Overall % of FROI in analytic sample 72%
SOURCE: 2005–2015 WCIS-EDD data.
Earnings Dynamics Through Injury for Injured and Uninjured Workers
To illustrate our matching methodology, we now show the trajectories of earnings,
employment, and at-inju


05–2015 WCIS-EDD data.
The key assumption justifying our method for es timating earnings loss is that injured and
control workers would have contin ued to have nearly identical tr ajectories if the injury had not
taken place. This assumption is in


laces them  at risk of workplace
injury). The control workers offer a data-drive n way to adjust injured worker outcomes for
ordinary labor market dynamics and t hus isolate the impact of injury.
Figure 2.3 shows injured and control worker tr ajec


at will ultimately be filed is more complete at any given point in time than the observed population of claims that will ultimately receive indemnity benefits. This means that overall
trends can be estimated on a more timely basis than trends for in


s. .6.7.8.91(I/C) Quarterly Earnings
-4 -3 -2 -1 0 1 2 3 4 5 6 7 8
Quarter Relative to Injury
Medical-only
Indemnity22 Definition of Economic Outcome Measures
We use several different measures to char acterize outcomes for injured workers. To
famil


 If an injured worker matche s to multiple control workers, we use the average
outcome for the selected c ontrol workers to construct ௜,௧஼. Outcomes are averaged over the sample of N injured
workers. We note that, by construction, all groups contai


 binary variable equal to one if injured worker i is employed t quarters after the quarter of injury and
zero if injured worker i  is not employed t quarters after the quarter of injury. ௜,௧஼ is defined as the proportion of
worker i’s control worke


loss that behave differently
from the overall average by running a regression interacting each subgroup with the time periods of interest in the study. These estimates capture  whether particular gr oups experience changes
that are different from t


ady, relative at-injury employment actually
declined slightly in 2014 and 2015. Relative at -injury employment during the first and second
post-injury year was 87 and 80 percent, resp ectively, compared to 88 and 82 percent,
respectively, in 2013.


medical-only and indemnity claims.
Worker Characteristics and Changes in Case Mix
To examine the extent to which the changes (or lack of changes) in earnings losses can be
explained by worker characteristics rather th an economic or policy f actor


 25% 27% 27% 26%
SOURCE: 2005–2015 WCIS.
NOTE: Sample contains all injury claims in analysis sample, including medical-only and indemnity claims.

to 26 percent in 2014–2015. As me ntioned earlier, the lower share of workers receiving
indemnity


Earnings relative to counterfactual
First post-injury year 81% 78% 76% 76% 76%
Second post-injury year 85% 80% 79% 80% 81%
Relative employment
First post-injury year 89% 84% 83% 84% 85%
Second post-injury year 90% 84% 84% 86% 88% Relative at


s explained by case-mix changes over the business cycle. The
fact that case-mix adjusted earnings losses also fluctuated over  the business cycle suggests
that the state of the labor mark et directly affects the post-in jury employment prospects of


s can help establish a set of agreed-upon
facts to inform discussion of both broad reform s and targeted interventi ons to improve worker
outcomes. While RAND has examined factors associated with wage loss among permanently disabled workers in prev


ine, workers in that subgroup have lower relative earn ings than the average worker.
As described in Chapter 2, we also tested fo r statistically signifi cant differences between
group-specific trends and overall average trends. These statistical t


e regression coefficients in Table A. 9a show that relative earnings for workers in
37 firms with 11–50 employees increased faster than the statewide trend between 2013 and 2014–
2015, even after adjusting for multiple hypothesis testing.
Figure 4.


 the
Great Recession. Relative earnings for lower-tenu red workers are approximately 8 percentage
points lower on average, with some convergence after the Great Recession. While earnings for
39 higher tenured workers have begun to increase  in 201


multiple injuries have significantly lower injuries  over the entire decade. The trends in earnings
losses are relatively flat across all of thes e subgroups, however, and we do not detect any
statistically signifi cant changes in 2014–2015.
41


th cumulative
injuries in Southern California, and so we ha ve updated these estimates through the 2015 injury
year to evaluate whether th ere has been any improvement.
First of all, similar to Figure 4.5, Figure 4.8 demonstrates workers with cumu


er were thus essentially unchanged from the 2013 injury year. Among workers injured in
2014–2015 who received indemnity benefits, earnings we re 81 percent of what they would have
been in the absence of the in jury. Although injured worker earnings


ificant, and so we cannot draw the conclusion that labor market outcomes
changed for workers injured at very large employers. Taken t ogether, these changes in the
case mix are much smaller than  those observed after the start of the Great Recessio


 job tenure at the at-i njury firm did not match the
injured worker’s tenure. We defined tenure as  the number of consecuti ve quarters prior to
injury with positive earnings at the at-injury firm, leading to five tenure categories: 4, 3,
2, 1, or


s tenure definition may, for example, lead relatively higher-ear ning workers with two
or three quarters out of the labor market to be matched with lower earning workers with just one
quarter out of work, which may bias earnings loss estimates for


 for
comparison to previous RAND studies. Across the four time periods examined here, the average
imbalance is around 1 percent of ea rnings or less. This analysis indicates that injured workers
had earnings that were generally within 1 perc ent o


strators, and a wa ge history. The average match weight in our
analysis sample is 1.17, and th e largest is 15.76. In our second weighting step, we define
categories of workers by age, gender, region, self-i nsured status, injury year, and quartile


ilable for study in this report is incomplete. There are claims that are
currently medical-only that may begin receiving indemnity benefits  in the future, and there are
also claims that may not yet have been filed, for instance because a hea lth c


 Coefficient estimates for
this model are shown in Table A.8. We estimate ch anges in the level of relative earnings across
the four time periods using the following specification:
௤ସ
ሽ൅
൐ൌ 2008ሽ൅
൐ൌ 2010ሽ൅
൐ൌ 2013ሽ൅
௤          (1)
In this model,


2008–2009 injuries are compared to
2005–2007 injuries, 2010–2012 injuries are compared  to 2008–2009 injuries, 2013 injuries are
compared to 2010–2012 injuries, and 2014–2015 injuries are compared to 2013 injuries. The
group-specific trend break c


%
Relative employment
First post-injury year 89% 84% 83% 84% 85%
Second post-injury year 90% 84% 84% 86% 88%
Relative at-injury employment
First post-injury year 82% 80% 78% 78% 78%
Second post-injury year 76% 73% 71% 72% 72%
SOURCE: 2005–2015


p-values in
brackets. The p-values presented above are unadjusted. ** indicates Holm-adjusted statistical significance based on
a benchmark of α  = .05.
Table A.8d. Permanent Differences in Relative Earnings by Nature of Injury
Indemnity
Cumulat


5, 2018: https://www.dir.ca.gov/dwc/wcis/WCIS_tables/AggregateFRO ISROIData/AggregateFROIS
ROIData-Archive.html
Dworsky, Michael, Stephanie Re nnane, and Nicholas Broten, Wage Loss Monitoring for Injured
Workers in California’s Workers’ Compensatio


C-17-20, 2017. As of November
15, 2018: https://www.wcrinet.org/reports/adequacy-of- workers-compensation-income-benefits-in-
michigan
Seabury, Seth A., Robert T. Reville, Stephani e Williamson, Christopher F. McLaren, Adam H.
Gailey, Elizabeth Wi


Not Everything Is Broken
The Future of U.S. Transportation and Water
Infrastructure Funding and Finance
Debra Knopman, Martin Wachs, Benjamin M. Miller, Scott G. Davis,
Katherine Pfrommer
CORPORATIONLimited Print and Electronic Distribution Rights


 boundaries; and understanding different types of financing—public, private, and public-private partnerships. The premise is that if compel -
ling public benefits can be articulated and financial incentives properly aligned on both the public and pri


topics, and share our findings in innovative and compelling ways. RAND’s research findings and recommenda -
tions are based on data and evidence, and therefore do not necessarily reflect the policy prefer -
ences or interests of its clients, donors,


18.  Gr
owth in O&M Funding for Mass Transit by Source, 2000–2014  ...................... 26
  2.
19.  Fe
deral Spending Versus State and Local Spending on Water Infrastructure  ............. 28
  2.
20.  Pu
blic-Private Partnership Investment in th


ld focus its policies on incentivizing increased public and private spending on maintenance and modernization where it is needed.
But increased spending will not fix what is broken in our approach to funding and financ -
ing public works—and not eve


al public spending on highways decreased as a percentage of
GDP and has been relatively flat since then. Spending on mass transit, rail, water resources, and water utilities as a percentage of GDP increased or remained relatively flat between 1980 a


e at least 1956. The system of financing new and major rehabilitation projects through public borrowing and, to a much lesser extent, some version of public-private part -
nerships (PPPs) is generally working for projects that fall within single stat


riorities, policy constraints, and regional differences.
Though state and local governments are responsible for many pieces of this mosaic, Con -
gress could take a number of steps in conjunction with states, local governments, and the pri -
vate se


oning to a new federal system that more effectively links revenue collection to highway use.
Long-Term Priorities
Target longer-term projects likely to produce significant national benefits. Fund transportation and water improvements that will increa


fety, and environmental benefits and to those state and local governments that work together to identify their top priorities for federal capital spending. Federal funding would be conditional on regional sponsors securing matching funds from any com


opportunity to make design changes in old infrastructure or rethink infrastructure concepts entirely to meet new condi -Summary and Recommendations    xv
tions.  Following the lead of many states and cities, Congress should embed resilience guide-
li


water resource management in partnership with states, local governments, and other stakeholders; and bring the water infrastructure programs of the two agencies under the same congressional oversight. Consolidating the transportation modal administr


tions and investment.xviiAcknowledgments
This project was funded in part through RAND’s program of self-initiated research. We are
grateful to Susan Marquis, dean of the Pardee RAND Graduate School and Vice President of Innovation at RAND, and Howar


ic maintenance and repair of the infrastructure we already have and plans to raise enough money to keep it viable in the long term (Jaffe, 2016).
Largely missing from the current debate are clear and compelling answers to three fun -
damental questi


rom loaning money to governments to finance construction to footing the bill in exchange for the ability to collect user fees or other benefits. (In contrast, private investors dominate infrastructure spending for energy, telecom -
munications, and f


the investments it identifies will trim $4 trillion off of the U.S. gross domestic product (GDP) between 2016 and 2025. ASCE also suggests that the burden of the under -
investment falls disproportionately on the most disadvantaged communities, with


ports. ASCE’s
definitions of transportation and water infrastructure differ from CBO’s definitions.4    Not Everything Is Broken: The Future of U.S. Transportation and Water Infrastructure Funding and Finance
In the United States, infrastructure has


yors Water Council, 2007; Copeland, 2016). The federal government’s role in city water supplies is minimal in the eastern United States—but dominant in the western states through the massive public works projects of the U.S. Bureau of Reclamation (BO


ears, many advocates of increased infrastructure spending, as well as academics, have maintained that lengthy local, state, and federal environmental reviews of major projects impede construction and are a cause of underspending. They argue that “str


is a highly uncertain business, with an unimpressive track record (Flyvbjerg, Bruzelius, and Rothengatter, 2003). For technical reasons, cost and demand forecasts are characterized by large errors. It has been documented that where public funds are a


