Data Collection Instruments’ Delineation
The article utilized data gathered between 1950 and 2010 while focusing on assessing the implications of distinct inflation measures toward burglary, larceny, theft of motor vehicles, and robbery. Whereas robbery is regarded as a crime that utilizes violence, its inclusion in the property crime’s lust revolves around the idea that it has a property element. Data regarding crime rates on property are acquired from the Uniform Crime Report (UCR) of the Federal Bureau of Investigation (FBI). The UCR offers countrywide records of offenses that individuals have reported to local and state law enforcement within the U.S. Whereas homicide is measured with most accuracy, the different other crime forms usually suffer mostly due to the issue of underreporting bias. Whereas the UCR features certain limitations, it serves as the most ideal for offering aggregate data pertaining to crime within the U.S. For this article, it lay emphasis in rise in the number of crimes between the 1960s and 1970s together with the considerable decline during the 1990s (Nunley, Stern, Seals, & Zietz, 2016) . The data realized here is crucial to understanding ways in which inflation influenced the different kinds of crimes.
For the article, it collected data by locating theft and burglary victims via utilizing random digital dialing (RDD) screening process. Allegheny, Washington, Fayette, Pittsburgh, and Westmoreland counties served as the target geographical areas for the study. It undertook interviews from June 1989 to May 1990 with the interviews being female. They undertook the interviews using computer assisted telephone interviewing (CATI) approach. For the individuals to be considered as eligible for the study, they needed to be aged over 18 years, having served as a crime or burglary or theft during the last 12 months, and having reported the crime to law enforcement officers. The sampling and data collection approach eradicated persons associated with numerous crimes, including violent offences during the prior year thereby making it possible to realize a sample of property crime. The interviewees answered several screener questions aimed at determining the form and the number of victimization incidences they witnessed during the last 12 months (Greenberg & Beach, 2004) . The study modelled the questions in while utilizing the official definitions by the FBI while the screener instrument also determined whether the police received reports of theft or burglary.
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The study focused on a typical crime analysis process aimed at identifying patterns of crime by gathering data from the Port St. Lucie Police Department regarding how micro-time hot spots operate. The city was the key area of gathering the data in line with identifying how often vehicle crimes prevailed in the city and how the police responded while utilizing the resources available to them. The criteria by the agency revolved around identifying two or several residential thefts associated with motor vehicle, taking place between 14 days to another crime, and within a radius of 0.5 miles. The police department selected the optimal radius depending on the size of the city, including more than 110 square miles, zoning nature (many ¼ acre homes with single families (Santos & Santos, 2015) . They also revolved around the things that they felt were ideal for law enforcement officers to respond when on a given shift or a key geographic responsibility area.
Regarding the article, the means of collecting data revolved around cases gathered from Survey of Inmates in State and Federal Correctional Facilities (SISFCF) during 2004. This approach revolves around taking surveys inside prisons of a countrywide prison inmates probability sample who went through the interview from October 2003 and May 2004. The U.S. Bureau of Census employees undertook the task. The study utilized two subset samples, including the imprisoned inmates due to robbery and those in state prisons of burglary. Targeting these individuals did not require focusing on the other kinds of crimes they had committed (Kleck & Jackson, 2016) . The major area of emphasis was property crime since previous research reveals that property crime serves as the form of offense, which unemployment might not affect considerably.
The study gathered data from neighborhoods. With the various recorded crimes failing to march with the property locations the goal of the study was not to target the attacks on key properties. Rather the study lay emphasis on acquiring measures of anticipated crime density within the neighborhood in which a property is located, such as a few streets or blocks. Regarding the property level data, the research calculates the crime numbers of the different crime forms recorded within residential areas within a 250m radius within which the property is situated. Additionally, it is also vital to focus on the implied crime density for each kilometer squared (Gibbons, 2004) . On matters related to non-residential crimes, the researchers focused on doubling the distance in an effort to compensate for the lower incidence associated with non-residential properties.
When it comes to the article, it gathered data by targeting 142 metropolitan regions within the U.S. For these metropolitan areas, the researchers selected them, depending on the existing data for its key independent variable, including the HMSI. It tested the influences affiliated with foreclosure on various kinds of crime. It started by approximating the distinct models associated with violent offences of murder together with non-negligent manslaughter, aggravated assault, and robbery. It then approximated the distinct models associated with acquisitive crimes of larceny, burglary, and motor vehicle theft. Regarding the data on each dependent variable pertaining to the sample of metropolitan regions acquired from the Uniform Crime Reports by the FBI, they represented the rates for every 100,000 residents (Jones & Pridemore, 2012) . The data depicted influence of inflation on property crime.
Creating Research Question on Identified Gaps.
