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Resilience Dividend

Valuation Model

Framework Development and Initial Case Studies

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Preface

Policymakers, program practitioners, and inv_{estors who want to achie}v_{e the greatest possible}

beneits from the resilience projects that they support lack efectiv_{e tools to estimate the net}

beneits of those projects. In large part, howev_{er, quantiication of the net beneits from}

increas-ing system resilience has largely relied on indices or scorecards, in which v_{arious indicators}

assumed to be correlated with resilience are measured and possibly aggregated. While useful if

v_{alidated, these indices do not pro}v_{ide information about the}_value_{of resilience in}v_estments,

which is needed if decisionmakers striv_{e to made e}v_{idence-based choices consistent with}

maxi-mizing ov_{erall social welfare.}T_{o date, howe}v_{er, there has been little research into approaches to}

do so, perhaps due to the complexity of systems, the multitude of potential short- and long-term beneits that might arise from a resilience project or portfolio, and problems of measurability.

Motiv_{ated by a desire to pro}v_{ide more structure for thinking about the beneits and costs of}

projects dev_{eloped with a resilience lens, the RAND Corporation and the Rockefeller}

Foun-dation formed a partnership to dev_{elop a modeling framework that can be used in a decision}

analysis env_{ironment. In particular, we sought to de}v_{elop a model that could be used to e}v

alu-ate resilience outcomes by quantifying the resilien_{ce divide}n_d_{, deined herein as the diference} in net beneits between outcomes resulting from a resilience project v_{ersus business as usual}

(e.g., no project at all). he resultant conceptual modeling framework is the Resilience Div

i-dend Valuation Model (RDVM).

his report describes the RDVM and its application to six case studies selected jointly by RAND and the Rockefeller Foundation. It is intended for use by practitioners, analysts, and researchers to understand how to conceptualize particular systems and interv_{entions in a}

struc-tural economic framework, and to use this information to plan data collection and modeling eforts that can be used to estimate parts of the resilience div_idend.

his research complements much of the past and ongoing research in RAND’s Infrastructure Resilience and Env_{ironmental Policy program, including research on coastal resilience,}

emer-gency preparedness, infrastructure, and economic recov_{ery. Interested readers are referred to}

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RAND Infrastructure Resilience and Environmental Policy

he research reported here was conducted in the RAND Infrastructure Resilience and

Env_{ironmental Policy program, which performs analyses on urbanization and other stresses.}

his includes research on infrastructure dev_{elopment; infrastructure inancing; energy policy;}

urban planning and the role of public–priv_{ate partnerships; transportation policy; climate}

response, mitigation, and adaptation; env_{ironmental sustainability; and water resource}

management and coastal protection. Program research is supported by gov_{ernment agencies,}

foundations, and the priv_{ate sector.}

his program is part of RAND Justice, Infrastructure, and Env_{ironment, a di}v_{ision of the}

RAND Corporation dedicated to improv_{ing policy and decision making in a wide range of}

policy domains, including civ_{il and criminal justice, infrastructure protection and homeland}

security, transportation and energy policy, and env_{ironmental and natural resource policy.}

Questions or comments about this report should be sent to the co-project leaders, Craig Bond (Craig_Bond@rand.org) or Aaron Strong (Aaron_Strong@rand.org). For more information

about RAND Infrastructure Resilience and Env_{ironmental Policy, see www.rand.org/jie/irep}

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ADB–Bangladesh Interv_{ention Background ...1}3₀ Applying the Resilience Div_{idend Model to Establish a Di}v_{idend for} ADB’s Bangladesh Project ...13₀ Aspects of the Resilience Div_{idend ...1}33 Empirical Methods ...13₄ Data ...13₅ Conclusions and Lessons Learned ...13₇ CHAPTER 5 he Resilience Dividend Valuation Model: Lessons Learned and Next Steps ...13₉ Lessons Learned about Quantifying the Div_{idend ...1}3₉ Lessons Learned about the Role of Behav_{ior ... 141}

Lessons Learned about Data and Ev_{idence ...14}3 Lessons Learned about Model Limitations ... 145

Conclusions and Further Research ...146

Appendix A. Characteristics of Resilient Systems and the Allocation Mechanism ... 149

Appendix B. Key Deinitions Used in this Report ... 151

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Figures

Figure 2.1. City Resilience Framework ...10

Figure 2.2. Norris et al. (2008) Deinition of Resilience ...12

Figure 2.3_{. Rose (1999) Framework ...14}

Figure 2.4. Francis and Bekera (2014) Framework ... 15

Figure 2.5. Bruneau et al. (2003_{) Framework ...17}

Figure 2.6. Bruneau et al. (2003_{) Framework ...17}

Figure 3_{.1. Schematic of a Dynamic System Based on Inclusi}v_{e Wealth ...2}3 Figure 3_{.2. Changes in Outcomes due to Changes in the Allocation Mechanism...28}

Figure 3_.3_{. Valuing a Project with Co-Beneits and a Single Shock...}3₆ Figure 4.1. Mapping of the Nepal System ...46

Figure 4.2. Changes in Outcomes Due to Changes in the Allocation Mechanism ...49

Figure 4.3_{. Notional Absorption, Reco}v_{ery, and Co-Beneits from the Inter}v_{ention ...50}

Figure 4.4. Mapping of the Pakistan System ...65

Figure 4.5. Conceptualization of Dev_{elopment Process with Inter}v_{ention and Without Shock ...70}

Figure 4.6. Conceptualization of Recov_{ery Capacity Estimation ...72}

Figure 4.7. 2016 Annual Allocated Water Rights v_{s. Estimated Consumpti}v_{e Use} v_{s. Perennial Yield ...80}

Figure 4.8. Mapping of the Basic Diamond Valley System ...82

Figure 4.9. Estimated Resilience Div_{idend from Agricultural Production, Net Present Value,} 3_0-YearT_{ime Horizon ...88}

Figure 4.10. Distribution of Estimated Resilience Div_{idend from Agricultural Production for} Rightholder Groups, Net Present Value, 3_0-YearT_{ime Horizon...89}

Figure 4.11. Acres and number of wildires since 1960 ...98

Figure 4.12. Mapping a Forest Ecosystem ...100

Figure 4.13_{. Mapping of the Resilience System ... 119}

Figure 4.14. Notional Absorption, Recov_{ery, and Co-Beneits from the Inter}v_{ention ...121}

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Tables

T_{able 2.1. Sample Deinitions of Resilience at Diferent Le}v_{els of Analysis ...7}

