USAID's Collecting Taxes Database (CTD) is a compilation of international statistics about taxation designed to provide policymakers, practitioners, and researchers with the means to conduct analysis on domestic revenue mobilization (DRM). It is part of a wider agenda of the international community to help countries strengthen their tax systems and mobilize domestic revenue. The CTD includes information on tax performance and tax administration variables for 200 countries and territories. USAID plans to update the CTD annually. The CTD comprises a set of 30 indicators divided into three main categories -- (1) Tax Rates and Structure; (2) Tax Performance; and (3) Tax Administration -- and includes information on 200 national tax systems. The tax administration indicators examine the main features of the revenue authority.

The Household Market and Nonmarket Activities (HUS) project started as a joint research project between the Industrial Institute for Economic and Social Research (IUI) and Göteborg University in 1980. The ambition was to build a consistent longitudinal micro data base on the use of time, money and public services of households. The first main survey was carried out in 1984. In addition to a contact interview with the selected individuals, all designated individuals participated in a personal interview and two telephone interviews. All respondents were asked about their family background, education, marital status, labor market experience, and employment. In addition, questions about the household were asked of the head of household, concerning family composition, child care, health status, housing, possession of vacation homes, cars, boats and other consumption durables. At the end of the personal interview the household head had to fill out a questionnaire including questions about financing of current home, construction costs for building a house, house value and loans, imputation of property values and loans, additions/renovations 1983, maintenance and repairs, leasing, sale of previous home, assets and liabilities, and non-taxable benefits. All the respondents had to fill out a questionnaire including questions about tax-return information 1983, employment income, and taxes and support payments. Two telephone interviews were used primarily to collect data on the household´s time use and consumption expenditures. The 1986 HUS-survey included both a follow-up of the 1984 sample (panel study) and a supplementary sample. The 1986 sample included 1) all respondents participating in the 1984 survey, 2) the household heads, partners and third persons who should have participated in 1984 but did not (1984 nonresponse), 3) those individuals who started living together after the 1984 interview with an selected individual who participated or was supposed to participate in 1984, 4) members of the 1984 household born in 1966 or 1967. If entering a new household, for example because of leaving their parental home, the household head and his/her partner were also interviewed. Respondents participating in the 1984 survey were interviewed by telephone in 1986. Questions dealt with changes in family composition, housing, employment, wages and child care, and it was not only recorded whether a change had occurred, and what sort of change, but also when it occurred. The respondents also received a questionnaire by mail with questions mainly concerning income and assets. Respondents not participating in the earlier survey were interviewed in person and were asked approximately the same questions as in the 1984 personal interview. The 1988 HUS-survey was considerably smaller than the previous ones. It was addressed exclusively to participants in the 1986 survey, and consisted of a self-enumerated questionnaire with a nonrespondent follow-up by telephone. The questions dealt with changes in housing conditions, employment and household composition. The questionnaire also contained some questions on household income. In many respect the 1991 HUS-survey replicated the 1988 survey. The questions were basically the same in content and range, and the survey was conducted as a self-enamurated questionnaire sent out by mail. This time, however, in contrast to the 1988 survey, an attempt was made to include in the survey the new household members who had moved into sample households since 1986, as well as young people who turned 18 after the 1986 survey. Earlier respondents received a questionnaire by mail containing questions about their home, their primary occupation and weekly work hours since May 1988 (event-history data), earnings in 1989, 1990 and 1991, household composition and any changes in it that might have occurred since 1988, child care and some questions on income. New respondents were also asked about their education and labor-market experience. With respect to its design and question wording, the 1993 survey is a new version of the 1986 survey. The survey is made up of four parts: 1) the panel survey, which was addressed mainly to respondents in the 1991 survey, with certain additions; 2) the so-called supplementary survey, which focused on a new random sample of individuals; 3) the so-called nonresponse survey, which encompassed respondents who had participated in at least one of the earlier surveys but had since dropped out; 4) the time-use survey, which included the same sample of respondents as those in the panel and supplementary surveys. Individuals in the nonresponse group were not included in the time-use survey. Most of the questions in the first three surveys were the same, but certain questions sequences were targeted to the respondents in a specific survey. Thus certain retrospective questions were asked of the nonresponse group, while specific questions on social background, labor market experience etc. were addressed to new respondents. In the case of respondents who had already participated in the panel, a combined contact and main interview was conducted by telephone, after which a self-enumerated questionnaire was sent out to each respondent by mail. The panel sample also included young people in panel households who were born in 1973 or 1974 as well as certain new household members who had not previously been interviewed. These individuals, like new respondents, were not interviewed by telephone until they had been interviewed personally. Thus technically they were treated in the same manner as individuals in the supplementary sample. The new supplementary sample was first contacted by telephone and then given a fairly lengthy personal interview, at the conclusion of which each respondent was asked to fill out a written questionnaire. In this respect the survey design for the nonresponse sample was the same as for the supplementary sample. The nonresponse sample also included young people born in 1973 or 1974 as well as certain new household members. The time-use interviews were conducted by telephone. For each respondent two days were chosen at random from the period from February 15, 1993 to February 14, 1994 and the respondents were interviewed about their time use during those two days. If possible, the time-use interviews were preceded by the other parts of the survey, but this was not always feasible. In each household the household head and spouse/partner were interviewed, as well as an additional person in certain households. Questions regarding the household as a whole were asked of only one person in the household, preferably the household head. As in earlier surveys, data from the interviews was subsequently supplemented by registry data, but only for those respondents who had given their express consent. There is registry information for 75-80 percent of the sample. The telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; and cars and boats. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1992. The 1996 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and environment. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1995. The 1998 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and municipal service. The questionnaire was divided into nine sections: sale of previous home; house value and loans; insurance; home-related expenses; assets; household income; inheritances and gifts; black-market work; and respondent income 1997.

