questions on environmental and social acceptability, we focused the test on the choice experiment. The questionnaire was printed out, and we told the respondents that they could write on it whenever they did not understand a question, if they had any comments to formulate regarding their understanding of a sentence, or to discuss the relevance of the attributes. Once they finished reading the questionnaire, we debriefed the participants about the questionnaire in general. The respondents received an email inviting them to respond to our questionnaire through the online survey platform Limesurvey. 5  The objective was to obtain answers from the most representative sample as possible of the general French population.
[Table 2 here] We also collected data on the respondents' education. In our sample, 13. 56% have a master's degree or higher, 41. 39% have a bachelor's degree (or attended a university for a short time), 26. 14% have a high school education, 16. 63% have a secondary school education, and 2. 28% have no diploma. Regarding age, gender and location, our sample is, overall, representative of the French population, except that respondents older than 55 years old are underrepresented, as well as respondents from the Southwest of France. Note also that 77% of the sample visited a forest at least once during the last 12 months. This corresponds to previous estimates of the French population's use of forests  (Dobré et al. , 2005).
1   We thank  Henrik Andersson  for his careful reading and his comments. The UMR BETA is supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" programme  ( ANR-11-LABX-0002-01 ,  Lab of Excellence ARBRE ). This project also received financial support by the  Région Grand-Est. Benjamin Ouvrard  acknowledges funding from the  French National Research Agency (ANR)  under the Investments for the  Future (Investissements d'Avenir) program , grant  ANR-17-EURE-0010.
Reducing the cost of remitting is one of the targets within the 2030 Sustainable Development Goals (SDG 10). A key factor that causes migrants to use informal channels when sending money back home is the high cost of transferring funds through formal channels. This study examines whether and to what extent the reduction in the cost of sending remittances increases the flow of remittances to developing countries, and whether larger amounts are remitted when the cost per transaction decreases (the so-called scale effect). It uses bilateral data on remittance flows and exploits a novel dataset covering transaction costs for 30 sending and 75 receiving countries for the period 2011-2017. A gravity model of remittance flows is estimated using panel data and instrumental variable techniques to address endogeneity issues.
The results lack external validity given their national and regional focus. In terms of methodology, a one-side gravity model-with only one recipient country-is estimated in Ahmed and Martínez-Zarzoso, (2016) meaning it is not possible to properly account for multilateral resistance factors, while  Kakhkharov et al. (2017)  estimate basic panel data models at the country level with fewer than 100 observations. To address the limitations that these studies have in terms of methodology, scope and data used, this study uses bilateral data on remittance flows and exploits a global dataset of transaction costs for 30 sending nations and 75 receiving countries for the period 2011-2017. Employing an instrumental variable (IV) design, this paper examines the question of whether and to what extent the cost of remittances reduces the flow of formal remittances to developing countries 3.
Remittances are now increasingly seen as a 'new development mantra'  (Kapur, 2004). In an early study on the topic,  Lueth and Ruiz-Arranz (2008)  examine bilateral remittances for 11 countries in Asia and Europe for the period 1980-2004 in order to determine the factors that drive those flows. Their results indicate that economic activity in the sending and recipient country and other gravity variables account for more than 50% of the variation in remittances. The study finds that underdeveloped financial sectors in the home country may discourage remittances through formal channels. Distance, used as a proxy for financial transaction cost, is reported to have a negative effect on remittance flows. Similarly,  Frankel (2011) , using the same dataset, finds that distance is negatively associated with remittances.
| Data and variables The summary statistics of the main variables used in the empirical analysis are shown in Table  1. Table  A1  shows the description of the variables used in the estimations, units of measurement and sources of the data used. The list of sending and receiving countries included in the dataset is shown in Table  A2  in the Appendix. Bilateral remittances received by country i from country j in current US dollars are estimated by the World Bank using the method described in  Ratha and Shaw (2007). Annual remittance matrices are combined to generate the bilateral remittances panel for the period 2011-2017. The bilateral migration data used in this study come from two distinct sources. The starting point is the bilateral migration stocks for destination countries by major countries of origin retrieved from the United Nations Population Division.