T_{able 4.1. Summary of Analyzed Cases ...40}

T_{able 4.2. Basic Case Information for Oxfam Nepal Case ...44}

T_{able 4.}3_{. E}v_{idence for a Resilience Di}v_{idend in Nepal ...44}

T_{able 4.4. Impact of Beha}v_{ioral Actions on Crop Loss ...54}

T_{able 4.5. Increased Probability of Action Following Early Warning Relati}v_{e to BAU ...55}

T_{able 4.6. Diferences in Assets Between Inter}v_{ention and BAU Households ...57}

T_{able 4.7. A}v_{erage Increase in Probability of Adopting New Agricultural Practices} from Interv_{ention ...58}

T_{able 4.8. Basic Case Information for Oxfam Pakistan ...62}

T_{able 4.9. Impact of Practices on Virtual Crop Income ...7}3 T_{able 4.10. Increase in Probability of Adoption of Process by Inter}v_ention Compared to Non-Interv_{ention ...74}

T_{able 4.11. Basic Case Information for Diamond Valley ...78}

T_{able 4.12. Quantitati}v_{e and Qualitati}v_{e Estimates of the Resilience Di}v_{idend in} Diamond Valley by Rightholder Group, 3_{0-Year Horizon ...79}

T_{able 4.1}3_{. Major Assumptions of Baseline and Project Scenarios ...87}

T_{able 4.14. Basic Case Information for Forest Bond Case ...97}

T_{able 4.15. Estimated Annual Partial Resilience Di}v_{idend ...97}

T_{able 4.16. Relationship between Forest Structure and Snowpack ...105}

T_{able 4.17. Relationship Between Forest Structure and Runof ...105}

T_{able 4.18. Runof by Restoration and Fire in Conklin}_{et al.}_{(2015) ...106}

T_{able 4.19. Other Studies hat Estimate the Relationship Between Restoration and Runof ...107}

T_{able 4.20. Value of Water Runof for Consumption ...108}

T_{able 4.21. Value of Water Runof for Hydroelectric Power ...108}

T_{able 4.22. Summary of Resilience Di}v_{idend ... 111}

T_{able 4.2}3_{. Basic Case Information for ISE}T_{Da Nang Vietnam ... 114}

T_{able 4.24. E}v_{idence for a Resilience Di}v_{idend in Da Nang, Vietnam ... 115}

T_{able 4.25. ISE}T_Pre-interv_{ention questions to consider for inclusion in post-inter}v_ention data collection—mapped to the conceptual model. ...123 T_{able 4.26. Basic Case Information for ADB Bangladesh Case ...129}

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Summary

Policymakers, program practitioners, and inv_{estors who want to achie}v_{e the greatest possible}

beneits from the resilience projects that they support lack efectiv_{e tools to estimate the net}

beneits of those projects. Current approaches tend to focus on resilience indices or scorecards, which often compile indicators that are assumed to relect the ability of a community (or, more broadly, a “system”) to absorb or recov_{er from a shock or stressor. While useful if}v_{alidated, this}

approach does not prov_{ide a framework for}v_{aluing the net beneits of a purposeful inter}v

en-tion—or any beneits that might accrue from a project aimed at increasing resilience ev_{en if a}

shock does not occur.

he RAND Corporation and the Rockefeller Foundation formed a partnership to dev_{elop a}

modeling framework that can be used to estimate the net beneits, whether positiv_{e or}

nega-tiv_{e, of a resilience project. We call the framework the Resilience Di}v_{idend Valuation Model}

(RDVM), and use the term resilien_{ce divide}n_d_{to describe the net beneits. he resilience di}v

i-dend includes net beneits associated with the absorption of shocks and stressors, the recov_ery

path following a shock, and any co-beneits that accrue from a project ev_{en in the absence of a}

shock. For any giv_{en project, the estimated di}v_{idend may be positi}v_{e or negati}v_e.

he RDVM described in this report is designed to prov_{ide a systematic, “structural”}

frame-work for assessing resilience interv_{entions that ultimately create beneits and costs within a}

system such as a community or city. he model is a means to systemically account for the returns to resilience inv_{estments across a}v_{ariety of contexts.}

About the Resilience Dividend Valuation Model

he RDVM is a modeling framework designed to help analysts and practitioners estimate the realized or potential resilience div_{idend from a project. he RDVM combines elements of}

proj-ect ev_{aluation and economic}v_{aluation, and can be used to guide thinking about the probable}

outcomes of resilience inv_{estments and how}v_{aluable these outcomes might be to stakeholders}

that operate within the system. he objectiv_{e of building and applying this model is to}

estab-lish a theoretical and empirical basis for estimating the resilience div_{idend o}v_{er a range of}

proj-ects, settings, and scales. he RDVM will be most useful in settings where there is an existing or potential resilience inv_{estment within a complex system and for which data exist or can be}

collected for critical components of that system. he approach is also relev_{ant e}v_{en if data do}

not exist or cannot be collected, since it can help stakeholders structure their thinking about how the inv_{estment will or will not contribute to resilience.}

he RDVM is based on the theory of inclusiv_{e wealth, which represents the (net present)}v_alue

of a system deriv_{ed from the contributions of capital assets to society’s well-being. he RDVM}

takes adv_{antage of this underlying intuition and conceptual structure, which assume that}

capi-tal stocks (human labor or man-made capicapi-tal) combine with technology (methods and tools)

to produce lows of goods and serv_{ices. he consumption of goods and ser}v_{ices contributes}

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improv_{ing quality of life, among other beneits. he theory also takes into account (through}

what is called an allocation mechanism) how humans respond to changes in capital stocks or the broader system.

he RDVM applies these concepts to create a framework for v_{aluing and monetizing the}

impacts of a resilience project (or potential resilience project) compared to a business as usual (BAU)scenario in which the project does not take place.1_{he diference between the two is the}

resilience div_idend.

his structure can be used to illustrate the causal relationships among key system elements like capital stocks, the goods and serv_{ices that they are used to produce, and the beha}v_{ior of actors}

within the system. his mapping of relationships can be used to generate hypotheses about system relationships that, giv_{en the right data, might be tested for any gi}v_{en project, or used to}

create simulation models that can represent the system going forward into the future.

he RDVM is a lexible approach that helps users think about interv_{entions in a structured,}

systems-focused way, and it guides users in how to use data to prov_{ide e}v_{idence of the di}v

i-dend. In real-world settings with limited data, the RDVM may only be useful in quantifying a

partial resilience div_{idend, especially when some goods and ser}v_{ices that are afected by a}

proj-ect cannot be measured, the relationships between capital stocks may not be well understood, or people’s response to the project may be uncertain. Furthermore, if a project is expected to create beneits or costs that persist into the future, a full accounting of the div_{idend may not be}

possible. In general, howev_{er, the better a system can be characterized and measured, the more}

fully can the resilience div_{idend be estimated.}

Model Advantages and Disadvantages

he broad adv_{antages of RDVM o}v_{er other models include}

• an explicit link to project-related resilience beneits

• a focus on identifying and measuring changed behav_iors

• the guidance it prov_{ides in terms of modeling, data collection, and estimation.}

Howev_{er, the RDVM also has some limitations:}

• he approach is more complex than more traditional ev_{aluation and monitoring approaches.}

• he data needed to quantify the resilience div_{idend are extensi}v_e.