National or Regional Priorities
Unlike China or the European Union, the United States lacks a vision of how infrastructure can enhance economic growth and productivity, and, in the absence of such a vision, priori -
ties are difficult to articulate.


 billion between FYs 2005 and 2014 (GAO, 2016). Further, the dollar value of damage from extreme weather events has qua -
drupled in real terms over the past four decades (National Oceanic and Atmospheric Admin -
istration, National Centers for Envir


uence of the Sacramento and San Joaquin rivers (Rieke, 1996).
Misallocation of Capital
Unintended consequences of policies can lead to a misallocation of capital, whether public or private.
Bias Toward Capital Spending over Operations and Maintenance


so, in the name of regional equity, federal funding is distrib -
uted among regions and states using allocation formulas and, to some degree, earmarking of appropriations.
Legal Constraints on Public and Private Capital Flows
The federal tax code al


OR and the USACE have spent the better part of the past 30 years “reverse engi -
neering” their major 20th century water resource projects (e.g., dams on the Colorado River, the Everglades, and the lower Mississippi River) to mitigate the damages the


n    11
We first identified the features of transportation and water policies and programs that
exert a strong influence on priority setting, project evaluation, and funding and finance. Next,
we examined the supply side for infrastructure. We revi


-sector funding where possible and to rationalize public-sector investment to meet future needs. In Chapter Six, we consider some of the more significant recent changes in policy and practices across all levels of government in the United States. Som


Transportation and Water Infrastructure Funding and Finance
rehabilitation of structures and equipment already in place. Operation and maintenance  refers
to the costs of providing necessary operating services (e.g., air traffic control system); mai


 either increasing costs for repair and rehabilitation or an increasing likelihood that the project will become unusable. Decisions at this stage are further complicated by the need to consider
1  Federal support for water resource research has larg


ries are many different types and blends of funding options. On the public side, the
primary funder can be federal, state, or local government. It can also be some combination of those three or a regional authority that spans jurisdictions, such as


ral to state level, as well as from the state to local level, contribute a portion of the total funds spent on transportation, but the majority of total money spent comes from local governments’ own-source funding.
The proportion of spending by leve


on)Status of and Trends in Spending on Transportation and Water Infrastructure    19
Trends in Public Spending on Transportation and Water Infrastructure
CBO assembled a consistent data set on public infrastructure spending dating back to 1956,
when


l, State, and Local Spending on Transportation and Water Infrastructure, as a Share of Gross Domestic Product, 1956–2014
SOURCE: CBO, 2015, Exhibit 3, p. 10, based on data from OMB, the U.S. Census Bureau, and the U.S. Bureau of
Economic Analysis.
R


 GDP22    Not Everything Is Broken: The Future of U.S. Transportation and Water Infrastructure Funding and Finance
Figure 2.11
Per Capita Federal, State, and Local Spending on Transportation and Water Infrastructure, 1956–2014
1956
195819601962196419


ure suggests that the decline is consistent with the “built out” nature of our national highway system (Shatz et al., 2011; Mamuneas and Nadiri, 2006). Support for this view can be found in returns on invest -
3  Because of its land management respon


r vehicle-mile s traveled a nd vehicle-miles traveled per person include both
passenger and freight vehicles.
a The amounts show are based on the population residing in the United States.
RAND RR1739-2.16Index (1980 = 100)250
0
2010 2005 2000 1995


mmittee on U.S. Army Corps of Engineers Water Resources Science, Engineering, and Planning, 2011).
Federal spending on water utilities, shown in the top panel of Figure 2.19, peaked in the
mid-to-late 1970s, when it required local governments to bui


ic combined public and private investment, and the dashed line rep -
resents a regression model of the trend in the data.  The trend appears to show that invest -
ment is rising and may eventually become more significant in the future, especially as


 in federal funding for water and wastewater treatment infrastructure reflects congressional decisions to scale back involvement.
Taken as a whole, evidence of federal underspending on infrastructure from a national
perspective appears to be stronge


ers may sometimes also be direct beneficiaries of an infrastruc -
ture project, but not always. Depending on the funding and financing mechanism used, ben -
eficiaries may also include bondholders, shareholders, and various individual and institution


stment.
Federal Models for Funding
The federal government has many ways to spend money. Congress appropriates funds directly
to agencies that then disburse those funds themselves, through state and local governments, or through contracts, grants, an


Army Corps of EngineersNational Oceanic and Atmospheric
Administration
House Committee on Natural ResourcesU.S. Bureau of ReclamationNational Oceanic and Atmospheric
Administration
U.S. Fish and Wildlife Service
House Committee on Energy and Commer


not confined to a specific project. Examples are the annual distributions from the Highway Trust Fund by DOT to states and the U.S. Department of Housing and Urban Development’s Community Develop -
ment Block Grant (CDBG) Program to all 50 states and


nment pumps additional funding into the state revolving funds (SRFs)
each year, although year-to-year spending has been uneven, as shown in Figure 3.1 (Gies, 2012). States review and rank proposed projects according to their own priorities and withi


998, Congress enacted the Transportation Infrastructure Finance and Innovation Act (TIFIA; Pub L. 105-178, Title I, Subtitle E, Chapter 1) credit program, offering federal loans, loan guarantees, and lines of credit to state and local governments to


erty acquisition. The first $20 million of funds were not appropriated until December 2016 (EPA, no date-c; American Water Works Association, 2016). WIFIA can provide loans to state, local, and tribal governments for all projects eligible for CWSRF a


 are paid partially by the employer and partially by the employee, go toward the Social Security Trust Fund and the Hospital Insurance Trust Fund for use by the Social Secu -
rity and Medicare programs, respectively.
While income and payroll taxes a


form of lower interest payments, and mainly benefits the higher-income households that claim the tax break. Because the main incentive for purchasing these lower-yielding bonds is that the interest is tax-free, 75 percent of municipal bonds are held


he large upfront construction costs, which are then paid back over time using revenue from taxes or user fees. There are several ways in which this borrowing and repayment can occur.
Bonds
Local government bonds are effectively crowd-sourced loans


5 percent interest rate, the lender receives $1.05 million, assuming a term of one year. If the federal government pays 20 percent of the interest, then the state or local government that issued the bond pays only $1.04 million and the federal govern


g costs (DOT, Federal Highway Administration, Office of Innovative Program Delivery, no date-c).
A relatively new type of bond based on “pay for performance” is called an Environmental
Impact Bond and was recently used to support a “green infrastru


tor pay construction costs up front in exchange for the right to collect a revenue
15  Also see publications from the “Center for Transportation Excellence” for extensive data about sales taxes used all over
the country for transportation funding (


rrently in Use in the United States    43
The role of private finance in public infrastructure is complicated. First, as a baseline
condition, any owner of infrastructure, public or private, needs to be fully accountable to the
public in its compli


ansportation. It includes such approaches as transit impact fees, property tax increment financing, special assessment dis -
tricts, and increased property taxes (Moliere, 2017).
An important aspect of risk sharing in PPP arrangements relates to whic


ugh fees” (Kousser, McCubbins, and Moule, 2008), that TELs may raise borrowing costs (Poterba and Reuben, 1999), and that TELs harm overall economic growth through mechanisms such as encouraging underinvestment in infrastructure (Deller, Stallmann, a


 there is simply the risk of building something ambitious and long-lasting in a rap -
idly changing economy and technological environment. The amount of revenue that will flow from a project that will last for decades is difficult to predict. Estimat


hat cannot be easily
monetized through user fees or customer charges. These tend to be the projects least attractive to private investors seeking a predictable return competitive with other investment options. Mass transit projects fall into this ca


). Truckers have every reason to overload trucks to the point that they damage roads because doing so increases their returns in the short run (National Research Council, Transportation Research Board, 1997, pp. 24–25). While charging trucks directly


lls, 2012). The federal government does not operate, manage, or control most transporta -
tion infrastructure. It is one actor in a transportation infrastructure network that has national consequences but, by design, is highly decentralized. Most rur


tion. These plans, by definition, are financially constrained, in that they must include realistic plans for funding the implementation of the projects that comprise the regional plans (DOT, Federal Highway Administration, 2017d).
Dominance of Local


finance it.
3 Congress clearly articulated that states were the decisionmakers and provided them with
90 percent of the construction costs of interstate highways. In return, states agreed to build roads in compliance with a set of national standards


otection Act,
2  The Lincoln Highway was conceived in 1912 and dedicated in 1913 (Lincoln Highway Association, no date).
3  The federal Highway Trust Fund was created through the Interstate Highway Act of 1956. A 1947 map of the then-
proposed Natio


rtation infrastructure, includ -
ing revenues from the sale of strategic oil reserves, from repatriated corporate profits on foreign operations, or from a revamped fuel tax. One idea is a tax linked to both inflation and aver -
age fuel efficiency. T


red that DOT publish systematic
assessments of the “conditions and performance” of the surface transportation system. These biannual reports incorporate estimates of resources that would be required to meet anticipated needs. States are required to


. The physical condition of bridges improved slightly over the past few years, but, as with all classes of assets, location matters. Figure 4.1 displays a snapshot of the percentage of structurally deficient bridges, by county, for the entire United


sment, and the ASCE, which pub -
lishes the periodic Infrastructure Report Card , all represent deep knowledge of infrastructure
needs yet all are also ultimately advocates for improved infrastructure. 54    Not Everything Is Broken: The Future of U


ly measure current performance and state goals and objectives,
and quantify financing needs according to these federally specified criteria. There is an evolv -
ing federal “toolbox” of methods that facilitates the transition. While there is recogni


e
ings due to changes in travel costs; and, often, environmental impacts, such as changes in air
pollutant emissions.
CBA requires that benefits be “monetized” by estimating dollar values of benefits that are
not usually measured in dollar terms.


