Yards and Theft Insurance Claims in 51 U.S. Cities

Kevin W. Whiteacre, Ph.D.

Director

Raeann Howes

Research Assistant

University of

Community Research Center

Research Brief #2

Presented at the American Society of Criminology annual meeting in Philadelphia, PA November 5, 2009

Community Research Center University of Indianapolis 1400 East Hanna Avenue Indianapolis, IN 46227 [email protected]

317-788-4929 ACKNOWLEDGMENTS

Thanks to Joe Kudla and Aaron Soline at the National Insurance Crime Bureau for sharing their data and for their helpful suggestions. Thanks also to Detectives Thomas Hildebrand and Andrew Starks of the Indianapolis Metropolitan Department for their invaluable assistance on this project.

Funding for this study was provided by an InQuery Collaborative Grant sponsored by the University of Indianapolis Office of Grants and Sponsored Programs.

The University of Indianapolis Community Research Center (CRC) serves as an educational facility in research and evaluation design for university students; supports the need of community organizations for data collection, storage, and analysis; and provides a setting to support university faculty and student research.

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INTRODUCTION

Metal theft describes the theft of items for the value of their constituent (Whiteacre, Medler, Rhoton, & Howes, 2008). Jurisdictions across the country are reporting increased concerns over metal thefts. The Institute of Scrap Industries, Inc. (ISRI) has called the growth in an “overwhelming problem” for communities, police, and scrap metal recyclers. i Thefts of wires have resulted in power outages and decreased grid functioning. ii In 2007, a single insurance company in the U.K. received more than 1,300 metal thefts claims worth £4.4 million just from Anglican churches. iii A recent study of metal theft in Indianapolis counted eight metal thefts a day in the first half of 2008 (Whiteacre, Howes, Soika, & Rhine, 2009). During that six-month period, an average of one and a half catalytic converters was stolen from every day, and the aluminum siding was stolen off a house once every four and a half days. There does seem to have been a substantial drop in the thefts since a peak in mid-2008, due to a drop in the values of the metals.

Numerous local and state legislatures in the U.S. have enacted, or are considering, metal theft legislation. iv In the U.S. Congress, The Secondary Metal Theft Prevention Act of 2009 (H.R. 1006; S. 418) was recently proposed “To require secondary metal recycling agents to keep records of their transactions in order to deter individuals and enterprises engaged in the theft and interstate sale of stolen secondary metal, and for other purposes.” The bulk of these new laws tend to increase the regulation and oversight of scrap yards, which are believed to provide the market for the majority of stolen metals. v

There may be good reason to focus prevention efforts on scrap yards. In his refinement of Cohen and Felson’s (1979) Routine Activity Theory, Ronald Clarke (1999) coined the acronym CRAVED to identify products’ attributes putting them at a higher risk for theft: Concealable, Removable, Available, Valuable, Enjoyable, and Disposable. Certainly the steep increase in metal prices up to mid-2008 increased the value of items made from metal. A buyer of these stolen metal goods, however, is necessary for the disposal of the items, which, unlike other stolen items like electronics and clothes, are not usually enjoyable themselves. Also unlike electronic goods and other items, the resale of metal items, such as catalytic converters, copper and wires, and aluminum siding requires a rather specialized second-hand market.

Interviews with thieves have found they are interested in high value, portable items that are easy to dispose of and difficult to identify (Kock, Kemp, & Rix, 1996). The British Crime Survey found that for novice thieves, the ability to convert stolen property into cash appears to play an important part in whether they continue to offend (Sutton, 1998).

Scrap yards provide the specialized market for metal items. The nature of the product, moreover, coming to the yards in pieces, makes it difficult for scrap yards to distinguish between stolen and legitimate items. By unknowingly (or sometimes knowingly) purchasing stolen items, scrap yards may facilitate the disposal of stolen goods, thus increasing the theft of those items. The presence of scrap yards, therefore, might play a role in increasing metal thefts in the area. This study tests the hypothesis that the number of scrap yards in a city correlates with that city’s rate of metal thefts.

