ve leverage points that could help in strengthening the system. In the list that follows, we break these options down into the categories of institutional governance, accounting standard setting, and prudential regulation.
Governance
• Policymakers s


quired concerning the mechanics of valuation for either approach in financial statements.
• Policymakers should clarify whether financial statements really are required to disclose suf- ficient detail about FVA mechanics to allow users of financial s


. These kinds of concerns could be made directly transparent to the users of financial statements, given basic disclosures describing the extent to which concentrated ownership of an asset (or of a relevant category of assets) applies on the part of


an be used to investigate and help buttress the fidelity of valuation across institu- tions, while imposing some common baseline assumptions on related practice. Regulators should consider whether and how prudential oversight of institutional valuati


 See, e.g., Isaac (2009).
  73
74 Fair Value Accounting, Historical Cost Accounting, and Systemic Risk
all companies publicly traded on a U.S. stock exchange must file quarterly financial statements prepared consistent with GAAP standards. Thus, even


ed at SFAS 133); and ASC 825 (“Financial Instruments,” formerly codified at SFAS 159).
4 To clarify, FASB standards defining GAAP do not seek to exhaustively enumerate all the specific situations where HCA applies. Instead, an HCA approach is implici


 of market illiquidity. Complementary guidance was simultaneously issued by FASB to address ambiguities in impairment accounting given similar illiquidity for securities either held-to-maturity or available for sale.
How Does Historical Cost Accounti


gests that in 2006, the typical bank held a far smaller percentage of its balance sheet in FVA-denominated assets than did the 50 banks actually examined by the SEC.5 Figure A.1 shows our “fair value” measure for selected large institutions in 2006,


r things) would eliminate the need for non-U.S. companies registered in the United States to reconcile their IFRS financial statements with GAAP requirements.6 The IFRS convergence process has now been ongoing for more than five years, and has made s


te IFRS convergence, and the likelihood that the GAAP framework will continue to shift as a result of the IFRS convergence process.
6 See discussion in IASB and FASB (2006).
7 See discussion in IASB and FASB (2011).
8 Journal of Accountancy (2011).


lity in the banking sector. GAAP standards that define FVA and HCA are also notably tied to a series of deeper disagreements and philosophi- cal arguments about financial information, which in turn have contributed to a long-running dispute about the


, “The Economic Consequences of Relaxing Fair Value Accounting and Impairment Rules on Banks During the Financial Crisis of 2008–2009,” working paper, 2010.
Breeden, Richard C., “Thumbs on the Scale: The Role that Accounting Practices Played in the S


rnal of Finance, Vol. 60, No. 2, 2005, pp. 615–647.
———, “Fear of Fire Sales and the Credit Squeeze,” National Bureau of Economic Research Working Paper 14925, April 2009. As of August 7, 2013:
http://w w w.nber.org/papers/w14925
Dixon, Lloyd, Noreen


 B l o b S e r v e r ? b l o b c o l = u r l d a t a & b l o b t a b l e = M u n g o B l o b s & b l o b k e y = i d & b l o b w h e r e =117 5 8 2 0918856&blobheader=application%2Fpdf
———, Recognition and Presentation of Other-Than-Temporary Impairm


-to-Market Now!” Forbes.com, September 29, 2008. As of August 7, 2013:
http://www.forbes.com/2008/09/29/mark-to-market-oped-cx_ng_0929gingrich.html
Goldman Sachs, “Comment Letter to FASB re: Accounting for Financial Instruments and Revisions to the A


, Vol. 34, 2009, pp. 826–834.
———, “Did Fair Value Accounting Contribute to the Financial Crisis?” Journal of Economic Perspectives, Vol. 24, No. 1, 2010, pp. 93–118.
McLean, Bethany, and Joe Nocera, All the Devils Are Here: The Hidden History of the


or Innocent Victim: Exploring the Links Between Fair Value Accounting, Bank Regulatory Capital and the Recent Financial Crisis,” Federal Reserve Bank of Boston, Working Paper No. QAU10-01, 2010.
Shearer, Jana, “Mark-to-Market: Delivering the Financia


s in triggering the crisis. This report investigates and clarifies the relationship between these two accounting approaches and risks to the financial system. The authors examine the risk implications of FVA and HCA in the various situations in which


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Cover image: Hoover Dam Water Electricity Power Station, © malajscy/Fotolia. The cover image shows the current low level of the Lake Mead reservoir and two of the four water intake t


o Reclamation with respect to implementa- tion of the Basin Study based on the analysis presented in this report. The intended audience includes the participants and stakeholders of the Basin Study as well as water policymakers, managers, and stakeho


45 46 . 47
vii
viii
Adapting to a Changing Colorado River
5.5. Percentage of Traces in Which Five Options Are Implemented by Year for
Portfolio D (Common Options). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


................
3.5. Performance Metrics and Vulnerability Thresholds for the Two Water-Deliveries Metrics Used in This Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


new hydrologic regime for which past data and experience are not an adequate guide for future river conditions. Climate simulations applied in the Colorado River Basin Study (Basin Study) are generally consistent in indicating that the entire Basin w


enarios to determine how much they could improve Basin outcomes
• analyzed the results from the system simulations to identify key trade-offs among the portfolios.
This report summarizes RAND’s contribution to the Basin Study (the Colorado River Basi


volve over the study’s 49-year time horizon (2012–2060).
The Basin Study Team developed four supply scenarios based on different sources of future streamflow estimates. Each scenario is composed of many different 2012–2060 time series of streamflows—


wn in Table S.1). It also evaluated a wide array of different supply-augmenta- tion and demand-reduction options that could improve system performance and reduce vul- nerabilities. Such options were organized into eight categories: (1) agricultural c


 the lettered names (Reclamation, 2012f, 2012h).
Simulating the Colorado River System and Performance Metrics (R and M)
The Basin Study used the Colorado River Simulation System (CRSS), Reclamation’s long-term planning model, to simulate the Colorado


external conditions lead to those projected vulnerabilities. Using RDM vulnerability analysis techniques and statistical summaries of streamflow at Lee Ferry, we looked for a set of future conditions that best captures the vulnerable traces. We find


lio B (Reliability Focus) in reducing vulner- abilities. For the Lower Basin Reliability metric—Lake Mead Pool Elevation—implementing the portfolios significantly reduces the number of years in which the Basin goals are not met. Even in the most stre


imilar costs.
However, when we focus on traces corresponding to the two vulnerable conditions, we see some differences across the portfolios. First, in the Low Historical Supply conditions (the middle band in the figure), we see that the portfolio wi


der-derived portfolios (Portfolios B and C), options always or frequently implemented in this portfolio as soon as they are available can be considered both near-term and high priority.
Figure S.3 summarizes how frequently options from Portfolio D (C


d in response to changing conditions.
Summary xix
xx
Adapting to a Changing Colorado River
Figure S.3
Percentage of Traces in Which Options Are Implemented and Associated Implementation Delay for Portfolio D (Common Options)
NOTE: Ag = agricultural;


 performance and other attributes of additional approaches alongside the adaptive options evaluated for the Basin Study would support the successful implementation of a robust, adaptive strategy.
Summary xxi
Acknowledgments
 The authors are grateful


the water-management model in response to emerging vulnerabilities
a description of uncertain future parameters pertaining to, for example, supply, demand, and reservoir operations
a specific approach, in terms of the types of options used, for addre


was signed, water was used primarily for agricul- tural development, and specific allocations of water within the states were still loosely defined.
1 An acre-foot (af) is the volume of water that covers one acre to a depth of a foot: 43,560 cubic fe


ear, water not used in the Upper Basin has been avail- able for redistribution to Lower Basin states such as California and Nevada that have in the past requested more water than legally allocated by the Law of the River (Glennon and Pearce, 2007). S


 ens to alter the characteristics of basin hydrology and to reduce long-term average river flows, further threatening sustainable river use.
A growing body of literature suggests that the Colorado River system is now—or soon will be—operating in a ne


palan et al., 2009; Wildman and Forde, 2012).
The second part of Figure 1.2 captures the substantial uncertainty about projected water demand and supply out to the year 2063. As the figure shows, uncertainty in supply (the wider blue band) is much gr


analysis to grapple with future uncertainty at this scale, yielding a large number of potential scenarios to consider and options to evaluate. To meet this challenge, Reclamation and the Basin States asked research- ers from the RAND Corporation to j


with the Basin Study Team and state partners to complete this analysis. We use only a small subset of the study results here to tell the story of emerging water supply vulnerability and possible actions to reduce vulnerability. For example, although


certainty has implications for the kind of long-term planning needed. Specifically, as managers and users of the Colorado River plan over the coming decades, they need to move beyond the traditional prediction-based approaches that work well when the


es, 2003). This approach has been used in a number of real-world applications, including energy resources, flood risk management, national defense, and water management (Popper et al., 2009; Dixon et al., 2007; Lempert and Groves, 2010).1 When applie


R242-2.2
2 The approach to identifying key vulnerabilities uses statistical “scenario discovery” algorithms (Bryant and Lempert, 2010; Groves and Lempert, 2007). The terms “scenario discovery” and “vulnerability analysis” are synonymous.
   12 Adapti


s”—that would make a strategy vul- nerable to not meeting its objectives. Such decision-relevant scenarios focus decision makers’ attention on the uncertain future conditions most important to the challenges they face and help facilitate discussions


very unlikely, then the reduction in the corresponding vulnerabilities may not be worth the cost or effort. On the other hand, the vulnerable conditions identified may be viewed as plausible or very likely, lending support for a strategy designed to


elp structure the analysis of options and strategies to alleviate the possible Basin imbalances.
This chapter uses the XLRM framework introduced in Chapter Two to describe the decision-structuring step of RDM (Step 1 of Figure 2.2) as applied in the


demand ranges from 13.8 maf (Slow Growth demand scenario) to 15.6 maf (Rapid Growth demand scenario).
Table 3.2
Demand Scenario Storylines, Scenarios, Descriptions, and Statistics
   Storyline and Scenario
Current Projected [CRBS A]a
Slow Growth [CRB


erry:3
• annual mean (2012–2060)
• trend (2012–2060)
• variance (2012–2060)
• annual mean of driest N-year period (examined five-, eight-, and ten-year periods)
• year of driest N-year period (examined five-, eight-, and ten-year periods)
• annual me


rical and Future Climate scenarios:4
• change in temperature from 1950 to 1999 historical baseline (degrees F)
• change in precipitation from 1950 to 1999 historical baseline (percent)
• variance in temperature and precipitation (2012–2060)
• annualp


re Changes Across Traces (left) and Precipitation Changes Across Traces (right) for the Historical and Future Climate Scenarios
  Mean Change in Temperature from Historical Baseline (1950–1999) [Degrees Fahrenheit]
2
0
4
Historical Future Climate Sup


scaled GCM Projected)
112 total 1,959
  5 For the vulnerability analysis, the Historical, Paleo/Historical Blend, and Future Climate scenarios were replicated so that they were the same size as the Paleo scenario (14,928 records). For the analysis of


e 3.4 many times for this study. First, the traces were evaluated to identify the vulnerabilities of the baseline man- agement of the system (described in Chapter Four). Next, they were evaluated for each of the four portfolios discussed above (descr


