Kyle Scholz: Final Blog

Does Crime Take the Metro?

Kyle Scholz

Public Policy M224A

Professor Yoh Kawano

March 23, 2012

I. Introduction

As an engineer working on the construction of the new Expo Line from downtown Los Angeles to Culver City, I often encounter local residents who want to express their thoughts of the new line. These thoughts are given in a variety of ways: curious questions, words of gratitude, or honking horns and selective displays of fingers. Although big decisions on transit systems are far above my pay grade, I am often the only person around wearing a hard hat and neon vest (see below), so for better or worse people see me as an outlet for their opinions and questions.

Author unsuccessfully attempting to photograph Expo Line test train interior.

One of the most interesting questions I hear is related to the demographics along the path of the new line:

Expo Line (Phase I) on Google Maps

Expo Line (Phase I) on Google Maps:Stations on which the author works are shown with red markers.

(To explore the above Google Map in a new window, click Expo Line (Phase I))

Phase I of the Expo line travels from downtown LA (in the northeast corner of the above map) to Culver City (at the far west). The next phase of the line (to be completed in the next few years) will travel even further west into Santa Monica.

Because LA residents know that crime is generally higher at the origin of the line (downtown) than it is at the destination (Culver City/Santa Monica), it is often assumed that the new line will provide a pathway for criminals from downtown to reach more affluent victims in the safer western areas. This is one of the reasons that many residents in those “safe” areas express their disapproval of the new line with the aforementioned horns and fingers or with the lawn signs shown below:

Lawn signs protesting current plans to take the Expo Line to Santa Monica.

[ It is worth noting that the signs shown do not explicitly advocate against the Expo Line. Instead, they argue (fairly) that the line would be safer and less obstructive if built entirely above-grade (on bridges above streets) or below-grade (subway), rather than at-grade (with blinking street crossings). However, having worked on the different types of stations (see below), I can attest that building the entire line above or below grade would significantly increase the cost of the line, likely exceeding the amount budgeted for the project. The organizers behind the signs undoubtedly know this, which may explain the emphasis in their slogan “Build it right or DON’T BUILD IT!” ]

At-Grade Station

At-grade stations are better for budgets, but worse for pedestrians & traffic.(Farmdale Station, Expo Line)

Above-grade stations are better for pedestrians & traffic, but are far more expensive.(Culver City Station, Expo Line)

The logic of the crime exporting theory appears sound, based on the following two assumptions:

  1. Some portion of criminal activity seeks out the most affluent victims
  2. Some portion of criminal activity is limited geographically by lack of transit options

Although these assumptions seem reasonable to me, they are still only assumptions. Since I have no training in public policy or urban planning (and even less training in criminal psychology), I have not been able to give an informed answer to the question of public transit exporting crime. With this project, I aim to find a sufficient and historically-based answer to the question:

“Will the Expo line bring crime from downtown LA to Culver City?”


II. Literature

There is extensive literature on record regarding “transit crime” – that is, crime which occurs within the transit system itself. Ronald V. Clarke (2002) discusses in depth the types of crime which are common within the confines of a transit system. These include system-related crimes (such as graffiti and cheating fares) as well as more serious crimes like pick-pocketing and molestation on crowded stations or vehicles.  Having helped coordinate the installation of closed circuit televisions and emergency “blue light station” telephones on the Expo line, I can attest that Metro is making an effort at reducing this type of crime.

Notwithstanding the seriousness of crimes occurring within the transit system itself, this project focuses instead on crime which will use the transit system not as venue, but as a vehicle to reach an outside destination. This type of crime is much more difficult to track and prevent, which partially explains why literature on the subject is very sparse. The best analysis available is a paper by Nicole Achs (1991) which discusses crime as one of the many reasons why suburban communities have fought the expansion of public transit. The crime problem is presented therein by a very powerful anecdote:

“On a mild, early March evening last year, Marion Roberts waited for his wife at an Atlanta rapid rail station. At 5 p.m., the station was active as work-weary passengers shuffled to buses and cars, anxious to get home. Here and there security officers stood around, keeping an eye on the crowd.

But suddenly, the scene of everyday urban life changed, and the brightly lit station became a set for the darker realities of urban violence.

Roberts, waiting in his car, was accosted by a group of teenage boys. The leader brandished a gun and demanded Roberts hand over the keys. When Roberts refused, the teenagers pulled him from the car and shot him repeatedly.