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METHODS

The hypothesis discussed in the introduction is tested using as the outcome variable insurance claims for metal thefts identified by the National Insurance Crime Bureau. Independent variables tested for their relationship to metal theft claims include the number of scrap yards, burglary rates from Uniform Crime Reports, and manufacturing payroll computed from the U.S. Census. Analyses are run for the fifty-one U.S. cities with the most insurance claims in the NICB data set.

Dependent Variable

The dependent variable of interest is, of course, metal theft rates. Unfortunately, standardized data on metal thefts are not available across jurisdictions. In fact, few areas collect such specifics at all. In 2009, however, the National Insurance Crime Bureau (NICB) released a report on metal theft nationwide (Kudla, 2009). The report analyzed insurance claims for metal theft, which the researcher identified through the Insurance Services Office (ISO) ClaimSearch (Kudla, 2009). The researcher queried the ISO ClaimSearch for claims from January 2006 to November 2008 containing the words “copper,” “aluminum,” “” or “” in the Loss Description field. To include only those claims involving metal theft, the dataset was narrowed to only those claims also containing “stole,” “theft,” “took,” “thief,” “thieves,” “steal,” or “missing” (Kudla, 2009). This method identified a total of 13,861 claims related to metal theft during that time period.

The NICB report identified the 10 American cities and states with the most claims and then correlated metal theft claims with copper and aluminum prices over the three-year period (2006-2008). In April 2009, the NICB subsequently provided the University of Indianapolis Community Research Center with the claim counts for all cities reporting at least 30 claims for the time period January 2006 to November 2008.

There were 53 cities with at least 30 insurance claims identified by the NICB through the ISO Claimsearch metal theft query. One extreme outlier, Decatur, GA was eliminated because of its extremely high rate (due to a very small population). Kansas City was eliminated because we could not find the UCR data for this city. This left 51 cities with at least 30 metal theft related claims identified by the NICB.

These cities had a wide range of claims, from a low of 30 in Los Angeles, CA to a high of 321 in Cleveland, OH. The mean number of claims was 83 (mdn=55; sd = 66.8). The data were skewed positively due primarily to Cleveland’s high number of claims. vi The next highest city, Detroit, MI, had 271 claims. Regardless, raw numbers are not useful since they fail to account for differences in population size.

The raw number of claims, therefore, was transformed into a rate per 100,000 residents. vii This produced a more normal distribution, with a mean rate of 20.2 claims per 100,000 (mdn = 18.5; sd = 15.0). When the data were transformed into rates, Cleveland, OH remained at the top with a rate of 73.0 claims per 100,000 residents, and Los Angeles remained at the lowest with 0.8 claims per 100,000 residents. Table 1 provides the raw numbers and rates for the 10 cities with the highest number of claims and the 10 cities with the highest rate of claims.

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Table 1 Cities with Highest Numbers and Rates of NICB Metal Theft Claims City Number of Claims City Claims per 100,000 residents Cleveland, OH 321 Cleveland, OH 73 Detroit, MI 271 Flint, MI 66 , IL 240 Birmingham, AL 64 Dallas, TX 207 New Orleans, LA 56 Atlanta, GA 182 St. Louis, MO 50 St. Louis, MO 174 Atlanta, GA 37 Columbus, OH 172 Macon, GA 36 Indianapolis, IN 157 Cincinnati, OH 35 Birmingham, AL 146 Dayton, OH 33 Houston, TX 139 Providences, RI 33

Validity Issues

The ISO data provided by the NICB presented a problem with validity. The claims identified by NICB greatly undercounted the actual numbers of metal thefts. As mentioned above, the ISO ClaimSearch query found 13,961 cases from 1/06 to 11/08 for the entire United States. However, in just the first six months of 2008, Indianapolis alone counted 1,520 metal thefts (Whiteacre, et al., 2009). Of course, one would not expect the number of thefts to match exactly the number of insurance claims. Nevertheless, this issue raised concerns over the validity of the counts.

To establish the usefulness of these data for our present analysis, we examined their validity on several points.

