Abstract

The Survey on Interest Rate Controls 2020 was conducted as a World Bank Group study on interest rate controls (IRCs) in lending and deposit markets around the world. The study aims to identify the different types of formal (or de jure) controls, the countries that apply then, how they implement them, and the reasons for doing so. The objective of the study is to advance knowledge on this topic by providing an evidence base for investigating the impact of IRCs on economic outcomes.

The survey investigates present IRCs in each surveyed country, the reasons why they have been applied, the framework and resources associated with their application and the details as to their level and functioning. The focus is on legal forms of control (i.e. codified into law) as opposed to de facto controls. The new database on interest rate controls, a popular form of financial repression is based on a survey of 108 countries, representing 88 percent of global gross domestic product. The interest rate controls presented in this dataset were in effect in 2019.

Geographic coverage

Global Survey, covering 108 countries, representing 88 percent of global GDP.

Analysis unit

Regulation at the national level.

Universe

Banking supervisors and Local Banking Associations.

Kind of data

Sample survey data [ssd]

Mode of data collection

Mail Questionnaire [mail]

Research instrument

Bank supervisors and banking associations were provided with a standard excel file with five parts. The survey was structured in five parts, each placed in a different excel sheet. Part A: Introduction. Countries with no IRCs in place were asked to only answer this sheet and leave the rest blank. Part B: Presented the definitions of controls, institutions, products and additional aspects that will be covered in the survey. Part C: Introduced a set of qualitative questions to describe the IRCs in place. Part D: Displayed a set of tables to quantitatively describe the IRCs in place. Part E: Laid out the final set of questions, covering sanctions and control mechanisms that support the IRCs' enforcement. The questionnaire is provided in the Documentation section in pdf and excel.

The evolution of internal fertilization has occurred repeatedly and independently across the tree of life. Â As it has evolved, internal fertilization has reshaped sexual selection and the covariances among sexual traits such as testes size and gamete traits. But it is unclear whether fertilization mode also shows evolutionary associations with traits other than primary sex traits. Theory predicts that fertilization mode and body size should covary, but formal tests with phylogenetic control are lacking. We used a phylogenetically-controlled approach to test the covariance between fertilization mode and adult body size (while accounting for latitude, offspring size, and offspring developmental mode) among 1,232 species of marine invertebrates from 3 phyla. Within all phyla, external fertilizers are consistently larger than internal fertilizers: the consequences of fertilization mode extend to traits that are only indirectly related to reproduction. We suspect that other traits may also c..., We compiled data for adult size, fertilization mode, developmental mode, and latitude for 1,232 species of marine annelids, echinoderms, and molluscs, and for a subset of the species for which it was available, we compiled additional data for offspring size. Most of the species in our dataset came from previously published meta-analyses on various marine invertebrate life-history traits (Marshall et al. 2012; Monro and Marshall 2015), supplemented with additional data for the adult size from the literature. Data were compiled in Microsoft Excel and analyzed in RStudio v. 4.2.2 (RStudio Team 2022). Literature cited

Marshall, D. J., P. J. Krug, E. K. Kupriyanova, M. Byrne, and R. B. Emlet. 2012. The biogeography of marine invertebrate life histories. Annual Review of Ecology, Evolution, and Systematics 43:97–114. Monro, K., and D. J. Marshall. 2015. The biogeography of fertilization mode in the sea. Global Ecology and Biogeography 24:1499–1509. RStudio Team. 2022. RStudio: Integrated Dev..., Programs/software required to open/analyze the data files:

Microsoft Excel (view raw data and metadata, .csv files for analyses) Adobe Reader (view PDF's of phylogenetic trees) RStudio (open files, manipulate and analyze data) ,

Abstract

The documentation covers Enterprise Survey panel datasets that were collected in Slovenia in 2009, 2013 and 2019.

The Slovenia ES 2009 was conducted between 2008 and 2009. The Slovenia ES 2013 was conducted between March 2013 and September 2013. Finally, the Slovenia ES 2019 was conducted between December 2018 and November 2019. The objective of the Enterprise Survey is to gain an understanding of what firms experience in the private sector.

