The Uniform Crime Reporting (UCR) Program of the FBI divides criminal offenses into two groups: Part I and Part II Crimes. Part I Crimes are serious crimes that occur with regularity in all areas of the country and are likely to be reported to the police. The UCR collects information on the age, sex, and race of people arrested for Part I Crimes. Part I Property Crimes include burglary, larceny theft, motor vehicle theft, and arson. The presence of property crime in a neighborhood can cause mental distress in residents and may impact property values in an area. Part I Violent Crimes include murder and non-negligent manslaughter, forcible rape, aggravated assault, and robbery. Exposure to violent crime can significantly hinder psychological, social and academic development in children and leaves them at a higher risk of committing violence in the future. Individuals living in high-crime areas may be less likely to spend time outdoors and foster social connectedness with neighbors. Rates of violent crime significantly vary across neighborhoods and are often related to poverty rates, job access, segregation, and residential stability among many other factors. Neighborhoods segregated along race and economic lines tend to have higher reported rates of violent crime, which often hinder economic and institutional investment in an area.

• Data manipulation: There have been cases of law enforcement agencies or governments manipulating crime statistics for political purposes. This can be especially problematic in jurisdictions where police officers are evaluated on their ability to reduce crime rates, as it can create pressure to manipulate the data. In 2012, for example, it was revealed that the New York Police Department had been systematically underreporting certain crimes, including rapes and assaults, in order to make the city appear safer (Francescani, 2012).
• Validity: Many people may turn to crime data to answer questions about public safety. In reality, crime data is not purely a measure of criminal activity that occurs, but rather a measure of criminal activity that is responded to by police. Crime data thus serves as a measurement of both criminal and police activity, and areas which face heavy police presence may be overrepresented in crime statistics. This can create a positive feedback loop where policing increases in high crime-reported areas, resulting in even more negative citizen/police interactions. 
• Underreporting: Crime statistics are often based on reported incidents, which means that crimes that are not reported to the police are not included in the statistics. This can be a significant problem, especially for crimes that are often underreported such as sexual assault, domestic violence, or hate crimes. The lack of accurate data on these crimes can lead to a misrepresentation of the true crime rate, which can in turn result in inadequate policy responses.
• Inconsistent definitions: Different jurisdictions may have different definitions of what constitutes a particular crime. For example, the definition of “burglary” may vary from state to state or country to country. This can make it difficult to compare crime statistics across different jurisdictions, as the reported crime rates may not be directly comparable. Additionally, changes in the definition of a particular crime over time can also affect the comparability of crime statistics.
• Selection bias: Crime statistics may be based on samples of reported incidents, which can be biased towards certain types of crime or certain areas. For example, crimes committed in low-income neighborhoods may be overrepresented in crime statistics compared to crimes committed in affluent areas. Additionally, some crimes may be more likely to be reported by certain groups of people, which can also result in selection bias.

Written by Debarun Sarbabidya