Risk, Vulnerability and Asset Based Approach to Disaster Risk Management

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Risk, Vulnerability, and Asset-based Approach to Disaster Risk Management by Krishna S. Vatsa, Institute for Crisis, Disaster and Risk Management, George Washington University,Washington, D.C. Abstract Households are exposed to a wide array of risks, characterized by a known or unknown probability distribution of events. Disasters are one of these risks at the extreme end. Understanding the nature of these risks is critical to recommending appropriate mitigation measures. A household’s resilience in resisting the negative outcomes of these risky events is indicative of its level of vulnerability. Vulnerability has emerged as the most critical concept in disaster studies, with several attempts at defining, measuring, indexing and modeling it. The paper presents the concept and meanings of risk and vulnerability as they have evolved in different disciplines. Building on these basic concepts, the paper suggests that assets are the key to reducing risk and vulnerability. Households resist and cope with adverse consequences of disasters and other risks through the assets that they can mobilize in face of shocks. A sustainable strategy for disaster reduction must therefore focus on asset-building. There could be different types of assets, and their selection and application for disaster risk management is necessarily a contextual exercise. The mix of asset-building strategies could vary from one community to another, depending upon households’ asset profile. The paper addresses the dynamics of assets-risk interaction, thus focusing on the role of assets in risk management. Keywords: Risk, Vulnerability, Assets, and Mitigation Section I: Introduction Contrary to what we often get to see in the preamble to many publications on disasters, global trends and macroeconomic variables help us little in understanding the impact of disasters on people, their habitat, and livelihoods. It is necessary to disaggregate the impact of disasters to understand how regions, communities or households within a country are affected by disasters. Disaster impacts and losses are not distributed evenly across populations. Its

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distribution depends upon underlying vulnerabilities which arise from factors such as location of human settlements and economic enterprises, conditions of housing, and access to resources and information. These vulnerabilities exist in both the developed and developing countries, though spatial and physical aspects of vulnerability tend to be more pronounced in developing countries. It is often stated that the poorer segments of the population are more exposed to disaster risks. With increasingly greater concentration of settlements and buildings in hazard-prone areas, this statement needs to be qualified somewhat. In the Bhuj earthquake (2001) in India, the high- and middle-income groups lost more of their asset value. Most of the people who died in collapse of mid-rise apartment buildings in Ahmedabad and Bhuj belonged to the middle class (Vatsa, 2002). In the Marmara earthquake (1999) in Turkey, 90 percent of casualties took place in mid-rise reinforced concrete apartment blocks, owned by urban upper middle classes (Erdik, 2001). In Germany, 2002 floods in River Elbe inundated the city of Dresden, did not spare any segment of the population, as it caused inundation of all the residential and commercial properties and damaged many historical buildings in the city center (Toothill, 2002). In the United States, when an earthquake strikes California hillsides or a hurricane strikes the coastal areas of Florida, absolute disaster losses in dollar terms are higher for upper and middle classes than for the poor, though in relative terms the poor generally lose a larger percentage of their material assets and suffer more lasting effects (Bolin and Stanford, 1999). While the distribution of disaster impacts has become more complicated across social classes, it is also true that stable employment, insurance, credit and assets help upper and middle classes to recover faster from a disaster. The low-income group, on the other hand, has fewer options than the wealthy for coping with a disaster. They have fewer assets, almost no insurance, and less diversified sources of income, and a disaster can push them into destitution (World Bank, 2001). In rural areas in Vietnam it was reported that those with capital have a buffer and are better able to survive and