The calculations are based on the 2015 and 2017 bilateral migration matrices. The second step involves a collection of similar immigration data from the OECD Database on Migration to obtain data on stocks of emigrants from various developing countries living in OECD countries. These two datasets are merged to generate an indicator of migrant stocks for both OECD and non-OECD countries for the period 2011-2017. Data for remittance costs are taken from Remittance Prices Worldwide (RPW), a database managed by the World Bank. The transaction cost data are available on a quarterly basis for different channels such as banks, MTOs, post offices and mobile phones. We constructed an indicator for the average transaction cost of sending USD 200 and USD 500. The total cost charged by a provider includes the remittance transaction fee and the implicit exchange rate cost that applies when the remittance transactions are paid in local currencies (computed in this database when the foreign exchange rate applied by the remittance service provider is known) 5.
This is in contrast to REM, which rests upon the strong assumption of exogeneity of all explanatory variables with respect to the error term. The solution we adopt is to use the CRE method proposed by  Mundlak (1978) , which uses F I G U R E 1 Regional overview of the costs of sending USD 200 (2011 and 2017). Source: Remittance Prices Worldwide Database 2019, World Bank. a linear projection of the time-invariant unobserved heterogeneity to relax the strong exogeneity assumption. The CRE method is easily implemented in practice by augmenting the REM with the mean of the explanatory variables that change over time  (Wooldridge, 2010). It can be shown that the coefficients of the time-varying explanatory variables are identical to the FEM estimates  (Wooldridge, 2010). Nevertheless, it is still possible that transaction costs are endogenous to remittances; failing to account for this in the model might result in biased estimates.
The results indicate that the coefficient of remittance cost remains negative and significant. The results for the top three and top five corridors are very similar. Conversely, when major corridors are excluded from the sample, the estimates of the target coefficients are not found to be statistically significant, indicating a lack of evidence to support the relevance of remittance costs for smaller corridors. As a further robustness check, we examine whether or not the remittance-enhancing effect of a reduction in transfer charges is valid for receiving countries regardless of the size of remittance inflows. In our dataset, the median amount of remittances received was USD 329. 42 million. Columns (  5 ) and (6) in Table  5  show estimations carried out on the sub-samples of receiving countries with above-and below-median remittance inflows, respectively.
| CONCLUSIONS One of the targets of SDG 10 is to bring down the cost of remitting to 3% globally by 2030, that is, less than half of today's level. In this study, we examine the extent to which reductions in remittance costs drive formal remittance flows. We used data on bilateral remittances for 30 sending and 75 receiving countries for the period 2011-2017 to estimate a gravity model of remittances applying panel data and instrumental variables approaches. The main results suggest that a reduction in remittance costs has a substantial impact on the amount of remittances received by developing countries. In particular, we found that a 1% drop in the cost of transferring USD 200 is associated with as much as a 1. 6% increase in remittance inflows. The magnitude of the impact is substantially lower when using standard panel data techniques that do not address endogeneity issues.
This simulation is used to estimate the rate at which SSW frequency might change in the future (one aspect of the so-called "dynamical sensitivity" of the stratosphere;  Grise & Polvani, 2016). Anomalies are defined as the departure from the daily evolving annual cycle of each respective model. In the piControl run, the climatology is based on the whole period, while in the historical run, only the 1979-2014 is considered for calculating the climatology. In the abrupt4xCO 2 runs, a trend is identified in some variables during the first 50 years following the switch-on of the forcing. To avoid this trend, the climatologies are computed after omitting the first 75 years except for IPSL-CM6A-LR where we omit the first 300 years, but we keep the following 600 years. A similar omission of data is performed for the analysis of SFW or vortex formation dates.
Several aspects of the stratospheric polar vortex (formation, final breakdown, and variability) are analyzed using the zonal mean zonal wind at 60°N and 10 hPa (u 60N10hPa ) for the NH and 60°S and 10 hPa for the SH. 2004 ) method (https://github. com/apendergrass/cmip6-ecs) apart from the estimate for GISS-E2. 2AP which was provided by a reviewer. We use the term "Effective Climate Sensitivity" here following the discussion in and recommendation of  Zelinka et al. (2020). 1. SSWs are identified following the criterion proposed in  Charlton and Polvani (2007) , which is based on the reversal in the sign of u 60N10hPa from November to March. Their criterion includes two additional restrictions: (1) Winds must return to westerly for at least 20 consecutive days between events and (2) winds must return to westerly for at least 10 consecutive days before 30 April of each year.