—if this provision were threatened by low flows over a ten-year period. A “Lee Ferry Deficit” is the amount of curtailment that would be necessary in such an event. The Basin Study used the methods described in this report to look at six primary wate


ons—about 80—accord- ing to rough estimates of option yield, availability, and 16 other criteria, including technical feasibility, permitting risk, legal risk, policy risk, and energy intensity.7 The Basin Study Team assigned each project a score bet


y and Demand
7 The study team was unable to analyze each option individually using more detailed criteria for the purposes of prioritiz- ing options within a portfolio. As described below, however, the portfolios are evaluated not on these criteria,


options and an Upper Basin water bank (not represented in the table, as it does not increase yield of the system—it only reallocates it).
Figure 3.6
Schematic Representing Options Included in Each of the Four Portfolios
 RAND RR242-3.6
Table 3.6
Desc


ch of the six water delivery indicator metrics (Table 3.8). Signposts specify a set of observable system conditions and thresholds that indicate vulnerabilities are developing. During a simulation, CRSS monitors the signpost conditions: If any thresh


lorado River Basin 29
Figure 3.7
Simulated Lake Mead Pool Elevation Over Time Without Options (red) and With Options Implemented by a Simple Dynamic Portfolio
 RAND RR242-3.7
ChAPtER FoUR
Future Vulnerabilities to Colorado Basin Water Deliveries
Intr


elivery reliability metrics in this analysis: Lee Ferry Deficit (Upper Basin Reliability) and Lake Mead Pool Elevation below 1,000 feet msl (Lower Basin Reliability). A Lee Ferry Deficit occurs in the CRSS simulations when the ten-year sum of flows a


y times. Figure 4.1 shows these results in three separate time periods over the 49-year horizon: 2012 through 2026, 2027 through 2040, and 2041 through 2060. The end of the first time period was selected to coincide with the expiration date of the 20


bove, in the study simulations, the Upper Basin experiences a Lee Ferry Deficit in 19 percent of traces by the last 20 years of the simulation. In mining those simulations in the vulnerability analysis, we first sought to answer the question: what fu


ons encompasses most but not all of the vulnerable traces, which is why some of the vulnerable traces (red Xs) appear outside of the boundaries.
Figure 4.2 shows that, despite the evident correlation between long-term low flows and acute drought flow


apture 92 percent of all traces where objectives are not met (coverage). Once again, only two input parameters are needed to describe such vulnerable conditions, leading them to be easily understood and interpreted.
Figure 4.3 shows a scatterplot of


streamflow and climate vulnerable conditions identify nearly the same set of traces. Overall, 95 percent of traces are categorized in the same manner—in or out of vulnerable conditions—across the two types of vulnerable conditions. Thus, even though


ditions (density). The conditions also describe 86 percent of all traces that lead to unacceptable results (coverage). And, as was true in the two Upper Basin sets of conditions, only two input parameters are needed to describe such vulnerable condi-


center and right of the graph). In a warming climate, Lower Basin objectives are most often met only in traces that are at least 4 percent wetter than the historical average, while the large majority of traces that are drier include at least one year


s a result, in subsequent chapters we will refer to these collectively as Low Historical Supply, and for convenience, we will use the streamflow-defined conditions to illustrate potential vulnerability reduction when new invest- ment options are test


f this feature, CRSS calculated a unique sequence of options to be implemented for each of the 23,508 traces comprising the demand, supply, and reservoir options scenarios. In this chapter, we present the effects of the portfolios on improving perfor


ty metric: Lake Mead Pool Elevation. Similar to the Upper Basin results, the implementation of the portfolios sig- nificantly reduces the number of years in which the Basin goals are not met. Even in the most stressing Declining Supply vulnerable con


l). This translates to a nearly complete elimination of unmet goals for climate conditions similar to his- torical conditions (Figure 5.4, bottom panel), while further restricting the temperature and pre- cipitation range from the climate scenario in


ions Are Implemented by Year for Portfolio D (Common Options)
NOTE: Large options are disaggregated into 200 taf/year “steps” to represent likely project phasing.
RAND RR242-5.5
gests that in many plausible futures, there is a need for substantial ad


uce the amount of Colorado River exported to these regions.
Local supply options capture local water sources that would otherwise go unused
options that increase water conservation in the municipal and industrial sectors and reduces demand for Colora


-offs among the four portfolios. First, there is little difference between portfolios when looking across all traces evaluated. That is, the range in vulnerability reduction and costs overlap significantly for all the portfolios (Figure 5.8, top pane


to identify those options most fre- quently implemented across many or most traces. Next, we reviewed the costs incurred when implementing options included in different portfolios. Costs could be high when vulnerable conditions emerge, with Portfolio


ent strategy. Instead, the Basin Study presents key trade-offs among portfolios in terms of costs and vulnerability reduction, and highlights which options are most needed and when. The report concludes by describing a range of near-term steps to be


s consistent with the two key vulnerable conditions—Low Historical Supply and Declining Supply—more options are needed, and with less delay. The middle panel of Figure 6.1 shows that for the Low Historical Supply vulnerable conditions, the urgency of


e easier to discern whether the future climate is going continue to deviate from the historical record, drawing from new climate models or higher resolution regional climate projections (e.g., Seager et al. [2012]). In particular, additional advances


y modeled by CRSS within the time available to complete the study. As suggested by the Basin Study, evaluating these additional options in the coming months could further improve the ability for the portfolios to address supply and demand imbalances.


od (PRIM) (Friedman and Fisher, 1999) to identify the uncertain external conditions that lead the system to not meet key objectives. The uncertain external condi- tions are statistical or numerical characterizations of the futures evaluated in Step 2


three of the four vulnerable simulations (75 percent coverage)—and three of the four simulations described by the definition are vulnerable (75 percent density). The other vulnerability definitions shown in Table A.1 show the trade-off between covera


ditions
NOTES: Red lines are simulations that do not meet goals and are included in the vulnerable conditions. Yellow lines are those that do meet goals and are included in the vulnerable conditions. Thin gray lines are simulations that meet the Lake


Portfolio Analysis
   Option Type
Agricultural Conservation
Desalination
Energy water Use Efficiency
Import
Local Supply
M&I Conservation
Reuse
Description
options that increase water conservation in the agriculture sector and reduce demand for Color


control improves supply by reducing dust accumulation on snow that can lead to earlier snowmelt and more evaporative moisture losses. weather modification consists of cloud seeding, or adding silver iodide to the atmosphere to serve as condensation


hew Hoover, and Jordan Ostwald, Coastal Louisiana Risk Assessment Model, Santa Monica, Calif.: RAND Corporation, TR-1259- CPRA, 2012. As of August 4, 2013:
http://www.rand.org/pubs/technical_reports/TR1259.html
Friedman, Jerome H., and Nicholas I. Fi


per_012110.pdf
Meko, David M., Connie A. Woodhouse, Christopher A. Baisan, Troy Knight, Jeffrey J. Lukas, Malcolm K. Hughes, and Matthew W. Salzer, “Medieval Drought in the Upper Colorado River Basin,” Geophysical Research Letters, Vol. 34, No. 10, 2


a t e 1 7 8 7. h t m l
Simon, Herbert A., “Rational Choice and the Structure of the Environment,” Psychological Review, Vol. 63, No. 2, 1956, pp. 129–138.
Stockton, C. W., and G. C. Jacoby, “Long-Term Surface-Water Supply and Streamflow Trends in the


erior, 2012f. As of December 31, 2012: http://www.usbr.gov/lc/region/programs/crbstudy/finalreport/Technical%20Report%20F%20-%20 Development%20of%20Options%20and%20Stategies/TR-F_Devlpmnt_of_Ops_and_Strats_FINAL_ Dec2012.pdf
References 69
70 Adapting


uld improve basin outcomes; and analyzing the results from the system simulations to identify key tradeoffs among the portfolios. This report describes RAND’s contribution to the Basin Study, focusing on the methodologies used to identify vulnerabili


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ed. RAND documents are protected under copyright law. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of our r


hat are readily available and develop simple assumptions to explore uncertainty that is often ignored in
1 The study team included researchers from RAND Corporation and the Stockholm Environment Institute (SEI). Staff from EID provided data, advice,


ics
Availability of new supplies
Relationships or Systems Model (R)
Water planning model of EID
Results
Management Strategies or Levers (L)
2010 Urban Water Management Plan Additional Management Strategies
  • •
Additional urban water use efficiency


erable?
In order to focus the analysis on outcomes that would not meet EID broad planning goals, we defined a vulnerability threshold of 90 percent—reliability outcomes less than this threshold for either region indicate a vulnerability. Through iter


not reduce the vulnerabilities in the Western Regions, but in the Eastern Region it does reduce vulnerabilities when UARP supplies are available from 69 percent to 46 percent of futures. Increasing efficiency and constructing the Alder Reservoir prov


ncertainties. In this case, the study considers uncertainty about future climate and hydrologic conditions, urban growth rates, and success in developing a new, large water supply. The approach can be easily expanded to consider many more uncertainti


er rates they must charge their customers, they seek solutions that will ensure reliable future supply of water but that are not overly costly. In some instances, this approach does not guarantee that needs will be completely met under all future con


he veracity of any particular estimate (Groves and Lempert, 2007; Lempert, Popper, and Bankes, 2003). Instead, it supports a systematic exploration of plausible climate effects and impacts, identifying vulnerabilities—or the specific scenario conditi


es
Figure 2-1 illustrates the steps of an emerging paradigm for addressing climate change in long-term natural resource plans (National Academy of Sciences: Committee on America’s Climate Choices, 2011). It describes a series of iterative steps in wh


and refine strategies that are increasingly robust. Final decisions among strategies are made by considering a few robust choices and weighing their remaining vulnerabilities. More information on RDM and descriptions of its application to a variety