The Bibliography of Chinese Administrative Geography is a historical collection of bibliographic information on 75 published books describing the administrative geography of China. The information resides in a searchable database and includes title, author/editor, subject, spatial (national, provincial, local) and temporal coverage, publisher, description, and language, as well as location of the reference, for works published during the 1949-1994 period. This data set is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project, Universities Service Center at the Chinese University of Hong Kong, and the Center for International Earth Science Information Network (CIESIN).

States are required by the CCDF Final Rule to ensure that families receiving child care assistance have equal access to comparable care purchased by private-paying parents. A market rate survey (MRS) is a tool States use to achieve this program objective. Some States conduct surveys to collect the child care market rate and others use administrative data, such as data collected by child care resource and referral (CCR&R) and State licensing agencies, to analyze the market rate for child care. This survey was one strategy used to collect child care market price data. Comparing findings garnered from different methods allows one to evaluate whether different data collection methods produce different price findings (convergent validity) and how well these data collection methods represent the child care market (criterion-related validity). These data can also be used to explore several validity issues of concern with market price studies. Units of Response: Program Type of Data: Survey Tribal Data: No Periodicity: One-time Demographic Indicators: Not Applicable SORN: Not Applicable Data Use Agreement: Yes Data Use Agreement Location: https://www.icpsr.umich.edu/rpxlogin Granularity: Childcare Providers;Individual;Program;Region Spatial: United States Geocoding: Unavailable

Abstract

The importance of administrative statistics is much worth as it offers a good opportunity to get data at a cheaper cost compared to censuses and sample surveys. Administrative statistics are also very essential to calculate some important demographic measures for instance health administrative statistics such as crude birth rate, general fertility rate, age specific fertility rate, total fertility rate, gross reproduction rate, net reproduction rate, crude death rates, marriage and divorce rates, etc., under the condition that they are complete and accurate.

Geographic coverage

National coverage

Analysis unit

The development of Health Administrative Data Progress Assessment focused on women and children as units of analysis.

Universe

This assessment targeted women and children

Kind of data

Administrative records data [adm]

Mode of data collection

Other [oth]

Cleaning operations

For the calculation of fertility indicators, two sources of administrative statistics( HMIS and CRVS) were used.

The Health Management Information System (HMIS) has collected the aggregated number of births in 2015 and 2016. For the corresponding years, the Civil Registration and Vital Statistics system (CRVS) has collected the number of births by the age of their mothers at the time of birth. To calculate fertility indicators like ASFR, TFR, and GRR, we need the number of births tabulated according to age of their mothers at birth.