Two of the assailants jumped into the car and sped away, and the others dispersed as Roberts fell to the ground. He died a few hours later in an area hospital.” (Achs, 1991)

While the paper does not argue that this tragedy occurred as a direct result of the public transit system, it acknowledges that an irrefutable connection doesn’t really matter. The boys who committed this crime could have committed the same crime at a grocery store, post office, or school. Fair or not, their choice to do so at a train station understandably created an “image of public transit and its tie to big city problems that may not be easy to erase.” (Achs, 1991)


III. Method of Research

In order to predict the crime effect of the new Expo line, I decided to:

  1. Find a historical example of a similar transit line
  2. Compare the distribution of crime before and after the historical line was opened
  3. Hypothesize an explanation for the changes in crime
  4. Compare the historical example to existing conditions along the Expo line
  5. Apply the pattern seen at the historical line to predict the future of the Expo line


III-1: Find a historical example of a similar transit line

The line chosen for analysis of historical crime effects is the north extension of the Los Angeles Metro Red Line, which opened in 1999/2000 to connect Downtown LA to Hollywood:

Extent of Historical Study: Metro Red Line North Extension

The decision to use the Red Line North Extension was based on several factors:

  • It is the nearest segment to the Expo line
  • It was recently installed (in two phases between 1999 and 2000), so data is more available and more applicable to the present
  • Its entire path lies within unincorporated LA county, meaning the crime statistics are recorded and reported by the same police department (LAPD)
  • As will be shown in section III-4, the crime and income distributions are similar to those of the Expo line


III-2: Compare the distribution of crime before and after the historical line was opened

As expected, the largest obstacle to show historical changes was finding data. Although Professor Yoh recommended the excellent resource (new window), its range of data only reaches back to September 2011 — about a decade after the Red line was installed in 1999/2000. Without GIS-ready data, I searched for a resource from which I could create my own layers of crime data. The best available data was the LAPD statistical digests (e.g. 2001 (new window)). Buried within these 100+ page pdfs was the number of Type I offenses (Homicide, Rape, Aggravated Assault, Robbery, Burglary, Larceny, Vehicle Theft ) for each LAPD station during the year studied. I extracted and averaged over the three years before the Red Line extension (1997 to 1999) and the three years after (2000 to 2002), which allowed me to generate numbers for the change in crime that occurred for each station.

Changing LAPD reporting areas (With best available maps)

Unfortunately for me (but fortunately for the residents of Los Angeles), LAPD has added LAPD stations and adjusted the reporting areas of the region over the years. Thus no GIS map was available with the reporting areas as they existed at the time of the Red Line extension. The best I could find was a series of course resolution, undated image files with rough maps of the LAPD reporting areas. By matching the pre-baked map labels to the station names in the statistical digests, I discerned which image showed the reporting areas for the period of study. To use this map in GIS, I georeferenced the image over a standard map of LA county and used the split polygon tool to carve unincorporated LA into the proper reporting areas for the Red Line extension (above, purple) and again for the Expo line (above, red). For each new file I filled in the attribute table with the LAPD district, reporting area, square mileage, and Type I crimes for each of the 6 years being studied. In order to further simplify my displays, I then extracted the 4 reporting areas which lie in the path of the Red Line extension.

With this new map and attribute table, I used the field calculator to determine the average crime level during the 3 “before” years (1997 to 1999) to show the spatial crime distribution as it existed prior to the Red Line extension:

Crime Before Red Line North Extension

The general trend in the distribution is a decrease in crime from the origin of the Red Line (in the high-crime Rampart area) to the destination (in the lower crime Hollywood/North Hollywood areas). [The Northeast area is noticeably low crime, but since the new line only has one stop in the far corner of the area, I chose to focus mainly on the other three reporting areas as better representations of the effect of the line.]

If the theory that mass transit “exports” crime from high crime to low crime regions is true:

  • The low crime destinations (Hollywood/North Hollywood) should increase in crime once the Red Line North Extension opened
  • The high crime origin (Rampart) should decrease in crime once the Red Line North Extension opened

To test this hypothesis, I plotted the % change in crime between the three year “before” average and the three year “after” average:

Change in Crime After Red Line Extension

The results clearly contradict the hypothesis made above: the low crime Hollywood destinations actually decreased about 2% in crime after the Red Line Extension opened, and the high crime Rampart area increased crime by almost 8%.

Although this is only one example, it appears to show that the effect of mass transit on crime is the opposite of what many transit opponents believe and/or fear: new transit systems may actually increase crime in already dangerous areas and decrease crime in already safe areas.