 5
strategy or strategies that might reduce these vulnerabilities (Step 4). Based on this tradeoff analysis, decision makers may decide on a robust strategy, or they may decide that none of the strategies under consideration is sufficiently robust a


n conditions used to define the scenario serves as a proxy for interpretability. The smaller the number of parameters, the higher the interpretability.
These three measures are generally in tension with one another. For instance, increasing density m


 3-1: Location of EID Service Area in California
SOURCE: Map courtesy of EID.
EID was constituted in 1925, largely to meet the water supply needs of agricultural interests in the watershed. In earlier years, EID relied upon a network of old mining di


es. The Integrated Water Resources Master Plan and Wastewater Facilities Master Plan (hereafter the Master Plan) (El Dorado Irrigation District, 2013) identifies a number of different strategies including developing additional programs that increase


rn how to incorporate climate change into their long-term planning efforts. This report summarizes this collaboration.
The work proceeded in two phases. The first phase was conducted from the fall of 2009 through the spring of 2011. During this time,


h presented here has been reviewed by the Master Plan analysis team but has not been endorsed or yet assimilated into EID planning processes or documents.
XLRM Framework for Structuring Uncertainty Analysis
The following subsections describe the scop


 gradually over time as people and businesses move into the service area, and temperature and precipitation factors, which vary weekly.
The hydrologic component of the WEAP EID model was calibrated and validated to the naturalized flows on the South


Climate Scenarios
Uncertain future climate conditions are represented by diverse sequences of temperature and precipitation applied to geographically disaggregated catchment areas in the water management model. As described below, the WEAP applicatio


graphics, economic growth, resource use and energy systems, and cultural factors. There is a de-emphasis on globalization, reflected in heterogeneity of economic growth rates and rates and directions of technological change. These and other factors i


n demand because of a variety of operational constraints and instream flow requirements represented by the model.
This analysis considers a baseline strategy or current plan, consistent with the 2010 UWMP. It also considers three additional managemen


n of the agreement with SMUD, allows for a portion of the Eastern Region to receive supply from UARP, a potential major new supply source for EID. EID now expects for this supply to be available to only the Western Regions.
   22
assumed that increas


conditions is EID’s current plan most vulnerable? (Step 3)
• How can EID’s vulnerabilities be reduced through additional management options?
(Steps 2 and 3)
• What are the key tradeoffs among EID’s strategies for reducing its vulnerability? (Step 4)


ent plan across the 52 futures defined in Table 3-5.
Figure 4-3 summarizes unmet demand over all futures for the Western Regions (top panels) and the Eastern Region (bottom panels) across the 2020-2050 time period. The horizontal black lines indicate


Regions to about
10 percent (assuming an 85-percent reliability threshold), and to 0 percent for the Eastern Region, (assuming a 90-percent reliability threshold). The most favorable climate and demand assumptions, however, lead reliability to exceed


 all futures lead to poor outcomes. We next perform a statistical analysis of the simulation results to understand which external conditions lead to vulnerabilities. This information is useful in three ways:
• to guide the exploration of additional s


l the vulnerable outcomes (100-percent coverage) and none of the non-vulnerable outcomes (100-percent density) (Table 4-1). Figure 4-8 shows the definition of these vulnerable conditions graphically in terms of precipitation and temperature (horizont


n the historical record.
How Can EID’s Vulnerabilities Be Reduced Through Additional Management Options?
The preceding subsection analyzed how well EID’s current plan would perform across a wide range of futures. This subsection analyzes EID’s additi


he Increase Efficiency and Construct Alder Reservoir strategies for the Western and Eastern Regions, respectively. Table 4-3 and Table 4-4 define the vulnerable conditions for the same strategies.
In the Western Regions, increasing efficiency improve


ities in Eastern Region for EID Strategies
 39
Table 4-4: Vulnerable Conditions with Strategies for Eastern Region
   Strategy
Current plan
Increase Efficiency Only
Increase Efficiency and Construct Alder Reservoir
Definition of Vulnerable Conditions


 tradeoff information (see Lempert and Groves, 2010).
13 There is one climate scenario, A2 CNRM-CM3, which is vulnerable even with the additional strategies implemented (see Figure 4-7 and Figure 4-12).
14 The Construct Alder Reservoir Only strategy


ve assessment of how likely the key vulnerable conditions are. The 20-percent robustness threshold was set to demonstrate one possible way for EID to balance between investing to eliminate all possibilities of incurring a vulnerable outcome with the


the robustness threshold. For subjective probabilities greater than
20 percent but less than 25 percent, the current plan strategy would lead to higher than 20 percent expected vulnerabilities and the Increase Efficiency Only strategy would be the le


al determination about strategy. In this analysis, how much additional investment is needed in conservation or the construction of a new reservoir depends upon the likelihood EID might ascribe to either not successfully obtaining additional supplies


ing a planning activity using RDM.
Figure 5-1: Simple Recipe for Augmenting a Planning Process with Robust Decision Making
Implementing these steps requires more extensive scoping, additional modeling, and new analyses of results than what is needed


 Water Plan Update 2013: Plan of Study,” 2012b. As of March 14, 2013: http://www.waterplan.water.ca.gov/docs/cwpu2013/ae/future_scenarios-plan_of-study.pdf
 51
Deser, Clara, Reto Knutti, Susan Solomon, and Adam S. Phillips, “Communication of the Role


cenovic, Daniel Sarewitz, and Michael Schlesinger, “Characterizing Climate-Change Uncertainties for Decision-Makers: An Editorial Essay,” Climatic Change, Vol. 65, No. 1, 2004, pp. 1–9.
Lempert, Robert J., and Steven W. Popper, “High-Performance Gove


tional Academies Press, 2011. As of March 15, 2013: http://www.nap.edu/openbook.php?record_id=12781
National Research Council, Informing Decisions in a Changing Climate, Washington, D.C.: The National Academies Press, 2009. As of April 30, 2012: http


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R® is a registered trademark.
Cover image: A man walks through flood waters to survey damage from Hurricane Sandy in the New Dorp Beach neighborhood of the Staten Island borough of New York, November 1, 2012 (Reu


silient New York,” June 2013.
 iii
iv Flood Insurance in New York City Following Hurricane Sandy
tion and homeland security, transportation and energy policy, and environmental and natural resources policy.
Questions or comments about this report and


. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flood Insurance Claims and Payments for Hurricane Sandy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . National Flood Insurance Program Claims and Payments . . . .


ctures in the High-Risk Zones of the 2007 Flood Insurance
Rate Map on One- to Four-Family Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6. Take-Up of National Flood Insurance Program Policies for One- to Fou


. . . . . . . . .
4.4. Take-Up of National Flood Insurance Program Policies for One- to Four- Family Structures in the High-Risk Zones Added by the Preliminary Work Map, by Mortgage Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


. . . . . . . . . . . . . . . . . . . . . 93
C.1. Distance from Base Flood Elevation to Ground Level in High-Risk Areas
of the Preliminary Work Map, 61,668 Parcels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
C.2. Se


mulated billions of dollars of cost overruns since Hurricane Katrina in 2005, on a stronger financial footing by moving toward more risk-based premiums.
The first of these changes, the Biggert-Waters Flood Insurance Reform Act of 2012 (BW-12) (Pub. L


 (RAMPP), “Preliminary Work Map Data,” June 18, 2013.
NOTE: Areas subject to riverine flooding are not included.
RAND RR328-S.1
Proportion of Residences and Businesses with Flood Insurance
We estimate that 55 percent of the one- to four-family homes


due to Hurricane Sandy were roughly half those for Hurricane Katrina. This figure does not include NFIP claim payments and is likely dominated by
wind-related losses. Even though claim payments were substantial, Hurricane Sandy’s impact on the overal


n of the new flood map, assuming that it is similar to the preliminary map that has not yet been formally adopted. In some cases, premiums increased by $1,000 to $2,000 per year. As stipu-
Summary xv
xvi
Flood Insurance in New York City Following Hur


r own homes, as well as on renters and landlords.
Homeowners
Cost increases of this size would pose economic hardships for many households in the city. About 37 percent of households living in owner-occupied units in the floodplain earn less than $75


and stabilization policies in New York and how these policies would change over time.
Policy Options to Consider in Response to Premium Increases
New York City is considering a range of options that could provide residents with some relief in the cos


tructures from some areas when property owners are willing to sell.
• Work with FEMA and the New York State Department of Financial Services to increase the take-up rate. Higher take-up rates mean that more resources are available for recovery after


ence and speed its recovery by taking steps to mitigate the risk of flood damage and to increase flood insurance coverage for its residents and businesses. To achieve these goals, the city needs to work with FEMA and other agencies to collect better


 Christopher H. Perini of Verisk Analyt- ics; Martin Koles of M. Koles and Associates; Danielle McHeffey and Kirsten Squires of Maran Corporate Risk Associates; Robert P. Hartwig of the Insurance Industry
xxi
xxii Flood Insurance in New York City Fol


t-backed National Flood Insurance Program (NFIP), which has been operating at a loss in recent years. These developments will provide a more accurate basis for assessing flood risk and setting premiums that reflect those risks. But they will also imp


ap for New York City so property owners could rebuild based on this updated information, but it approximated flood risk information. In June 2013, that map was then superseded by the Preliminary Work Map (PWM) that incorporated more-refined wave mode


s to mitigate flood risk that will also lower their premiums.
Study Purpose
As a government, New York City is concerned with ensuring that its residents and their property are safe. When events like Hurricane Sandy hit and residents incur damages, th


rk City after Hurricane Sandy as of Feb- ruary 2013. To estimate insured losses, we drew on data collected by the insurance industry.
To describe the structures and residents at risk in current and future flood zones, we used geospatial (geographic i


es, the number of structures in high-risk flood zones, and the take-up rate for flood insurance for both residences and businesses on the eve of Hurricane Sandy. It also examines the typical prices of flood insurance in New York City pre–Hurricane Sa


are associated with one- to four-family dwellings, most residential hous- ing units are in multifamily structures or mixed commercial and residential proper- ties. Even in densely populated New York City, roughly 60 percent of the parcels and
Brookly


is one property parcel that is classified as single-family homes. However, the Breezy Point parcel includes 1,897 structures and 1,885 residential units, each of which is a single-family home. Even though some parcels have a large number of structur


res with flood insurance compared with the proportion without, on the eve of Hurricane Sandy in the high-risk areas of New York City. The share of the total number of structures with flood insurance is also referred to as the take-up rate. We first d


olicy with the address of the parcel to which the policy was assigned. We randomly sampled 491 of the 25,916 NFIP policies in New York City as of October 31, 2012 (1.9 percent). For residential parcels, the address on the NFIP policy matched the parc


rcel. That would not be the case at Breezy Point, for example, where the number of NFIP policies is far smaller than the number of structures on the parcel (1,897). The 55-percent take-up rate estimate lies approximately in the middle of the 49- to 6


r- cent of owner-occupied housing units in the high-risk areas of the 2007 FIRM have mortgages, substantially below the 77-percent figure. The two figures are not neces- sarily inconsistent, however, because the CoreLogic data include properties that


se parcels for which property taxes were paid by a mortgage service company, thus indicating that a mortgage was attached to the property. Mortgages may exist on other parcels but would not be flagged in the New York City data. These include properti


ypes of flood coverage available.)
Interviews with informed industry sources suggest that flood insurance take-up among large commercial firms is very high, estimated at 80–90 percent. These take- up rates apply regardless of whether insured structur


ty as of October 2012 and the amount of coverage purchased. The analysis is based on the 25,916 residential and commercial NFIP policies in force in New York City as of October 31, 2012.13 The findings provide a base against which to assess the chang


