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Home Crime in the U.S. 2016 Crime in the U.S. 2016 Topic Pages Larceny-Theft


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The FBI’s Uniform Crime Reporting (UCR) Program defines larceny-theft as the unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another. Examples are thefts of bicycles, thefts of motor vehicle parts and accessories, shoplifting, pocket-picking, or the stealing of any property or article that is not taken by force and violence or by fraud. Attempted larcenies are included. Embezzlement, confidence games, forgery, check fraud, etc., are excluded.


  • In 2016, there were an estimated 5,638,455 larceny-thefts nationwide. The number of larceny-thefts declined 1.5 percent when compared with the 2015 estimate. The number decreased 8.6 percent when compared with the 2012 estimate, and it declined 14.5 percent when compared with the 2007 estimate.
  • The rate of estimated larceny-thefts in 2016 was 1,745.0 per 100,000 inhabitants. From 2015 to 2016, the rate of estimated larceny-thefts declined 2.2 percent, and from 2007 to 2016, the rate decreased 20.2 percent. (See Tables 1 and 1A.)
  • Larceny-thefts accounted for an estimated 71.2 percent of property crimes in 2016. (Based on Table 1.)
  • The average value of property taken during larceny-thefts was $999 per offense. When the average value is applied to the estimated number of larceny-thefts, the loss to victims nationally was an estimated $5.6 billion. (Based on Tables 1 and 15.)
  • Thefts from motor vehicles accounted for 26.2 percent of all larceny-thefts in 2016. (See Table 15.)

Expanded data

Expanded offense data are the details of the various offenses that the UCR Program collects beyond the count of how many crimes law enforcement agencies report. These details may include the type of weapon used in a crime, type or value of items stolen, and so forth. In addition, expanded data include trends (for example, 2-year comparisons) and rates per 100,000 inhabitants.

Expanded information regarding larceny-theft is available in the following tables:

What you won't find on this page

  • Statistics about embezzlement, confidence games, forgery, check fraud, etc.

  • Clearance and arrest data for larceny-theft.