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recover, whereas poorer households without capital reserves go under with even the smallest shock (Narayan, et al., 2000). In the 1990s, El Niño-related disasters and the East Asian financial crisis underscored the importance of reducing risk and vulnerability to sustain our economic and welfare gains. Reducing volatility in income and consumption has become a serious public policy concern. Along with opportunity and empowerment, security as embodied in risk and vulnerability reduction is posited as a cornerstone of development and poverty eradication (World Bank, 2001). Households1 are exposed to a wide array of risks, characterized by a known or unknown probability distribution of events. Disasters are one of these risks at the extreme end. A household’s resilience in resisting the negative outcomes of these risky events is indicative of its level of vulnerability. The means of resistance are the assets that households can mobilize in face of these shocks (Moser, 1997). This paper aims to develop a conceptual framework of risk management, focusing on the role of assets in risk management. The paper is divided into six sections. The following section discusses the concept of risk and how it has been understood in physical and social sciences. Section III analyzes the meaning and structure of “vulnerability”. Section IV briefly presents a brief review of literature on vulnerability assessment, measurement, indexing, and modeling. Section V presents the asset framework of risk management and the dynamics of assets-risk interaction. Section VI discusses specific asset-building strategies for disaster risk management. Section II: Understanding Risk During the past quarter-century, the term “risk” has been a subject of intensive conceptual and empirical research. The field of risk analysis has grown rapidly, focusing on issues of risk assessment and risk management. The former involves the identification, quantification, and characterization of threats to human health and the environment. The latter, risk management, centers around processes of communication, mitigation, and decisionmaking (Slovic and Weber, 2002).

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2.1 Classical Concept of Risk The classical conception views risk as “the chance of injury, damage, or loss.” It distinguishes between risk— defined as the probability that a particular adverse event occurs during a stated period of time, or results from a particular challenge— and detriment— defined as a numerical measure of the expected harm or loss associated with an adverse event. The probabilities and consequences of adverse events are assumed to be produced by physical and natural processes in ways that can be objectively quantified by risk assessment. One way to describe risks and uncertainty is to construct an exceedance probability (EP) curve. An EP curve specifies the probabilities that a certain level of losses will be exceeded. A critical issue in constructing an EP curve is the degree of uncertainty regarding both probability and outcomes. For low probability-high consequence risks, the spread between the three curves depicted in Fig.1 shows the degree of indeterminacy of these events. Information on uncertainty enhances the credibility of a risk assessment exercise (Swift, 1999; Adams, 1995; Kunreuther and Slovic, 1996; Kunreuther, 2002).

Figure 1: Example of Exceedance Probability Curves

Source: Kunreuther, 2002

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Such a view of risk agrees upon the objective nature of risk. There is general agreement among those who hold such a view of risk that progress lies in refining the methods of measurement and collecting more data on both the probabilities of adverse events and their magnitudes. A report by the Britain’s Royal Society called “Risk Assessment” concluded that there was a need for “better estimates of actual risk based on direct observation of what happens in society” (cited in Adams, 1995).2 This approach also distinguishes between objective risk—the sort of thing “experts” know about—and perceived risk—the lay person’s often very different anticipation of future events. Perceptions of risk play a prominent role in the decisions people make, in the sense that differences in risk perception lie at the heart of disagreements about the best course of action between technical experts and members of the general public (Slovic and Weber, 2002). We may express objective and perceived risk as in the matrix below: Figure 2: Risk Matrix Risk Objective (measured as)

Statistical probability

Perceived (measured as)

Perceptions of likelihood of different events by different actors

Detriment Economic cost · Economic cost · Non-economic cost (including, self-esteem, community solidarity, future livelihood solidarity)

Source: Swift, 1999

2.2 “Risk” in Social Sciences Much social science analysis rejects such a notion of risk. In this tradition, such objective characterization of the distribution of possible outcomes is incomplete at best and misleading at worst. The distinction between objective risk and perceived risk is considered false. According to this perspective, both the adverse nature of particular events and their probability are inherently subjective. For example, between 1950 and 1970, coal mines in

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the US became much less risky in terms of deaths from accidents per ton of coals, but they became marginally riskier in terms of deaths from accidents per miner. Which measure one thinks more appropriate for decision-making depends on one’s point of view (Kunreuther and Slovic, 1996; Adams, 1995). In social science, the concept of risk is primarily concerned with the distribution of risky outcomes and its impact on the people who experience them. Over their lifetime, all men and women are subject to a wide variety of risks: unemployment, illness, injury, disability, death, loss of residential and commercial property, crop failure, etc. Different disciplines within social science have discussed these risks from their own point of view. One of the most important contributions to social theories of risk came from the European sociologists, Ulrich Beck and Anthony Giddens. In the globalized modern world, which Beck characterized as a “risk society”, the future has become uncertain. Possible events which technology unintentionally generates cannot be insured against because they have unimaginable implications. Beck, citing the example of the Chernobyl nuclear explosion in 1986, associates nuclear power with suspension of “the principle of insurance not only in the economic, but also in the medical, psychological, cultural and religious sense. The residual risk society has become an uninsured society” (Beck, 1992: 101).3 Giddens makes a similar point by distinguishing between external risks emanating from bad harvests, floods, plagues or famines and manufactured risks which include most of the environmental risks. Not only has external risks been supplanted by manufactured risks, but we know very little on how to handle the latter. As manufactured risk expands, there is a new riskiness to risk. “We simply don’t know what the level of risk is, and in many cases we wouldn’t know for sure until it is too late.” Further, “we live in a world where hazards created by ourselves are as, or more threatening than those that come from outside” (Giddens, 2000 cited in Quarantelli, 2000).