    Structure Location and Construction Date
In high-risk flood zone of 2007 FIRM Pre-FIRM
Post-FIRM
Outside high-risk flood zone of 2007 FIRM
Pre-FIRM
Post-FIRM All policies
Number
11,217 8,034 3,183
11,199
8,779
2,420 22,416a
Average Premium (dolla


were matched with the pertinent NFIP policy and linked with the appropriate property parcel using the meth- ods described in Chapter Two.
As of February 2013, the NFIP had received 16,264 claims for losses in New York City attributed to Hurricane San


ge was $10,000 or less on 10 percent of closed claims and $25,000 or less on 29 percent of closed claims.
Changes in the maximum policy limits on building coverage have also been pro- posed over the years. Table 3.4 provides some insight into the con


 Following Hurricane Sandy
Table 3.3
Number of Closed National Flood Insurance Program Claims in New York City for Hurricane Sandy, by Amount of Building Damage, as of February 28, 2013
 Building Damage ($)
0 to 5,000
5,001 to 10,000
10,001 to 25,000


 expensive. Whether policyholders would find basement coverage attractive at actuarially fair rates is an open question. (More information on the basement coverage provided by the NFIP is given in Appendix A.)
Complaints were widespread among those w


 its floor below ground level (subgrade) on all sides” (NFIP, “Resources: Glossary,” last updated September 26, 2013b). This definition appears straightforward, although perhaps not what many would like it to be.
6 See Office of the Governor, “Govern


l properties that had private flood insurance that included business-interruption coverage, for many, the business-interruption coverage was never triggered because the loss did not occur on their own premises. This came as a sur- prise to many prope


st be adjusted by a certified flood damage adjuster, but these adjusters are more common in areas that experience frequent hurricanes and other flood-related events. As a consequence, the adjusters for Hurricane Sandy tended to come from the South. A


f the observations by the insurers and insurance brokers about Hurricane San- dy’s impact on insurance pricing are consistent with the conclusion reached by Advisen in its January 2013 white paper.7 Advisen concluded that Hurricane Sandy will, at wor


e changed. Members are asked to characterize the premium changes for similar coverage that is renewed with the same carrier or moved to a new carrier during the quarter. Results from two quarters prior to Hurricane Sandy through two quarters post–Hur


ate Department of Financial Services. If the coverage they seek is not available from admitted insurers, individuals and businesses can turn to the nonadmitted (or surplus-lines) insurers for coverage.
   32 Flood Insurance in New York City Following


ly to keep them aggressive and the marketplace competitive for the near future.
10 RMS’s North Atlantic Hurricane Model predicts hurricane landfall rates and the associated damage. Ver- sion 11 was released in 2011, and Version 13 was released in the


e affected by changes summarized in the first three changes. Another 580,000 (13 percent) will be affected when an insured property is sold or the policy lapses (the last change).4
As shown in Table 2.4 in Chapter Two, a high percentage of structures


e considered severe-loss or repetitive-loss properties. Esti- mates of the turnover of structures in New York City’s high-risk areas have not been developed, although the U.S. Government Accountability Office (GAO) analysis of BW-12 assumes that betw


e Subsidies
 Subsidized Premium Paid Prior Zone Elevation to BW-12a
AE –1 2,922 AE 0 2,922 VE –1 6,016 VE 0 6,016
Full-Risk Premium Paid After BW-12 Phased Inb
5,090 1,722 9,530 7,094
Difference
2,168 –1,200 3,514 1,078
  SOURCE: Torrent Technologies


te the new FIRM will become effective in New York City is unknown; it depends on the number of appeals submitted that need to be resolved. A target date may be early 2015.
The coastal floodplain study was performed using the latest storm-surge modeli


ing the ABFEs would not only help reduce future flood risk but also help avoid paying higher flood insurance premiums when the new map became effective, especially because, as discussed in the section on rate grandfathering later in this chapter, the


isk of Coastal Flooding
2013 high-risk areas that were high risk in the 2007 flood map
2013 high-risk areas that were not high risk in the 2007 flood map
Bronx
Staten Island
Manhattan
SOURCES: FEMA Map Service Center data for 2007; RAMPP, “Preliminar


-up rates are very low regardless of whether there is a mortgage on the property (see Table 4.4). This is not surprising because households outside the high- risk areas of the 2007 FIRM have not been told they are at risk of flooding and face no MPR


ot have flood insurance Take-up rate (percentage)
NOTE: Structure counts are rounded to the nearest hundred. a Excludes areas subject to riverine flooding.
2007 FIRM
25,800 55 72 68 21
18,500 12,600 5,900 68 7,200 1,500 5,700 21 25,800 14,100 11,600


er than 3.1 feet. The changes in Brooklyn, Man- hattan, and Queens are similar, with larger increases on Staten Island. The BFE in the Bronx changed little on average, with approximately as many parcels showing an increase in BFE as those showing dec


current FIRM for future rating when the new FIRM becomes effective so long as the policyholder maintains the policy. Examples of affected map changes include buildings newly mapped into a high-risk area (e.g., Zone X to Zone A), mapped from a high- t


d risk. These areas outside of known floodplains are shown as B, C, or X zones on a FIRM. To be eligible for a PRP, a structure must also meet certain loss history requirements. For example, there cannot be three or more flood insurance claim payment


a range of cases to illustrate the potential effect of map changes on NFIP premiums paid by property owners in New York City. For a given structure elevation, the NFIP premium depends importantly on whether the building has a basement. (Recall that


d not be surprising to see NFIP premiums of $3,700 to $15,900 for the same structure once it is reclassified as being in a high-risk area.
Cases 4 through 7 apply to a pre-FIRM one- to four-family structure with base- ment that remains in the high-ri


 Situation
–4 9,995
    Table 4.8—Continued
Current Situation
a Lowest Floor Relative to BFE Zone (feet)
Case Basement
Remains in Zone AE, primary residence, currently insured
Remains in Zone AE, currently not insured
Remapped from Zone AE to Zone VE


side high-risk zones to inside high-risk zones
Remain in high-risk zones All post-FIRM structures
Insured as of October 2012
400
3,200 3,600
Not Insured as of October 2012
2,100
1,900 4,100
Total
2,500
5,200 7,700
    NOTE: Insurance status is based


h-risk areas. Because these structures were outside the high-risk zones when constructed, it would not be surprising to see structures with large negative elevations under the new FIRM. As can be seen, cases in which premiums rise by $2,000 to $7,500


to more accurately reflect risk may lead to large increases in flood insurance premi- ums for households in New York City. The increases will depend on the location and characteristics of the structure and, in some cases, whether there is flood insur


ir data.5
The premium-increase example presented here assumes that the property owner must purchase flood insurance. The effect of increased premiums might be less on structures for which the purchase of flood insurance is voluntary.6 However, even i


sented in Chapter Four, which amounts to 5–10 percent of median household income. The percentage of median income is even higher when one considers the full premium rather than just the increase from an initial level. For comparison, national census


 14
High-RiskZones High-RiskZones
  Race (% of population)
White 44 Black 25 Asian 13 Other 18
Households below poverty line (%)b
Education (% of population greater than 25 years old)
Less than high school degree High school degree
Some college
Bache


ffect—particularly for pre-FIRM structures and properties subject to grandfathering—will depend on how FEMA implements certain provisions of BW-12.
Renters of Residential Housing Units
Renters account for approximately two-thirds of the households li


cant rent increases that do occur could have adverse effects on the renter population. As shown in Table 5.1, approximately one-third of households living in rental units in New York City’s high-risk areas earn less than $25,000 per year. Rent increa


more accurately reflect risk. The risk-based premiums can create incentives for property owners and government planners to take appropriate measures to reduce risk. They also put the cost of living in high-risk areas on those who own property in thos


s would occur. The most important piece of missing information is the elevation of structures in the high-risk areas of the PWM. Structure elevation relative to BFE is currently available for relatively few structures in the high- risk areas of the P


gent must submit the policy to the insurer administering the NFIP policy or to FEMA to determine the rate, rather than quickly pull it off a rate table. Submitting a policy for rating can cause delay and may depend on subjective assessments. Conseque


ation on businesses, individuals, and neighborhoods. The reports, even once produced, will not necessarily address the unique concerns of major metropolitan areas, such as New York City, so it is important for New York City to understand how various


uctible for lower-income house- holds should an event occur.10 The actuarial costs of a policy are a function of the deductible, the limit, and the risk of an event. By increasing the deductible above the $5,000 limit currently allowed on residential


weather events are real, and it is just a matter of time before another catastrophic storm strikes the eastern seaboard. But if the city takes steps to mitigate the risk of flood damage and increase flood insurance coverage for its residents and bus


c.
Personal property on premises
Personal property off premises
Additional living expenses
Percentage of Insured Value
10
50
10 (or $1,000, whichever is greater) 20
    Perils
SOURCE: New York State Department of Financial Services,
“Homeowners Resou