1. Face Validity . At the most basic level, the data do seem to correspond with what one might expect. The worst cities tend to be industrialized, manufacturing cities, undergoing difficult economic times – cities where one might expect more levels of metal thefts and thus more insurance claims for metal thefts. 2. Trends . The original 2009 NICB report, using some of these same data, found that the number of metal theft claims nationally rose steadily from 2006 until the middle of 2008, then dropped steeply after July 2008. This trend is consistent with general agreement about the rise in metal thefts during that time and the subsequent drop in the summer of 2008. NICB also found that the claims correlated strongly with the market prices of aluminum and copper (Kudla, 2009). This is consistent with other research focusing on specific jurisdictions, including Rochester, NY (Posick, 2008), which find metal prices strongly related to metal thefts. So, the data do accurately reflect trends in metal thefts nationally. 3. Convergent Validity . We then correlated the NICB insurance claim rates for our 51 cities with the 2006 Uniform Crime Rates (UCR) data. If the insurance claims rates are valid, they should correlate with UCR rates. Specifically, they should correlate most strongly with burglary crime rates and have a weaker relationship with personal/violent crimes. Table 2 shows that the obtained relationships follow the hypothesized pattern exactly. Larceny generally refers to shoplifting, so the weak relationship to metal theft claims is not surprising.

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4. Scrap Yard Claims . Scarp yards are sometimes victimized by metal thieves. To make sure any identified relationship between scrap yards and insurance claims for metal thefts did not result from more claims filed by scrap yards themselves, a researcher with NICB ran another search to identify any claims filed by scrap yards or others who deal in scrap metal. Searching in both the loss descriptions and loss addresses for the terms “scrap,”“junk,” “wreck” (included because is sometimes used to describe a scrap yard), and “yard.” He then reviewed those claims to see if they had any indication of the theft occurring from a scrap yard. None were found. 5. Availability . Finally, the data set is available. As far as we know, it is the only national estimate of trends in metal thefts. So, for this and the reasons listed above, we feel these data provide a good starting point for analysis. It is a systematic sample of metal thefts across the country compiled by an industry with a vested interest in the utility of such data. It appears to rather accurately rank U.S. cities on the extent to which metal theft is a problem; it correlates strongly with metal prices, reflects the same overall trends other data have shown, and correlates strongly with other valid crime data.

Table 2 Correlations between NICB Metal Theft Claims and UCR Crime Rates UCR UCR UCR Burglary Larceny Violent Crime

NICB Claims .683** .199 .505** Rate **Correlation is significant at the 0.01 level

Independent Variables

The study utilized three independent variables that are hypothesized to affect metal thefts: number of scrap yards per 100,000 residents, burglary rates, and the presence of manufacturing.

Number of Scrap Yards

The most important variable that is being tested is the rate of scrap yards per 100,000 residents for each city. This information was collected through Yellowpages.com (during the month of May 2009 viii ). We used the search term “scrap metal.” Using phone directories to count business establishments has been used successfully to count pawnshops (Fass & Francis, 2004). It also has the added benefit of counting scrap yards that actively advertise to the public. These are the markets most likely to have foot traffic and to purchase from non-commercial sources (i.e., individuals). The counts were transformed into rates per 100,000 residents.

To confirm the validity of our counts, we also referenced the 2008 North American Scrap Metals Directory (NASMD ). That source includes brokers and others that do not purchase directly from private individuals, so it is less useful for this study, but we ran correlations between the NASMD numbers and our Yellowpages.com count. This produced a Pearson’s r

Community Research Center | 5 of 0.75 (sig. at 0.01), suggesting pretty good consistency between the two sources. So, we have stuck with the phone directory counts.

UCR Property Crime Rates

To control for other variables related to property crimes, we use 2006 UCR property crimes themselves. ix This provides an excellent control for area property crime rates, eliminating the need to include other traditional measures like transience, poverty, racial mix, etc., that are used to predict crime. Using UCR crime rates as the control by its nature controls for those variables to whatever extent each affects crime. The study uses UCR burglary rates, since they correlate most strongly with our independent variable (see Table 2).

