In 2023, the nationwide larceny-theft rate in the United States was 1,347.2 cases per 100,000 of the population. This is a decrease from the previous year, when the larceny-theft rate stood at 1,416.6 cases per 100,000 of the population.

In 2023, the District of Columbia had the highest larceny-theft rate in the United States, with 2,990.8 cases of reported larceny-theft per 100,000 inhabitants. Colorado, New Mexico, Oregon, and Louisiana rounded out the top five states for larceny-theft in that year.

In 2023, about 4.51 million reported cases of larceny-theft occurred in the United States. The number of larceny-theft cases has decreased since 1990, when about 7.95 million reported cases occurred nationwide.

The average for 2016 based on 74 countries was 783 thefts per 100,000 people. The highest value was in Denmark: 3949 thefts per 100,000 people and the lowest value was in Senegal: 1 thefts per 100,000 people. The indicator is available from 2003 to 2016. Below is a chart for all countries where data are available.

In 2020, Great Falls, Montana had the highest rate of larceny theft in the United States, with 3,335 reported cases of larceny per 100,000 inhabitants. Fairbanks, Alaska had the second highest larceny theft rate, at 2,961.5 cases per 100,000 inhabitants.

The purpose of this study was to examine the crime of identity theft from the offenders' perspectives. The study employed a purposive sampling strategy. Researchers identified potential interview subjects by examining newspapers (using Lexis-Nexis), legal documents (using Lexis-Nexis and Westlaw), and United States Attorneys' Web sites for individuals charged with, indicted, and/or sentenced to prison for identity theft. Once this list was generated, researchers used the Federal Bureau of Prisons (BOP) Inmate Locator to determine if the individuals were currently housed in federal facilities. Researchers visited the facilities that housed the largest number of inmates on the list in each of the six regions in the United States as defined by the BOP (Western, North Central, South Central, North Eastern, Mid-Atlantic, and South Eastern) and solicited the inmates housed in these prisons. A total of 14 correctional facilities were visited and 65 individuals incarcerated for identity theft or identity theft related crimes were interviewed between March 2006 and February 2007. Researchers used semi-structured interviews to explore the offenders' decision-making processes. When possible, interviews were audio recorded and then transcribed verbatim. Part 1 (Quantitative Data) includes the demographic variables age, race, gender, number of children, highest level of education, and socioeconomic class while growing up. Other variables include prior arrests or convictions and offense type, prior drug use and if drug use contributed to identity theft, if employment facilitated identity theft, if they went to trial or plead to charges, and sentence length. Part 2 (Qualitative Data), includes demographic questions such as family situation while growing up, highest level of education, marital status, number of children, and employment status while committing identity theft crimes. Subjects were asked about prior criminal activity and drug use. Questions specific to identity theft include the age at which the person became involved in identity theft, how many identities he or she had stolen, if they had worked with other people to steal identities, why they had become involved in identity theft, the skills necessary to steal identities, and the perceived risks involved in identity theft.

In 2023, the police registered 31,070 offenses of pocket-picking in the United States. The largest number of reported larceny-thefts were thefts from shoplifting, with about 1.8 million thefts in that same year.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Thief River Falls. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Thief River Falls. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Thief River Falls, householders within the 45 to 64 years age group have the highest median household income at $78,156, followed by those in the under 25 years age group with an income of $74,154. Meanwhile householders within the 25 to 44 years age group report the second lowest median household income of $71,574. Notably, householders within the 65 years and over age group, had the lowest median household income at $46,696.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Thief River Falls median household income by age. You can refer the same here

About this dataset

Context

The dataset tabulates the Thief Lake township population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Thief Lake township. The dataset can be utilized to understand the population distribution of Thief Lake township by age. For example, using this dataset, we can identify the largest age group in Thief Lake township.

Key observations

The largest age group in Thief Lake Township, Minnesota was for the group of age 65 to 69 years years with a population of 10 (33.33%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Thief Lake Township, Minnesota was the Under 5 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Thief Lake township is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Thief Lake township total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Thief Lake township Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Thief River Falls population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Thief River Falls. The dataset can be utilized to understand the population distribution of Thief River Falls by age. For example, using this dataset, we can identify the largest age group in Thief River Falls.

Key observations

The largest age group in Thief River Falls, MN was for the group of age 60 to 64 years years with a population of 753 (8.52%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Thief River Falls, MN was the 85 years and over years with a population of 223 (2.52%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Thief River Falls is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Thief River Falls total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Thief River Falls Population by Age. You can refer the same here

What are the top vacation rentals in Thief River Falls? How many vacation rentals have private pools in Thief River Falls? Which vacation homes in Thief River Falls are best for families? How many Rentbyowner vacation rentals are available in Thief River Falls?

The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2016 dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.

This layer shows the property crime index in the U.S. in 2017 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Property crime indexSub-categories of the property crime indexThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.For more information about the AGS Crime Indices, click here. Additional Esri Resources:Esri DemographicsU.S. 2017/2022 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) from 2006 to the end of last year (2015). For additional details, please see the attached data dictionary in the ‘About’ section.

The primary purpose of the Identity Theft Supplement (ITS) is to measure the prevalence of identity theft among persons, the characteristics of identity theft victims, and patterns of reporting to the police, credit bureaus, and other authorities. The ITS was also designed to collect important characteristics of identity theft such as how the victim's personal information was obtained; the physical, emotional and financial impact on victims; offender information; and the measures people take to avoid or minimize their risk of becoming an identity theft victim. The information is intended for use by policymakers, academic researchers, practitioners at the Federal, state and local levels, and special interest groups who are concerned with identity theft to make informed decisions concerning policies and programs. Responses are linked to the NCVS survey instrument responses for a more complete understanding of the individual's circumstances. The 2018 Identity Theft Supplement (ITS) was the fifth implementation of this supplement to the annual NCVS to obtain specific information about identity theft-related victimization on a national level. Since the ITS 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 dataset provides information about the number of properties, residents, and average property values for US Highway 59 cross streets in Thief River Falls, MN.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2019). For additional details, please see the attached data dictionary in the ‘About’ section.

GapMaps provides Crime Risk data sourced from Applied Geographic Solutions (AGS) which has been used by thousands of companies for over 20 years, providing valuable comparative information on the spatial patterns of crime.

Crime Risk Data includes crime risk indexes and projections on detailed crime types like murder and motor vehicle theft, and summary indexes of crimes against persons, crimes against property and overall crime risk. Crime Risk Data is available at the highly detailed census block level to capture the different risk levels across business and residential places. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide.

The crimes included in the Crime Risk Data database are the “Part 1” crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative “overall” crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. In 2020, 5-Year Projections were added to the database.

Use cases: 1. Insurance underwriting and risk mitigation. 2. Evaluating the security measures needed to protect employees and customers at retail facilities. 3. The study of the effects of neighborhood crime on wellness and health care outcomes.

Methodology: Crime is tracked for multiple years using both FBI aggregate crime reports and for many parts of the country at the individual incident level. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.

U.S. Census Bureau QuickFacts statistics for Thief River Falls city, Minnesota. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

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.