NWS declaration)
Hurricane declaration by NWS anywhere in the state (within 12 hours before and 12 hours after)
Hurricane declaration by NWS anywhere in the state or a contiguous state
Background on Flood Insurance 71
 Trigger
 72 Flood Insurance in


ails to fix it in a reasonable time frame.2
In most cases, a landlord’s insurance does not cover a tenant’s personal property. Thus, tenants are liable for their own property damages and losses. Renters face the additional risk of paying for injuries


ew York City as a result of Hurricane Sandy, but we are not sure about the total number of renters’ ALE claims due to Hur- ricane Sandy.
Premiums
The price of renter’s insurance varies depending on the New York City neighborhood, the amount of person


mpensation cov- erage for employees. The condo association and the building owner typically work together to shop for coverage and, between the two, ensure that everything is covered. There is not a standard separation between what the building owner


itate efficient access to participating private-market insurance companies to cover personal residential property risks located in coastal areas. NYPIUA insures the dwelling, and private insurers cover contents. Insurance companies voluntarily partic


typical homeowner’s policy. NYPIUA issues basic coverage policies using the standard deductible published by the Insurance Services Office for its dwelling program. The basic coverage protects property against loss caused by fire, lightning, windstor


he producer, NYPIUA will provide building coverage on a repair or replacement-cost basis.
National Flood Insurance Program
Background on the National Flood Insurance Program
Flooding is a major source of loss to individuals and businesses in the Unit


unity participating in the NFIP. Loans on homes in SFHAs sold to government-sponsored enterprises, such as Fannie Mae and Freddie Mac, are also subject to this MPR. The act prohibits federal agencies from providing financial assistance for acquisitio


tal areas. Chapter Four discusses the changes resulting from BW-12 in more detail.
National Flood Insurance Premium Coverage Types
For residential buildings and individual condominium units, the NFIP offers a max- imum $250,000 in structure coverage


for the building if the limit is at least 80 percent of the condo- minium’s replacement cost (or the maximum limits allowed, whichever is smaller); otherwise, a co-insurance penalty will be applied at the time of loss. The RCBAP does not cover the co


he high-risk flood zones begin with A or V.
Table A.6 provides example premiums for a set limit of coverage ($200,000 in building and $80,000 in contents) for a single-family primary residence. The examples vary by flood zone, elevation, and pre- and


ea with a temporarily increased flood risk due to the building or restoration of a flood-control system (such as a levee or a dam). MPRs for flood insurance will apply, but rates will not exceed the rates for unnumbered A zones if the structure is bu


• air-conditioning units, portable or window type
• clothes washers and dryers
• food freezers, other than walk-in
• food in any freezer.
With a PRP, contents located entirely in a basement are not eligible for contents- only coverage.
Elevating elec


e very high
25 Casualty includes liability coverage.
Background on Flood Insurance 87
 88 Flood Insurance in New York City Following Hurricane Sandy
uptake of flood insurance among these firms. Large firms tend to have these policies regardless of wh


urance related to the flooding event (the standard business- interruption coverage would exclude flood damage).
The smaller firms in this middle market (between $50,000 and $200,000 in pre- miums per year) may not carry any flood insurance, and those


urance coverage for losses over $500,000.
Background on Flood Insurance 89
 90 Flood Insurance in New York City Following Hurricane Sandy
what is called the excess market primarily provided by surplus line carriers. According to those we interviewed,


Barrier Resources Act, October 18, 1982. The CBRA removed the federal gov- ernment from financial involvement associated with building and development in undeveloped portions of des- ignated coastal barriers. CBRA banned the sale of NFIP flood insura


mily Structures with Mortgages in the High-Risk Zones of the Preliminary Work Map (as of October 31, 2012)
    Structure
Structures with mortgages (based on 34,018 parcels)
Take-up rate for structures with mortgages (based on 26,695 parcels)
Take-up


ed.
95
96 Flood Insurance in New York City Following Hurricane Sandy
Table C.1
Distance from Base Flood Elevation to Ground Level in High-Risk Areas of the Preliminary Work Map, 61,668 Parcels
Average Distance in Parcel
from BFE to Ground Level (feet


It Comes to Coverage for Flood,” Northbrook, Ill., press release, March 21, 2013. As of April 23, 2013: http://www.allstatenewsroom.com/channels/News-Releases/releases/ survey-shows-a-large-knowledge-gap-amongst-americans-when-it-comes-to-coverage-f


ing Tests,” Cochrane Database of Systematic Reviews, Vol. 2, February 28, 2013.
Federal Emergency Management Agency, “National Flood Insurance Program: Program Description,” August 1, 2002. As of October 11, 2013:
h t t p : / / w w w . f e m a . g o


on-the-road-recovery-press-briefing.html
Independent Insurance Agents and Brokers of New York, “Coastal Markets Assistance Program (C-MAP), Agents’ and Brokers’ Guide to Insuring Coastal Property,” May 2009.
Kousky, Carolyn, and Howard Kunreuther, “A


nters.htm
———, New York State Homeowners Coverage: Approved Independent Mandatory Hurricane Deductibles: Revised as of 3/20/2013, March 2013a.
———, “Homeowners Resource Center,” updated April 8, 2013. As of October 11, 2013: http://www.dfs.ny.gov/con


hington, D.C., GAO-13-607, July 3, 2013. As of October 11, 2013:
http://w w w.gao.gov/products/GAO-13-607
U.S. Statute 61-193, Housing and Rent Act of 1947, June 30, 1947.
Watt, Richard, Francisco J. Vázquez, and Ignacio Moreno, “An Experiment on Ra


  CHILDREN AND FAMILIES EDUCATION AND THE ARTS ENERGY AND ENVIRONMENT HEALTH AND HEALTH CARE INFRASTRUCTURE AND
TRANSPORTATION INTERNATIONAL AFFAIRS LAW AND BUSINESS NATIONAL SECURITY POPULATION AND AGING PUBLIC SAFETY SCIENCE AND TECHNOLOGY
TERRORIS


rohibited. RAND documents are protected under copyright law. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any o


........ Washington State Healthy Youth Survey of 10th and 12th Graders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Washington State Treatment Admissions from SCOPE-WA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


13 (Unadjusted for Survey Undercounting/Misreporting). . . . . . . . . . .
3.6. County-Level Estimates of Past-Month Marijuana Users and Marijuana
Consumption, by Rank in 2013 (Unadjusted for Survey Undercounting/
Misreporting).......................


sights from this report include the following:
• The National Survey on Drug Use and Health (NSDUH) reports that for 2010 and 2011 the average number of individuals in Washington who used marijuana or hashish in the past month was 556,000, with a 95-


cknowledgments
 We are deeply indebted to Susan Andrzejewski, Steve Davenport, Mark Kleiman, and the larger BOTEC I-502 team for their insights and suggestions. We could not have conducted this analysis without the support of Sharon Foster, Rick Garz


hile marijuana remains illegal under federal law, the U.S. Department of Justice announced in August 2013 that—for now—it would not block the implementation of state legalization in Washington and other states with “strong and effective regulatory an


d used; it also presented them with scaled pictures of marijuana buds and ground material to improve the accuracy of their responses about weights consumed. It also included multiple questions that sought to get at the issue of sharing.
This report i


t is computed separately for different types of users and then summed (weight- ing by the numbers of each type of user) to obtain the overall market estimate.1 Information about the first two values is readily available from government surveys, cavea


blishes state-level prevalence information, it has historically been difficult to obtain information about other marijuana variables at the state level. Fortunately, there have been two recent advances. First, SAMHSA now allows researchers to generat


ays in the past month (e.g., Cohen, 1999; Zhang, Friedmann, & Gerstein, 2003; Robbins et al., 2006).
Trends in Prevalence Since 2010/2011
Our task is to estimate consumption throughout 2013, but the analysis was done during 2013, and the most recent


Washington and elsewhere, users may now be more likely to report their use on surveys. Whether this occurs is an empirical question (see Fendrich & Rosenbaum, 2003), but if it does, the decrease observed for 10th graders in Washington between 2010 a


 to 2013 of between 5 percent and 15 per-
Size of the Marijuana Market in Washington in 2013 7
8 Before the Grand Opening: Measuring Washington State’s Marijuana Market
cent, with a middle estimate of 10 percent. While this parameter is impossible to


per day of use, while those who used one to three days in the previous month con- sumed 1.7 joints per day of use (Table 2.1). However, these figures are likely inflated since survey respondents could not report using less than one joint. Marijuana


a from seven European Union countries (Bulgaria, Czech Republic, Italy, Netherlands, Portugal, Sweden, and United Kingdom), Caulkins and Kilmer (2013) estimate consumption of 35 grams per month for those using 20 or more times per month. Similar to w


nd grams consumed per use day.
The web survey created to generate these European data (van Laar et al., 2013) motivated some of the questions included in our CCS (see Appendix A for detailed information about the survey).6 Namely, the use of picture


pondent grew their own marijuana, whether the respondent had a medical access card, and whether the respondent had a college degree. (The first two predicted greater amounts consumed per day of use; having a college degree predicted lower quantities


no med
typical Grams per Use Day Weighted mean
Weighted Winsorized mean
37.5% 19.0% 26.3%
1.89 1.59
  nOte: these figures are based on a
In Scenarios 2, 4, and 6, the “college grad” and “less than college grad” groups were merged, hence a single perc


e military).
2. Use by people who are in the sampling frame but nonetheless are not surveyed (e.g., because they were never home or refused to answer).
3. Misreporting of past-month use by people who are successfully surveyed.
4. Misreporting of quan


ton
Substance use treatment admissions for marijuana in Washington
past-month use by 12th graders nationwide
Characteristics of daily and near-daily marijuana users, use patterns, and expenditures in Washington
   figure by two to three, since survey


Washington marijuana users in calendar year 2013. Estimates also assume a 3 percent increase in sales beginning in 2015 to account for population growth and inflation. Frequency of consumption is estimated using the pattern contained in the United Na


that many of these “increases” could not possibly be real and are likely to be artifacts of the changes in the survey procedures. A key finding was that the increases in rates of lifetime use were inconsistent with rates of new use. For example, NHSD


te’s counties, we employ data from several sources. Ideally, we would like to capture the heavy marijuana users well, as they account for a very large share of the total market.
The following section presents information about data sources; the subse


eems to be an overall upward trend, even that weighted average may tend to underestimate current prevalence.
We chose to employ a third method to project the current and future prevalence from the past data. We passed a linear regression line through


State University is in Pullman. So it would seem somewhat naïve to presume that marijuana demand in Stevens County matches that in Whitman County. It might make more sense to focus not on total population but rather on the number of 15–34 year-olds,


r heavy use, as most people admitted for substance abuse treatment for marijuana are heavy users.
There is significant geographic variation in reported marijuana-related treatment admis- sions that may not be tied directly to use, but rather to count


rs based on each series at the region level for a time period. (1) Region total number of past-month usersi =
Prevalencei × Population 12 and overi
   l
a
l
l
Bellingham W
San Juan Island
W
m
S S
t
e
h
h
k
y r
k
r
a
a
a
a
t
t
g
g
c
c
i
i
t
o
o
m
 nP


month use, treatment admissions with marijuana as a primary substance, and treatment admissions with a marijuana as a secondary substance.
We investigate placing various weights on each of these series. (e.g., putting 100-percent weight on total popu