• Some stakeholders may be uncomfortable with the underlying assumptions of the model.

he primary reason for the complexity of the model is that resilience is an inherent property of complex systems that ev_olv_{e o}v_{er time. his introduces the need to e}v_{aluate outcomes o}v_er

time and to measure or model changes in behav_{ior that contribute to those outcomes. he}

RDVM thus prov_{ides an organizational structure to think about the likely logical chain from}

interv_{ention to outcomes o}v_{er time. As with all models, practitioners may opt to trade of}

model complexity with comprehensiv_{eness, and estimate a partial resilience di}v_idend.

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Application of the RDVM to Resilience Case Studies

Ov_{er the course of the six-month project in which the model was de}v_{eloped, RAND applied}

the model to v_{arious case studies in Bangladesh, Nepal, Pakistan, Vietnam, and the United}

States, using pre-existing data, project designs, and models not necessarily designed for use

with the RDVM. hese cases were selected jointly with the sponsor and an adv_{isory committee}

to span the Rockefeller Foundation’s div_{erse resilience portfolio, and not necessarily because}

the project and/or av_{ailable data were ideally suited for the RDVM. hrough the course of this}

exercise, we learned a number of lessons about the use of the model ov_{er a}v_{ariety of archetypes,}

the data structures that can best suit quantiication of the div_{idend, the importance of beha}v_ior

in generating a resilience div_{idend, and the limitations of the model. While we belie}v_{e that the}

inclusiv_{e wealth conceptualization of systems for e}v_{aluating resilience projects is a promising}

way forward, the need to generate and use extensiv_{e quantities of data in complex ways does}

prov_{ide some barriers to adoption.}

As might be expected from the dev_{elopment of a new approach to tackle a complex problem,}

our results are mixed. We maintain that the theoretical underpinnings of the RDVM (and in particular, the relationships inherent in an inclusiv_{e wealth modeling approach) are}v_aluable

in clearly and explicitly representing the expected causal pathways from project interv_{ention to}

changes in social welfare, but we are aware of the signiicant empirical challenges (not the least of which is data intensity) in applying the model.

Future Research

Looking forward, there is considerable opportunity for more research into the quantiication of the resilience div_{idend. A key irst step stemming directly from one of our lessons learned}

is to jointly design the data collection mechanism and RDVM for a number of well-funded archetypal cases at the outset of a project or program to begin to build more intuition about the art of the possible in resilience ev_{aluation (and the tradeofs in terms of costs). Building on}

this work with subsequent cases and projects can help to create a portfolio of ev_{idence about}

the resilience div_{idend, and to de}v_{elop best practices for empirical strategies, simulation}

mod-eling, and data collection.

Of particular interest is research into understanding and quantifying the behav_ioral

implica-tions of changing instituimplica-tions, social norms, and social relaimplica-tions (social capital), and how these elements relate to the resilience div_{idend both indi}v_{idually and together. his is no small task}

and will require multi-disciplinary inv_{estigations into any number of cases, as well as creati}v_e

empirical and data collection strategies.

Cataloguing this information in an easily accessible, public manner is also needed. he env

i-ronmental and ecosystem serv_{ice communities ha}v_{e done this with regard to en}v_ironmental

non-market v_{alues, pro}v_{iding opportunities for researchers and practitioners to share}

informa-tion, use a methodological technique known as beneit transfer, and perform meta-analysis ov_{er multiple studies to gain insight into diferences in}v_{alues across contexts. Because e}v_ery

system is diferent, research into this aspect of v_{ariation in the resilience di}v_{idend could be}

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he case studies used to this point hav_{e focused on speciic projects. Mo}v_{ing away from}

proj-ects and toward portfolio design will allow for better understanding of the complementar-ity and substitutabilcomplementar-ity of diferent projects. Additionally, knowing the winners and losers of speciic projects will allow for the construction of portfolios that can, potentially, make all stakeholders winners with the appropriate choices of projects with portfolios. he budget constraints that arise in portfolio analysis prov_{ide additional limitations that this approach is}

designed to handle.

Organization of this Report

his report compiles the results of sev_{eral outputs prepared at the request of the Rockefeller}

Foundation; namely, a rev_{iew of pre-existing resilience frameworks in the literature, a}

descrip-tion of how the RDVM and the inclusiv_{e wealth framework can be used to characterize}

sys-tems, resilience interv_{entions, and, ultimately, the resilience di}v_{idend, and se}v_{eral case studies}

that were used to illustrate v_{arious aspects of the approach. In this report, we ha}v_{e generally}

compiled each of these outputs as a separate chapter.

Chapter 2 prov_{ides some background information on the deinitions and foundations of}

resil-ience, and rev_iewsv_{arious resilience frameworks. Chapter}3_{presents the RDVM, including}

a brief discussion of the theory or inclusiv_{e wealth and the elements of the model. Chapter 4}

reports the results of the case studies analyzed as part of the research project. For each case, we applied the principles of the RDVM and attempted to quantify as many of the elements of the resilience div_{idend as possible gi}v_{en the data and project documentation a}v_{ailable. Chapter 5}

reports the ov_{erall lessons learned about the RDVM from the case studies and our experience}

ov_{er the course of the project and conclusions. For the con}v_{enience of the reader, a discussion}

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Acknowledgments

We thank Dr. Judith Rodin and Dr. Zia Khan of the Rockefeller Foundation for their ov_erall

support of the project. Sundaa Bridgett-Jones and Carol T_{an of the Rockefeller Foundation}

were instrumental in prov_{iding day-to-day support and feedback on the research. We would}

also like to thank the other Rockefeller Foundation personnel who met with us and prov_ided

critical information on their projects and activ_{ities, including Alex Martinez, Fred Boltz, and}

Adam Connaker. Leah Hershey at RAND prov_{ided in}v_{aluable administrati}v_{e support.}

Our adv_{isory panel, consisting of Claire Hutchings (Oxfam Great Britain), Dr. Edward Barbier}

(Univ_{ersity of Wyoming), Colin McQuistan (Practical Action), and Dr. Pankaj Lal}

(Mont-clair State Univ_{ersity), pro}v_{ided excellent guidance and research o}v_{er the course of the project,}

including formal comments on our written products.