As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms' experiences and enterprises' perception of the environment in which they operate.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must take its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

As it is standard for the ES, the Slovenia ES was based on the following size stratification: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Slovenia ES 2009, 2013, 2019 were selected using stratified random sampling, following the methodology explained in the Sampling Manual for Slovenia 2009 ES and for Slovenia 2013 ES, and in the Sampling Note for 2019 Slovenia ES.

Three levels of stratification were used in this country: industry, establishment size, and oblast (region). The original sample designs with specific information of the industries and regions chosen are included in the attached Excel file (Sampling Report.xls.) for Slovenia 2009 ES. For Slovenia 2013 and 2019 ES, specific information of the industries and regions chosen is described in the "The Slovenia 2013 Enterprise Surveys Data Set" and "The Slovenia 2019 Enterprise Surveys Data Set" reports respectively, Appendix E.

For the Slovenia 2009 ES, industry stratification was designed in the way that follows: the universe was stratified into manufacturing industries, services industries, and one residual (core) sector as defined in the sampling manual. Each industry had a target of 90 interviews. For the manufacturing industries sample sizes were inflated by about 17% to account for potential non-response cases when requesting sensitive financial data and also because of likely attrition in future surveys that would affect the construction of a panel. For the other industries (residuals) sample sizes were inflated by about 12% to account for under sampling in firms in service industries.

For Slovenia 2013 ES, industry stratification was designed in the way that follows: the universe was stratified into one manufacturing industry, and two service industries (retail, and other services).

Finally, for Slovenia 2019 ES, three levels of stratification were used in this country: industry, establishment size, and region. The original sample design with specific information of the industries and regions chosen is described in "The Slovenia 2019 Enterprise Surveys Data Set" report, Appendix C. Industry stratification was done as follows: Manufacturing – combining all the relevant activities (ISIC Rev. 4.0 codes 10-33), Retail (ISIC 47), and Other Services (ISIC 41-43, 45, 46, 49-53, 55, 56, 58, 61, 62, 79, 95).

For Slovenia 2009 and 2013 ES, size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

For Slovenia 2009 ES, regional stratification was defined in 2 regions. These regions are Vzhodna Slovenija and Zahodna Slovenija. The Slovenia sample contains panel data. The wave 1 panel “Investment Climate Private Enterprise Survey implemented in Slovenia” consisted of 223 establishments interviewed in 2005. A total of 57 establishments have been re-interviewed in the 2008 Business Environment and Enterprise Performance Survey.

For Slovenia 2013 ES, regional stratification was defined in 2 regions (city and the surrounding business area) throughout Slovenia.

Finally, for Slovenia 2019 ES, regional stratification was done across two regions: Eastern Slovenia (NUTS code SI03) and Western Slovenia (SI04).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Questionnaires have common questions (core module) and respectfully additional manufacturing- and services-specific questions. The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as (-8). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response.

For 2009 and 2013 Slovenia ES, the survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Up to 4 attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals. Further research is needed on survey non-response in the Enterprise Surveys regarding potential introduction of bias.

For 2009, the number of contacted establishments per realized interview was 6.18. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The relatively low ratio of contacted establishments per realized interview (6.18) suggests that the main source of error in estimates in the Slovenia may be selection bias and not frame inaccuracy.

For 2013, the number of realized interviews per contacted establishment was 25%. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 44%.

Finally, for 2019, the number of interviews per contacted establishments was 9.7%. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The share of rejections per contact was 75.2%.

Fichier Excel qui retrace les différentes structures pour l'accueil de la petite enfance de la ville de Villemomble

The data set contains the data presented in the journal articles. The data set is in the form of an Excel spreadsheet. Each table in the journal article is a unique worksheet in the Excel spreadsheet. The other worksheet in the spreadsheet contains the raw data used to calculate the data presented in the journal article. This dataset is associated with the following publication: Gallardo, V., B. Morris, and E. Rhodes. The Use of Hollow Fiber Dialysis Filters Operated in Axial Flow Mode for Recovery of Microorganisms in Large Volume Water Samples with High Loadings of Particulate Matter. The Journal of Microbiology. Springer, New York, NY, USA, ., (2019).