Manufacturing

We also wanted to control for the presence of manufacturing in each city. It is possible that the number of scrap metal dealers and scrap theft could be spuriously related through a shared relationship to the presence of available scrap. Indeed, scrap yards developed in city centers in manufacturing areas like the Midwest primarily because of the presence of manufacturing and thus more scrap to be purchased and sold (Zimring, 2005). This might also lead to more scrap available to be stolen, arguably independent of scrap yards’ presence.

Manufacturing was originally measured with two variables from the U.S. Census Bureau’s County Business Patterns. x Using the Metropolitan Statistical Areas for our 51 cities, we recorded the number of manufacturing establishments within Industry Code 31 for 2006 (the most recent year for which the data were available) (MANUNUM) and the total annual payroll for manufacturing establishments (MANUPAY). These raw numbers were also transformed into rates. Further analysis showed that MANUNUM and MANUPAY were very strongly correlated with one another (Pearson’s r = .937) and had similar correlations with the dependent variable. So, we chose only one of the variables (MANUPAY due to its more normal distribution) in order to reduce the threat of multicollinearity in the final regression model.

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FINDINGS

We ran a correlation matrix for our study variables. The matrix is presented in Table 3 below. As hypothesized, the rate of NICB metal theft insurance claims has a strong, positive, and significant relationship with the number of scrap yards per 100,000 residents. Metal theft claims also have a strong positive relationship with UCR burglary rates (as discussed earlier) and a moderately weak positive relationship with manufacturing payroll, as expected. Interestingly, metal theft claims have a stronger relationship to the scrap yard rate than to the overall UCR burglary rates.

Table 3 Correlation Matrix for Variables Metal Theft Scrap Yard Burglary Manufacturing Claims Rate Rate Payroll Rate Metal Theft Claims 1.0 Scrap Yard Rate .768** 1.0 Burglary Rate .683** .383** 1.0 Manufacturing Payroll .391** .396* .140 1.0 **Correlation is significant at the 0.01 level *Correlation is significant at the 0.05 level

Next, we ran a linear multiple regression analysis to see if scrap yards still have a relationship to metal theft claims while controlling for the other independent variables. Table 4 below provides the results for the regression model. In the model, the number of scrap yards per 100,000 residents maintains the strongest relationship to metal theft claims, followed by burglary rates. Manufacturing payroll is rendered insignificant when the other two variables are included. Thus, even when controlling for manufacturing and other property crimes, the rate of scrap yards is strongly related to metal theft claims. The adjusted r-square indicates that 75 percent of the variance in metal theft claims can be explained by this model.

Table 4 Regression Results Ind. Variables Beta t Sig. Scrap Yard Rate .527 5.714 .000 Burglary Rate .461 5.253 .000 Manufacturing Payroll Rate .118 1.270 .187 Adjusted r-square = .753

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DISCUSSION

The analysis supports the hypothesized relationship between the presence of scrap yards and metal thefts in the 51 cities studied. The number of scrap yards per 100,000 residents showed a positive correlation with the rate of metal theft claims identified through the NICB’s ISO Claimsearch. In fact, the rate of scrap yards was the strongest predictor of metal thefts in the model, followed by burglary rates. Manufacturing lost its significance when included in the model. It appears that the more scrap yards a city has, the more metal thefts it may have.

That said, it is important to keep in mind several caveats to this finding. Foremost, correlation does not mean causation. Discussing other secondhand markets, such as pawnshops, Sutton (1995) explains, “the importance of the second-hand market should not be underestimated because it is there that many goods stolen from cars and household burglary victims will be sold. The question remains as to whether the existence of a market for stolen goods is merely a downstream consequence of crime or whether it feeds back to provide motivation for theft and to influence what is actually stolen” (400).

Similarly, quicker sales of stolen goods do not necessarily increase the rate at which thieves steal. “[T]here may be limits to the influence of incentives and a ceiling may be reached where a ready market may lead only to specialization in stealing particular items, or may simply have little effect upon the general motivation to steal more” (Sutton, 1995, p. 403).