We would also like to thank the Rockefeller Foundation project partners at Oxfam, the Asian

Cities Climate Change Resilience Network (ACCCRN), ISET_{(Vietnam), Sierra Ne}v_ada

Adaptiv_{e Management Project, and Blue Forest Conser}v_{ation. In particular, Phong}T_{ran at}

ISET_{; Simone Lombardini and Rob Fuller at Oxfam; Nick Wobbrock at Blue Forest}

Con-serv_{ation; Sasank Vemuri and Elma Morsheda at the Asian De}v_{elopment Bank; Phil Saksa}

at Sierra Nev_{ada Adapti}v_{e Management Project; Michael Young at the Uni}v_{ersity of}

Ade-laide and Nicholas Institute for Env_{ironmental Policy Solutions at Duke Uni}v_{ersity; and Greg}

Characklis at the Univ_{ersity of North Carolina and Chapel Hill pro}v_{ided information and}

data that were critical to the research.

Our peer rev_{iewer, Dr. Radha Iyengar, pro}v_{ided helpful comments on the manuscript that}

greatly improv_{ed its clarity.}

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Abbreviations

ADB Asian Dev_{elopment Bank}

ATT _av_{erage treatment efect on the treated}

BAU business as usual

BCA beneit cost analysis

BEEJ Balochistan Env_{ironmental and Educational Journey}

CMA critical management area

GMP groundwater management plan

ISET _{Institute for Social and En}v_ironmentalT_{ransition-Vietnam}

NGO non-gov_{ernmental organization}

NSE Nev_{ada State Engineer}

RDVM Resilience Div_{idend Valuation Model}

SAFWCO Sindh Agricultural and Forestry Workers Coordinating Organisation

SPLAT_S _{Strategically Placed Landscape}T_reatments

USFS United States Forest Serv_ice

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CHAPTER 1

Introduction

Communities, cities, states, and countries around the world are often faced with complex decisions about how to mitigate risk and be more resilient in their responses to large political, economic, and env_{ironmental e}v_{ents or stressors. Determining how best to respond to ad}v_erse

ev_{ents is complex and multifaceted; this complexity can result in inefecti}v_{e or suboptimal}

responses that do not maximize the community’s ov_{erall well-being. With such high stakes,}

decisionmakers and practitioners could beneit from decision-support tools that help them compare alternativ_{e courses of action.}

In general, efectiv_{e tools to estimate the net beneits of resilience projects are lacking for}

policymakers, program practitioners, and inv_{estors who want to achie}v_{e the greatest possible}

beneits from the projects that they support. Current approaches tend to focus on resilience indices or scorecards, which often compile indicators that are assumed to relect the ability of a community (or, more broadly, a “system”) to absorb or recov_{er from a shock or stressor. While}

useful if v_{alidated, this approach to shocks does not pro}v_{ide a framework for}v_{aluing the net}

beneits of a purposeful interv_{ention—or any beneits that might accrue from a project aimed}

at increasing resilience ev_{en if a shock does not occur. In addition, many of the scorecards and}

indices assume that the resilience of subsets of a larger system implies resilience of the whole system, which may not necessarily be the case.

Dev_{eloped to help o}v_{ercome these issues, the Resilience Di}v_{idend Valuation Model (RDVM)}

documented in this report is a modeling framework designed to help analysts and practitioners estimate the realized or potential resilience div_{idend from a project. Based on inclusi}v_{e wealth}

theory, the RDVM is a dynamic, systems-based approach that maps changes in the low of

goods and serv_{ices from a resilience project into}_{changes in well-being, and pro}v_{ides guidance}

on the data needed to estimate the resilience div_{idend. he model pro}v_{ides the theoretical and}

empirical basis for estimating the resilience div_{idend o}v_{er a range of projects, settings, and}

scales. RDVM combines elements of project ev_{aluation and economic}v_{aluation, and can be}

used to guide thinking about the probable outcomes of resilience inv_{estments and how}v

alu-able these outcomes might be to the system’s stakeholders.

Background and Motivation of the Research Project

he academic literature has largely v_{iewed the concept of resilience as the study of “how}

com-plex systems self-organize and change ov_{er time.”}1_{Carpenter and Brock}2_{—intellectual leaders}

in deining and analyzing the term—succinctly summarize resilience as a “broad, multifac-eted, and loosely organized cluster of concepts, each one related to some aspect of the interplay of transformation and persistence.” Despite these rather broad notions, most authors appear to recognize resilience as the capacity to withstand and recov_{er from shocks and stressors.}

1 _{Anderies, J., Folke, C., Walker, B., and Ostrom, E. (201}₃_{). “Aligning key concepts for global change policy: Robustness,}

resilience, and sustainability.” Ecology an_{d Society,}₁₈_{(2), 8.}

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As such, our working deinition of resilien_ce_{is the capacity of a system—a household, a} com-munity, an organization, or a coupled natural-human system—to prepare for disruptions from

outside the system, to recov_{er from shocks and stresses, and to adapt to and grow from a}

disruptiv_{e experience. A}_resilien_{ce project}_{is deined as an inter}v_{ention that, at least in part,}

targets improv_{ing the ability to manage, respond to, or reco}v_{er from a shock or stress outside}

of a system that would likely decrease well-being, and that has the potential to produce other beneits not directly related to the shock or stressor. his latter concept—often termed the “co-beneits” associated with the resilience project—is a key part of what distinguishes a resil-ience project from an interv_{ention that focuses solely on disaster risk reduction outcomes. In}

particular, what might be termed a resilien_{ce le}n_s_{is a}v_{iew that approaches project de}v_elopment

and inv_{estment strategies in a way that takes into account the system’s properties and addresses}

both the risk of loss from an outside shock or stressor and any co-beneits the project or inv

est-ment produces.

Howev_{er, as noted by Anderies, et al.:}

he resilience lens is useful for making suggestions about broad categories of inv_estment

such as in the capacity to learn, adapt, and transform without being too speciic about what this actually means in practice, i.e., how much it costs, who pays, who beneits, etc. hus, although resilience thinking prov_{ides heuristics for li}v_{ing in a complex world, its}

system-lev_{el nature limits its utility in concrete decision analysis, at least in its current state of}

dev_elopment.3

Motiv_{ated by a desire to pro}v_{ide more structure for thinking about and characterizing the}

beneits and costs of projects dev_{eloped with a resilience lens, RAND and the Rockefeller}

Foundation formed a partnership to dev_{elop a modeling framework that can help support}

decisionmaking.