Since the number of births registered in HMIS is close to expectation vis-à-vis the expected annual birth, fertility indicators were computed using HMIS data and these data have been imputed following the births distribution by age of the mothers (15-49) from the CRVS assuming that the same distribution of births according to the age of their mothers applies.

Data appraisal

A combination of sources of data namely Health Management Information System (HMIS) and Civil Registration and Vital Statistics web based application (CRVS) is very useful for quality data. The 4th Rwanda Population and Housing Census conducted in 2012 and Rwanda Demographic and Health Survey (RDHS) conducted in 2014/15 were also used to benchmark on expectations and achievements for now.

This dataset represents a group of paper records (a "series") within the Harvard School of Public Health Longitudinal Studies of Child Health and Development records, 1918-2015 (inclusive), 1930-1989 (bulk), which can be accessed on-site at the Center for the History of Medicine at the Francis A. Countway Library of Medicine in Boston, Massachusetts. The series consists of research data and related administrative and regulatory records generated during the fifty-year follow-up study of the Harvard School of Public Health Longitudinal Studies of Child Health and Development. Research data includes raw, summarized, analyzed, and coded data, and consists of: completed data collection worksheets and survey instruments; reproductive and gynecological examination records and histories; subject case summaries; data tables and charts; 5.25" floppy disks containing analyzed and coded data related to blood pressure and nutrition; and coded data computer punch cards. Some data is from the original study, but was reused and maintained with records of the fifty-year follow-up study. Administrative records consist of: subject participation and appointment scheduling records; research plans and reports; and administrative correspondence. Regulatory records include: protocols and methodologies; codebooks; and blank data collection instruments. Frequent topics include: gynecological and reproductive health; memory of diet in the distant past; anthropometric measurements; blood pressure; and nutrition, among other topics. Data and associated records are accessible onsite at the Center for the History of Medicine per the conditions governing access described below. Conditions Governing Access to Original Collection Materials: The series represented by this dataset includes personnel and student information that is restricted for 80 years from the date of record creation, longitudinal patient information that is restricted for 80 years from the most recently dated records in the collection, and Harvard University records that are restricted for 50 years from the date of record creation. Access to electronic records in this series is premised on the availability of a computer station, requisite software, and/or the ability of Public Services staff to review and/or print out records of interest in advance of an on-site visit. Researchers should contact Public Services for more information. The Harvard School of Public Health Longitudinal Studies of Child Health and Development records were processed with grant funding from the Andrew W. Mellon Foundation, as awarded and administered by the Council on Library and Information Resources (CLIR) in 2016. An online finding aid to the collection may be accessed here: http://nrs.harvard.edu/urn-3:HMS.Count:med00211

Administrative data category for the MDS for EB, Delphi technique.

Abstract

This study examines various dimensions of primary health care delivery in Uganda, using a baseline survey of public and private dispensaries, the most common lower level health facilities in the country.

The survey was designed and implemented by the World Bank in collaboration with the Makerere Institute for Social Research and the Ugandan Ministries of Health and of Finance, Planning and Economic Development. It was carried out in October - December 2000 and covered 155 local health facilities and seven district administrations in ten districts. In addition, 1617 patients exiting health facilities were interviewed. Three types of dispensaries (both with and without maternity units) were included: those run by the government, by private for-profit providers, and by private nonprofit providers, mainly religious.

This research is a Quantitative Service Delivery Survey (QSDS). It collected microlevel data on service provision and analyzed health service delivery from a public expenditure perspective with a view to informing expenditure and budget decision-making, as well as sector policy.

Objectives of the study included: 1) Measuring and explaining the variation in cost-efficiency across health units in Uganda, with a focus on the flow and use of resources at the facility level; 2) Diagnosing problems with facility performance, including the extent of drug leakage, as well as staff performance and availability;
3) Providing information on pricing and user fee policies and assessing the types of service actually provided; 4) Shedding light on the quality of service across the three categories of service provider - government, for-profit, and nonprofit; 5) Examining the patterns of remuneration, pay structure, and oversight and monitoring and their effects on health unit performance; 6) Assessing the private-public partnership, particularly the program of financial aid to nonprofits.

Geographic coverage

The study districts were Mpigi, Mukono, and Masaka in the central region; Mbale, Iganga, and Soroti in the east; Arua and Apac in the north; and Mbarara and Bushenyi in the west.