III-3: Hypothesize an explanation for the changes in crime

At first I was at a loss when trying to explain why the observed effect took place. After much thought, I came up with two possible explanations:

Theory A: Coincidence

Since I only measured one transit system, and since the reporting areas for the data are of poor resolution, it seems to me very possible that the observed change in crime distribution may be a result of factors besides the installation of the Red Line extension. The Red Line opening may have coincided with other social or policy changes, thus rendering our analysis ineffective due to aliasing of outside factors.

However likely the coincidence conclusion may be, it would make for a very short and very underwhelming public policy analysis. Therefore, I constructed an alternate hypothesis which may explain the changes in crime:

Theory B: Crime Economics

One of the primary motivations for installing a system like the Red Line or the Expo Line is to provide a means for residents to commute to jobs outside the range of their previous mode of transportation. For example, the extension of the Red Line likely opened up opportunities for those without cars to commute to job openings in the more prosperous Hollywood & North Hollywood regions. For a snapshot of the median incomes in the region before the Red Line Extension opened, see the following map:

Family Median Incomes Before the Red Line Extension

The gradient of family incomes before the Red Line extension is shown by the map and bar graph to be more or less linear: low median incomes at the Rampart origin, and steadily increasing incomes going north through the Hollywood regions.

After the Red Line extension opened, residents at the low-income south section of the line were better able to commute and compete for jobs in the more affluent Hollywood areas. This is evidenced by the following map, which shows the change in median incomes in the census period following the Red Line extension:

Change in Median Income After Red Line Extension

As expected, the vicinity of the station in the Rampart area increased dramatically after the Red Line extension opened, while the stations in the previously more affluent Hollywood area decreased severely. Although this change is likely due to a number of confluent factors, it can be reasonably argued that the increased availability of commuting options played a role in this change, by the following hypothesized mechanism:

  • Rampart residents became more able to commute to Hollywood and bring their paychecks home with them, thus increasing the median income in that area.
  • Hollywood residents faced greater competition for the jobs in their region due to the increased number of commuters, thus decreasing the median income in that area.

The implications of this economic shift are significant in how they may explain the shift in crime. The two assumptions given for the crime exporting theory imply that some criminals will choose victims based on affluence and accessibility. As shown in the income maps, the Red Line extension greatly increased the affluence of the residents within the Rampart area itself. Criminals thus have less need to “commute” to find affluent and accessible targets, as the increased incomes in their own neighborhood make their home turf a target rich environment.

If this economic theory is valid, the Red Line Extension did not export criminals out of the Rampart area to the safer and wealthier communities on the line. Instead, it imported jobs and income into the Rampart area, which then further concentrated the criminal activity within that region.


III-4: Compare the historical example to existing conditions along the Expo line

For this section I shift focus to the upcoming opening of the Expo line, southwest of the Red Line Extension:

Extent of Future Study (Expo Line Phase I)

The pattern of crime before the Expo Line opens is remarkably similar to that of the Red Line Extension prior to its opening. As seen below, the path of the line travels from a high crime density area downtown to a much lower crime area in Culver City.

Crime Distribution Before Expo Line Opens

Through the use of a user-created model (below), I extracted an areal-weighted average of the crime levels within the half-mile radius surrounding each of the 12 stations of the expo line:

Model used to extract areal weighted averages

I then joined the generated areal weighted averages to the stations from which they came to generate a graduated symbol map to show more explicitly the gradient of crime along the Expo Line:

Crime Distribution Before Expo Line Opens

The income distribution along the line is also very similar to what was seen along the Red Line Extension: Low incomes at the origin of the line (downtown), with substantially higher incomes at the destination (Culver City):

Income Distribution Along Expo Line

The similarities between the crime and income distributions before each line is opened can be summarized as follows:

  • High crime & low income at the origin of the line
  • Low crime and high income at the destination of the line

Although there are surely many differences between the lines (resulting from geography, demographics, and year of opening), the similarities in crime and income make the Red Line an ideal historical example for predicting the effects of the Expo Line under the simplified assumptions of this study.


III-5: Apply the pattern seen at the historical line to predict the future of the Expo Line

If the pattern observed for the installation of the Red Line North Extension is repeated, we can predict the changes in crime and income resulting from the upcoming opening of the Expo Line:

Income along the Expo Line:

  • Increased access to commuting options will bring workers from the low income area downtown to the higher paying jobs near Culver City
  • The increase in job commuting will result in more wealth flowing to the residents downtown, raising the median income there significantly
  • The Expo Line will force current residents of the higher income area near Culver City to compete with commuters for local jobs, lowering the median income there

Crime along the Expo Line:

  • The income predictions made above will affect crime according to the crime economics theory proposed in section III-3.
  • Criminals seeking affluent and accessible victims will increase their activities downtown due to the elevation in local incomes. This will raise the crime rate at the already high crime origin of the Expo Line.
  • Criminals will be less motivated to “commute” to find wealthy victims, thus decreasing the crime rate at the currently low crime areas near Culver City.