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2.3 Elements of Risk The concept of “risks” as discussed by Beck and Giddens derives its context from the developed world. Such a notion of “risk” is inherent in the pursuit of energy-intensive economic growth and affluence, an inescapable condition of the post-industrial society. These risks are qualitatively different from those faced by households with limited resources in both developed and developing countries. Most of the households are exposed to “risks”, which arise from an economy based on lack of resources and limited options. In the field of development, the “risk” is closely related to poverty, deprivation and lack of insurance. A great deal of research has taken place on the subject of household risks, but most of it deal with agricultural and pastoral societies trying to cope with individual risks such as illness and unemployment or collective risks such as droughts and scarcities (Udry, 1994; Morduch, 1995; Dercon; 1999, Sinha and Lipton, 1999; Fafchamps, 1999). At the level of households, risk refers to uncertain events that can damage well-being—the risk of becoming ill, or the risk that a drought will occur. The uncertainty can pertain to the timing or the magnitude of the event (World Bank, 2001). Many risks such as illnesses, death of an earning member, or individual loss of job, are household-specific, and called idiosyncratic (individual) risks. The natural disaster risks such as floods and drought simultaneously affect many households in a community or region, and are called covariate (collective) risks. The covariation of risks depends upon the size of risk pool, the group that households can draw upon for assistance in managing the impacts of risk. The capacity to insure depends upon the size of risk pool. If the risk pool is small, as could be the case in remote rural areas, even idiosyncratic risks have impacts similar to those of covariate risks. The distinction between idiosyncratic and covariate risks is, therefore, largely contextual (Siegel, 2000). While the probability and frequency of these risks and their magnitude, an outcome of physical and natural processes, can be estimated with some approximation, it is difficult to forecast what will be the ultimate impact of the risky event on vulnerable households. It depends upon the household’s level of vulnerability or resilience (Holzmann and Jørgensen, 2001,

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Siegel and Alwang, 1999). The EP curve is useful here only in a limited sense, and the concept of risk in these situations clearly diverges from the one used in physical and engineering sciences. Risk, combined with the household responses, lead to the outcome. The outcome is the change in welfare that results from the realization of risk – the shock – and from the success or failure of risk management instruments applied. Asset losses, unemployment, decline in production and wages, illness, injuries, deaths are some of the outcomes of a disaster. Households cope with these losses by withdrawing their savings, borrowing, reducing their expenditures, and selling their assets. Their capacity to insure against these losses is enhanced by the availability of public-funded and market-based mechanisms of risk management. A household’s vulnerability is ascertained on the basis of its asset endowment, likely welfare losses, and risk management strategy. The household is thus said to be vulnerable to suffering an undesirable outcome, and this vulnerability comes from exposure to risk (Alwang, Siegel and Jørgensen, 2001). Risk (disaster) in disaster management has been defined as the cumulative impact of hazard and vulnerability (Blaikie et. al., 1994), expressed through the following equation: R = HV where R stands for the loss or realized risk (disaster), H for hazard (the probability of occurrence of a specific hazard in a given area over a given time period, and V for vulnerability (the degree of loss resulting from the occurrence of the phenomenon). The United Nations Disaster Relief Coordinator (UNDRO) provided an official definition of risk as “expected losses from a given hazard to a given element at risk over a specified period of time (cited in Coburn et. al. 1994). For example, risk may be expressed in terms of average expected losses, such as “10,000 lost over 20 years period” or a “10 percent probability of economic losses to property exceeding US$25 million in the town of Puerto Novo within the next 10 years.” It introduces stochastic factors in calculation of risk, as total risk (RT ) becomes a function of exposure to hazard over time (tE), vulnerability (V) of elements at risk (E), and