e these projects.
5  Some oppose CBA on grounds that include the ultimate subjectivity of the choices of economic values, and because of
the propensity to “double count” benefits when, for example, air quality improvements result in increased proper


be replaced or should be financed dif -
ferently going forward.
Improvement of navigable waters came first when Congress in 1824 authorized the
USACE, formally established in 1802, to improve navigation on the Ohio and Mississippi 58    Not Everythi


because they have outlived their useful lifetimes and otherwise disrupt natural sys -
tems (Wegner, 1990). To some extent, the water resource agencies’ missions in the 21st century can be characterized as one of “reverse engineering” many of their ma


xtent.
For the same reasons that user fees or their equivalent are essential for maintenance of
transportation facilities, proper pricing of water services is critical to the sustainability of water utilities. Yet, full-cost pricing, in which life-


. Since the early 1990s, Detroit has generally maintained its lead levels in compliance with federal standards. In 2013, Detroit canceled its arrangement with Flint after Flint’s city council voted to switch to a new pipeline from Lake Huron. In Apri


movement toward intermodal transportation planning identified in Chapter Three.
Even though integrated water resource management is widely accepted among water pro -
fessionals in the United States and throughout the world, actual implementation has


from wastewater and drinking water systems, water resource infrastructure includes dams, levees, harbors, canals, and the locks and dredged channels of navigable waterways. Capital spending for federal water resource programs has been in decline for


stgarten and Sadasivam, 2015; Reisner, 1986).Table 5.1
Federal Cost-Sharing for Capital and O&M by Type of Water Infrastructure
Project PurposeMaximum Federal Share of
Construction (%)Maximum Federal Share of
O&M (%)
Navigation
Coastal ports
<20 f


er markets and trading, now in limited use
in the western United States, could lead to more efficient pricing and hence allocation of water from federal water projects, but, thus far, the idea has not taken hold because of significant technical, ins


al Safe Drinking Water Act regulates the qual -
ity of drinking water at the tap for more than 152,000 public water systems in the United States. Ninety-seven percent of these public water systems serve communities of 10,000 or fewer people, but, in


population growth and age of the system. Assumptions about construction costs, including the price of energy, also influence the numbers. Assessments also differ by the method used to generate the estimates. For example, the EPA’s Drinking Water Inf


2011 dollars for comparison purposes.Figure 5.3
Comparison of Needs Assessments for Water Utility Infrastructure
SOURCES: EPA, 2013; American Water Works Association, 2012.
NOTE: WIN = Water Infrastructure Network; AWWA = American Water Works Associa


WIN estimates “the cost of building, operating, and maintaining needed drinking water and wastewater facili -
ties over [2000–2019] approaches $2 trillion” in 1999 real dollars.
In sum, the wide range of estimates produced from inconsistent assessme


 projects. Principles, Requirements and Guidelines for Water and Land Related Resources Implementation Studies  (PR&G), a document maintained by the Council on Environmen -
tal Quality, establishes principles and evaluation criteria to guide federal


ion of water or wastewater infrastructure projects, but the federal government influences project selection indirectly through regulatory actions (e.g., court orders to force local or state action on a storm water or wastewater facility as a conseque


ies, for which 90 percent of investment
happens at the local level, largely through the use of municipal revenue bonds and property assessments. Federal water quality and drinking water laws and regulations drove much of 70    Not Everything Is Brok


attributes of such a policy. This is not impossible to do. A report published in 2006, known as the Eddington Report, is an example of such a long-term vision and policy statement (Eddington, 2006). While originating in the UK, the report is directe


hese markets.
3.
 Pr
omote the federal role of inducing and encouraging investment in multijurisdictional
programs, such as those that serve intercity travel and freight transport and those that address river basins and large watersheds that cross s


an also be expressed through federal grant programs. Project-based
grants have the ability to more effectively target federal resources to the most critical needs from a national perspective. They can demand certain conditions of project submissions


ted States for the Impacts of Climate Change ).74    Not Everything Is Broken: The Future of U.S. Transportation and Water Infrastructure Funding and Finance
demand that far exceeds available resources. For the FY 2016 round ($500 million available),


tion to plan for and implement feder -
ally assisted transportation and water projects according to their needs and priorities. DOT’s Surface Transportation Program, through which states pass a substantial portion of funds to regions, has historicall


implify administration of currently stovepiped grant programs while increasing flex -
ibility and outcomes is likely to be worth the effort.
The Trump Administration’s budget document for FY 2018 highlights its priority to
remove, reduce, or better


r Fee Pilot Program Results Summary,” no date). These are increas -
ingly feasible because of developing technology, such as vehicle telematics, global positioning satellites, cell towers, and on-board diagnostics, that can report vehicle movements.


ation, and the Investing in Manufacturing Communities Partnership. Policy Options    77
The policy sought to maximize economic growth and increase the cost-effectiveness of federal
financial investments. It also directed agency staff and technical a


cent examples can be seen is the Desal Prize, sponsored by the U.S. Agency for International Development and the BOR, and the Smart City Challenge, sponsored by DOT.
The Desal Prize was an engineering competition to develop technologies that could d


ecutive order, and a detailed implementation plan (U.S. Depart -
ment of Treasury and U.S Department of Transportation, Build America Investment Initiative Interagency Working Group, 2015).
In his first days in office, President Trump announced his i


r 5 percent of GDP, under current program assumptions (CBO, 2017). This projection will change depend -
ing on tax cuts and spending increases enacted in the coming years.
Direct Federal Spending
The challenge for sponsors of bills authorizing direc


ls. In addition, they would set aside $200 million of the $1 trillion for projects of national 80    Not Everything Is Broken: The Future of U.S. Transportation and Water Infrastructure Funding and Finance
significance or what they call “vital infras


t of the total $1 trillion investment will become new wages, and 10 percent will
become new corporate profits.
• Wa
ges and corporate profits will be taxed at an average rate of 28 percent (personal
income) and 15 percent (the capital gains tax rat


ling properties as potential investors, but they currently invest relatively little in domestic infrastructure. This is because their long-run investment interests tend to match the long lifespans of infrastructure projects better than the investment


opening the door to more-effective means for alternative investors to assess and choose attractive long-term investment opportunities. In parallel with such thinking, states could also share their experiences with past PPPs to do a better job of fulf


ralia has been experimenting with an “asset recycling” program, essentially a means
of privatizing many public infrastructure systems while generating cash for local government Policy Options    83
to invest in new infrastructure. Its success has st


U.S. GDP has been remarkably stable since 1956. Private funding in these areas of infrastructure is less than 3 percent of the total, nearly all of which is for rail. When federal spending has declined, state and local governments often have picked u


percent of capital investment (CBO, 2015). The evidence suggests that the division of responsibility among the levels of government is generally appropriate and does not warrant wholesale change. In addition, the federal government could do a better


ve value to different types of public assets and services. Under our system of federalism, states are empowered to make their own choices on these matters.
Some projects may generate national economic benefits, but not commensurate revenues,
in part


olicy landscape. The justification for the BOR in 1902 to reclaim the Great American Desert is no longer valid. At the beginning of the 20th century, the U.S. population was 60 percent rural and 40 percent urban (U.S. Census Bureau, 1995). Now, 80 pe


e hybrid and electric vehicles come into wider use, the decline in revenues from the sale of motor fuels will continue. To restore stability and sustainability to the Highway Trust Fund, Congress should support a robust program of pilot testing and e


sting assets will make matters worse for local governments struggling to make payments on existing debts.
Congress should place its highest maintenance priorities on vital federal assets. The
federal government has a responsibility to properly main


could provide technical assistance and help with tax issues and permitting processes.
The federal government should streamline regulatory approval processes involving
multiple federal agencies while honoring applicable environmental, health, and sa


 infrastructure and Summary of Findings and Recommendations    91
improve building methods and materials, engineering designs, cost-effectiveness and efficiency,
and all aspects of system operations.
Widespread adoption of newer construction method


ilt the Transcontinental Railroad, 1863–1869 ,
New York: Touchstone, 2000.
American Public Transit Association, 2016 Public Transportation Fact Book , Washington, D.C., February
2017a. As of September 18, 2017:
http://www.apta.com/resources/statis


Boschetti, T., Building Oregon’s Future: The Current Landscape of Infrastructure Finance in Oregon , Portland,
Ore.: Oregon Chapter of the American Planning Association, December 2014.Braun, Martin Z., “Meadowlands Mega-Mall Wins Bond-Market Subsidy


 Drinking Water and Wastewater Infrastructure , Washington,
D.C., November 2002.———, “Options for Reducing the Deficit: 2014 to 2023: Eliminate the Tax Exemption for New Qualified
Private Activity Bonds,” November 13, 2013. As of September 18, 2017


t Cut in TIFIA Funding Justified?” Eno Transportation Weekly ,
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-9971-6ISBN-10 0-8330-9971-X
53500$35.00This report identiﬁes the policies that promote and deter investment in and maintenance of U.S. transportation and
water infrastructure. It focuses on status and trends in operations and maintenance (O&M) and


CORPORATION
Los Angeles County
Juvenile Justice Crime Prevention Act
Fiscal Year 2015–2016 Report
Terry Fain and Susan TurnerLimited Print and Electronic Distribution Rights
This document and trademark(s) contained herein are protected by law. This


atively mandated evaluation of the county’s JJCPA programs, including analyzing data and reporting findings to the BSCC. This report summarizes the fiscal year (FY)  2015–2016 findings reported to the BSCC, as well as additional program information g


le Justice Crime
Prevention Act: Fiscal Year 2007–2008 Report , Santa Monica, Calif.: RAND Corpora -
tion, TR-746-LACPD, January 2010a
• Sus
an Turner, Terry Fain, and Amber Sehgal, with Jitahadi Imara and Felicia Cotton of
the Los Angeles County P


oups and Reference Periods for JJCPA Programs  ............................. 103
B. Pro
bation’s Ranking of the Big Six Outcome Measures  ......................................... 105
C. Com
munity-Based Organizations That Contracted to Provide Servi


............... 18
 2.5
. Dem
ographic Factors for Special Needs Court and Comparison Group  .................. 23
 2.6
. Pro
grams and Comparison Groups in the Enhanced Services to High-Risk/
High-Need Youths Initiative  ...........................