Analysis unit

• local dispensary with or without maternity unit

Universe

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covered government, for-profit and nonprofit private dispensaries with or without maternity units in ten Ugandan districts.

The sample design was governed by three principles. First, to ensure a degree of homogeneity across sampled facilities, attention was restricted to dispensaries, with and without maternity units (that is, to the health center III level). Second, subject to security constraints, the sample was intended to capture regional differences. Finally, the sample had to include facilities in the main ownership categories: government, private for-profit, and private nonprofit (religious organizations and NGOs). The sample of government and nonprofit facilities was based on the Ministry of Health facility register for 1999. Since no nationwide census of for-profit facilities was available, these facilities were chosen by asking sampled government facilities to identify the closest private dispensary.

Of the 155 health facilities surveyed, 81 were government facilities, 30 were private for-profit facilities, and 44 were nonprofit facilities. An exit poll of clients covered 1,617 individuals.

The final sample consisted of 155 primary health care facilities drawn from ten districts in the central, eastern, northern, and western regions of the country. It included government, private for-profit, and private nonprofit facilities. The nonprofit sector includes facilities owned and operated by religious organizations and NGOs. Approximately one third of the surveyed facilities were dispensaries without maternity units; the rest provided maternity care. The facilities varied considerably in size, from units run by a single individual to facilities with as many as 19 staff members.

Ministry of Health facility register for 1999 was used to design the sampling frame. Ten districts were randomly selected. From the selected districts, a sample of government and private nonprofit facilities and a reserve list of replacement facilities were randomly drawn. Because of the unreliability of the register for private for-profit facilities, it was decided that for-profit facilities would be identified on the basis of information from the government facilities sampled. The administrative records for facilities in the original sample were first reviewed at the district headquarters, where some facilities that did not meet selection criteria and data collection requirements were dropped from the sample. These were replaced by facilities from the reserve list. Overall, 30 facilities were replaced.

The sample was designed in such a way that the proportion of facilities drawn from different regions and ownership categories broadly mirrors that of the universe of facilities. Because no nationwide census of for-profit health facilities is available, it is difficult to assess the extent to which the sample is representative of this category. A census of health care facilities in selected districts, carried out in the context of the Delivery of Improved Services for Health (DISH) project supported by the U.S. Agency for International Development (USAID), suggests that about 63 percent of all facilities operate on a for-profit basis, while government and nonprofit providers run 26 and 11 percent of facilities, respectively. This would suggest an undersampling of private providers in the survey. It is not clear, however, whether the DISH districts are representative of other districts in Uganda in terms of the market for health care.

For the exit poll, 10 interviews per facility were carried out in approximately 85 percent of the facilities. In the remaining facilities the target of 10 interviews was not met, as a result of low activity levels.

Sampling deviation

In the first stage in the sampling process, eight districts (out of 45) had to be dropped from the sample frame due to security concerns. These districts were Bundibugyo, Gulu, Kabarole, Kasese, Kibaale, Kitgum, Kotido, and Moroto.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available:

• District Health Team Questionnaire;
• District Facility Data Sheets;
• Uganda Health Facility Survey Questionnaire;
• Facility Data Sheets;
• Facility Patient Exit Poll Questionnaire.

The survey collected data at three levels: district administration, health facility, and client. In this way it was possible to capture central elements of the relationships between the provider organization, the frontline facility, and the user. In addition, comparison of data from different levels (triangulation) permitted cross-validation of information.

At the district level, a District Health Team Questionnaire was administered to the district director of health services (DDHS), who was interviewed on the role of the DDHS office in health service delivery. Specifically, the questionnaire collected data on health infrastructure, staff training, support and supervision arrangements, and sources of financing.

The District Facility Data Sheet was used at the district level to collect more detailed information on the sampled health units for fiscal 1999-2000, including data on staffing and the related salary structures, vaccine supplies and immunization activity, and basic and supplementary supplies of drugs to the facilities. In addition, patient data, including monthly returns from facilities on total numbers of outpatients, inpatients, immunizations, and deliveries, were reviewed for the period April-June 2000.