Dataset underlying publication of the same title. Data added in Excel file is the numerical values behind Figures 2,3 and 4

Many disciplines (geotechnique, hydraulics, geology, environment, pharmaceutics…) analyze the size distribution of poly-disperse solids. This document explains the principles of a modal decomposition method (MDM) to fit any grain size distribution (GSD) and decompose it into subpopulations of grains or modes. The examples here are in the field of geotechnique. Several researchers have proposed methods to fit GSD data with a theoretical curve. These previous methods were shown to have a coefficient of determination, R2, typically in the 0.5–0.9 range. The proposed MDM has a R2 that usually exceeds 0.999, a marked advantage. For field investigations, soil samples taken in boreholes are remoulded mixtures of thin layers. These samples have lost information on stratification but the MDM can recover this information, as shown in published case studies. The MDM improves the prediction of hydraulic conductivity, K, in stratified soils, which is central for groundwater and pollution studies. Single layers in stratified soils are found to be unimodal, with a single population of grains. Multimodal soils are either homogeneous (till, crushed stone) or stratified (sandy aquifers). Sand samples may have up to four sub-populations or modes in their GSDs. Free Excel spreadsheets are provided to any person who wants to analyze or decompose a GSD into its subpopulations of grains. The free Excel files are made available through Scholars Portal Dataverse. An Excel file with a few GSD examples to be treated is also provided. De nombreuses disciplines (géotechnique, hydraulique, géologie, environnement, pharmacie...) analysent la granulométrie de solides variés. Ce document explique les principes de la méthode de décomposition modale (MDM) pour décrire n'importe quelle distribution de la taille des grains (GSD) et la décomposer en sous-populations de grains, ou modes. Les exemples présentés ici sont du domaine de la géotechnique. Plusieurs chercheurs ont proposé des méthodes permettant d'ajuster les données granulométriques à une courbe théorique. Ces méthodes antérieures, c’est démontré, ont un coefficient de détermination, R2, généralement compris entre 0,5 et 0,9. La MDM proposée a un R2 qui dépasse généralement 0,999, ce qui constitue un avantage significatif. Pour les études in-situ, les échantillons de sol prélevés dans les trous de forage sont des mélanges remaniés de couches minces. Ces échantillons ont perdu des informations sur la stratification, mais la MDM peut récupérer ces informations, comme l’ont montré des études de cas publiées. La MDM améliore la prédiction de la conductivité hydraulique, K, dans les sols stratifiés, ce qui est essentiel pour les études sur les eaux souterraines et la pollution. Les couches simples d’un sol stratifié s'avèrent être unimodales, avec une seule population de grains. Les sols multimodaux sont soit homogènes (till, pierre concassée), soit stratifiés (aquifères sableux). Les échantillons de sable peuvent avoir jusqu'à quatre sous-populations ou modes dans leurs GSD. Des feuilles de calcul Excel gratuites sont fournies à toute personne qui souhaite analyser ou décomposer une GSD en ses sous-populations de grains. Les fichiers Excel gratuits sont disponibles sur Scholars Portal Dataverse. Un fichier Excel contenant quelques exemples de données de GSD à traiter est également fourni.

Passenger Information System Market size was valued at USD 29.3 Billion in 2023 and is poised to grow from USD 32.93 Billion in 2024 to USD 83.9 Billion by 2032, growing at a CAGR of 12.4% during the forecast period (2025-2032).

This repository is supplementary to the manuscript "High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in Suspect and Nontarget Screening" (DOI: 10.1021/acs.est.1c04168) and includes an overview of all measured chemical features and annotations in a waste water treatment plant (WWTP) effluent, dust standard reference material (SRM) 2585 and fetal calf serum (FCS) sample.

Samples were measured using liquid chromatography - high resolution mass spectrometry (LC-HRMS) and fractionated into 80 micro-fractions encompassing a couple of seconds from the chromatographic run. The fractions were tested for their bioactivity in the antibiotics and the TTR-binding assay. The samples were processed separately using one, two, and three technical replicates in positive and negative ion mode. The first excel sheet includes all measured chemical features, suspect screening annotation, and corresponding bioassay responses. The second sheet includes all possible isomer annotations from the CECscreen database (DOI: 10.5281/zenodo.3956586) for the annotated features.