e Costs for Special Needs Court  ................................... 77Figures and Tables    xi
 3.5. Estimated Juvenile Justice Costs for Gender-Specific Community  .......................... 79
 3.6
. Est
imated Juvenile Justice Costs for High Risk


m the hall.
3 At-risk youths are those who have not entered the probation system but who live or attend school in areas of high crime
or who have other factors that potentially predispose them to participating in criminal activities.xiv    Los Angel


les County for JJCPA programs and services. The actual final budget was $26.3 million. JJCPA funding represents roughly 15 percent of field expenditures for juve-nile justice programs, or about 5 percent of all expenditures for programming for youths


n of community service.
An ideal outcome would be for no program participants to be arrested, incarcerated, or in
violation of probation and for all to complete probation and (if applicable) restitution and com -
munity service. However, because, fo


e or she receives services and could therefore count that youth more than once.
Table S.1 lists the JJCPA programs in each initiative in FY 2015–2016 and the number of
participants who received services in each program.
Table S.1
Programs in the Thr


and Numbers of Participants for Whom Probation Reported Outcomes
Initiative or
Program Participants Comparison GroupComparison-
Group Members
I. Enhanced Mental Health Services
MH 1,117 FY 2014–2015 MH participants 1,081
MST 74 MST-identified near m


youths. We do not determine whether a given outcome is “good” or “bad.” We simply report whether a between-cohorts comparison shows a statistically significant difference between the two measures.
Although we do have data to look at historical trends


and comparison-group youths.
 –SBH
S-PROB participants showed more-positive outcomes for four of the big six out -
comes.
 –SBM
S-PROB participants had significantly higher rates of completion of probation.
There was no significant difference betwee


results for MH participants is the finding that program participants had signifi -
cantly fewer incarcerations than comparison-group youths and did not differ significantly on any of the other big six outcomes. The difference-in-differences analyses


it from the program, which -
ever came first. Among HRHN participants, measures of family relations also improved sig -
nificantly in the six months between program entry and exit. In the YSA program, the two supplemental outcomes—percentage of youth


st program that used a contemporaneous comparison
group, were significantly more positive for all supplementary outcomes (school attendance, suspensions, expulsions, and overall strength and risk scores) following program entry. For xxii    Los Ange


OTE: FY 2015–2016  in this table indicates that the FY 2015–2016 cohort had a significantly more positive result,
while FY 2014–2015  indicates that the FY 2014–2015 cohort had a significantly more positive result. A dash
indicates no significant d


tice Crime Prevention Act: Fiscal Year 2015–2016 Report
Estimated Total Cost of Programs and Initiatives
Table S.6 shows the estimated mean baseline and follow-up costs per participant in each JJCPA
program in FY 2015–2016. The table also shows weig


4 162
Camp –1,400 1,667 –28
Court –1,404 –613 –96
Juvenile hall –4,088 –628 –174
Program –621 –2,094 –443
Supervision –315 –98 –74
Total –7,349 –1,563 –555
NOTE: A positive number in this table indicates that mean costs were lower in the six months a


e appropriateness of any findings based on such a small subsample. For example, of the 1,117 MH participants whose outcomes the program reported, only 142 (12.7 percent) had supplementary outcome data.
FY 2015–2016 was the 16th consecutive year for w


’s superb editing of this and previous Juvenile Justice Crime Prevention Act reports.xxxiAbbreviations
AB assembly bill
ACT Abolish Chronic Truancy
ADA average daily attendance
BOC Board of Corrections
BOS Los Angeles County Board of Supervisors
BSCC


ods, schools, and other areas of high juve-
nile crime
• a str
ategy to provide a continuum of graduated responses to juvenile crime.
In addition, the county required that, to be funded, a program be based on approaches
demonstrated to be effective


paring rates between pro -
gram and comparison groups for each outcome. A chi-square test requires that each cell of a 2 × 2 table contain at least five observations.
3 Some programs (e.g., very small programs or
those with very low arrest rates) di


f all expenditures for programming for youths.
JJCPA programs are grounded in social-ecological research. The central tenet of this
approach is that behavior is multidetermined through the reciprocal interplay of a youth and his or her social ecolog


atment group in all ways except for the receipt of treatment (i.e., the comparison group
would not receive any). In practice, the evaluation might not identify or measure all factors. However, in criminal justice research, researchers often match co


is weakness in mind. In particular, pre–post comparisons for probation-related outcomes, such as successful completion of probation, do not take into account whether the youth was on probation prior to program entry. This can tip the scale in favor o


se to 18 years old or because Probation did not consider their level of mental illness, which would have qualified them for the program in previous years, to be severe enough after SNC changed its qualification criteria. Prior to FY 2007–2008, histor


completion of probation, arrests, probation violations, incar -
cerations, successful completion of restitution, and successful completion of community ser -
vice. See Appendix B for an explanation of this rank ordering.
An ideal outcome would be for


ram start.Background and Methodology    7
Difference-in-Differences Analyses
When using the previous year’s program participants as a comparison group for the current
year’s program participants, we implicitly assume that the two groups have compara


rp ost 01 23 , () () () () =+ ×+ ×+ ××
where outcome  is the logarithm of the odds ratio for a binary outcome measure (e.g., whether arrested during the reference
period), year is a binary variable coded 1 for the current year and 0 for the previo


017, p. 7). Using these historical comparison groups produces a weaker design than using one that includes a contemporaneous comparison group does.
Data Quality
Probation extracted data used to compute outcome measures from its databases. Probation h


ang order (i.e., an order not to associate with known gang members).
Organization of This Report
The remainder of this report focuses specifically on JJCPA programs in Los Angeles County
in FY 2015–2016. Chapter Two details JJCPA programs and presen


ogram, ACT, was administered
to 12,871 youths who had no involvement in the juvenile justice system. Of the remaining 20,633 youths who received JJCPA service, 13,073 (63.4 percent) were probationers, while 7,560 (36.6 percent) were at-risk youths.


obationers and At-Risk YouthsSBHS-AR 3,511
SBHS-PROB 1,905
SBMS-AR 1,231
SBMS-PROB 85
Total 33,504
NOTE: We determine the number of participants in a given program by who received services during the fiscal
year, which lasted from July 1, 2015, to J


icipants. We statistically matched routine probationers used as members of comparison groups for SBHS-PROB and SBMS-PROB to program participants. MH reported outcomes only for participants who received treatment services. See Appendix A for more deta


records for dispositions are sometimes incomplete, so, for some probationers, we cannot determine whether they completed probation or had probation violations. Sample sizes for sup -
plemental outcomes might be considerably smaller because, for insta


use disorders, then develops individual treatment plans. In conjunction with treat -
ment providers, probation officers and case managers supervise the youths. An evaluation of the program found that it provides an important service and coordinating


We base the supplemental outcome for the MH program on mean scores on the BSI.
Leonard R. Derogatis developed the BSI (Derogatis and Melisaratos, 1983) to reflect the psy -
chological distress and symptom patterns of psychiatric and medical patient


ar comparisons of program outcomes. In many instances, counties have no expectation that program outcomes will improve from year to year, given that no signifi  cant changes are expected in the program and/or the youth served by the program. Th  us,


revious year to the current year. A negative value in
that column indicates a reduction, while a positive value shows an increase, in the difference in differences.
Multisystemic Therapy
MST is an intensive family- and community-based treatment that


ighly individualized and comprehensive basis. MST practitioners are available 24 hours per day, seven days per week, and provide services in the home at times convenient to the family. This approach attempts to circumvent barriers to service access t


e six months following program entry for MST
participants. For comparison-group youths, we measured big six outcomes during the six months following the date of nonacceptance into the MST program. We measured supplemen -
tal outcomes for MST partici


2015–2016 Report
Evidence Base for the Program
In April 2000, the U.S. Department of Justice (DOJ) reviewed four then–recently developed
adult mental health courts in Fort Lauderdale, Florida; Seattle, Washington; San Bernardino, California; and Anc


e juvenile courts actually had a sig -
nificant advantage over adult courts because therapeutic intervention is more consistent with the general approach to juvenile justice. The juvenile drug court model was soon generalized to address concerns othe


eeds Court and Comparison Group
Factor SNC ( N = 25) Comparison Group ( N = 24)
Mean age, in years 15.2 15.5
Gender, as a percentage
Male 64.0 62.5
Female 36.0 37.5
Race and ethnicity, as a percentage
Black 24.0 29.2
White 16.0 16.7
Hispanic 60.0 54.


other supplemental outcome was statistically significant between the two groups.
In the MH program, the only one in this initiative that used the previous year’s par -
ticipants as a comparison group, difference-in-differences analysis agreed with a


l success and healthy social development.
School-, park-, and housing-based DPOs refer female participants to gender-specific ser -
vices. The DPOs rely on the Los Angeles Risk and Resiliency Checkup (LARRC) to assess criminogenic risk and need facto


(such as friends, relatives, neighbors, and church
members)
• pro
grams that tap girls’ cultural strengths rather than focusing primarily on the indi -
vidual girl (e.g., building on Afrocentric perspectives of history and community relation -
ships


omparison group for the current year’s GSCOMM participants consists of GSCOMM participants whose outcomes we reported for the previous year (FY 2014–2015), with the goal of them performing at least as well in the current year as they did in the previ


ly and other parts of the participant’s environment. It focuses on school attendance and per -
formance, parenting skills, and family functioning. The SLC is designed as a set of program enhancements to supplement services for HRHN participants. The


eam, along with program staff. MTFC parents implement a structured, indi -
vidualized program for each participant, designed to simultaneously build on the partici -32    Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016


uired for high-risk and high-need parolees unless they broker services through a host of community resources (Altschuler and Armstrong, 1994; Wiebush, McNulty, and Le, 2000).
The employment component of the HRHN program draws from Guide for Implement


trument used to measure family relations.
Outcomes
For outcome analyses, we examined 1,237  HRHN participants from FY  2015–2016 and 1,275 program participants whose outcomes we reported in FY 2014–2015. The FY 2014–2015 cohort showed significantly h


e value shows an increase, in the difference in differences.
a Difference is statistically significant ( p < 0.05).
Difference-in-differences analyses produced results slightly different from those of a
simple comparison between the two cohorts. We


ded to enhance self-control. Specific techniques include exploring the positive and negative consequences of continued use, self-monitoring to recog -
nize drug cravings early on and to identify high-risk situations for use, and developing strate-gie


ome measures on the performance of 200 YSA participants in FY 2015–2016
and 156 in FY 2014–2015. Diff  erences between the two cohorts were not statistically signifi  -cant for any of the big six outcomes, thus meeting program goals of no diff  eren


or the population of probationers and at-risk youths in the schools. A secondary goal is to enhance protective factors through improved school per -
formance. The program identified the 85 targeted neighborhoods as the most crime-affected neighborhoo


d were statistically significant ( p < 0.05), meaning
that the performance of JJCPA participants differed significantly from that of comparison-group youths or from their baseline measures.
9 Sample sizes indicated are for the entire pro -
gram and