The Resilience Dividend

We sought to dev_{elop a model that could be used to e}v_{aluate resilience outcomes by}

quantify-ing the resilien_{ce divide}n_d:_{the diference in outcomes resulting from a resilience project} com-pared to what those outcomes would hav_{e been without the resilience project, a counterfactual}

that we call the business as usual (BAU) scenario (Rodin, 2014).4_{Outcomes are typically}

related to the ability of “people to better withstand disruption in the future, to improv_{e current}

situations, and/or to positiv_{ely change the trajectory of a place and/or people’s li}v_es.”5_{In other}

words, the resilience div_{idend can be deined as the diference in the stream of net beneits}

between a world in which resilience projects are implemented and a counterfactual setting. his counterfactual, which can be deined as either a no-project case or an alternativ_{e project}

that is not dev_{eloped with a resilience lens, pro}v_{ides the baseline against which the project-le}v_el

beneits are compared.

3

Anderies, J., et al. (2013_{). “Aligning key concepts for global change policy: Robustness, resilience, and sustainability.”}

Ecology an_{d Society,}₁₈_{(2), 8.}

4 _{Rodin, J. (2014). he resilience di}v_{idend: Being strong in a world where things go wrong. New York: PublicAfairs.}

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It is important to understand that the resilience div_{idend is not}n_ecessarily_{restricted to beneits/} costs related to recov_{ering from a particular shock or withstanding a stressor. Rather, we take a}

broader interpretation of the div_{idend that is more inclusi}v_{e: the total net expected beneits of a}

project or portfolio designed with a resilience lens ov_{er time, relati}v_{e to a chosen baseline. his}

allows for the possibility that projects dev_{eloped with a resilience lens could ha}v_{e “co-beneits”}

(or, in some cases, costs) that accrue ev_{en in the absence of an ad}v_{erse e}v_{ent. As such, the}

resil-ience div_{idend is not equi}v_{alent to the}v_{alue of increased resilience of the system, though it}

theoretically includes these potential net beneits.

Valuing the resilience div_{idend requires that we understand how resilience policy and program}

interv_{entions change the}v_{aluable elements of any gi}v_{en system o}v_{er time. Projects can change}

these elements directly or indirectly by prov_{iding resources, relaxing constraints, or increasing}

opportunities to stakeholders. Stakeholders’ reactions to these changed elements may alter the low of goods and serv_{ices (both market and non-market) as a result of the inter}v_{ention. It is}

this changed low that creates v_{alue for stakeholders and that should be monetized in order to}

estimate the resilience div_{idend. As such, estimating the (experienced or expected) net beneits}

that a project prov_{ides requires e}v_{aluating its impacts.}6

Using the Resilience Dividend

From an economic standpoint, good decisionmaking requires prioritizing feasible projects with the greatest total net beneits. Failure to fully take positiv_{e resilience di}v_{idend beneits into}

account will underestimate the total v_{alue of a project, perhaps leading to suboptimal decisions}

since the true v_{alue of the project will not be accurately estimated. In particular, a decision}

needs to consider co-beneits and changes to structural dynamics to relect the full range of

beneits and costs. For example, changing land use planning compared with building a lev_ee

may hav_{e the same reductions in the risk of damage from loods but ha}v_ev_{ery diferent beneits}

and costs. Failure to take into account the non-lood-related beneits such as ecosystem

ser-v_{ices (e.g., better water quality, recreation) that arise from land use planning may bias the}

deci-sion toward lev_{ees. E}v_{en if the full resilience di}v_{idend cannot be explicitly}v_{alued (due to, e.g.,}

data limitations), qualitativ_{e information about diferent streams of beneits and costs might}

be useful in describing project outcomes and choosing between competing courses of action.

Objectives of this Report

he RDVM is based on the theory of inclusiv_{e wealth and sits within the broader literature on}

resilience frameworks and metrics. his report sets the context for the RDVM, explains how we dev_{eloped the approach, and pro}v_{ides a set of case studies that ofer insight into the}

oppor-tunities and challenges of using the RDVM to estimate the resilience div_{idend. It pro}v_ides

detailed, technical background information, documents the inclusiv_{e wealth framework, and}

deconstructs the components of the RDVM that low out of the framework. It is intended for researchers and other indiv_{iduals and organizations interested in the details of measuring and} v_{aluing resilience and the resilience di}v_idend.

6 _{As noted later in this report, estimates of the resilience di}_v_{idend can be calculated either before (ex ante) or after (ex post)}

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his report is not designed to be a users’ guide for the RDVM. We hav_{e produced a separate}

guidethat focuses on when and how to estimate a partial resilience div_{idend. his guide is}

designed for stafers and management interested in using an RDVM to generate information that could be used to inform recommendations to senior decisionmakers.

Organization of this Report

his report has four major components, organized into chapters. Chapter 2 prov_ides

back-ground information on deinitions and foundations of resilience and rev_iewsv_{arious resilience}

frameworks.

Chapter 3_{formally describes the theory of inclusi}v_{e wealth and shows how this modeling}

approach can be used to estimate the resilience div_{idend. his chapter outlines the elements of}

the RDVM and documents the major types of beneits and costs in the resilience div_{idend. It}

concludes with a brief summary of challenges to estimating the resilience div_idend.

Chapter 4 reports the results of the case studies analyzed as part of the research project. he cases explore the model’s application across a wide range of projects, and they help us under-stand the usefulness of the theoretical and empirical approach embodied in the RDVM.

Chapter 5 concludes the report with lessons learned and some implications for future work.

For the conv_{enience of the reader, a discussion of the characteristics of resilient systems and}

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CHAPTER 2

A Review of Resilience Frameworks

he concept of resiliency is gaining ground in hazards and risk communities that want to mov_{e away from traditional assessments of risk and}v_{ulnerability. While the frameworks and}

analytic methods for traditional risk assessment are fairly mature, this is not necessarily the case for resiliency. As a recent National Academies report on the topic states: “no systematic or ev_{idence-based assessment has been conducted to identify which strategies are most efecti}v_e

in fostering local collaborations to build community resilience.”1_{One of the main obstacles is}

the lack of an agreed upon deinition of resilience and a common framework for assessing it.

his chapter rev_{iews some of those deinitions, describes major components of the resilience}

concept, and discusses past resilience frameworks that appear in the literature.

Foundations of Resilience

Resilience has its foundations in materials science, mathematics and physics, with the focus primarily on equilibrium analysis.2_T_{wo main considerations within this realm are the}

magni-tude of a stressor, as measured by the mov_{ement of the system from one equilibrium state to}

another, and the length of time it takes for the system to rebalance once the stressor has been remov_{ed. C.S. Holling}3

was the irst to transfer these ideas from the physical sciences to the bio-logical sciences. Holling’s distinction from the physical sciences is that there is a clear diference between resilience and stability. For example, although an ecological system may luctuate or hav_{e cycles and not be stable, it may be resilient to outside stressors. Holling’s}v_{iew suggests that}

the main concern of resilience is on how large a stress the system can take and still maintain its integrity, as opposed to mov_{ement to new equilibrium point. Since this is not an equilibrium}

analysis and cycles may exist within the system, there is less focus on time than on magnitude.