Coding Bootcamp Market size was valued at USD 399.91 million in 2021 and is poised to grow from USD 442.59 million in 2022 to USD 889.37 million by 2030, growing at a CAGR of 10.7% in the forecast period (2023-2030).

The Students in Higher Education publication is presented as folders of Microsoft Excel tables. These include breakdowns by subject of study, level of study, mode of study, age, sex, ethnicity, disability, domicile and much more. There are also tables providing a comprehensive look at the qualifications obtained by students at all levels. Data included for 1994/95 to 2015/16

This is supplementary data for the paper 'Optimisation of mobility hub locations for a sustainable mobility system'. The Excel file 'InputParameters' contains the parameters used as input for the bilevel optimization model. Note that it contains two sheets: one for the calibrated parameters in the utility function, and one for the mode-specific input parameters. The external cost data are based on the study by Bieler, C. & Sutter, D. (2019), whereas the cost parameters were derived from the websites of the local service providers.

The result folder contains the result files of all the experiments discussed in the paper. Each subfolder corresponds to one test instance. The subfolders contain the information on the built mobility hubs (build_mobilityhubs.csv), the modal split information (wegcount.rating.csv for both absolute and proportional data), the number of transfers for each mode at each station (transfercount.csv), and also the full list of modes that each user group used in their travels (user_paths.csv). Note that the stations are given by ID, and the ID is taken from the GTFS data for Aachen.

The additional experiments from Section 5.5 on the modal split for a higher number of bike- and car-sharing stations are contained in the "Further Maximization of Sharing Modes Test.zip." Each subfolder contains specific data for the test instances, while the Excel sheet modal_split_Percent.xlsx summarizes and visualizes the modal split data.

Further result data can be provided upon request.

Bieler, C., Sutter, D., 2019. Externe Kosten des Verkehrs in Deutschland: Straßen-, Schienen-, Luft- und Binnenschiffverkehr 2017.

ANOVA for grain yield and yield components among different tillage treatments in winter wheat is based on this dataset. (XLSX)

Menée depuis 1997, l'Enquête sur les dépenses des ménages a été effectuée chaque année dans les dix provinces. Les données pour les territoires sont disponibles pour 1998, 1999 et tous les deux ans par la suite. À compter de l'année de référence 2004, l'Enquête sur les réparations et les rénovations effectuées par les propriétaires-occupants fait partie de l'Enquête sur les dépenses des ménages. L'objet principal de l'enquête est d'obtenir des renseignements détaillés sur les dépenses des ménages pendant l'année de référence (l'année civile précédente). On recueille également des renseignements sur les caractéristiques des logements ainsi que sur l'équipement ménagers. Les renseignements sur les habitudes de dépenses, les caractéristiques du logement et l'équipement ménager des ménages canadiens pendant l'année 2007 ont été obtenus en demandant aux résidants dans les 10 provinces et trois territoires de se rappeler les dépenses engagées au cours de l'année civile précédente (pour les habitudes de dépenses) ou l'information à la date de l'interview (pour les caractéristiques du logement et l'équipement ménager).

Microsoft Excel file containing the entire dataset (Table S1) used in our analyses, with details about the sources used to realise the dataset.

ANOVA for the population size under different tillage treatments at the seedling stage in winter wheat is based on this dataset. (XLSX)

Original data is provided as an excel file Avedik_HippoTeeth_RawData.

Abstract

The objective of the WMS is to provide rapid information about the selected core indicators in the population, as well as monitoring changes over time when repeated on a regular basis. More specifically, the objectives of the WMS are: · Elaborating main indicators for monitoring MDG's, MGDS indicators and other indicators on social welfare and basic needs of the population and various subgroups · Monitoring changes over time in the MDG's, MGDS indicators and the other indicators used to monitor the development of living conditions and poverty in the population and various target groups · Providing a database for social research. · Elaborating on numerous sector programs aimed at improving the welfare of the population across the country. In order to prepare these programs, it is necessary to identify the problems to be addressed by the policies and to know to which extent the population is affected by these problems

The following are the contens covered in this survey: · Characteristics of the Household Members · Health · Education · Employment · Food Security · Housing Condition and Amenities · Poverty Predictors · Child health - Birth and anthropometric measures · Child health - Malaria protection and Treatment · Child health - Vaccination · HIV/AIDS Testing and Knowledge

Geographic coverage

National

Analysis unit

A living standards survey questionnaire with the following units of analysis: individuals, households, and children under 5 years of age.

