In 2023, the District of Columbia had the highest rate of motor vehicle theft in the United States, with 1,070.9 cases per 100,000 inhabitants. Washington, Nevada, Colorado, and Maryland rounded out the top five states for motor vehicle theft in that year. Nationwide, the rate of motor vehicle theft stood at 318.7 cases per 100,000 residents.

In 2022, Chile recorded the highest car theft rate in the world, with nearly *** incidents per 100,000 inhabitants. Other countries with notably high rates included Uruguay, Israel, and Luxembourg.

When incidents happened, where it took place, the victim’s perception of the incident, and what items were stolen or damaged. Annual data from the Crime Survey for England and Wales (CSEW).

In 2023, the nationwide rate of motor vehicle theft in the United States was 318.7 reported cases per 100,000 population. While this is an increase from the previous year, it is a significant decrease from the rate in 1990, which stood at 657.8 motor vehicle thefts per 100,000 of the population.

In 2023, California was the state with the most motor vehicle thefts, with 208,668 motor vehicle thefts. Texas had the second most motor vehicle thefts, at 115,013.

1800C_Hsinchu County Government Police Department Car Theft Statistics Form

In 2023, an estimated 1,067,522 reported motor vehicle theft cases occurred in the United States. This is an increase from the previous year, when there were an estimated 948,119 cases of motor vehicle theft nationwide.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at PSITAdministration@ChicagoPolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data are updated daily. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

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.

This dataset includes all Theft from Motor Vehicle occurrences by reported date and related offences since 2014. The Theft from Motor Vehicle offences include Theft from Motor Vehicle Under and Theft from Motor Vehicle Over.Theft from Motor Vehicle DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various offences used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Provide robbery, snatch, forcible intercourse, car theft, residential theft, drugs, motorcycle theft and 7 other types of cases, weekly statistics on occurrences, clearance, and clearance rate. (This data is a preliminary statistics change file for each week, for reference only, and the correct statistics are still based on the annual criminal statistics of this department.) Case type, number of occurrences, number of clearances, clearance rate

This trends and best practices evaluation geared toward motor vehicle theft prevention with a particular focus on the Watch Your Car (WYC) program was conducted between October 2002 and March 2004. On-site and telephone interviews were conducted with administrators from 11 of 13 WYC member states. Surveys were mailed to the administrators of auto theft prevention programs in 36 non-WYC states and the 10 cities with the highest motor vehicle theft rates. Completed surveys were returned from 16 non-WYC states and five of the high auto theft rate cities. Part 1, the survey for Watch Your Car (WYC) program members, includes questions about how respondents learned about the WYC program, their WYC related program activities, the outcomes of their program, ways in which they might have done things differently if given the opportunity, and summary questions that asked WYC program administrators for their opinions about various aspects of the overall WYC program. The survey for the nonmember states, Part 2, and cities, Part 3, collected information about motor vehicle theft prevention within the respondent's state or city and asked questions about the respondent's knowledge of, and opinions about, the Watch Your Car program.

The data is sourced from the NIBRS Group A Offense Crimes dataset and covers the period from January 1, 2020, to the end of the most recent complete month. The displayed number represents the total motor vehicle thefts within the specified timeframe and sector.

As of July 19, 2015, the PD District boundaries have been updated through a redistricting process. These new boundaries are not reflected in the dataset yet so you cannot compare data from July 19, 2015 onward to official reports from PD with the Police District column. We are working on an update to the dataset to reflect the updated boundaries starting with data entered July 19 onward.

Incidents derived from SFPD Crime Incident Reporting system Updated daily, showing data from 1/1/2003 up until two weeks ago from current date. Please note: San Francisco police have implemented a new system for tracking crime. The dataset included here is still coming from the old system, which is in the process of being retired (a multi-year process). Data included here is no longer the official SFPD data. We will migrate to the new system for DataSF in the upcoming months.

The data is sourced from the NIBRS Group A Offense Crimes dataset and covers the period from January 1, 2020, to the end of the most recent complete month. The displayed number represents the total motor vehicle thefts within the specified timeframe and sector.

In 2020, there were approximately 950 instances of car theft per 100,000 of the population in New Zealand. In comparison, Singapore recorded about one instance of car theft per 100,000 of the population that year.

This dataset includes all auto theft occurrences by reported date and related offences since 2014.Auto Theft DashboardDownload DocumentationThis data is provided at the offence and/or vehicle level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Private car theft rate of Philippines sank by 25.25% from 6.1 cases per 100,000 population in 2017 to 4.5 cases per 100,000 population in 2018. Since the 5.91% jump in 2014, private car theft rate plummeted by 65.41% in 2018. Private Cars' means motor vehicles, excluding motorcycles, commercial vehicles, buses, lorries, construction and agricultural vehicles.(UN-CTS M4.5)

This data set is no longer compiled by the Ministry of the Solicitor General.

Property crimes are typically non-violent in nature and include:

• breaking and entering
• motor vehicle theft
• theft over $5,000 (non-motor vehicle)
• theft under $5,000 (non-motor vehicle)
• mischief

The data can be accessed from "https://www150.statcan.gc.ca/n1/en/type/data?text=property+crime">Statistics Canada.

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.