Base for the Program
An OJJDP paper, Truancy: First Step to a Lifetime of Problems (Garry, 1996), cites truancy as an indicator of and “stepping stone to delinquent and criminal activity” (p. 1). The paper notes that several studies have documented t


omes six months before and six months after program entry.
We measured the supplemental outcome, school absences, in the six months before and after
entry into the program.
Outcomes
For outcome measures, we examined 6,397  ACT participants. Consist


follow-up periods, we do not present a figure
illustrating outcomes for ACT.Current JJCPA Programs and FY 2015–2016 Outcome Measures    43
mance, decreasing the youth’s involvement with delinquent drug-using peers, and increasing
association with p


15 and FY 2015–2016. Those hous-
ing sites had received JJCPA services in previous years.44    Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016 Report
Outcomes
For outcome measures, we compared the baseline and follow-u


al communi -
cation
• rec
ognition: distribution of participants’ writing to parents, schools, libraries, government
officials, and the general public.
Evidence Base for the Program
Many juvenile detainees have reading and writing levels significant


IOW program met program goals for five of the big six outcomes and exceeded the program goal for arrests.
The mean number of SIRs six months after program entry (or in the last 30 days of the
program, whichever came first) were significantly lower i


vice providers, and the Probation Department collaborate to provide after-school enrichment programs and supervision for youths on formal probation, as well as at-risk youths, in selected locations in the 85 school service areas. These after-school e


ool, sports, and work; and (3) successfully navigate the various rules and socially accepted routines required in a vari -
ety of settings (J. Hawkins and Catalano, 1992; Connell, Aber, and Walker, 1995). Implicit in this perspective is the recogniti


s by enforcing conditions of probation and by daily
monitoring of school performance (attendance, performance, and behavior)
• pre
venting arrest and antisocial and delinquent behavior by at-risk youths
• hol
ding probationers and at-risk youths and


ram’s call for case-management interventions that
•
 asse
ss the probationer’s strengths and risk factors
• emp
loy strength-based case-management interventions
• add
ress both risk factors and criminogenic needs
• emp
loy evidence-based treatment in


try and the term following program entry. We compared strength and barrier scores at program entry and six months later.
Outcomes for School-Based Probation Supervision for High School At-Risk Youths
For outcome analyses, we compared 1,765 SBHS-AR an


dicates that no one in the cluster had the indicated outcome.
Difference-in-Differences Analyses for School-Based Probation Supervision for High School
At-Risk Youths
SBHS-AR uses program participants from the previous year as a comparison group, so


score weighting to obtain weights for comparison-group youths so that
their characteristics matched those of the program participants. We included only probationers with valid data on all vari -
ables in creating weights for the comparison group. Be


 risk scores 56    Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016 Report
decreased signifi  cantly, from a mean of 7.3 at program entry to 3.6 six months after entering
the program. Strength scores also increased sig


ams.Current JJCPA Programs and FY 2015–2016 Outcome Measures    59
Table 2.15
Comparison of School-Based Probation Supervision for Middle School At-Risk Youths in FY 2015–2016 and Those in FY 2014–2015
Factor FY 2015–2016 ( N = 730) FY 2014–2015 ( N


61
Figure 2.14
Outcomes for School-Based Probation Supervision for Middle School At-Risk Youths, by Cluster, FY 2015–2016
NOTE: A missing bar for a cluster indicates that no one in the cluster had the indicated outcome.
Table 2.16Means, Differences i


 used the appropriate
weights for the comparison group. None of the differences between the two groups was statis -
tically significant. The standardized bias estimates were very low for all variables in the model, the highest being 0.03254 for gang


pants also had significantly lower risk scores (4.5 versus 6.8) and higher strength scores (13.2 versus 7.3) six months after entering the program than at program entry. SBMS-PROB participants were significantly more likely than comparison-group yout


and IOW showed signifi  cant improvements in supplemental outcomes as well.
Th  ree of the programs in this initiative—IOW, SBHS-AR, and SBMS-AR—used the pre-
vious year’s program participants as comparison groups. For IOW and SBMS-AR, diff  erence-i


venile justice costs. Probationers, by contrast, might have been under supervision prior to program entry and might have also incurred other juvenile justice costs. This implies that JJCPA programs that predominantly target probationers are more like


the cost of juvenile hall for those who spend time in the halls, the cost of juve-nile camp for those assigned to camp, and the various costs associated with arrests and court appearances. In our analysis of overall JJCPA costs, we have attempted to


n camp cost approximately $772.32 (Bryant, 2016). It estimated routine probation supervision to cost $7.41 per day (Bryant, 2016). The rates in FY 2015–2016 have increased from those of FY 2014–2015 because of a variety of factors, including increase


ys the youth attended school in the follow-up period than in the baseline period. The total cost was the sum of these individual costs, and the number of units was a mean over all program participants. Because of missing data for some components, tot


he cost is more evenly distributed among participants in the program.
Estimated Costs for Mental Health Screening, Assessment, and Treatment
Table 3.2 shows the estimated juvenile justice costs for the MH program. The only part of the MH program admi


geles
County JJCPA program. The 25 participants in this program spent no time in camp in either period. Driven primarily by the huge reduction in juvenile hall days, estimated total costs were only $1,383 higher in the follow-up period than during t


CPA Participants    79Table 3.5
Estimated Juvenile Justice Costs for Gender-Specific Community
Juvenile
Justice CostUnit Cost, in
Dollars UnitBaseline Follow-Up Difference, in Dollars
UnitsMean, in
DollarsMedian, in
Dollars UnitsMean, in
Dollars


 cost was higher after entering the program than before entering. Dollar amounts are in 2015 dollars.82    Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016 Report
define the follow-up period for IOW participants as the


 for IOW participants averaged $23,699 in the baseline period and $25,291 in the follow-up, a difference of $1,592 per participant.
Estimated Costs for After-School Enrichment and Supervision
As noted above, for JJCPA programs that target primarily a


le hall, and program administration. Program costs were relatively modest ($1,317 per participant), and school attendance improved. Overall follow-up costs were $162 more than baseline costs.
Estimated Costs for School-Based Probation Supervision for


 0 1,257 1,070 –1,069 –1,070
NOTE: A positive number in a difference column indicates that the cost was lower in the six months after beginning the program than in the six months before
beginning. A negative number indicates that the cost was higher


total number who received JJCPA services in FY 2015–2016, a large percentage of both are in the ACT program. ACT, whose primary goal is improved school attendance, exclusively targets at-risk youths who have virtually no involve-ment with the juveni


4    Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016 Report
a large number of at-risk youths, saw the bulk of its expenses in program costs, whereas its
costs for arrests and camp were lower in the six months after pa


pant can
receive services from more than one initiative and from multiple programs, within or across initiatives, and concurrently or consecutively. Probation counts a given youth as a participant within each program from which he or she receives se


rams, particularly those targeting only at-risk youths, the largest contribu -
tor to total juvenile justice cost was the cost of administering the JJCPA program itself.
 –Com
paring costs in the six months following program entry and those from the


ograms. A simple comparison between the two HRHN cohorts showed no significant difference in arrest rates at either baseline or follow-up. However, a difference-in-differences analysis revealed that the FY 2015–2016 participants showed a significantl


ee of the programs in this initiative—IOW, SBHS-AR, and SBMS-AR—used the pre-
vious year’s program participants as comparison groups. For IOW and SBMS-AR, difference-
in-differences analyses agreed with a simple comparison of rates for all outcomes.


articipants significantly improved their school attendance after program entry.
Outcomes of Simple Comparisons Between Cohorts
For seven Los Angeles County JJCPA programs (GSCOMM, HRHN, IOW, MH, SBHS-AR, SBMS-AR, and YSA), the county evaluates outcom


received.Table 4.1
Results from Simple Comparisons in Programs That Used the Previous Year’s Cohorts as Comparison Groups
Program Arrest IncarcerationCompletion of
ProbationCompletion of
RestitutionCompletion
of Community
ServiceProbation
Violat


016 — — — — —
IOW FY 2015–2016 — — — — —
MH — — — — — —
SBHS-AR FY 2014–2015 — n.a. n.a. n.a. n.a.
SBMS-AR — — n.a. n.a. n.a. n.a.
YSA — — — FY 2014–2015 — —
NOTE: FY 2015–2016  in this table indicates that the FY 2015–2016 cohort had a significantly


ting statewide juvenile jus -
tice data systems. Reports will also include a summary or analysis of how grant funded pro -
grams have or may have contributed to or influenced the countywide data that is reported.
The current outcome reporting require


youths (program participants) as 1. We then use these weights to compare the mean values of the two groups on each of the independent variables. If the treatment and comparison groups show similar mean values when we apply the weights, subsequent an


ation.
4.
 inc
arceration: Like arrest, incarceration is a valid indicator of delinquency and recidi -
vism. However, incarceration can also be used as a sanction for case-management pur -
poses, and courts often impose incarceration as a sanction to


 Individual Treatment and
Training (SPIRITT) Family ServicesSubstance abuse treatment 1, 5
Star View Children and Family Services Home-based HRHN, female 1
Home-based HRHN, male 2, 4
Tarzana Treatment Centers Substance abuse treatment 3, 5Table C.1—


measured supplemental outcomes during the last complete academic period before the youth entered the program and during the first complete academic period after the youth entered the program.
a Difference is statistically significant ( p < 0.05).BSCC


e and during the six months after the youth
entered the program. We measured the supplemental outcome during the 180 days before and the 180 days
after the youth entered the program.
a Difference is statistically significant ( p < 0.05).116    Los


nrichment and Supervision, FY 2015–2016
Mandated
OutcomeBaseline Follow-Up
Number Percentage Sample Size Number Percentage Sample Size
Arrest 3 0.18 1,652 6 0.36 1,652
Incarceration 1 0.06 1,652 3 0.18 1,652
Completion of probationn.a. n.a.
Completi


ion331 34.95a947 12 0.96 1,210
Completion of restitution151 27.11a557 186 20.38 911
Completion of community service80 15.01
a533 5 0.55 879
Probation violation47 4.96 947 62 5.13 1,210
Supplemental OutcomeBaseline Follow-Up
Number Mean Sample Size Nu


dle School Probationers, FY 2015–2016
Mandated
OutcomeProgram Comparison
Number Percentage Sample Size Number Percentage Sample Size
Arrest 7 15.91 44 133 28.52 466
Incarceration 2 4.55 44 38 8.07 466
Completion of probation4 12.12a33 5 1.20 444
Com


