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The Corporate Financial Fraud project is a study of company and top-executive characteristics of firms that ultimately violated Securities and Exchange Commission (SEC) financial accounting and securities fraud provisions compared to a sample of public companies that did not. The fraud firm sample was identified through systematic review of SEC accounting enforcement releases from 2005-2010, which included administrative and civil actions, and referrals for criminal prosecution that were identified through mentions in enforcement release, indictments, and news searches. The non-fraud firms were randomly selected from among nearly 10,000 US public companies censused and active during at least one year between 2005-2010 in Standard and Poor's Compustat data. The Company and Top-Executive (CEO) databases combine information from numerous publicly available sources, many in raw form that were hand-coded (e.g., for fraud firms: Accounting and Auditing Enforcement Releases (AAER) enforcement releases, investigation summaries, SEC-filed complaints, litigation proceedings and case outcomes). Financial and structural information on companies for the year leading up to the financial fraud (or around year 2000 for non-fraud firms) was collected from Compustat financial statement data on Form 10-Ks, and supplemented by hand-collected data from original company 10-Ks, proxy statements, or other financial reports accessed via Electronic Data Gathering, Analysis, and Retrieval (EDGAR), SEC's data-gathering search tool. For CEOs, data on personal background characteristics were collected from Execucomp and BoardEx databases, supplemented by hand-collection from proxy-statement biographies.

Over the past two decades, as the proportion of older Americans has increased, so too have instances of elder abuse, including physical, emotional, and sexual abuse; financial exploitation; and caregiver neglect. The most recent national survey estimates show at least 1 in 10 community-residing older adults experience elder abuse each year, which translates to over 7 million Americans annually. Rates of abuse are magnified for older adults with the least financial and social resources, including those with low incomes, living in isolated rural communities, and facing structural barriers such as systemic racism. Emerging research on the COVID-19 pandemic prompts even greater concern for elder abuse: the virus has disproportionately affected older adults, resulting in increased social isolation, physical health impairment, and exposure to COVID-related fraud. Recognizing the urgent need to develop and rigorously evaluate programs aimed at preventing elder abuse, the US Department of Justice's National Institute of Justice funded a demonstration from 2017 to 2021 during which researchers from the Urban Institute and practitioners at the Phoenix-based Area Agency on Aging, Region One ("the Area Agency") co-developed an elder abuse prevention program in Maricopa County, Arizona, which Urban's team then evaluated through a randomized controlled pilot study. This multiphase demonstration included an initial planning phase and a subsequent pilot study, which is the focus of this report. The EMPOWER: Building Late-Life Resilience program is a 12-week in-home intervention, with one-hour weekly visits designed to empower community-residing older adults with the resiliency and resources to lead safe and healthy lives throughout the aging process. EMPOWER provides one-on-one assessments, client-centered prevention education, and needs-responsive life skills training embedded in a series of cognitive reframing conversations with an experienced facilitator. The program has eight modules, each of which culminates in an action plan focused on strengthening a client's internal assets and identifying sources of positive social support. Caseworkers facilitate motivational discussions centered on clients' self-identified goals and action planning, with the aim of optimizing clients' home safety, physical health, social connectedness, and emotional and financial well-being.

The Eurobarometer series is a unique cross-national and cross-temporal survey program conducted on behalf of the European Commission. These surveys regularly monitor public opinion in the European Union (EU) member countries and consist of standard modules and special topic modules. The standard modules address attitudes towards European unification, institutions and policies, measurements for general socio-political orientations, as well as respondent and household demographics however this collection does not contain standard module questions. The special topic modules address such topics as agriculture, education, natural environment and resources, public health, public safety and crime, and science and technology. This round of Eurobarometer surveys covers the following special topics: (1) social climate, (2) development aid (3) cyber security (4) public transport (5) Anti-microbial resistance and (6) space technology. In regard to social climate, respondents were asked about their life satisfaction, employment, opinions on healthcare and pension provisions, unemployment benefits, cost of living and asked about past present and future options on the affordability of housing and energy. Lastly thoughts were measured on EU investments and knowledge of the European Social Fund. The development aid section includes questions on the importance of helping developing countries, the Millennium Development Goals, future focus of development policy, and practicality of achieving development goals. Questions in the cyber security section asks about frequency of Internet use, devices used to access the Internet, online activities, confidence in the ability to engage in Internet transactions, online banking concerns, adjustments to Internet use based upon concerns, online harassment and knowledge of cybercrime risks. Queries of public transport/ urban mobility special topic asks about use of car, public transportation, cycling and walking, frequency of travel within cities, problems during travel, opinions on problems in the city, ways to improve city travel, measures to improve travel and responsibility for reducing traffic. Measures taken from the anti-microbial resistance section include use of antibiotics, how antibiotics are obtained, reason for taking antibiotics, knowledge about antibiotics, opinions on group responsibility and knowledge and opinions about use of antibiotics. Lastly, the space technology section asks about the role of space derived technologies, opinions on investing in human space exploration, consequences of climate change, opinions on whether linking space activities to education would encourage students to choose STEM careers, ready to use automated vehicles, opinions on whether space investment will lead to job creation, concerns about asteroids and space-based services, reasons for and against investing in space exploration. Demographic and other background information collected includes age, gender, nationality, marital status and parental relations, occupation, age when stopped full-time education, household composition, ownership of a fixed or a mobile telephone and other durable goods, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview (select countries).