Nor do the findings mean law enforcement efforts should focus on the market (i.e., scrap yards) at the expense of other areas, such as “hot spots” where there are high densities of metal thefts, the thieves themselves, and victims – both past and potential.

In their discussion of pawnshops, Fass and Francis (2004) argue, “…our answer to the question is that efforts to disrupt markets for stolen goods are unlikely to succeed. One reason, for pawnshops, is that proposed methods are similar to those that have been applied with little effect for a long time. Writ larger, another reason is that stolen items are invisible in the flow of used merchandise between sellers and buyers. Markets for hot goods are inseparable from the market for all secondhand wares. Reducing demand for stolen goods, therefore, implies disrupting the whole retail market for used merchandise” (p. 157). This logic could be applied to scrap yards, and it is in fact one of the industry’s complaints about laws focusing on scrap yards.

Nevertheless, the unique nature of the market for stolen metal does provide an excellent opportunity for better cooperation between law enforcement and scrap yard operators to work together to reduce purchases of stolen metals and maintain the integrity of the market. Scrap yard operators could be law enforcement’s most important ally in the fight against metal theft. For example, the Institute of Scrap Recycling Industries, Inc. (ISRI), a member of the National Crime Prevention Council, maintains a Theft Alert System that allows law enforcement to notify scrap yards when metal theft is reported. This tool is available free of charge to any law enforcement agency and helps recyclers identify stolen material brought to their location. Police provide the estimated date and time of theft, location of theft, and a detailed description of the materials, including serial numbers and measurements if possible, the investigating jurisdiction, a contact phone number, and the

Community Research Center | 8 name of the investigating officer, when possible. The Theft Alert System then sends this information via email to local scrap yards, allowing operators to identify stolen material. More information can be found at http://www.scraptheftalert.com/ or on the ISRI website at http://www.isri.org/theft/.

Fass and Francis (2004) found that frequent pawners tended to have both high arrest and unemployment rates, implying that pawnbrokers have a correspondingly high probability of receiving stolen goods from such people.

In general, research by scholars and journalists suggests three things. First, pawnbrokers do have some role in recycling stolen goods. Second, frequent pawners present the highest likelihood of acting as main agents through which pawnshops acquire hot goods. Third, the volume and value of these goods may be substantially greater than the tiny fractions that have been proposed (Fass & Francis, 2004, p. 163).

This may also be the case with scrap metal sellers. Doubtless, most frequent sellers are businesses and/or individuals engaged in legitimate trade. Nevertheless, the research findings on frequent pawners point to another avenue for proactively identifying possible thieves. Beyond the Theft Alert System, scrap yard operators could provide law enforcement with names of frequent sellers of metals, in addition to alerting law enforcement whenever there is a suspicion of theft.

Further research on metal theft and stolen metal markets is needed. Little is known about this form of crime. For example, there is anecdotal evidence of “fly by night” scrap purchasers who work out of garages or other mobile operations and private haulers serving as middlemen between thieves and scrap yards. If stolen metals are passing through multiple “hands,” and undergoing chopping, stripping and other physical changes before arriving at established scrap yards, the situation seriously calls into question current legislative initiatives that focus on those established scrap yards. Unfortunately, there is currently little concrete information available on this phenomenon.

Following Sutton’s (1995) suggestions for studying stolen goods markets, future studies could examine such issues as “the dynamics of the buying process, both in terms of economic concepts of supply and demand and also in terms of the sociological and psychological factors that influence buying and selling: the importance of price; the effects of purchasers’ knowledge, beliefs, or suspicions of where good might have come from; what influences people to buy in the hope that goods are stolen and what factors induce guilt- neutralizing techniques before a purchase is made” (p. 413). There are many avenues to follow in this greatly under-researched crime problem.

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REFERENCES

Clarke, R.V. (1999). Hot products: Understanding anticipating and reducing demand for stolen goods . Police Research Series Paper 112. London, England: Home Office Policing and Reducing Crime Unit.