Nevertheless, conclusions do not change when considering the whole data record for abrupt4xCO 2 runs. First, let us consider the historical model simulations and contrast them to the reanalysis. Over the period 1958-2014, the polar vortex forms earlier in all models than it does in the reanalysis, with the exception of IPSL-CM6A-LR. In contrast, the SFW date is well reproduced by models. The latter implies an improvement with respect to previous generations of climate models, such as those contributing to CCMVal and CMIP5, which simulated a delayed SFW  (Butchart et al. , 2011; Kelleher et al. , 2019). CMIP6 models are also good at simulating the different range of interannual variability in the dates of vortex formation and SFW, the latter being considerably larger than the former. Second, we consider the changes caused by increased CO 2 , both for the formation and the final breakdown of the boreal polar vortex: These display robust changes across models.
e the previous misalignment value for the years in which the currency is undervalued. Note that the use of lagged values is justified by the fact that there exists a delay to produce an inflationary effect of undervaluations. Compared to equation (1), equation (3) allows us to assess if the inflation-growth nexus is affected by undervaluations' level thanks to the presence of an interaction term. In order to tackle endogeneity inherent to growth regressions, we rely on the System Generalized Method of Moments (SGMM,  Arellano and Bover, 1995; Blundell and Bond, 1998)  to estimate equations (1) to (3). Following  Roodman (2006) , we include temporal dummies as additional instruments, as it helps the assumption of no correlation across individuals to hold. 1  Furthermore, considering undervaluation episodes leads to an unbalanced panel dataset, we use forward orthogonal deviations to maximize the sample size as suggested by  Roodman (2006).
The sample of countries We consider annual data over the period 1980-2015 for advanced (18), emerging (  22 ) and developing (  22 ) countries. There are two main reasons behind the selection of this sample. First, we only include countries which present prolonged episodes of undervaluations over the 1980-2015 period. 4   Such dynamic in real exchange rate misalignments is important to be able to track the effects of an undervalued currency. Second, our sample is also characterized by a variety of monetary policy rules, allowing us to have results independent on the choosen rule as argued by  López-Villavicencio and Mignon (2011). A detailed description of the countries retained in our sample is available in appendix (Table  4 ). 2 According to  Raftery (1995) , a PIP between 0. 75 and 0. 95 denotes positive evidence of a regressor having an effect.
6 We include the human capital index proposed by PWT 9. 0 rather than the gross replacement rate arising from the WDI due to data availability. per woman reduces the incentive to accumulate human capital. In line with  Barro and Sala-i Martin (2004) , the relevance of life expectancy is considered. De la Croix and Licandro (1999) argued that a low life expectancy is expected to reduce human capital accumulation because of an important discount rate factor. In addition, as people die young, the economic development is hampered by a high depreciation rate of human capital.
Governance and institutions To investigate the relevance of the social-political indicators, our set of potential determinants includes political rights and civil liberties indexes, taken from the Freedom House database. The expected effect of such variables is not clear-cut in the literature. On the one hand, following  (Sirowy and Inkeles, 1990)  growth can be facilitated by the institution of an authoritarian regime which implements the needed policies. On the other hand, expansion of civil liberties and political rights provides an environment adequate to the innovation process with at the key a positive effect on growth. From an empirical point of view,  Barro and Lee (1994)  provide evidence of a negative effect of political freedom on growth.
Exchange rate misalignments Turning now to the exchange rate misalignment series, they are extracted from the EQCHANGE database  (Couharde et al. , 2018). A misalignment is defined as the deviation of the Real Effective Exchange Rate (REER) from the Equilibrium Real Exchange Rate (ERER). The REER of country i in period t (REER i,t ) is calculated as the weighted average of real bilateral exchange rates against each of its N trading partners j : REER i,t = N ∏ j=1 RER w ij,t ij,t (8) Where w ij,t is the trade-based weight associated to the partner j. 7  RER ij,t stands for an index of the real bilateral exchange rate of the currency of country i vis-à-vis the currency of the trading partner j in period t and is given by: RER ij,t = NER ij,t * P i,t P j,t with NER ij,t an index of the nominal bilateral exchange rate between the currency of country i and the currency of its trade partners j in period t.