The Supplemental Fraud Survey (SFS) obtained additional information about fraud-related victimizations so that policymakers; academic researchers; practitioners at the federal, state, and local levels; and special interest groups who are concerned with these crimes can make informed decisions concerning policies and programs. The SFS asked questions related to victims' experiences with fraud. These responses are linked to the National Crime Victimization Survey (NCVS) survey instrument responses for a more complete understanding of the individual victim's circumstances. The 2017 Supplemental Fraud Survey (SFS) was the first implementation of this supplement to the annual NCVS to obtain specific information about fraud-related victimization and disorder on a national level. Since the SFS is a supplement to the NCVS, it is conducted under the authority of Title 34, United States Code, section 10132. Only Census employees sworn to preserve confidentiality may see the completed questionnaires.

This multi-phase study was conducted to discover and learn more about the services offered to victims of identity theft and to evaluate the effect of these services on those who experienced this crime. The first phase of this study focused on the effects of identity theft services on its direct victims. This was accomplished by combining available data from the Identity Theft Supplement (ITS) with survey data associated with the Identity Theft Resource Center (ITRC). The second phase of this study was conducted as multiple focus groups where qualitative data was collected to help in understanding more about identity crime victimization. The participants that attended these focus groups were organizations and individuals who provided insight on the type of interactions within these identity crime services. The third phase of this study was to examine the level of efficiency of the ITRC victim call center by performing interviews with the victims. Demographic variables include gender, race, age, ethnicity, education, marital status, and income.

The 2014 Survey of State Attorneys General (SAG) collected information on jurisdiction, sources and circumstances of case referrals, and the participation of attorneys general offices in federal or state white-collar crime task forces in 2014. White-collar crime was defined by the Bureau of Justice Statistics (BJS) as: "any violation of law committed through non-violent means, involving lies, omissions, deceit, misrepresentation, or violation of a position of trust, by an individual or organization for personal or organizational benefit." SAG sought to analyze how attorneys general offices as an organization in all 50 states, the District of Columbia, and U.S. territories respond to white-collar offenses in their jurisdiction. BJS asked respondents to focus on the following criminal and civil offenses: bank fraud, consumer fraud, insurance fraud, medical fraud, securities fraud, tax fraud, environmental offenses, false claims and statements, illegal payments to governmental officials (giving or receiving), unfair trade practices, and workplace-related offenses (e.g., unsafe working conditions). Variables included whether or not offices handled criminal or civil cases in the above categories, estimated number of cases in each category, and what types of criminal or civil sanctions were imposed on white-collar offenders. Researchers also assessed collaboration with partners outside of state attorneys offices, whether cases were referred for federal or local prosecution, and what circumstances lead to referring cases to state regulatory agencies. The extent to which state attorneys offices maintain white-collar crime data was also recorded.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, 1 to 12 monthly header records, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the ''Crimes Known to the Police'' data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 49 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 49 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 49 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 49 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 49 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 49 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 49 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 49 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 44 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

The United Nations International Crime Prevention and Criminal Justice Branch began the Surveys of Crime Trends and Operations of Criminal Justice Systems (formerly known as the World Crime Surveys) in 1978. The goal of the data collection effort was to conduct a more focused inquiry into the incidence of crime worldwide. To date, there have been five quinquennial surveys, covering the years 1970-1975, 1975-1980, 1980-1986, 1986-1990, and 1990-1994, respectively. Starting with the 1980 data, the waves overlap by one year to allow for reliability and validity checks of the data. For this data collection, the original United Nations data were restructured into a standard contemporary file structure, with each file consisting of all data for one year. Naming conventions were standardized, and each country and each variable was given a unique identifying number. Crime variables include counts of recorded crime for homicide, assault, rape, robbery, theft, burglary, fraud, embezzlement, drug trafficking, drug possession, bribery, and corruption. There are also counts of suspects, persons prosecuted, persons convicted, and prison admissions by crime, gender, and adult or juvenile status. Other variables include the population of the country and largest city, budgets and salaries for police, courts, and prisons, and types of sanctions, including imprisonment, corporal punishment, deprivation of liberty, control of freedom, warning, fine, and community sentence. The countries participating in the survey and the variables available vary by year.