Norris et al.4_pro_v_{ide a broad o}_v_er_v_{iew of resilience deinitions that ha}_v_{e transitioned from the}

physical and biological sciences to the social sciences, and Alexander prov_{ides an}

etymologi-cal analysis of resilience.5_T_{able 2.1, taken from Norris et al.,}6_{lists deinitions from a}_v_ariety

1 _{National Academies of Science, Engineering and Medicine (2012). Disaster resilie}n_ce:_An_ation_{al imperative.} Washington D.C.: he National Academies Press.

2 _{Bodin, P., and Wiman, B. (2004). “Resilience and other stability concepts in ecology: Notes on their origin,}_v_{alidity, and}

usefulness.” ESS bulletin_,₂_(2),33_-43_.

3 _{Holling, C. S. (197}₃_{). “Resilience and stability of ecological systems.” A}_nn_{ual Review of Ecology a}_n_{d Systematics, 1-2}₃_.

4 _{Norris, F. H., Ste}v_{ens, S. P., Pfeferbaum, B., Wyche, K. F., and Pfeferbaum, R. L. (2008). “Community resilience as}

a metaphor, theory, set of capacities, and strategy for disaster readiness.” American_Journ_{al of Commu}n_{ity Psyc}h_ology, 41(1-2), 127-150.

5 _{Alexander, D. E. (201}3_{). “Resilience and disaster risk reduction: Aan etymological journey.” Natural Hazards a}n_{d Eart}h System Scien_ce,₁₃_{(11), 2707-2716.}

6 _{Norris, F. H., et al. (2008). “Community resilience as a metaphor, theory, set of capacities, and strategy for disaster}

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of disciplines and perspectiv_{es. he main commonalities among all of the community-le}v_el

deinitions of resilience are threefold.

• Absorption_capacity:_{How large a disaster/stress can a community absorb/resist and still} function in the pre-ev_{ent mindset? Some authors ha}v_{e described this as resistance or}

absorption capacity.

• Adaptive capacity:_{How adapti}v_{e is the system to stresses while still maintaining function?}

his can be v_{iewed as the redundancies within the system that enable the system to}

con-tinue to function (although potentially at a reduced capacity), what has been called the adaptiv_{e capacity.}

• Restorative capacity:_{How restorati}v_{e is the system once producti}v_{e capacity has been}

reduced? Speciically, how quickly can the system get back to “normal” functioning—

understanding that “normal” may look diferent after the ev_{ent than before it—labeled}

restorativ_{e capacity. hese ideas are laid out implicitly in Francis and Bekera}7_{and explicitly}

in Rose.8

he ideas underlying the study of resilience are linked to other eforts that emphasize v

ulner-ability and adaptiv_{e capacity. All these ideas are linked by a common goal of reducing the risk}

to a community from external forces.9_{As Miller et al., and other authors ha}_v_{e noted, resilience}

and v_{ulnerability should be}v_{iewed as complementing each other rather than being at odds.}10

he main distinguishing characteristic between these two v_{iews is that}v_{ulnerability appears}

to focus on the system whereas resilience focuses on the actors within the system. Cutter et al. note that the shift from v_{ulnerability to resilience among federal agencies may be thought of}

as a mov_{e toward a “more proacti}v_{e and positi}v_{e expression of community engagement with}

natural hazards reduction.”11_{Beatley also distinguishes resilience from mitigation in that}

resil-ience focuses on increasing adaptation and learning as well as building underlying capacity to deal with future stressors, as opposed to mitigation and recov_{ery after the fact.}12

7 _{Francis, R., and Bekera, B. (2014). “A metric and frameworks for resilience analysis of engineered and infrastructure}

systems.” Reliability En_gin_eerin_{g & System Safety,}₁₂₁_{, 90-10}3_.

8 _{Rose, A. (2004). “Deining and measuring economic resilience to disasters.” Disaster Preve}n_tion_an_{d Ma}n_agemen_t:_An In_tern_ation_{al Jour}n_al,₁₃_(4),3_07-3_14.

9 _{Lei, Y., Wang, J., Yue Y., and Yin, W. (2014). “Rethinking the relationships of}_v_{ulnerability, resilience, and adaptation}

from a disaster risk perspectiv_{e.” Natural Hazards,}₇₀_{(1), 609-627.}

10 _{Miller, F., et al. (2010). “Resilience and}v_{ulnerability: complementary or conlicting concepts?” Ecology a}n_d Society, 15(3_{), 1-25.}

11 _{Cutter, S. L., et al. (2008). “A place-based model for understanding community resilience to natural disasters.”}

Global En_viron_men_{tal C}h_an_ge,₁₈_{(4), 598.}

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Components of Resilience

here is a growing conv_{ergence of the deinitions of resilience used in disaster and risk}

plan-ning and mitigation that centers on the three principal components of absorption, adaptation and restoration. hese three components are v_{ery much in tune with the three phases of}

disas-ter planning: preparedness and mitigation, response, and recov_{ery. Although a large segment}

of the literature still distinguishes between hazard mitigation and resilience, these two con-cepts should be thought of as complements. Distinguishing between hazard mitigation and the recov_{ery process, as many authors ha}v_{e, may remo}v_{e some responses to risk that may be}

beneicial. In particular, if the focus is solely on what happens after a disaster occurs, there is a risk that strategies or actions to reduce v_{ulnerabilities will be under}v_{alued or ignored entirely.}

Alternativ_{ely, if the focus is solely on hazard mitigation, important capacities to the reco}v_ery

process may be ignored. A less v_{ulnerable community is a more resilient community since it}

faces fewer disasters from which to recov_er.