IV. Summary

Based on the example of the Red Line North Extension, the argument that mass transit systems inevitably “export” crime from unsafe areas into safe areas is shown to be false (or at least inconclusive, given the number of assumptions made and the limited scale of the study.)

In the case study used, the expected shift in criminal activity from high crime areas to low crime areas was not observed; in fact the opposite was seen: high crime regions increased in crime while lower crime regions decreased.

To explain the unexpected shift in crime distribution, an economic hypothesis was proposed: perhaps the increased availability of commuting increases the income of residents in the high crime areas, yielding additional monetary motivation for criminals to act there. To confirm the economic foundation of this explanation, the change in median incomes was mapped. As expected, the median income of the high crime area was shown to have increased dramatically due to increased commuting, while the low crime areas decreased in income due to increased competition from commuters.

Justification for using the Red Line North Extension as a historical predictor of the Expo Line was shown by mapping the similar conditions in income and crime distribution prior to each line’s opening.

Finally, the patterns observed at the Red Line North Extension were applied to predict the effect of the Expo Line, suggesting that upon its completion:

  • Culver City will enjoy a decrease in crime, but suffer from a decrease in income
  • Downtown will suffer an increase in crime, but enjoy an increase in income

V. Policy Recommendations

Considering my lack of a planning background and my financial dependence on the construction of the Expo Line, I am neither qualified nor unbiased enough to make policy recommendations on the value of the Expo Line to the community. Even if the results of this admittedly limited case study are to be trusted, the suggested tradeoff between income and crime is too complicated for a one-size-fits-all public transportation policy. To someone looking for a job, the observed increase in median income associated with increased commuting options may outweigh the societal cost of an increase in local crime. To the victims of the increased criminal activity, no economic boost could be worth the physical and/or psychological harm they have endured.

These types of questions, along with the myriad other interconnected issues caused by this type of transit expansion, must be weighed heavily by the public policy and urban planning professionals who ultimately make the decisions on these types of matters.

VI. Evaluation of GIS

GIS was incredibly useful throughout the project. Most of the data was collected from non-spatial sources, and thus could have been presented as simple tables and charts of figures. This approach would probably get the point across, but would lack much of the impact that comes through by displaying the data in the form of maps. By overlying the Red and Expo lines atop the reporting areas for crime and income, the conditions there are instantly clear, whereas convoluted tables, charts, and explanations require a more difficult process of mentally drawing the connections between the numbers and actual locations, crimes, and incomes.

As described in the earlier explanation of the research method, the largest difficulty was in accumulating data. Even though the period of study is barely a decade ago, the availability of GIS-ready data was almost non-existent. While I expected the quantitative data (on crime rates, etc) to be elusive, I was surprised to find that the spatial data (for LAPD reporting areas as of 1997-2002) was unavailable as well. The task of generating the maps which formed the backbone of the study was therefore doubly imposing, and required quite a bit of tedious (and unfortunately less-than-precise) manufacturing of map data from the georeferencing of course resolution, anonymous, and undated images found floating around the internet. Even if GIS-ready maps of the LAPD reporting areas were available, the areas themselves cover a much wider area than that which is likely to be impacted by the transit lines themselves. In order to improve upon the accuracy of the observations and subsequent predictions made in this study, crime data at a smaller resolution (such as that given for current crime on would be much preferred.


VII. Data Sources

  • UCLA Mapshare
  • LAPD Statistical Digests
  • LA Almanac
  • Census 2010
  • Metro Rail Authority
  • Balfour Beatty Infrastructure, Inc.
  • Achs, Nicole. “Roadblocks to public transit: for reasons ranging from prejudice to pragmatism, many suburbanites are fighting tooth and nail to keep mass transit out of their neighborhoods.” American City & County 106, no. 1 (January 1991): 28–32
  • Clarke R. V. G.  “Editorial introduction: Crime and the economics of mass transit.” In Clarke, ed., Preventing Mass Transit Crime. Crime Prevention Studies Volume 6 (1996): 1–4. Willow Tree Press, New York.