From the identified gaps relating to the key issue of larceny-theft, the major research question worth addressing is what it the prevalence rate of this kind of crime? For Larceny-theft, it is referred to as the process of taking, leading, carrying, or riding away the property that other people own, including motor vehicle accessories and parts, bicycles, picking pockets, shoplifting, and stealing other kinds of properties, which are stolen violently, by force, or through fraudulent acts (FBI, 2019) . Attempted cases of larceny theft comprise of confidence games, embezzlement, forgery, and check fraud among others.
The issue of larceny-theft demands considerable attention owing to its severity particularly in the recent years. In 2010, for example, the FBI’s UCR reported such incidences to amount to approximately 6,185,867 countrywide. Overall, the approximated incidences of larceny-theft declined by 2.4 percent compared to the estimates realized in 2009. For the figure witnessed in 2010, it depicted a 6.6 percent reduction from 2006. Of the approximated 2010 larceny-theft incidences, they amounted to around 2,003.5 for every 100,000 inhabitants. Additionally, between 2009 and 2010, the rate approximated larceny thefts declined by 3.0 percent while it reduced by 19.9 percent from 2001. In 2010, however, larceny thefts represented around 68.1 percent crimes related to property an indication of its prevalence. Furthermore, the relative value of each property lost due to larceny theft is around 988 dollars. This translates to the country losing over 6.1 billion dollars annually because of larceny (FBI, 2019) . Thus, this kind of crime is intense and requires significant consideration to determine means of reducing the negative associated with it particularly then it comes to property.
Research Methodology for Increased Understanding
In order to foster increased understanding of the larceny-theft issue, which is the major area of consideration, the paper will collect samples of 150 major metropolitan areas within the U.S., particularly those linked to high incidences of larceny-theft as a kind of crime. For the metropolitan areas, they will be selected depending on existing data regarding larceny-theft on the FBI’s UCR. The study will focus on estimating a unique model for larceny-theft with the data regarding the dependent variables acquired from the samples of the metropolitan areas acquired from the FBI’s Uniform Crime Reports, while it will be represented for every 100,000 residents (Sweeten, 2012) . This will provide all the information needed to deal with the problem.
Data Collection Technique
To foster increased understanding regarding the issue, the research will utilize the Uniform Crime Reporting approach by the FBI. The program serves as a countrywide and cooperative statistical method that comprises of approximately 18,000 county, college and university, city, tribal, state, and federal law enforcement organizations. These ensure to volunteer to report data regarding the crimes brought to their attention, while larceny-theft is one of the major crimes that is possible to acquire data from the program. For the FBI, it makes sure that the data received from its UCR is reliable with its continued assessment and monitoring of the type and nature of offenses taking place in the country. In the event of this approach, its key objective targets realizing reliable information that would be possible for utilizing in law enforcement operations, administration, and management. The data has grown to become among the key social indicator in the country with legislators, sociologists, criminologists, municipal planners, legislators, the media, and other criminal justice students utilize the data for various planning processes and diverse research efforts (Tonkin, Santilla, & Bull, 2012) . Thus, utilizing the data for understanding the larceny-theft issue will make it possible to understand how larceny theft influences property crime and the ideal means of dealing with the issue in different geographic locations owing to differing prevalent of the property crime.
References
FBI. (2019). Larceny-theft. Retrieved from https://ucr.fbi.gov/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/property-crime/larcenytheftmain
Gibbons, S. (2004). The costs of urban property crime. The Economic Journal, 114 , F441–F463.
Greenberg, M. S., & Beach, S. R. (2004). Property crime victims' decision to notify trhe police: Social, cognitive, and affective determinants. Law and Human Behavior, 28 (2), 177-186.
Jones, R. W., & Pridemore, W. A. (2012). The foreclosure crisis and crime: Is housing-mortgage stress associated with violent and property crime in U.S. metropolitan areas. Social Science Quarterly, 93 (3), 671-691.
Kleck, G., & Jackson, D. (2016). What kind of joblessnes afftects crime? A national case-control study of serious property crime. Journal of Quantitative Criminology, 32 , 489–513.
Nunley, J. M., Stern, M. L., Seals, R. A., & Zietz, J. (2016). The impact of inflaltion on property crime. Contemporary Economic Policy, 34 (3), 483-499.
Santos, R. G., & Santos, R. B. (2015). An post facto evaluation of tactical police response in residential thetf from micro-time hot spots. Journal of Quantitative Criminology, 31 , 679–698.
Sweeten, G. (2012). Scaling criminal offending. Journal of Quantitative Criminology, 28 , 533–557.
Tonkin, M., Santilla, P., & Bull, R. (2012). The linking of burglary crimes using offender behaviour: Testing research cross-nationally and exploring methodology. Legal and Criminology Psychology, 17 , 276–293.