 1 total* 100
Share of Region 1 Total and Weighted Average Share of Region’s Users
  population (%)
15–34 Year Olds (%)
2.3 7.4 4.1 0.7
10.4 0.8 3.7 1.0 56.3 3.6 9.8
100
primary tx (%)
0.6 11.2 4.4 1.3 6.2 0.8 5.2 1.3
62.0 4.7 2.3
100
Secondary tx (%


 .20 .20
  King
Kitsap 24,827 pierce 67,149 Clallam 8,923 Clark 37,503 Cowlitz 11,074 Grays harbor 8,592 Jefferson 2,903 Lewis 7,346 Mason 6,044 pacific 2,418 Skamania 1,229 thurston 23,736 Wahkiakum 414
State totals 610,000
nOte: Some state totals d


he Grand Opening: Measuring Washington State’s Marijuana Market
Table 4.1
Past-Month Marijuana Use, Percentage of the Population, NSDUH 2010–2011
State
26 or Older Est.
26 or Older 95% CI
26 or Older 95% CI
  12 or Older Est.
 12 or Older (95% CI (lo


nation. While past-year users in Washington approximately match the national age distribution and past-month users in Washington are slightly older than the national average, they are slightly younger than in Oregon (see Figure 4.2).
Race and Ethnici


 heavy use than other races or ethnicities. Overall, the rates of heavy use appear higher across each race and ethnicity in Washington than seen nationally.
Figure 4.3
Race and Ethnicity (Excluding White Non-Hispanic) of Marijuana Users, NSDUH 2010/2


010/2011
              Gender
Female Male
      Percentage
100
 90
 80
 70
 60
 50
 40
 30
 20
 10
  0
              USA Washington
Past-year, not past-month user
USA Washington
Past-month, non-heavy user
USA Washington
Heavy user (21–30 days per mon


oints. Oregon shows similar uncertainty.
Other illegal drug use
No other illegal drug use in past month
Other illegal drug use in past month
 38 Before the Grand Opening: Measuring Washington State’s Marijuana Market
Figure 4.8
Past-Month Tobacco Use


sampling artifact rather than reflecting actual state-to-state differences.
We also looked at how acquisition methods varied among past-month heavy and non- heavy users (Figure 4.11). Due to small counts for other categories, we include only the two


HSA, n.d.).
RAND RR466-4.13
Insights from Seattle’s Youth Risk Behavior Survey
                Percentage
       Oregon
       Source
Unspecified (other)
Someone just met/did not know
Relative/ family member
Friend
            Percentage
       The Y


significant mortality and morbidity during both youth and adulthood. These include: behaviors that result in unintentional injuries and violence; tobacco use; alcohol and other drug use; sexual behaviors that contribute to HIV infection; other sexua


1 the average number of individuals in Wash- ington who used marijuana or hashish in the past month was 556,000, with a 95-percent confidence interval of 475,000–650,000. NSDUH excludes some populations from its sampling frame and self-report surveys


ate level in the United States. Inasmuch as more than a few states may be considering legalizing marijuana in the near future, there will be cause to replicate this analysis in other states, and comparisons across states are likely to be insightful.


 D.C.: Executive Office of the President, Office of National Drug Control Policy.
Abt Associates. (2012). What America’s users spend on illegal drugs, 2000–2006. Washington, D.C.: Executive Office of the President, Office of National Drug Control Pol


l 26). Table GPS-10: Frequency of use of cannabis amongst users in the last 30 days in national general population surveys. Retrieved November 18, 2013, from http://www.emcdda.europa.eu/stats13/gpstab10a
49
50 Before the Grand Opening: Measuring Wash


n press). What America’s users spend on illegal drugs: 2000–2010. Washington, D.C.: Executive Office of the President, Office of National Drug Control Policy.
Kilmer, B., & Pacula, R. (2009). Estimating the size of the global drug market: A demand-si


g marijuana. Retrieved November 18, 2013 from http://www.people-press.org/2013/04/04/majority-now-supports-legalizing-marijuana/
PriceOfWeed.com. (2013). Washington weed prices. web page. Retreived May 29, 2013, from http://www.priceofweed.com/prices


-based state estimates. Retrieved November 25, 2013, from http://www.samhsa.gov/data/NSDUH/2k11State/NSDUHsaeMethodology2011.htm
Substance Abuse and Mental Health Services Administration. (n.d.). Restricted-use Data Analysis System. Retrieved Novembe


Journal of Drug Policy, 23(6), 436–441.
Wilkins, C., Reilly, J., Pledger, M., & Casswell, S. (2005). Estimating the dollar value of the illicit market for cannabis in New Zealand. Drug and Alcohol Review, 24(3), 227–234.
Wilkins, C., & Sweetur, P. (2


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g the Particulate Matter Standard on Key Health Endpoints in the Pittsburgh Metropolitan Statistical Area. . . . . . . . . . . . . . . . . . . .....
S.2. Annual Effect of Meeting the Ozone Standard on Key Health Endpoints
in the Pittsburgh Metropolit


. . . . .
A.5. Literature on Air Quality Regulations and Firm Location Decisions . . . . . . . . . . . .
xiv . xv xvi . . 5 38 . 39 40 . 41
. 41
42
44 . 45
48 . 52 . 53
56 .58 .62
ix
x Links Between Air Quality and Economic Growth: Implications for P


rough other channels. This report examines the relationship between air quality and economic growth through three pathways:
• Pathway 1: health and related workforce issues and costs. This effect links air quality to the health of the local populatio


would be associated with improving air quality to meet the NAAQS. For pathway 3, the fact that areas that fail to meet the NAAQS face more-stringent air quality regulations, which, in turn, affect business location and operation decisions, was consi


A, 2013i).
Meeting the NAAQS for PM2.5 would include improvements in a health-related metric that may be particularly salient to local business: work-loss days. In addition, meeting the NAAQS for ozone would reduce school-loss days, which, in turn, r


nd, it should be noted that coming into com-
xvi Links Between Air Quality and Economic Growth: Implications for Pittsburgh
Table S.3
Estimated Effect of Not Being in Attainment on Regulated Industry Outcomes in the Pittsburgh Metropolitan Statistica


ulated industries do face costs associated with improving air quality, meeting the NAAQS can make it easier for businesses in regulated indus- tries to locate and operate in the Pittsburgh region in the long run. In the Pitts- burgh region, being des


uspended particulates VNA Voronoi neighbor averaging VOC volatile organic compound
WLD work-loss day
WTP willingness to pay
CHAPTER ONE
Introduction
 Historically, Pittsburgh was a stronghold of the iron and steel industries in the United States and


required to develop plans, known as State Implementation Plans, for improving air quality in nonattainment areas and for preventing degradation in attainment areas. Nonattainment area plans must typically include more-stringent control measures for


wanna
Carbon
Hancock
Brooke Ohio
Marshall
0 20
Miles
Cambria
Blair
Berks
Cecil
Pittsburgh–Beaver Valley, Pa.
Erie
Crawford
Warren
Forest
McKean
Elk
Potter
Centre
Huntingdon
Fulton
Tioga
Lycoming
Union Snyder
Juniata Perry
Cumberland
Adams
Bradford
Su


n, Pa. Pittsburgh–Beaver Valley, Pa.
0 25 50 75 Miles
Lancaster, Pa.
Philadelphia-Wilmington, Pa.-N.J.-Del.
Cambria
Blair
Mifflin Juniata Perry
Pittsburgh–Beaver Valley, Pa. Harrisburg-Lebanon-Carlisle, Pa.
Huntingdon
Centre
Union
Franklin
Johnstown,


 size of fine PM is a concern because of the particles’ ability to penetrate deeply into the lungs. Major PM2.5 sources include fuel combustion from motor vehicles, diesel-powered vehicles, power plants, and industrial processes (EPA, 2009).
Hazardou


vehicle inspections; and indirect costs, such as productivity losses. Despite some controversy over the exact nature of the costs and benefits, the total value of benefits from major clean air legislation has been shown to exceed the costs substanti


nfluence economic growth through its influence on firm and individual decisions, and it sum- marizes our assessment of the existing literature for each of those channels. In Chapter Four, we present the results of our extrapolation of existing result


 Economic Growth: Implications for Pittsburgh
• •
(air quality OR air pollution OR clean air) AND (tourism OR recreation)
(air quality OR air pollution OR clean air) AND (housing prices OR willingness to pay OR hedonic).
We tried a variety of permuta


o summarize our findings from the literature.
Limitations
A key limitation of our literature review is that we may have missed relevant articles, despite our search of various databases. In addition, because we did not conduct a full systematic revie


holders, the interviewees are not meant to be representative of the local Pittsburgh or national population. Interviewee responses may have been shaped by personal experience and attitudes about air quality and economic develop- ment. As such, we did


te of endpoint J in the affected population, Pop J . Because β J is small, Equation 1 can be linearized and expressed as the following:
ΔOJ =βJ ×O0J ×ΔC×PopJ.
(2)
Linear and logistic are other forms that are commonly assumed to describe the pollutant


 may not be representative of the MSA, they are likely to be closer to the SLD rate due to respiratory illness.
Air Pollution Exposure
Selecting Monitor Data and Spatial Interpolation
BenMAP 4.0 includes monitor values for PM2.5 and ozone from 2000 t


concentrations are assumed to be unaffected by any air pollution control strategy and are therefore not adjusted using reduction methods. We assumed a constant background of 3 μg/m3 for PM2.5 yearly and daily standard metrics and backgrounds of 0, 40


 Growth: Implications for Pittsburgh
between 5 and 17 years old in the Pittsburgh MSA, while the affected population for WLDs includes adults between ages 18 and 64.
Economic Valuation
To estimate the economic benefits of improved health outcomes, we


me instead.
 take into account meteorology (temperature, humidity), terrain, precursor emissions, or other factors that an air quality model can incorporate. It is possible that our results do not capture the full range of benefits because numerous s


Methodology 17
18 Links Between Air Quality and Economic Growth: Implications for Pittsburgh
values of establishments, employment, and output. These studies identify the effects of nonattainment status by comparing counties that are in attainment wi


rent sense of the magnitude of the effect.
5 Because of data privacy issues, the census does not provide average payroll data for certain industries at the MSA level.
 1987, Greenstone controls for plant-specific characteristics and identifies the ef


nal level. To the extent that these industries have a larger or smaller share of major emitters in the Pittsburgh region than they have nationally, the effects may be larger or smaller. We examined the extent to which this could be a concern using EP


he three key ways in which local air quality could influence local economic growth. This framework was largely based on our review of relevant literature but also informed by our stakeholder interviews. For each of these effects, we then summarize ou


have long-run impacts via the size or productivity of the workforce. Workforce productivity, in turn, may affect economic growth directly or may be a factor in business location decisions (Figure 3.1).2
Air Quality and Health
An extensive body of evi