 Participants
Number Percentage Sample Size Number Percentage Sample Size
Arrest 1 2.78 36 2 5.88 34
Incarceration 0 0.00 36 0 0.00 34
Completion of
probationn.a. n.a.
Completion of restitutionn.a. n.a.
Completion of community servicen.a. n.a.
Proba


mple Size % Sample Size
Arrest 0.00 13 — 0 0.00 21 — 0 8.33 36
Incarceration 0.00 13 — 0 0.00 21 — 0 0.00 36
Completion of
probationn.a. n.a. n.a. n.a. n.a.
Completion of restitutionn.a. n.a. n.a. n.a. n.a.
Completion of community servicen.a. n.a. n


letion of community service0.00 2 15.38 13 — 0 0.00 1 3.33 3
Probation violation0.00 3 0.00 19 0.00 5 0.00 1 0.00 5
NOTE: — = No one was assigned restitution in this cluster.133APPENDIX G
Probation’s Form for Measuring Family Relations
This appendix


on
      Family Criminality
      Identify Family Criminality
      Economic Limitations

TOTAL CHECKS      TOTAL CHECKS

TOTAL STRENGTHS (SUM TOTAL CHECKED NUMBERS)      TOTAL RISKS (S


TAL RISKS (SUM TOTAL CHECKED
NUMBERS)      139Bibliography
AB 1913— See California State Assembly, 2000.
AB 1998— See California State Assembly, 2016.
Acton, Sgt. Jeffrey K., Los Angeles County Sheriff’s Department, email to the authors, November 4,


ounty Juvenile Justice Crime Prevention Act: Fiscal Year 2015–2016 Report
California Attorney General, “CJSC Statistics: Crimes and Clearances,” undated web page. As of February 7,
2017:
http://oag.ca.gov/crime/cjsc/stats/crimes-clearances
Califor


 Lisbeth B. Schorr, and Carol H. Weiss, eds., New Approaches to Evaluating Community Initiatives: Concepts, Methods, and Contexts, Washington, D.C.: Aspen Institute, 1995, pp. 93–126. As of February 7, 2017: http://eric.ed.gov/?id=ED383817
Cottle, Ci


eports/RR268.html
———, Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2012–2013 Report , Santa Monica,
Calif.: RAND Corporation, RR-624-LACPD, 2014. As of February 7, 2017:
http://www.rand.org/pubs/research_reports/RR624.html


 Peters, and Associates and Northwest Regional Educational Laboratory, Guiding Principles for
Promising Female Programming: An Inventory of Best Practices , Rockville, Md.: U.S. Department of Justice,
Office of Justice Programs, Office of Juvenile


.
Huddleston, West, and Douglas B. Marlowe, Painting the Current Picture: A National Report on Drug Courts
and Other Problem-Solving Court Programs in the United States , Washington, D.C.: National Drug Court
Institute, July 2011. As of February 7,


drugcourts_review.pdf
Morley, Elaine, Shelli B. Rossman, Mary Kopczynski, Janeen Buck, and Caterina Gouvis, Comprehensive
Responses to Youth at Risk: Interim Findings from the SafeFutures Initiative—Summary , Washington, D.C.,
November 2000. As of


, Handbook of Family Therapy , New York: Brunner/Routledge,
2003, pp. 323–348.
Skowyra, Kathleen R., and Joseph J. Cocozza, Blueprint for Change: A Comprehensive Model for the
Identification and Treatment of Youth With Mental Health Needs in Contac


 Counseling, Regent University, “Los Angeles County
Social Learning Model,” presentation to the Los Angeles County Probation Department, Downey, Calif., 2005.
Westermark, Pia Kyhle, Kjell Hansson, and Martin Olsson, “Multidimensional Treatment Foste


CORPORATION
Can an Informative Letter
Reduce Gun Crime and Be Cost-Effective?
A Study of Los Angeles
Priscillia Hunt, Layla Parast, Gabriel WeinbergerLimited Print and Electronic Distribution Rights
This document and trademark(s) contained herein ar


s deciding whether to implement a similar program.
 RAND Justice Policy
The research reported here was conducted in the RAND Justice Policy Program, which spans
both criminal and civil justice system issues with such topics as public safety, eff


rimes.
Furthermore, local, state, and federal governments have limited resources, so considering the
benefit-cost of a program to society compared with other programs can be one way of deciding
whether to select a program.
Study Intervention Back


atch, we tested whether there was any difference in firearm violence rates
between Los Angeles and the control group after the letter program was implemented (2013 and
2014). A number of robustness checks were performed to test the sensitivity of r


t able to access these data through the Bureau of Alcohol, Tobacco, Firearms and
Explosives or California’s Department of Justice for purposes of this study.
    x Acknowledgments
This study would not have been possible without the time and effo


rney’s Office initially publicized the program by mail to new handgun
purchasers in two high-crime neighborhoods of Los Angeles. The letter for this pilot project was
sent to a random subset of individuals making new handgun purchases during the te


prohibited from
possessing one, including someone with a known mental disorder. Furthermore, it emphasized that if a child gained access to the handgun and injured himself, herself, or others, the gun owner was subject to criminal prosecution.
Our


thers who commit the crimes, or who themselves quickly transfer the weapon again.  0
  1
  2
  3
  4
  5
  6
  7
  8
  9
  10

Boston

San
  Antonio

Fresno

Fort
  Worth

Las
  Vegas

Los
  Angeles

Albuquerque


mmunity suffering, but those mortgage payers receiving the letter about the
high proportion of compliers were less compliant. Similarly, a letter experiment aimed at
reducing the inappropriate provision of Schedule II controlled substances by “over


n of the effect of the letter on city-level firearm violence and the costs and
benefits of the program.

 6 2. Data on the  Los Angeles  Citywide Gun Letter Program
Although the first full month of the program was January 2013, the Los Angeles


ly a single-unit group to test whether the letter program
“interrupted” the gun crime time series in Los Angeles. We used a monthly data set starting in
October 2008 and ending in December 2015, and tested whether there was an interruption to the


roughout the process, we
interviewed staff to determine the direct costs (labor time spent and the equipment used) .
Additionally, we obtained documentation of indirect costs (overhead expenses) associated to the
Los Angeles City Attorney’s Office


m of higher taxes to hire someone or
purchase specific software, for example. Therefore, results of this cost study can be understood
as the amount of resources shifted away from other work they would have been doing toward
this firearm letter pro


s) in
2013 for government paralegal and legal assistants in the Los Angeles –Long Beach–Santa Ana
area of $21.61 (Bureau of Labor Statistics, 2014). This was then multiplied by the overhead rate
of the Los Angeles City Attorney’s Office, 26 percen


e needs.
Time  Resources Spent
Figure 5.1 shows that the time spent for the key personnel during the first stage was seven to
11 hours per day, which then fell to 3.5 to six hours and 2.5 to four hours for the second and third stages, respectivel


sed for a letter program. On the one hand, while the cost per letter for Stage 2 and
Stage 3 are similar when fewer letters are sent (Low), the change in cost increases at a higher
rate for Stage 3 than Stage 2 when more letters are sent out ( Usua


ver, the individuals who opened another person’s
mail may have violated the privacy of gun buyers in these cases. We are not able to quantify
these costs and benefits to the telephone line for the Los Angeles City Attorney’s Office and the public,


-term and the
short-term models for the letter’s effect on crimes in the city with alternative ITSA
specifications.
For the short-term model, we found an immediate decline in robberies committed with
firearms after implementation of the letter p


 it may be the case that the program
indeed had no effect on gun crime, it is also possible that we simply do not have the statistical
power required to detect the effect on aggregate behavior. On the one hand, if the number of gun
crimes committe


e confidence in
the results of comparing our control group with Los Angeles (see the Appendix). This raises an
interesting question: Why? We can see that the mean values of all the matching variables are
similar between Los Angeles and a synthetic


ty of Los Angeles.
However, even an effect too minor to detect using our methods might justify the gun letter
program. Given that the cost of the program is fairly low, it is possible to see how even minor
effects could easily result in the benefi


rage in crime reduction (i.e., we would achieve the same $24.19 benefit-
cost ratio). Using the findings shown in Table 7.1, this amounts to the prevention of
approximately 19 robberies, 15 aggravated assaults, or fewer than one homicide per year.


 FBI and U.S.
Department of
Justice, 2014b
Aggravated assault  Total number of known aggravated assault ; aggravated
assault is distinguished from regular assault by whether there
is a weapon involved  FBI and U.S.
Department of
Justice, 2014a


er with this model (specifically the use of the rate as the outcome), we also tested another approach of estimating the effect on the
changes in crime rates using the count outcome and first differences.  Specifically, our outcome is
a count variab


d recent simulation
work has shown this approach can lead to spurious findings (Schell and Griffin, 2017), so it is unclear that this is a reliable result.
The difference models found results of a similar direction. Model II indicated that there wa


bove with equation [1]). We remind the reader that this is a first-
differences result, which means that because there was the initial drop in crime because of the
letter, the number of robberies committed with a firearm remained lower in every mont


y.
We focused our analyses on  cities in the United States with populations over 500,000  in at least
one year since 1980 . The data are for law enforcement agencies serving these city jurisdictions.
This selection criterion of jurisdictions with


d more similar to other reports:
Weights were either zero or a small subset of cities received positive weigh ts.