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the probability that a natural hazard will strike in a certain way (P) (Alexander, 2001): RT = fcn { tE , V(E), P} Risk is compiled from hazard and vulnerability data and from the inventory of elements at risk. A variety of ways of presenting risk are available such as scenario mapping, potential loss mapping, and annualized risk. While the probability of occurrence of a hazard may always be estimated on the basis of historical data and physical information, and some of the elements at risk (buildings and population) can be identified and inventorized, the issue of measuring vulnerability and resilience is always difficult. While we understand that zoning, land use planning, improved building technology, and lower population density should lead to a lower number of deaths and injuries, the precise connection between human losses and spatial and demographic factors is always difficult to establish. This is why the equations as mentioned have remained abstract, and have not been used for actual estimation of risk. It points to the constraints in measuring a range of socio-economic factors which could be classified under the broad category of “vulnerability”. Section III: Perspectives on Vulnerability Vulnerability is the key factor which explains how the outcome of a risky event is distributed across households. Most of the literature regarding catastrophic risk in risk sciences is conspicuous by the absence of reference to “vulnerability.”4 In social sciences, however, the use of the term “vulnerability” has proliferated. It has been discussed in the context of a wide range of risks to which households are exposed. As there is a greater concern for reducing welfare losses before they actually happen, and more public policy support for ex ante approach to risk management, vulnerability has become a central theme of all the broader approaches to poverty alleviation and risk management. Vulnerability has been defined in terms of exposure to welfare losses, rather than in terms of exposure to poverty. An individual, a household, or a community can be considered vulnerable when there is a probability that they will experience a level of well being that is below a socially accepted

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threshold (Glewwe and Hall, 1998; Cunningham and Maloney, 2000; Alwang, Siegel and Jørgensen, 2001). It represents a general definition, though in the context of a specific discipline, the meaning of vulnerability changes according to its primary focus. For instance, in economics, vulnerability is discussed in terms of decline in income and consumption, whereas in disaster management, the focus is on human and property losses.5 Downing and Bakker (2000) list the central concepts of vulnerability as follows: ·

Vulnerability is a relative measure—critical levels of vulnerability must be defined.

·

Everyone is vulnerable, although their vulnerability differs in its casual structure, its evolution, and the severity of the likely consequences.

·

Vulnerability relates to the consequences of a perturbation, rather than its agent. Thus people are vulnerable to loss of life, livelihoods, assets and income, rather than to specific agents of disaster, such as floods, windstorms or technological hazards. This focuses vulnerability on the social systems rather than the nature of hazard itself.

·

The locus of vulnerability is the individual related to social structures of household, community, society and world-system. Places can only be ascribed a vulnerability ranking in the context of the people who occupy them.

·

Vulnerability is spatially and temporally variable. Vulnerable groups are dispersed over space and change over time. More critically, patterns of vulnerability depend on geographical linkages and are often contingent on past conditions.

3.1 Poverty and Vulnerability Though the poor and near-poor tend to be vulnerable, poverty and vulnerability are not synonymous. Poverty is a static concept, an ex post state of being, measured in terms of a minimum level of income and consumption. Vulnerability, on the other hand, is a dynamic concept, characterized by

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changes in socio-economic status, and refers to an inability to cope with risks, shocks, and stress. So a vulnerable household may have a level of welfare at a point in time that exceeds the minimum level, but under the influence of a shock, this household would fall below this level. Vulnerability is thus both an ex ante and ex post state associated with the probability of falling below a minimum threshold of well-being (Alwang, Siegel and Jørgensen, 2001; Glewwe and Hall, 1998).

Figure 3: Sequence of Vulnerability

Standard of Living

SL

Shock / Disaste r

Household Recovers Relief / Assistance /

Community Support / Household’ s

Household copes /

adapts Household Slips below

Poverty line

6

6

6!