Table 2.1. Sample Deﬁnitions of Resilience at Different Levels of Analysis

Citation, year Level of analysis Deﬁnition

Gordon, 1978 Physical The ability to store strain energy and deﬂect elastically under a load without breaking or being deformed

Bodin and Wiman, 2004

Physical The speed with which a system returns to equilibrium after displacement, irrespective of how many oscillations are required

Holling, 1973 Ecological system The persistence of relationships within a system; a measure of the ability of systems to absorb changes of state variables, driving variables, and parameters, and still persist

Waller, 2001 Ecological system Positive adaptation in response to adversity; it is not the absence of vulnerability, not an inherent characteristic, and not static

Klein, 2003 Ecological system The ability of a system that has undergone stress to recover and return to its original state; more precisely (i) the amount of disturbance a system can absorb and still remain within the same state or domain of attraction and (ii) the degree to which the system is capable of self-organization (see also Carpenter et al. 2001)

Longstaff, 2005 Ecological system The ability by an individual, group, or organization to continue its existence (or remain more or less stable) in the face of some sort of surprise….Resilience is found in systems that are highly adaptable (not locked into speciﬁc strategies) and have diverse resources

Resilience Alliance, 2006

Ecological system The capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure and feedbacks—and therefore the same identity

Adger, 2000 Social The ability of communities to withstand external shocks to their social infrastructure

Bruneau, 2003 Social The ability of social units to mitigate hazards, contain the effects of disasters when they occur, and carry out recovery activities in ways that minimize social disruption and mitigate the effects of future earthquakes

Godschalk, 2003 City A sustainable network of physical systems and human communities, capable of managing extreme events; during disaster, both must be able to survive and function under extreme stress

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Table 2.1.—Continued

Citation, year Level of analysis Deﬁnition

Sonn, 1998 Community The process through which mediating structures (schools, peer groups, family) and activity settings moderate the impact of oppressive systems

Paton, 2001 Community The capability to bounce back and to use physical and economic resources effectively to aid recovery following exposure to hazards

Ganor, 2003 Community The ability of individuals and communities to deal with a state of continuous, long term stress; the ability to ﬁnd unknown inner strengths and resources in order to cope effectively; the measure of adaptation and ﬂexibility

Ahmed, 2004 Community The development of material, physical, political, socio-cultural, and psychological resources that promote safety of residents and buffer adversity

Kimhi, 2004 Community Individuals’ sense of the ability of their own community to deal successfully with the ongoing political violence

Coles, 2004 Community A community’s capacities, skills, and knowledge that allow it to participate fully in recovery from disasters

Pfefferbaum, 2005 Community The ability of community members to take meaningful, deliberate, collective action to remedy the impact of a problem, including the ability to interpret the environment, intervene, and move on

Masten, 1990 Individual The process of, capacity for, or outcome of successful adaptation despite challenging or threatening circumstances Egeland, 1993 Individual The capacity for successful adaptation, positive functioning,

or competence…despite high-risk status, chronic stress, or following prolonged or severe trauma

Butler, 2007 Individual Good adaptation under extenuating circumstances; a recovery trajectory that returns to baseline functioning following a challenge

SOURCE: Compiled by Norris, Stevens et al. (2008).

Resilience Frameworks in the Literature

Many of the nuances in deinitions arise when dev_{eloping frameworks for analyzing resilience}

and community risk. A system-of-systems approach disaggregates a system into its constituent parts which are linked together in subsystems, and those subsystems themselv_{es are linked.}_he

premise is that indiv_{idual subsystems can be isolated to carry out speciic functions, thus the}

approach is a way of v_{iewing independent subsystems as part of a larger, more complex system.}

In considering the diferent frameworks that hav_{e been used, our approach builds on the work}

of Arup, which was used to dev_{elop the City Resilience Framework and City Resilience Index.}13

Additionally, the National Institute of Standards and T_{echnology (NIS}T_{) pro}v_{ides a broad}

ov_erv_{iew of the components of community resilience from a system-of-systems approach.}14_As

Arup explicitly say, “systems based approaches align more closely with the concept of resilience,

13

Arup International Dev_{lopment (2014). City resilie}n_{ce i}n_dex:_Un_derstan_din_{g a}n_{d measuri}n_{g city resilie}n_{ce. he Rockefeller} Foundation, Arup International Dev_elopment.

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and the long-standing notion of cities as ‘systems of systems.’”15_Howe_v_{er, Arup re}_v_iews

stud-ies on subsystems rather than on the system as a whole. his leav_{es the interdependencies that}

arise across systems mostly unconsidered. In contrast, NIST_{explicitly has a chapter on these}

cross-system dependencies.

Arup is explicit:

Ev_{ery city is unique. he way resilience manifests itself plays out diferently in diferent}

places. he City Resilience Framework prov_{ides a lens through which the complexity of}

cities and the numerous factors that contribute to a city’s resilience can be understood.16

According to Arup, resilient systems possess sev_{en main qualities:}

1. Relectiv_{e: Mechanisms that continuously e}v_olv_e

2. Robust: Anticipation of potential failures, prov_{isions to ensure failure is not}

dispropor-tionate to cause

3_{. Redundant: Spare capacity to accommodate disruption, pressure and change}

4. Flexible: System can change, ev_olv_{e and adapt}

5. Resourceful: People and institutions are able to rapidly ind diferent ways to achiev_e

their goal

6. Inclusiv_{e: Community engagement}

7. Integrated: Integration and alignment between systems to promote consistency

15 _{Arup International De}v_{elopment (2014). City resilie}n_{ce i}n_dex:_Un_derstan_din_{g a}n_{d measuri}n_{g city resilie}n_{ce. he Rockefeller} Foundation, Arup International Dev_{elopment, 4.}

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In a unifying framework depicted in Figure 2.1, Arupshow linkages across the v_arious

components of leadership and strategy, health and well-being, economy and society, and infrastructure and env_{ironment through the se}v_{en qualities of resilient cities. his integrates}

the indiv_{idual systems through}v_{arious channels.}

Figure 2.1. City Resilience Framework

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According to the Rockefeller Foundation,17_{resilient cities ha}_v_{e i}_v_{e characteristics:}

1. he capacity for robust feedback loops that sense and allow new options to be introduced quickly as conditions change.

2. he lexibility to change, and ev_olv_{e, in the face of disaster.}

3_{. Option for limited or “safe” failure, which pre}v_{ents stressors from rippling across}

systems—requiring islanding or de-networking at times.

4. Spare capacity, which ensures that there is a backup or alternativ_{e when a}v_ital

component of a system fails.

5. he ability for rapid rebound, to reestablish function quickly and av_{oid long-term}

disruptions.

he lists of characteristics from the Rockefeller Foundation and Arup are thus v_ery

much aligned.