At the facility level, the Uganda Health Facility Survey Questionnaire collected a broad range of information related to the facility and its activities. The questionnaire, which was administered to the in-charge, covered characteristics of the facility (location, type, level, ownership, catchment area, organization, and services); inputs (staff, drugs, vaccines, medical and nonmedical consumables, and capital inputs); outputs (facility utilization and referrals); financing (user charges, cost of services by category, expenditures, and financial and in-kind support); and institutional support (supervision, reporting, performance assessment, and procurement). Each health facility questionnaire was supplemented by a Facility Data Sheet (FDS). The FDS was designed to obtain data from the health unit records on staffing and the related salary structure; daily patient records for fiscal 1999-2000; the type of patients using the facility; vaccinations offered; and drug supply and use at the facility.

Finally, at the facility level, an exit poll was used to interview about 10 patients per facility on the cost of treatment, drugs received, perceived quality of services, and reasons for using that unit instead of alternative sources of health care.

Cleaning operations

Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.

STATA cleaning do-files and the data quality reports on the datasets can also be found in external resources.

The China Administrative Regions GIS Data: 1:1M, County Level, 1990 consists of geographic boundary data for the administrative regions of China as of 31 December 1990. The data includes the geographical location, area, administrative division code, and county and island name. The data are at a scale of one to one million (1:1M) at the national, provincial, and county level. This data set is produced in collaboration with the Center for International Earth Science Information Network (CIESIN), Chinese Academy of Surveying and Mapping (CASM), and the University of Washington as part of the China in Time and Space (CITAS) project.

The GuoBiao (GB) Codes for the Administrative Divisions of the People's Republic of China consists of geographic codes for the administrative divisions of China. The data includes provinces (autonomous regions, municipalities directly under the Central Government), prefectures (prefecture-level cities, autonomous prefectures, leagues), and counties (districts, county-level cities, autonomous counties, banners) for 1 January 1982 to 31 December 1992. This data set is produced in collaboration with the Chinese Academy of Surveying and Mapping (CASM), University of Washington as part of the China in Time and Space (CITAS) project, and the Columbia University Center for International Earth Science Information Network (CIESIN).

Abstract (en): This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines. The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, gender, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Datasets:DS0: Study-Level FilesDS1: Summary RecordsDS2: Family RecordsDS3: Child RecordsDS4: Setting RecordsDS5: Pooling FactorDS6: Adjusted Child Records File (Online Analysis Only)DS7: Unadjusted Child Records File (Online Analysis Only)DS8: Adjusted Family Records File (Online Analysis Only)DS9: Unadjusted Family Records File (Online Analysis Only) Children and families receiving assistance through the Child Care and Development Fund (CCDF), through their state, territory, or tribe. This sample dataset consists of monthly data provided by states that reported sample data and states that reported full population data, as well as any territory data received. Sampling of the data from states reporting full population data was done in accordance with Technical Bulletin #5, Appendix II: Annual Sampling Plan, Example A The month with the lowest caseload was selected for determining the sampling rate so that at least 200 samples were selected for each month. Additional information on the development of this sample dataset is provided in the accompanying technical documentation.

The Bibliography of Chinese Administrative Geography is a historical collection of bibliographic information on 75 published books describing the administrative geography of China. The information resides in a searchable database and includes title, author/editor, subject, spatial (national, provincial, local) and temporal coverage, publisher, description, and language, as well as location of the reference, for works published during the 1949-1994 period. This data set is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project, Universities Service Center at the Chinese University of Hong Kong, and the Center for International Earth Science Information Network (CIESIN).

Abstract

Objectives: To provide a summary of information for employers to help them recruit and support disabled people at work.

Reference Period: Na

Periodicity of Data Collection: Na

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: 15 years and over

Total population covered: Nearly 7 million people of working age

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers

Establishments: NR

Other limitations: No

Classifications: Sex, age, level of education, status in employment, type of disability

Cross-classification: Na

Kind of data

Administrative records data [adm]

Frequency of data collection

Periodicity of Data collection: Na

The Civil Rights Data Collection, 2011-12 (CRDC 2011-12), is part of the Civil Rights Data Collection (CRDC) program. CRDC 2011-12 (https://ocrdata.ed.gov/) is a cross-sectional survey that collects data on key education and civil rights issues in the nation's public schools, which include student enrollment and educational programs and services, disaggregated by race/ethnicity, sex, limited English proficiency, and disability. LEAs submit administrative records about schools in the district. CRDC 2011-12 is a universe survey. Key statistics produced from CRDC 2011-12 can provide information about critical civil rights issues as well as contextual information on the state of civil rights in the nation, including enrollment demographics, advanced placement, discipline, and special education services.