8 For clarity in reading this report, we do not present our findings from the annual


ot would have a line drawn at zero for every time point before the intervention, and then a positive or negative gap at the time of intervention and beyond  (if the intervention was effective).
We show this result in Figure 6.1 of this report, which


l, M., C. Christian, and J. Slemrod, “Do Normative Appeals Affect Tax Compliance?
Evidence from a Controlled Experiment in Minnesota,” National Tax Journal, Vol. 54,  No. 1, 2001, pp. 125–138. As of May 1, 2017: https://www.ntanet.org/NTJ/54/1/ntj-v


rch Can Tell Us About Investing in
Police, Santa Monica, Calif.: RAND Corporation, OP-279-ISEC, 2010. As of May 1, 2017: https://www.rand.org/pubs/occasional_papers/OP279.html
Hepburn, L., M. Miller, D. Azrael, and D. Hemenway, “The U.S. Gun Stock:


 No. 1, 2011, pp. 103–109.
Ridgeway, G., G. L. Pierce, A. A. Braga, G. Tita, G. Wintemute, and W. Roberts, Strategies for
Disrupting Illegal Firearm Markets: A Case Study of Los Angeles, Santa Monica, Calif.: RAND Corporation, TR-512-NIJ, 2008. As


ce: Compliance Effects of Informational and
Interpersonal Justice,” Social Justice Research, Vol. 19, No. 3, 2006, pp. 345–364.
Wright, J. E., “The Trayvon Martin Effect: Estimating the Effect of the Trayvon Martin Shooting
on Reading Performance


SOCIAL AND ECONOMIC WELL-BEING
After the Grand Opening
Assessing Cannabis Supply and Demand in
Washington State
Beau Kilmer, Steven Davenport, Rosanna Smart,
Jonathan P. Caulkins, Gregory Midgette
Prepared for the Washington State Liquor and Cannab


intended audience for this report is decisionmakers in Washington State tasked with
shaping cannabis policy. The methods applied herein should also be of interest to researchers and analysts in other jurisdictions that have implemented or are consid


... 17	Table 2.8. Flower and OPM Lot: Production Volume (MT), Semiannual .............................. 19	Table 2.9. Extract Ingredients: Production Volume (kg), Semiannual ................................... 20
Table 2.10. Extract Ingredients: THC


rces by Washington residents. Using data from Washington’s traceability system, the authors estimate that approximately 26 metric tons (MT) of THC were sold in the licensed retail stores in Washington from July 1, 2016, through June 30, 2017. About 1


To inform its earlier efforts, the Washington State Liquor and Cannabis Board (WSLCB) asked the RAND Corporation and BOTEC Analysis to estimate the size of the cannabis market circa 2013. Much has changed since then, and the WSLCB asked for an update


rocannabinol (THC)
and cannabidiol (CBD) content of cannabis products, as THC is the primary psychoactive ingredient in cannabis, and CBD may mediate some of the effects of THC (see, e.g., Englund et al., 2017). Cannabinoid content is measured eithe


, Washington’s producers were restricted to 70 percent of these canopy limits, raised to 100 percent by the beginning of 2017.
1 These tiers do
not specify a given growing method (indoor, greenhouse, or outdoor), although generally smaller (Tier 1)


s in the traceability system can be classified as (a) plant material, (b) lotted
plant material, (c) an “ingredient” produced from lotted material, which will later be converted to a retail product, or (d) a retail product, which is produced from in


Wax CO 2
Hash Oil  Kief Food -Grade
Solvent
Extract  Hash  Bubble
Hash  Infused
Cooking
Oil Infused
Butter/Fat  Total
Extract for
inhalation  235,512 66,293 10,946 10,317 9,435 5,313 18 6 337,840
Solid edible 3,563 2,395 85 5,129 29 5 413


tion (the remaining 36 percent of the time), as is the case with marijuana mix and infused cooking oil.
We can complement this picture of the supply chain flow by adding another chart, this time
linking products with arrows that point “upstream” t


versions” reports each time an item is converted from one product to a downstream product. The “dispensing” table holds information relating to the sale of products at retail. “Plants” and “plant derivatives” track information related to the status o


ng” table, which is filled with reports from retailers and appears to be fairly clean. This imbalance in data quality across the two sources makes it difficult to make an “apples-to-apples” comparison of production and retail sales volume, and theref


there any way in the dataset to identify which formula has been used for which observations. This inhibits estimation of THC or CBD content for these products, and therefore also for the total net weight of cannabinoid content produced or sold in Wa


ijuana extracts for inhalation, marijuana mix package, and marijuana mix infused), this method is the simplest. Each product’s THC and CBD test scores are retrieved from its associated potency test (linking via the “inventoryparentid”); monthly and a


d, lastly, to flexibly capture features of the “productname” text field, a term frequency–inverse document frequency (TF-IDF) matrix constructed from the “productname” text field and reduced to 50 principal components.
By summing together valid obs


ed system. We do not present data on cannabinoid content of OPM, which is never tested at the lot stage; instead, that material will be tested further downstream before conversion to a final product, e.g., as marijuana mix before conversion to mariju


pectively, in 2017). THC content among liquid edibles appears to have been flat since 2016, while estimated THC content in solid edibles has increased consistently since 2015.  16 Table 2.6. Average Estimated THC Content (mg) in Edibles
 2015  2016


data are missing from the plant derivatives table prior to November 2015.   17 accurate data points, any values above the 99th percentile of the distribution of OPM weights
were removed from analysis.
Marijuana harvests show very strong seasonal tr


ures products’ total weight (grams) before packaging. This
value appears alongside childweight, so an entry for usable marijuana with childweight = 10 and childusableweight = 350 indicates ten different retail packages, each containing 3.5 grams of


ases when this might not be accurate. First, a processor might have combined several 15-pound OPM
lots into a single larger lot before converting them into a downstream product, though this seems rare. Second, the
weight of some child products in a


olume (kg)
Year  Usable Marijuana  Extract for Inhalationa Marijuana Mix Infusedb Marijuana Mix Packageb
2014  3,023 — — —
2015  34,819 — 75 506
2016  85,000 6,610 1,327 2,349
2017  126,191 12,855 3,421 2,758
a Product weight not reported until


9 6,106 11,902
Solid edible 58 1,209 3,217 4,837
Marijuana mix infused  — 12 735 2,611
Marijuana mix package  — 126 908 1,658
Liquid edible 17 330 836 1,180
Marijuana -infused t opicals  0 45 188 355
Capsule  — — 3 165
Tincture  — — 7 55
Supp


e timing of which corresponds with the issuance of a memo establishing a federal policy of nonenforcement against medical cannabis patients (Ogden, 2009). This upward trend seems to have leveled off beginning in 2012/2013 but then increased again in


me use is acknowledged.  Unknown; could be greater or less
than 1.0.

We have no reason to believe that the values for Adjustments 1, 2, and 4 have changed much
over the past five years. Adjustment 3—misreporting by people who are successfully s


al data. While NSDUH collects information from respondents on the exact number of use days in the past month (and in the past year), RDAS confidentiality restraints limit detailed reporting of the frequency of cannabis use. To maintain protections of


lower products, with the fastest growing market segment being extracts for inhalation. However, to learn more about the patterns of cannabis consumption, we must look

days [280,000 – (32,000 + 55,000  + 16, 000 + 17,000 + 26,000 + 122,000) = 12 ,0


le, and more than 50 percent reported using an oil cartridge for a vape pen in the past year.

10 A comparison of respondent demographics for these web surveys and NSDUH  are presented in appendix Table
A.6.  32 Table 3.2.  Share of Respondents Re


rs  Web survey  Triangular
(1.3, 1.6, 1.9)
Ratio of grams per day for DND versus  once -per-month
users  Based on Kilmer et al.,
2013  Uniform  [2, 3]
NOTE : See text for clarification of sources and assumptions.

Figure 3.4 displays the f


s into MTs of THC. Our
baseline estimate applies the same THC level used to make the conversion for the store sales: 20 percent. However, flower obtained from the illicit market may be of lower potency than what is sold in the stores. Indeed, the ac


e average to
16% THC  250 16 10 59
If we didn’t make any adjustments to
NSDUH  200 20 10 59
NOTES : Column D  = (26 ´ (1–C)) / (A ´ B). WA = Washington.

None of those parameters is known with certainty, so the remaining eight rows of Table 4.


nd 60 percent.

  37 5. Concluding Thoughts
Agencies regulating cannabis need good information about the size of their cannabis market
and how it is changing. This can help them make informed decisions about several items ranging
from licen


on residents’ total THC consumption appeared to grow,
progress at shrinking the illegal markets’ volume is smaller than these proportions might suggest. For example, if total THC consumption grew by 40 percent over a period when the illegal  38 mark


cts that are particularly efficient at delivering THC gain or lose market share. Tracking trends in THC consumption might be of greater relevance to those studying public health outcomes.
Finally, by making its traceability system publicly availa


32  19.31  19.96
Infused Cooking Oil  1.88 6.75 22.94  16.57
Infused Dairy Butter or Fat in Solid Form  5.17 8.85 7.37 6.54
Kief 16.51  15.32  17.85  18.24
Marijuana Mix  NA 7.88 9.14 8.51
Marijuana Extract for Inhalation  21.44  19.51  26.50


au Kilmer, “Big Data on a Big New Market: Insights from Washington State’s Legal Cannabis Market,” International Journal of Drug Policy,
Vol. 57, July 2018, pp. 86–94.
Cole, James, Deputy Attorney General, “Guidance Regarding Marijuana Enforcement,


tional Survey on Drug Use and Health Restricted-Use Data Analysis System.
SAMHSA—See Substance Abuse and Mental Health Services Administration. Smart, Rosanna, Jonathan P. Caulkins, Beau Kilmer, Steven Davenport, and Greg Midgette,
“Variation in Ca


CORPORATIONThe Enemy of Good
Estimating the Cost of Waiting for
Nearly Perfect Automated Vehicles
Nidhi Kalra and David G. GrovesLimited Print and Electronic Distribution Rights
This document and trademark(s) contained herein are protected by law.