A series of other frameworks deserv_{e indi}v_{idual consideration. Most of them approach disasters}

as problems of risk management within a systems-of-systems framework combined with some form of either risk management or resilience. he major diferences are the detail and connec-tions among the diferent systems and subsystems that they present. here are generally two approaches for an initial segmentation of a community into systems. First, some frameworks (e.g., Ziyath et al.) distinguish among the ecological, economic, infrastructural, institutional, and social systems.18_{Others (e.g., Bruneau et al.) distinguish between the diferent}

infrastruc-tural systems: hospital, electrical, water, local emergency management, and other systems.19_As

discussed in Kahan et al., knowing the goals of the eforts to increase resilience are paramount to constructing a framework suitable for mov_{ing analysis and decisionmaking forward.}20

Norris et al. prov_{ide a useful starting point for the consideration of alternati}v_{e frameworks}

that inherently consider resilience (see Figure 2.2).21_{First, a stressor is applied to the system.}

his stressor can difer in sev_{erity, duration, and time to warning. he resilience of the system}

irst determines if there is a crisis situation that is in many respects similar to the ability of the system to absorb the shock, or if there is suicient redundancy in the system to absorb the shock through alternativ_{e channels. If the system is in crisis—meaning that there was a shock}

or impact that changed the system’s pre-ev_{ent conditions—then there are two paths that the}

system can take: Either the system is functioning but at a diminished capacity in the post-ev_ent

17 _{Rodin, J. (201}3_{, June 24). he city resilie}n_t.

18 _{Ziyath, A. M.,}T_{eo, M., and Goonetilleke, A. (201}3_{). “Surrogate indicators for assessing community resilience.”}

Proceedin_{gs of t}h_{e I}n_tern_ation_{al Co}n_feren_{ce o}n_Buildin_{g Resilie}n_{ce 2013.}

19 _{Bruneau, M., et al. (200}₃_{). “A framework to quantitati}_v_{ely assess and enhance the seismic resilience of communities.”}

Earth_{quake Spectra,}₁₉_{(4), 7}33_-752.

20 _{Kahan, J. H., Allen, A. C., and George, J. K. (2009). “An operational framework for resilience.” Jour}n_{al of Homela}n_d Security an_{d Emerge}n_{cy Ma}n_agemen_t,₆_{(1), 1-48.}

21 _{Norris, F. H., et al. (2008). “Community resilience as a metaphor, theory, set of capacities, and strategy for disaster}

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world, or there is residual dysfunction in the system. If the system is dysfunctional at this point, there are two more paths that the system can take. he system’s ability to adapt to the changed env_{ironment together with the system’s ability to reco}v_{er determines whether the system can}

adjust to the changed env_{ironment. hough the Norris et al}_._{framework fails to account for}

the feedbacks once a disruption has occurred, its setup does takes into account the three major elements of resilience: adaptation, absorption, and recov_{ery. Additionally, Norris et al. do not}

recognize that post-ev_{ent functioning from one e}v_{ent is the pre-e}v_{ent functioning for the next}

ev_{ent. his circularity is important as we consider the community eforts to increase resilience}

to the next ev_{ent from post-e}v_{ent funding opportunities that arise. As discussed in Godschalk,}

as ev_{ents occur in communities, learning takes places both within and across communities as to}

how better to prepare for and recov_{er from e}v_ents.22

Figure 2.2. Norris et al. (2008) Deﬁnition of Resilience

Pre-Event

SOURCE: Norris et al. (2008). Used with permission.

As an alternativ_{e, Rose de}v_{eloped a framework (see Figure 2.}3_{) that is more detailed but has the}

same structure as the framework proposed by Norris et al.23

he focus of Rose’s framework is to understand the role of mitigation activ_{ities on total regional economic impact. his}

frame-work is centered on the economic impact and only considers the economic subsystem within

the community and not the broader social and natural env_{ironments, though the framework}

could easily be adapted to incorporate such considerations. In particular, Rose dev_{elops his}

framework with two aspects in mind: how can this system be modeled in order to predict potential impacts, and what is the measure of resilience? he framework’s ov_{erarching goal is}

22 _{Godschalk, D. R. (200}₃_{). “Urban hazard mitigation: Creating resilient cities.” Natural Hazards Review,}₄₍₃_{), 1}₃_6-14₃_.

23

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to minimize the total regional economic disruptions, whichare modeled using a general equi-librium model. By focusing on the economic subsystem, a number of diferent roles for adapta-tion are rev_{ealed that could be applied in a broader framework.}

he key insight from Rose is that community resilience is a function of household resilience, irm resilience, and system resilience, but it is neither additiv_{e nor multiplicati}v_{e between these}

subsystems. In particular, a mitigating strategy irst afects the direct impact that an ev_{ent may}

hav_{e. Hence, mitigation irst operates to reduce the risk that a disruption will take place. Next,}

indiv_{iduals and irms adapt to a changed en}v_{ironment by changing as necessary the inputs}

they use to produce goods and serv_{ices and, ultimately, community well-being. How lexible}

the system is, inherently, and how it is enhanced through the mitigating activ_{ities of irms}

and indiv_{idual households determines the system’s inherent le}v_{el of resilience. Once the initial}

adaptation takes place, recov_{ery begins through a reconstruction of capital that was lost to the}

disruption and through alternativ_{e production functions that may be inherently more lexible}

and responsiv_{e to price signals that the system sends to the irms and households. In other}

words, how indiv_{iduals and irms beha}v_{e before, during, and after a shock (or in the presence}

of a stressor) serv_{e as mitigating factors that inluence the resilience of the system.}

Although Rose uses a diferent deinition of resilience—namely, “the ability or capacity of a system to absorb or cushion against damage or loss”—the three major aspects of resilience (absorptiv_{e, adapti}v_{e, and restorati}v_{e capacity) are embedded in his ideas of inherent}

resil-ience and adaptiv_{e resilience as subcategories of resilience.}24_Rose’s_v_{iew of resilience is that it}

is a property of the system and that it can be thought of at v_{arious spatial and organizational}

scales. Additionally, giv_{en the computable general equilibrium modeling that he uses, the}

link-ages across sectors are also considered. If infrastructure is damaged, it afects a v_{ariety of}

sec-tors and cascades through the system due to the efects on both upstream and downstream supply chains. Additionally, Rose is able to estimate the inherent resilience of a system due to the efects of mitigating activ_{ities and then to impro}v_{e understanding of how in}v_estments

afect resilience.25

24 _{Rose, A. (1999).}

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Figure 2.3. Rose (1999) Framework

As a means to combine the Rose and Norris et al. frameworks, Francis and Bekera dev_{elop a}

framework that is more easily incorporated into a decisionmaking process.26_{he Francis and}

Bekera framework has iv_{e main components (see Figure 2.4):}

1. System identiication

2. Vulnerability analysis

3_{. Resilience}_objectiv_{e setting}

4. Stakeholder engagement

5. Resilience capacities

here are two main pieces that distinguish this framework from the other two prev_iously

con-sidered. First, it explicitly discusses the objectiv_{es of increasing resilience. It is paramount when}

beginning an exercise aimed at increasing resilience to know what the goals are. hese goals tie into the metrics that will measure progress toward increasing resilience. If one does not know

26 _{Francis, R., and Bekera, B. (2014). “A metric and frameworks for resilience analysis of engineered and infrastructure}