6

Time

Adapted from Glewwe and Hall, 1998

A failure to distinguish vulnerability from poverty has led to making frequent statements about the disaster-poverty nexus, without any concrete evidence. It gives us little idea about how the non-poor are affected by disasters. It also has a bad impact on policy-making. Anti-poverty programs can reduce poverty, but at the same time they can increase vulnerability. Besides, elimination of poverty is a long-range goal requiring social justice and

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equity, and income and resource distribution, and disaster management need not wait for the achievement of such goals (Chambers, 1989; Wisner, 1993). 3.2 “Vulnerability” in Disaster Management In disaster management literature, the discussion of vulnerability had its precursor in the concept of ‘a range of adjustments’, developed by Gilbert White. White (1961) recommended a set of possible accommodations to given hazards, and the best mix of them is more effective than single solutions, as had prevailed for instance, in the approach to flood hazards in North American through engineering control works. In making these alternative adjustments, White emphasized the question of choice and adjustments people at risk choose or would prefer. An important theme is that the adjustments which people consider and make depend upon social organization, and the capacity to choose adjustments—or lack of it. Choice is constrained by status and rights within a society. Those least likely to have a voice in public safety and risky developments are so often the ones to suffer most in disasters (Hewitt, 1997). When the concept of “vulnerability” was introduced in disaster management in 1970s, it was predominantly in terms of vulnerability of the critical infrastructure and urban lifelines: buildings, pipelines, roads, etc. Vulnerability assessment was concerned with estimating losses and damages to physical objects (Arnold, 1984). The Office of the United Nations Disaster Relief Coordinator (1982, cited in Alexander, 1993) echoed this view in their definition of vulnerability as the “degree of loss (from 0 % to 100 %) to a given element or set of elements at risk resulting from the occurrence of a natural phenomenon of a given magnitude. It is expressed on a scale from 0 (no damage) to 1 (total loss).” Such a view considered that a natural hazard risk was the same for all who were exposed to it, and there was no concept of differential vulnerability. Around the same time, a more socialized interpretation of disasters emerged which suggested that economic processes could increase the vulnerability of populations to natural disasters and should be considered in the same way as were the more obvious physical or environmental phenomena. There was a process of marginalization at work, which had a strong spatial

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implication in terms of pushing the poor into unsafe living conditions. Some of these views traced their ideological underpinnings to the dependence theory, and provided a strong critique of the relationship between relief and underdevelopment. These views had a distinct flavor of political economy approach to disasters. Amartya Sen’s work on poverty and famines in 1981 reinforced such an interpretation of disasters. Sen challenged the widely held conviction that lack of food availability (or supply) due to lack of rains and crop failures was the primary explanation for famines; instead, he posited lack of purchasing power or access as the key to understanding who went hungry and why. Over the years, a number of social scientists and geographers have steadily developed this approach which repudiated the distinction between physical and social vulnerability, and developed a more integrated explanation of natural disasters (Westgate and O’Keefe, 1976, Winchester, 1992; Wisner, 1993; Blaikie, et.al., 1994, Varley; 1994, Cannon, 1994; Hewitt, 1997). Westgate and O’Keefe define vulnerability as “the degree to which a community was at risk from the occurrence of extreme physical or natural phenomena, where risk refers to the probability of occurrence and the degree to which socio-economic and socio-political factors affect the community’s capacity to absorb and recover from extreme phenomena.” This definition could be considered a definitive view of vulnerability within the field of disaster research. It suggests that the likelihood of being affected by disasters depends on (i) frequency and severity of the impact—the more frequent and severe the impact, if the impact is not cushioned and mitigated, higher the vulnerability; and (ii) the peoples’ resilience to a given shock. Resilience is therefore an integral part of the concept of vulnerability. It is linked to the household’s capacity to resist and recover from the adverse impact of a disaster. Since we take the view that assets are the means of resistance to the impact of a disaster, a household’s resilience is closely linked to the asset ownership. Miller and Nigg (1993) have developed the concept of “event vulnerability” and “consequence vulnerability”, the former referring to the household vulnerability associated with the direct impacts of a disaster event and

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the latter referring to the household vulnerability associated with the social and political processes of recovering from the disaster event. Whereas upper and middle income-groups are vulnerable to the “event”, the lower classes share both the “event” and “consequence” vulnerability. A low asset base and limited livelihood opportunities trap low-income group into a vicious cycle of poverty and deprivation. The vicious cycle of vulnerability can be represented as: Limited asset base >= management of risk leads to inefficient allocation of assets >= low returns >= low consumption >= low savings and investment >= limited asset base >=lower returns, consumption and savings (Siegel and Alwang, 1999, p. vi).