port RAND Model of Automated Vehicle Safety (MAVS): Model Documentation , which describes in
detail the model used for the analysis described in this report.
RAND Science, Technology, and Policy
This research was conducted in the RAND Science, Techn


rous gift to help RAND research and outreach teams extend the impact of completed research.
Support for this project is also provided, in part, by the income earned on client-
funded research, and by the generous contributions of the RAND Justice, In


when it comes to humans versus machines, but these values and beliefs can be informed by science and evidence. In this report, we seek to provide such evidence by addressing the question of how safe HAVs should be before they are introduced. We used


e same improvement cannot be achieved equally quickly in laboratory or simulation settings. Savings are smallest when the opposite conditions hold.
Second, what does the evidence suggest about the conditions that lead to small
costs from waiting for


s even deadlier—with 37,461 fatalities (NHTSA, 2017). U.S. motor vehicle crashes can pose economic and social costs of more than $800 billion in a single year (Blincoe et al., 2015). Moreover, more than 90 percent of crashes involve driver-related er


 concern for the transportation industry, policymakers, and the public.
4 Assessing safety requires considering two issues: How
should HAV safety be measured, and what threshold of safety should be required before HAVs are made publicly available? I


s would still cause many crashes, injuries, and fatalities—albeit fewer than their human counterparts. This may not be acceptable to society. A large body of research suggests that peoples’ willingness to accept technological risk is governed by fact


cy that waits to deploy HAVs only once
their safety performance is either 75 percent or 90 percent better than that of the aver -
age human driver (we call these options Improve75  and Improve90 , respectively). 4    The Enemy of Good: Estimating th


 drivers behind the wheel. Table 2.1 shows each level’s description taken directly from the SAE International taxonomy (in italics) and our simplified interpretation.
Consistent with Federal Automated Vehicles Policy (NHTSA, 2016b), we use the
term


d by
functions that automate both steering and acceleration, such as lane-keeping and adaptive cruise control; the human driver is responsible for monitoring the environment and intervening whenever needed.
Automated driving system performs the ent


 improve safety—for example, for coordinating vehicle movement through an intersection (Najm, Toma, and Brewer, 2013; Eccles et
 al
., 2012).
Rau, Yanagisawa, and Najm (2015) describes a method for identifying the types
and potential number of curre


overlook important ways in which new technologies could add to crashes. This could occur if technology erodes human drivers’ skills or attention, technology is vulnerable to cybersecurity failures that lead to new types of crashes, or HAVs simply per


over time; the timing, rate, and extent of HAV adoption and diffusion throughout the fleet; and the initial safety of HAVs and how much and how quickly it improves. Accurately predicting safety outcomes is fraught with complications because such fac


runs models over hundreds or thou -
sands of different sets of assumptions to describe how plans perform in many
 pla
usible
conditions. Unlike, for example, Monte-Carlo analysis, which attaches probabili -
ties to those assumptions to estimate exp


onomic costs, or other safety mea -
sures. For simplicity and because of the particular attention paid to road deaths, we measure safety by the number
of fatalities and the fatality rate.Figure 3.1
MAVS Inputs and Outputs
RAND RR2051-3.1Inputs
VMT
1


 by policy as 25%
(Improve75) or 10% (Improve90)
of the benchmark fatality rate
8. Fin
al HAV fatality rate Uncertain; constant, defined by initial fatality rates under
Improve75 and Improve90
9. HAV m
iles needed to reach 99%
of final HAV fatali


ficult to calculate and visualize in the results.
4 A Latin Hypercube Sampling procedure ensures that all variables are sampled uniformly across their entire range
and that the combinations of values across the variables are randomly selected (Salte


tes have declined significantly since the 1950s, there has
been a plateau over the past decade and an increase in recent years (Bureau of Transpor -
tation Statistics, 2016). Based on the estimates of the safety benefits of driver assistance systems


nt of HAV use, which we measure
at the point of full diffusion. To begin with, some percentage of non-HAV driving in the baseline future will ultimately be replaced by HAVs (MAVS input
 4).
This is
deeply uncertain, and we explore anywhere from 50


 defines it in terms of the
cumulative number of miles of postdeployment HAV driving needed to improve from an initial to a final fatality rate (MAVS input
 9). Th
ere is little real-world evidence that
would help bound this number. As of December


er these latter policies. This means that HAVs under Improve10 would reach target safety performance at the same time as or sooner than under Improve75 or Improve90. Thus, the soonest HAVs can be introduced under these latter policies is when they al


90 is defined by each
policy. As noted earlier, the best possible HAV fatality rate is uncertain, but, for sim -
plicity, we assume that the very definition of “near perfection” approaches a practical limit to HAV performance. Thus, HAVs under these


ehicles
Figure 4.1
Ensemble Difference in Cumulative Lives Saved over 15 Years for 500 Cases
RAND RR2051-4.1
Difference in cumulative fatalities200,000
150,000
0 500100,000
50,000
0
400 300 200 100
CasesImprove10 saves > 50,000 more lives than Improv


ce in cumulative fatalities. The figure shows that all of these futures have a 23
 per
cent or larger increase in VMT as a result of HAV use (horizontal axis) and
require 1 trillion miles or more of driving to achieve a 75-percent improvement in fat


lay in introducing HAVs under Improve75a
(used to calculate Initial year of HAV introduction)8 0–15
3 Improve10 Years to full diffusion of HAVs under Improve10 37 20–50
3 Improve75 Increase in pace of HAV adoption under Improve75a
(used to calcula


itions, and those savings can be significant—tens of thousands to hundreds of thousands of lives. The savings are particularly large when HAVs under Improve10 are adopted quickly. Conversely, the more stringent policies save more lives only when HAVs


r term, the difference in VMT and therefore cumulative fatalities is smallest in futures in which HAVs are intro -
duced under both policies nearly simultaneously. Figure
 4.8 s
hows that this gener -
ally occurs when (1)  th
e number of miles it tak


emain in operation. Nevertheless, our analysis reveals that these factors are not the primary drivers of dif -
ferent outcomes between these policies.
To summarize, in the longer term, more lives are cumulatively saved under an
Improve10 policy tha


 does this imply for policies governing the introduction of HAVs for con -
sumer use?30    The Enemy of Good: Estimating the Cost of Waiting for Nearly Perfect Automated Vehicles
What Does the Evidence Suggest About the Conditions That Lead to
Small


g gains that some might consider “near perfect” may take much more effort and time than reaching better-than-average human perfor -
mance, which may itself be still out of reach.
Second, there is no reason to believe that the value of real-world dri


servations Exploring a Year’s Change ,
Cambridge, Mass.: Massachusetts Institute of Technology AgeLab, White Paper 2017-2, 2017. As of September 12, 2017: http://agelab.mit.edu/sites/default/files/MIT%20-%20NEMPA%20White%20Paper%20FINAL.pdf
Anderson


blue.lib.umich.edu/bitstream/handle/2027.42/78178/
DeCicco_AutoEfficiencyHorizon_Sept2010.pdf?sequence=1Dietvorst, Berkeley J., Joseph P. Simmons, and Cade Massey, “Algorithm Aversion: People
Erroneously Avoid Algorithms After Seeing Them Err,” Jo


3-MCF, 2017. As of September 12, 2017: https://www.rand.org/pubs/research_reports/RR1673.html
Fischhoff, Baruch, Paul Slovic, Sarah Lichtenstein, Stephen Read, and Barbara Combs, “How Safe Is
Safe Enough? A Psychometric Study of Attitudes Towards Te


mental Change , Vol.
 17
, No.  1, 2
007, pp.  73
–85.
Harper, C., C. Hendrickson, S. Mangones, and S. Constantine, “Estimating Potential Increases in Travel with Autonomous Vehicles for the Non-Driving, Elderly and People with Travel-Restrictive Me


ny Miles of Driving Would It Take
to Demonstrate Autonomous Vehicle Reliability? Santa Monica, Calif.: RAND Corporation, RR-1478-RC, 2016. As of September 12, 2017: http://www.rand.org/pubs/research_reports/RR1478.html
Koopman, Philip, and Michael W


NE , Vol.
 8, N
o. 2, e
52669, 2013.
Najm, Wassim G., Samuel Toma, and John Brewer, Depiction of Priority Light-Vehicle Pre-Crash Scenarios for Safety Applications Based on Vehicle-to-Vehicle Communications , Washington, D.C.: U.S.
Department of Tra


 Neurauter, and J. F. Antin, Advanced Crash Avoidance Technologies (ACAT) Program—Final Report of the GM–VTTI Backing Crash Countermeasures Project , Washington, D.C.: U.S. Department of Transportation,
DOT HS 811 452, August 2011.
Petit,
 J.
, and


/files.shareholder.com/downloads/ABEA-4CW8X0/2238129554x0x913801/
F9E5C36A-AFDD-4FF2-A375-ED9B0F912622/Q3_16_Update_Letter_-_final.pdfWalden, Greg, “Opening Statement of Chairman Greg Walden,” hearing on “Self-Driving Cars:
Road to Deployment,” U.


uman drivers—what some might consider nearly perfect. We ﬁnd that, in the long term, under none of the conditions we explored does waiting for signiﬁcant safety gains result in fewer fatalities. At best, fatalities are comparable, but, at worst, wait


Law Enforcement Efforts to Fight the
Opioid Crisis
Convening Police Leaders, Multidisciplinary Partners,
and Researchers to Identify Promising Practices and to Inform a Research Agenda
Sean E. Goodison, Michael J. D. Vermeer, Jeremy D. Barnum, Dula


romo -
tion opportunities.
• Provide same-day, low-barrier access to treatment with a medication-first model of care.
• Provide syringe services to reduce associated harms and create treatment intervention opportunities.
• Use syndromic surveillance


opioid crisis, law enforcement officers experience additional physical dangers, mental trauma, and stressors. Needs related to officers’ mental health were seen as pressing, and participants gave high priority to strategies such as providing mental h


 dramatic spike in heroin-related over -
dose deaths in 2010. The deadliest wave of the epidemic began in 2013, with the introduction of synthetic opioids into the illicit drug supply. Today, synthetic opioids—primarily fentanyl and its analogs—remai


the epidemic (addressed in a keynote speech given by then–Attorney General Jeff Sessions), the science of addiction and treatment, law enforcement–led efforts to combat opioids, key areas of cooperation among governmental and community stakeholders,


pioid Crisis released a report detailing a broad variety of recommendations to address opioid use, addiction, and its consequences (White -
house.gov, undated; Christie et al., 2017). The report acknowl -edges that effective solutions to a crisis of


f food or by engaging in sexual activity. Under normal circumstances, the amount of dopamine in the body is naturally regulated by another chemical, gamma-aminobutyric acid (GABA). However, opioids bind to the part of the nerve that reduces GABA rele


motions and physical illness after a period of time without using opioids. Repeated opioid use interferes with the brain’s reward system by impairing an individual’s ability to experience pleasure. This compounds compulsive opioid use as individuals


ructured to include panels focusing on key topics related to law enforcement–driven responses to the crisis. The topics of interest were identified based on literature review and discussions among RAND, PERF, and NIJ experts. Each panel included a se