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size - Selection process (e.g., probability proportional to size or over sampling) - Stratification (implicit and explicit) - Stages of sample selection (WMS 2006 contained 4,500 households and 350 Enumeration Areas [EAs] across the country drawn as a two stage design) - Design omissions in the sample - Level of representation (More EAs were included in the sample so as to provide estimates at regional level) - Strategy for absent respondents/not found/refusals (replacement or not) -(Sampling of the households was with replacement) - Sample frame used, and listing exercise conducted to update it -(WMS 2006 sample was drawn from the The Second Integrated Household Survey [IHS2] 20003/04 sample. Since the EAs were from IHS2, there was no listing of the households)

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Generic WMS were structured questionnaires based on the WM Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household characteristics, o health, education, employment, food security, poverty predictors, housing conditions and amenities, child health and anthropometric measures and HIV and AIDS knowledge.

In addition to the household questions, the questionnaire asked questions on children under age five. For children, the questionnaire was administered to the mother or caretaker of the child. The children's questions included children's characteristics, birth registration and early learning, vitamin A, malaria, immunization, and anthropometry.

The questionnaires were developed in English from the WMS Model Questionnaire.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource. Data processing for this WMS involved: - • Scanning and editing of questionnaires, using Eyes and Hands software • Consistency checks and data cleaning in SPSS • Designing tabulation programs in SPSS • Final table editing in Microsoft Excel.

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2006 WMS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Abstract

This dataset was generated from a set of Excel spreadsheets from an Information and Communication Technology Services (ICTS) administrative database on student applications to the University of Cape Town (UCT). This database contains information on applications to UCT between the January 2006 and December 2014. In the original form received by DataFirst the data were ill suited to research purposes. This dataset represents an attempt at cleaning and organizing these data into a more tractable format. To ensure data confidentiality direct identifiers have been removed from the data and the data is only made available to accredited researchers through DataFirst's Secure Data Service.

The dataset was separated into the following data files:

1. Application level information: the "finest" unit of analysis. Individuals may have multiple applications. Uniquely identified by an application ID variable. There are a total of 1,714,669 applications on record.
2. Individual level information: individuals may have multiple applications. Each individual is uniquely identified by an individual ID variable. Each individual is associated with information on "key subjects" from a separate data file also contained in the database. These key subjects are all separate variables in the individual level data file. There are a total of 285,005 individuals on record.
3. Secondary Education Information: individuals can also be associated with row entries for each subject. This data file does not have a unique identifier. Instead, each row entry represents a specific secondary school subject for a specific individual. These subjects are quite specific and the data allows the user to distinguish between, for example, higher grade accounting and standard grade accounting. It also allows the user to identify the educational authority issuing the qualification e.g. Cambridge Internal Examinations (CIE) versus National Senior Certificate (NSC).
4. Tertiary Education Information: the smallest of the four data files. There are multiple entries for each individual in this dataset. Each row entry contains information on the year, institution and transcript information and can be associated with individuals.

Analysis unit

Applications, individuals

Kind of data

Administrative records [adm]

Mode of data collection

Other [oth]

Cleaning operations

The data files were made available to DataFirst as a group of Excel spreadsheet documents from an SQL database managed by the University of Cape Town's Information and Communication Technology Services . The process of combining these original data files to create a research-ready dataset is summarised in a document entitled "Notes on preparing the UCT Student Application Data 2006-2014" accompanying the data.

RawData table (excel file) shows sample code, category as diagnostic group, age and age at onset (≤55, 56-65- 66-75, >75), the raw NTA file name, raw values of cathepsin D in sEVs and in plasma. Raw NTA data of each sample analyzed consists of .csv file generated by Nano-Sight NS300 Instrument. NTA .csv file contains information about EV concentration (particles/ml, particles/frame), size (mean, mode, SD) and size distribution (D10, D50 and D90).