Cohen, L.E. & Felson, M. (1979). Social change and crime rate trends: a routine activity approach. American Sociological Review , 44, 588-608.

Fass, S.M. & Francis, J. (2004). Where have all the hot goods gone? The role of pawnshops. Journal of Research in Crime and Delinquency , 41, 2, 156-179.

Felson, M. & Clarke, R.V. (1998). Opportunity makes the thief: Practical theory for crime prevention . Police Research Series Paper 98. London, England: Home Office Policing and Reducing Crime Unit.

Kock, E., Kemp, T., & Rix, B. (1996). Disrupting the distribution of stolen electrical goods . Police Research Series Paper 69. London, England: Home Office Policing and Reducing Crime Unit.

Kudla, J. (2009). Metal theft claims from January 2006 to November 2008. Strategic Report, February 13. National Insurance Crime Bureau Strategic and Tactical Information Department.

Langworthy, R.H. & LeBeau, J.L. (1992). The spatial distribution of sting targets. Journal of Criminal Justice , 20, 541-551.

Murray, J. (2009). Judge convicts scrap dealer. Indianapolis Star , p. A17, June 9.

Posick, C. (2008). Copper burglary and copper prices in Rochester, N.Y . Working Paper # 120. Rochester Institute of Technology Center for Public Safety Initiatives.

Ryckaert, V. (2009). Police raid major metal recycling firm. Indianapolis Star , p. 1, February 23.

Sutton, M. (1995). Supply by theft. British Journal of Criminology , 35, 3, 400-415.

Sutton, M. (1998). Handling stolen goods and theft: a market reduction approach Home Office Research and Statistics Directorate Research Findings No. 69. London, England: Home Office.

Whiteacre, K., Medler, L., Rhoton, D., & Howes, R. (2008). Metal theft database pilot study . Presented at the American Society of Criminology annual meeting November, 2008.

Whiteacre, K., Howes, R., Soika, E., & Rhine, Z. (2009). Indianapolis Metal Theft Project 2008 second quarter report . Presented at the Academy of Criminal Justice Sciences annual meeting, March 13.

Zimring, C.A. (2005). Cash for your trash . Rutgers University Press: New Brunswick, New Jersey.

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iInstitute of Scrap Recycling Industries, Inc. [ISRI]. (2008). Metals thefts. From http://www.isri.org/AM/ Template.cfm?Section=Materials_Theft&Template=/TaggedPage/TaggedPageDisplay.cfm&TPLID=153&ContentID=14163 . Retrieved on 9/16/08. ii Arizona State Senate. (2007). Metals Theft. Arizona State Senate Issue Brief. From http://www.azleg.state.az.us/briefs/Senate/SCRAP%20METAL.pdf . Retrieved on 10/14/08. iii Ecclesiastical. (2008). iv Schwartz, E. (2008). Price hikes lead to rash of metals thefts. U.S. News and World Report . March 27. From www.usnews.com/articles/news/national/2008/03/27/price-hikes-lead-to-rash-of-metal-thefts.html . Retrieved 9/16/08. v Indeed, in the winter of 2009 Indianapolis police and federal agents raided six scrap yards run by Indianapolis’ largest metal recycling business on allegations they knowingly purchased stolen goods (Ryckaert, 2009). In June, 2009 another Indianapolis scrap yard operator was convicted of knowingly purchasing stolen copper power cable (Murray, 2009). vi Eliminating Cleveland results in a mean of 79 claims (median = 52 and std = 58.6). vii Population counts based on 2006 UCR data retrieved from http://www.icpsr.umich.edu/NACJD/ in May 2009 viii Though this is a year after the dates of the NICB data, we feel it is a good measure of scrap yard presence during the study time, since such yards require a pretty large outlay and do not pop up and disappear over night. ix Retrieved from http://www.fbi.gov/ucr/cius2006/data/table_08.html x Retrieved from http://www.census.gov/econ/cbp/index.html 5/18/09.

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