(1984) show that a one-standard- deviation increase in TSP is associated with a 10-percent increase in WLDs. Ostro (1987) confirms that increased PM concentrations are associated with more restricted- activity days and WLDs, although the effects var


Chen et al., 2000; Currie et al., 2007; Peters et al., 1997).
School absenteeism may affect the workforce in two ways: by requiring parents to take days off work to care for their children and by affecting long-term educa- tional attainment (and thus


was no discernible difference in school performance as mea- sured by reading, math, and language test scores, grade-point averages, grade promo- tion, or class rank of graduating students. Moonie et al. (2008) study an urban African American populati


rtality have a positive impact on long-run national gross domestic product (GDP) by providing more labor to the workforce (EPA, 2011a).5 A strength of this type of model is that it does allow a projection of the impact of air quality improvements on


ecisions
Air quality
Quality of life
   Quality of environment
        Health effects
    People’s decisions about where to live
Business
decisions about where to invest and grow
Population size and workforce quality
Outdoor recreation
       Access


ld would be willing to pay $149–185 (in 1982–1984 dollars) for a 1-μg/m3 reduction in PM.
Although Banzhaf and Walsh (2008) find evidence that people do “vote with their feet” for cleaner air, they point out, “given constraints on mobility related to


y-of-life factors. Although quality-of-life factors were considered less important than economic factors, quality of air and water was one of the top-ranked quality-of-life factors, which also included the educational system, cost of living, housing,


- ducted during the late 1990s, and many of these studies find that regulations do deter businesses from locating in an area. In contrast, the first wave took place during the late 1980s and early 1990s and typically provided little support for the h


ect compliance costs of the Clean Air Act Amendments range from about $20 billion (in 2006 dollars) in 2000 to $65 billion in 2020 (EPA, 2011a). To some extent, cost projec- tions should be cautiously interpreted because there is empirical evidence (


followed by TSP and SO2; in contrast, carbon monoxide nonattainment status is associated with an increase in productivity. The effects also vary by industry; for ozone and carbon mon- oxide, effects are positive for some industries and negative for


because regulations may require more inputs for the same amount of output, thereby increasing employment; a factor-shift effect because activities required by envi- ronmental regulations may be more or less labor-intensive than other activities, whic


other parts of the United States; they conclude that, although the regulations raised costs among affected refineries, there was no statistically significant effect on employment. Morgenstern, Pizer, and Shih (2002) examine the relationship between e


th 35
approach is to consider potential job gains in the pollution control sector. These gains are often assumed to be short term and are reported in terms of job-years. A broader version of this approach examines changes in employment that may be in


d result in 46,000 one-time job-years gained in the pollution control sector. It also estimates that the rules will lead to 5,950 ongoing net job-years gained due to various changes in other sectors (3,890 job-years gained due to demand for pollution


 of the Pittsburgh region’s nonattainment status on establishments, employment, and output in pollution-intensive industries.
Analysis of Key Health Endpoints
We estimated the effects that reducing PM2.5 and ozone concentrations in the Pitts- burgh M


s on EPA’s selection of epidemiological studies available in BenMAP.
2 Specifically, Monte Carlo simulation methods were used—5,000 draws were specified where, at each iteration, a value was chosen at random from the distribution of results and used


at reductions in PM2.5 are associated with approximately 13,000 to 15,000 fewer WLDs per year. Given a median wage rate of $131.60 per day for the Pittsburgh MSA, this translates into a value between $1.7 mil- lion and $1.9 million per year.
For ozon


ool-Loss Days: Public School Medical Leave and Sickness Incidence Rate
   Background Level (ppb)
40 20 40 20
Number
4,301 6,688 4,310 6,694
Standard
Deviation Amount
Standard Deviation
Hourly Background Level (ppb)
0
0 40 20
SLDs Avoided (baseline SL


 10-percent level. The effect of being out of attainment for TSP is 2.4 percent lower employment in pollution-intensive industries, but the result is not statistically significant.
The “Employment in Relevant Industries in the Pittsburgh MSA” column


n.
Table 4.8 presents results for output. Greenstone’s estimated percentage change
in output associated with nonattainment status for each pollutant is shown in the first “Value” column, with associated 90-percent confidence intervals in the first “9


fect”) by employment in Pittsburgh (“Value of Shipments in Relevant Industries in the Pittsburgh MSA”). The second “90% Con- fidence Interval” column presents the 90-percent confidence intervals associated with these extrapolations. Being designated


ociated with a value of approximately $128 million. These values are driven primarily by reduced premature mortality.
We then performed a more detailed examination of the value associated with two health endpoints that may be particularly salient for


ations, and others interested in air quality and local growth in the Pittsburgh region and elsewhere.
Our findings suggest that local policymakers and others concerned with improv- ing air quality in Pittsburgh may find it worthwhile to consider seve


mic Growth: Implications for Pittsburgh
               Literature on Work-Loss Days
Table A.1
Main Findings
Main Methods, of Evidence Assumptions, and Types
Key Outcome
Regulation Key Pollutant or
Study Date and Location
Author and Year Published
Req


scertainment through potential sources sensitivity analyses of bias, such as
School absenteeism
2 10 Ozone, NO , PM
1996, California
Gilliland et al., 2001
  54 Links Between Air Quality and Economic Growth: Implications for Pittsburgh
  Main Finding


 of Evidence Assumptions, and Types
Key Outcome
Regulation Key Pollutant or
Study Date and Location
Author and Year Published
but higher attendance at recreational site. Higher attendance at one site associated with lower concentrations are Higher ox


outdoor facilities Attendance at three
Smog alerts for ozone
1989–1997, California
Neidell, 2006
higher life satisfaction concentrations are associated with measures. Longitudinal regression Lower NO and lead and time fixed effects of life satisfacti


ittsburgh
  Main Findings
Main Methods, of Evidence Assumptions, and Types
Key Outcome
Regulation Key Pollutant or
Study Date and Location
Table A.4—Continued Author and Year Published
respondents; “important to plant operation” by 30% of respondents


n Air Quality and Economic Growth: Implications for Pittsburgh
        Literature on Air Quality Regulations and Firm Location Decisions
Table A.5
Main Findings
Main Methods, of Evidence Assumptions, and Types
Key Outcome
Regulation Key Pollutant or


.5—Continued
Number of new plants in pollution-intensive industries
Nonattainment status for ozone
State 1980–1990, New York
Fredriksson, et al., 2003 List, Millimet,
Plant modifications and closures
Nonattainment status for ozone
State 1980–1990, Ne


d $19.9 billion in 2000, is estimated to be 2006 dollars).
Estimated direct costs using a combination measures and least- cost optimization of per-unit cost measures
the 1990 Clean Air Act Direct cost estimates of compliance with Amendments
2 10 VOC,


s Research and development
Environmental expenditures compliance
1974–1991, United States
Jaffe and Palmer, 1997
environmental regulations the productivity slowdown accounted for 8–16% of to productivity, of the 1970s. With respect
manufacturing firm


penditures. Controls employment on air of manufacturing Panel regression pollution abatement and fixed effects earnings and
employment in an MSA Manufacturing earnings and
expenditures in an Air pollution abatement MSA
1974–1982, United States
Duffy-


th firms, community organizations, government agencies, and other local stakeholders to understand how Allegheny County’s air quality, or its nonattainment status, might affect the decisions that firms and individuals make, for example, with respect


ision? Did air quality directly, or environmental regulations to achieve better air quality, play any role?
Day-to-Day Operations and Employment
We would also like to discuss the extent to which air quality may affect firms’ day-to- day operations or


buy a home? If so, are there specific types of residents who are most concerned about air quality issues?
Do new residents with children ever express concerns about the effect of air qual- ity on child health, school absences, or other issues?
What a


C
Site Selection Process
 This appendix summarizes our discussions with site selection firms regarding the pro- cess they use to help firms select new sites.
Overview of the Site Selection Process
The firms we interviewed indicated that they often be


inment areas, particularly those that are considered “severe” nonattainment areas or those that are not working to address their air quality issues. The decision would be for strategic reasons (for example, because of reputational issues for the com-


centered not on additional costs but rather on the increased length of time and uncertainty surrounding permitting and offset issues.1
Our discussions with site selection firms indicated that the screening process is affected by many factors, particu


” Journal of Environmental Economics and Management, Vol. 58, No. 1, July 2009, pp. 1–14.
Becker, Randy A., “Air Pollution Abatement Costs Under the Clean Air Act: Evidence from the PACE Survey,” Journal of Environmental Economics and Management, Vol


hael K., and Henry Solomon, “Air Pollution and Recreational Behavior,” Journal of Social Psychology, Vol. 100, No. 1, 1976, pp. 149–150.
Chay, Kenneth Y., and Michael Greenstone, “Does Air Quality Matter? Evidence from the Housing Market,” Journal of


n Economic Review, Vol. 102, No. 7, December 2012, pp. 3652–3673.
Gray, Wayne B., and Ronald J. Shadbegian, Pollution Abatement Costs, Regulation, and Plant-Level Productivity, Cambridge, Mass.: National Bureau of Economic Research Working Paper 4994


dam B., and Karen Palmer, “Environmental Regulation and Innovation: A Panel Data Study,” Review of Economics and Statistics, Vol. 79, No. 4, November 1997, pp. 610–619.
Jaffe, Adam B., Steven R. Peterson, Paul R. Portney, and Robert N. Stavins, “Envi


y Using the Life Satisfaction Approach,” Economic Journal, Vol. 119, No. 536, March 2009, pp. 482–515.
———, “Life Satisfaction and Transboundary Air Pollution,” Economics Letters, Vol. 107, No. 1, April 2010, pp. 4–6.
Malecki, Edward J., and Susan L.


the Medical Sciences, Vol. 321, No. 3, April 2001, pp. 178–180.
Neuzil, Kathleen M., Cynthia Hohlbein, and Yuwei Zhu, “Illness Among Schoolchildren During Influenza Season: Effect on School Absenteeism, Parental Absenteeism from Work, and Secondary I


n of the Environment- Competitiveness Relationship,” Journal of Economic Perspectives, Vol. 9, No. 4, 1995, pp. 97–118.
Public Law 88-206, Clean Air Act, December 17, 1963. As of November 5, 2013: http://w w w.gpo.gov/fdsys/pkg/STATUTE-77/pdf/STATUTE


cbp/
———, “American FactFinder,” undated; referenced November 2012c. As of November 5, 2013: http://factfinder2.census.gov/
———, “North American Industry Classification System: Concordances,” last revised September 13, 2013; referenced August 2, 2013