Abstract

Objectives: To present the data on the network, medical activities, personnel of the medical institutions, some groups of diseases as well as on social security.

Reference Period: Year

Periodicity of Data Collection: Na

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: All age groups

Total population covered: All country

Economic activities: NR

Sectors covered: NR

Labor force status: Employment, unemployment, persons outside in labour force

Status in Employment: Employees, employers, own-account workers

Establishments: NR

Other limitations: No

Classifications: Sex, age, level of education, other personal characteristics, type of living arrangements (e.g. in a household, institution), place of residence, status in employment, occupation, economic activity.

Cross-classification: Na

Kind of data

Administrative records data [adm]

Frequency of data collection

Periodicity of Data collection: Na

Abstract

From 2008 to 2012 researchers from the World Bank conducted an impact evaluation study in the state of Minas Gerais, Brazil, to evaluate the effect of Minas Fácil Expresso program. This program was designed to extend a business simplification process already present in the most populous municipalities in the state to its remaining municipalities. This was intended as a quick and low-cost way to integrate the remaining municipalities, with the goals of facilitating the opening of businesses in these municipalities, reducing informality, and increasing state and municipal tax collection.

Researchers used administrative data provided by the Junta Comercial de Minas Gerais (JUCEMG), the Minas Gerais Chamber of Commerce.

There are 853 municipalities in Minas Gerais. Thirty-one of these, including Belo Horizonte, the state capital, have a physical Minas Facil office and are generally much larger in size. The dataset consists of the monthly formalization and tax data by municipality for the remaining 822 municipalities, along with the details of which of these received a Minas Fácil Expresso office.

Geographic coverage

The state of Minas Gerais

Analysis unit

• firms;
• municipalities.

Kind of data

Administrative records data [adm]

Mode of data collection

Other [oth]

The Civil Rights Data Collection, 2017-18 (CRDC 2017-18) is part of the Civil Rights Data Collection (CRDC) program; program data are available beginning with the 2000 collection at https://civilrightsdata.ed.gov/data. CRDC 2017-18 is a cross-sectional survey that collects data on key education and civil rights issues in the nation's public schools, which include student enrollment and educational programs and services, disaggregated by race/ethnicity, sex, limited English proficiency, and disability. LEAs submit administrative records about schools in the district. CRDC 2017-18 is a universe survey. Key statistics produced from CRDC 2017-18 can provide information about critical civil rights issues as well as contextual information on the state of civil rights in the nation, including enrollment demographics, advanced placement, school discipline, and special education services.

This collection contains data obtained through two rounds of an online survey of faculty and research staff at Iowa State University conducted in May 2018 and September 2021 by the Center for Survey Statistics and Methodology (CSSM) at Iowa State University. All faculty and research staff with job titles or characteristics that suggested they might have research responsibilities employed at the time of each survey were invited to complete the survey through an email invitation and several follow up messages.

The Law Enforcement Management and Administrative Statistics (LEMAS) survey collects data from a nationally representative sample of state and local law enforcement agencies in the United States. Although the data collection instrument (see page 150 of the codebook) uses the year 2012 for the title, most questions have a reference date of January 1, 2013. For this reason, the study title uses the year 2013. The 2013 LEMAS sample design called for the survey questionnaire to be sent to 3,336 general purpose state and local law enforcement agencies including 2,353 local police departments, 933 sheriffs' offices, and the 50 primary state law enforcement agencies. The design called for all agencies employing 100 or sworn personnel to be included with certainty (self-representing) and for smaller agencies to be sampled from strata base on number of officers employed. A total of 26 local police departments were determined to be out-of-scope for the survey because they were closed, outsourced, or operating on a part-time basis. A total of 38 sheriffs' offices were excluded from the survey because they had no primary law enforcement jurisdiction. The final mailout total of 3,272 agencies included 2,327 local police departments, 895 sheriffs' offices, and the 50 state agencies.