 July 31, 2013d. As of November 6, 2013:
http://www.epa.gov/airquality/greenbook/
———, “About Air Toxics,” last updated August 8, 2013e. As of November 13, 2013: http://www.epa.gov/ttn/atw/allabout.html
———, “Design Values in Areas Previously Designa


n and $488 million, respectively. Although regulated industries do face costs associated with improving air quality, meeting the NAAQS can make it easier for businesses in regulated industries to locate and operate in the Pittsburgh region in the lon


  CHILDREN AND FAMILIES EDUCATION AND THE ARTS ENERGY AND ENVIRONMENT HEALTH AND HEALTH CARE INFRASTRUCTURE AND
TRANSPORTATION INTERNATIONAL AFFAIRS LAW AND BUSINESS NATIONAL SECURITY POPULATION AND AGING PUBLIC SAFETY SCIENCE AND TECHNOLOGY
TERRORIS


w.rand.org/publications/permissions.html).
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www.rand.org
 Preface
 In 2000, the California state legisla


 Report, Santa Monica, Calif.: RAND Corpora- tion, TR-832-LACPD, September 2010b
iii
iv
Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2011–2012 Report
• Terry Fain, Susan Turner, and Greg Ridgeway, Los Angeles County Juvenile


nced Services to High-Risk/High-Need Youth. . . . . . The Youth Substance Abuse Intervention Program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gender-SpecificCommunityProgram...........


 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......
E. Board of State and Community Corrections–Mandated and Supplemental
Outcomes for Individual JJCPA Programs, FY 20


Chronic Truancy, FY 2011–2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
E.12. Outcomes for After-School Enrichment and Supervision, FY 2011–2012. . . . . . . . . . . . . . . . 111
E.13. Outcomes for Housing-Based Day S


rd of State and Community Corrections (BSCC), formerly called the Corrections Standards Authority (CSA), formed in July 2005 by merging the BOC and the Commission on Peace Officer Stan- dards and Training (CPOST). BSCC is required to submit annual re


no appropriate comparison group could be identified, a pre/post measurement design was used. Generally, outcomes for program participants are measured for a six-month period after starting the program (for community programs) or after release into th


ram youth and those not accepted into the program but deemed comparable to program youth, are weak designs, and such comparisons should be interpreted with this weakness in mind. In particular, pre/ post comparisons for probation-related outcomes, su


luding Young Women at Risk)
High Risk/High Need Youth
Enhanced School- and Community-Based Services
School-Based Probation Supervision for Probationers and At-Risk Youth
Abolish Chronic Truancy
After-School Enrichment and Supervision Housing-Based Da


comparison 5,038 Pre/post comparison 869 Pre/post comparison 60
FY 2010–2011 IOW 1,400 participants
 NOTE: The number of participants in a given program is determined by who received services during the fiscal year, which goes from July 1, 2011, to J


AR and SBMS-AR cohorts had no sig- nificant differences in rates of arrest or incarceration. The FY 2011–2012 cohort of HRHN participants had significantly higher rates of completion of probation, completion of restitu- tion, and completion of commun


re not comparable, then a difference-in-differences analysis is more informative than a simple comparison between the two cohorts.
Out of 34 outcomes for the seven programs that used the prior year’s cohort as a compari- son group (six outcomes for G


gibility period mandated for big six outcomes, the number of program youth matches the number used to report outcomes to BSCC, not the total number served during the fiscal year.
Summary xxi
 xxii Los Angeles County Juvenile Justice Crime Prevention


h initiative, which targets a large number of at-risk youth, saw the bulk of its expenses in program costs, whereas costs for juvenile hall, camp, and court were lower in the six months after entering the program, with camp costs averaging $6,073 les


m youth had data available for supplementary measures, calling into question the appropriateness of any findings based on such a small subsample. RAND will continue to work with Probation to increase the amount of data available for supplemental outc


 Assessment of Functioning
GED General Educational Development Test
xxix
xxx Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2011–2012 Report
GIS Gang Intervention Services
GSCOMM Gender-Specific Community
HB Housing-Based Day S


 services, drug and alcohol abuse treatment, and youth service resources in a collaborative manner, using information sharing to coordinate strategy and provide data for measuring program success (AB 1913, 2000).
JJCPA provided funds to counties to a


change of adult and juvenile probationers. In FY 2011–2012, the state allocated approximately $23.7 million to Los Angeles County for JJCPA programs and services. JJCPA funding represents roughly 15 per- cent of field expenditures for juvenile justi


, evaluations are often done using quasi-experimental designs, in which a comparison group is chosen to match the characteristics of the treatment group as closely as possible.
Clearly, the more similar comparison groups are to their program groups,


program youth and those not accepted into the program but deemed comparable to program youth, are weak designs, and results from such comparisons should be interpreted with this weakness in mind. In particular, pre/post comparisons for probation-rela


lly consisted of youth who otherwise qualified for the program but were not accepted because of language difficulties or lack of Medicaid coverage needed to cover the cost of program participation. SNC near misses failed to qualify for inclusion in S


would be for no program youth to be arrested, incarcerated, or in viola- tion of probation and for all to complete probation and (if applicable) community service and restitution. However, because, for most JJCPA programs, the big six outcomes are me


ental Health Services initiative, in recogni- tion of the fact that most SNC participants have significant mental health issues. This move of SNC from one initiative to another was simply a reorganization and does not imply any change within the SNC


onclude that the current year’s cohort had a more favorable outcome (i.e., improved more), while an upper bound of the CI less than 1 indicates a less favorable outcome (i.e., improved less).
A difference-in-differences analysis for each big six outc


r families (AB 1913, 2000). Although BSCC does not require details about the characteristics of JJCPA participants, many participants are fairly high risk because the program specifically targets youth who live or attend school in 85 high-risk areas


ased Probation Supervision for Probationers and At-Risk Youth SBHS-PROB
SBMS-PROB SBHS-AR SBMS-AR
Abolish Chronic Truancy ACT After-School Enrichment and Supervision PARKS Housing-Based Day Supervision HB Inside-Out Writers IOW
Total
Participants
8,5


oups for SBHS-PROB and SBMS-PROB were statistically matched to program participants. Outcomes for MH were reported only for youth who received treatment.
mental health issues were addressed in Los Angeles County in FY 2011–2012 by three pro- grams wi


eferred for a more comprehensive assessment.
In addition to providing screening, assessment, and treatment services for newly detained youth entering juvenile hall, MH is designed to provide a therapeutic environment with inten- sive mental health an


).
Comparison Group and Reference Period
Although everyone who enters a juvenile hall is tested, only a subset—typically 20 to 25 percent—require mental health treatment. In FY 2008–2009, we were able, for the first time, to identify individuals who


seline and follow-up means, the odds ratio of the interaction term year × post in the logistic regression, and 95-percent CI for the odds ratio. These results differ from the findings of a simple comparison in incar- ceration rates, for which the FY


designated and staffed to super- vise juvenile offenders who suffer from diagnosed axis I (serious) mental illness, organic brain impairment, or developmental disabilities. The Juvenile Mental Health Court processes its cases under the guidelines of


at 50 to 65 percent of drug court graduates stopped using drugs (NIJ, 1995). According to DOJ, “[t]he drug court innovation set the stage for other special court approaches, including mental health courts, by providing a model for active judicial pro


arily because their cases were not deemed sufficiently “serious.” SNC and comparison-group youth showed roughly comparable demographic distributions, as indi- cated in Table 2.5. None of the differences between the two groups was statistically signif


s the key set- tings, or systems, within which youth are embedded. MST strives to promote behavior change in a youth’s natural environment, using the strengths of each system (e.g., family, peers, school, neighborhood, indigenous support network) to


epartment staff, and RAND staff. A large majority (69.1 percent) of MST program youth were Hispanic. For the compari- son group, we have no data on race and ethnicity. The two groups had similar gender distri- butions, with males making up 77.2 perce


 compared with the six months before entering the program.
The difference-in-differences analyses for MH agreed with the results of a simple compar- ison between the two cohorts, with two exceptions: (1) incarcerations, for which the FY 2010– 2011 co


 22 Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2011–2012 Report
provider within the first 36 hours following release from the camp facility. If the assessment indicates the need for treatment, the substance abuse treatment


he goal of performing at least as well in the current year as in the previ- ous year. Big six outcomes for both program and comparison groups were measured for the six months following program entry.
Supplemental outcomes for this program were measur


use Outcomes
   Mean: Current Year (%)
Mean: Previous Year (%)
  Outcome Baseline
Arrest 37.78
Incarceration 7.10
Completion 1.31 of probation
Completion 15.17 of restitution
Completion 0.55 of community
service
Probation 7.87 violation
Follow-Up
22.


, have grown up in poverty, were victims of neglect or abuse (emotional, physical, or sexual), or have grown up in neighborhoods with high crime rates.
The outcomes for this program are based on pre- and posttest comparisons. The program goals are
•


e for girls to talk and to conduct emotionally safe, comforting, challenging, nurturing conversations within ongoing relationships
• opportunities for girls to develop relationships of trust and interdependence with other women already present in the


tio of the interaction term year × post in the logistic regression, and 95-percent CI for the odds ratio. We were unable to compare the two groups for completion of commu- nity service because the baseline for both cohorts was 0. For all other big si


e modeling by adults in the probationer’s social environment.
The HRHN program consists of two components: a home-based component and a job- based component. A given individual may receive services from either component or from both. As the program n


ved by helping professionals as not motivated to change.
• MTFC. MTFC provides adolescents who are seriously delinquent and in need of out- of-home foster care with close supervision, fair and consistent limits, predictable con- sequences for rule br


sanctioning schemes. At the same time, the model points to a need to reinforce the youth’s progress consistently via a graduated system of meaningful rewards.
– creation of links with community resources and social networks. This element of case mana


ased component, scores on a scale measuring family relations were measured at program entry and six months later or upon program exit, whichever came first.
Outcomes
For outcome analyses, we examined 1,779 HRHN participants from FY 2011–2012 and 2,18


hat the FY 2011–
32 Los Angeles County Juvenile Justice Crime Prevention Act: Fiscal Year 2011–2012 Report
Figure 2.6
High Risk/High Need Outcomes, FY 2011–2012
 NOTE: A star indicates a statistically significant difference (p < 0.05) between the two