3.3 Structure of Vulnerability Resilience is just one part of their vulnerability map; a number of structural factors contribute to and complete this map. These factors could be identified as social class, gender, race, caste, ethnicity, age, etc (Winchester, 1992; Cannon, 1993; Blaikie, et.al., 1994; Bolin and Stanford, 1999). It is necessary to assess these structural factors to understand who is vulnerable to the sufferings and losses from a natural disaster, and which segment of population is more likely to be affected by a disaster event. Social class is generally a marker of access to resources and can include type and stability of employment, income, savings, and education levels (Blaikie, et.al., 1994). People in low-income groups find it difficult to secure financial resources and technical skills to recover after disaster. Loss of life, injury, and disability can trap poor families in chronic poverty (World Bank, 2001). Women as a group are disproportionately affected by disasters. For example, post-disaster mortality, injury, and illness rates are often (but not universally) higher for girls and women. Women also have to assume greater responsibility following a disaster in managing household responsibilities, reviving livelihoods and supporting reconstruction. There have also been reports of increased incidence of sexual and domestic violence against girls and women in disaster contexts (Enarson, 2000).

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In all the multiethnic and pluralistic societies, race / caste / ethnicity is closely related to the material losses experiences and to differential abilities to acquire resources for recovery. The effects of race / ethnicity in disaster have been documented in numerous US disasters. Research on recent U.S. disaster documents racial and ethnic discrimination in relief aid (Bolin and Stanford, 1999). In the relief operations following the Bhuj earthquake in India, it was reported that there was discrimination against the lower caste people in the distribution of aid.6 Elderly victims of natural disasters find it difficult to recover from natural disasters due to impaired coping abilities, limited incomes, the availability of support systems and their own health (Covan, et.al, 2000).7 In some instances, elders are overrepresented among the casualties of disaster due to frailty and being housebound (Hewitt, 1997, cited in Bolin and Stanford, 1999 p. 96). In rural areas, vulnerable groups include smallholder agriculturalists, pastoralists, landless laborers, and the destitute. In urban areas, these could come from unemployed destitute, underemployed poor people, and refugees (Downing and Bakker, 1997). Winchester (1992) identifies household characteristics, which contribute to the making of differential vulnerability. Important characteristics are: family type, household size, age, sex composition of the household, skills / education, and caste. However, it needs to be pointed out that these specific categories of population by themselves do not mark vulnerability. It is their level of participation in social and economic processes that impinges on vulnerability. Lack of education and skills, weak social support and protection, low income, poor health care, and single parenthood are the attributes that make these segments of civil society especially vulnerable. This explains why the state policies and social protection measures have a substantial impact on the levels of vulnerability. In many developing countries, where social welfare and protection policies are not adequate, the level of vulnerability is high, particularly for lower-income groups. Public policies are not always non-partisan, and tend to marginalize certain communities. In the U.S., federal relief programs traditionally privilege middle class home owners over

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renters and the marginally housed, revealing a persistent (if unintended) class preference (Comerio et.al. 1996, cited in Bolin and Stanford, 1999). In erstwhile socialist countries, where the public-supported welfare system has been dismantled, the level of vulnerability has gone up significantly. In Mongolia, the dismantling of state support for pastoral collectives wreaked havoc on nomadic communities when they were struck by droughts and winter zud between 1999 and 2002 (Bass, Batjargal, and Swift, 2001). Section IV: Modeling, Assessing, Measuring, and Indexing Vulnerability 4.1 Modeling Vulnerability Blaikie, et.al. (1994) have attempted to model vulnerability for explaining its causation, structure and possible response. They discuss two models, which are (1) Pressure and Release and (2) Access models. The Pressure and Release (PAR) model attributes disasters to the interaction between vulnerability on one side and physical exposure to hazard on the other side. Increasing pressure can come from either side, but to relieve the pressure, vulnerability has to be reduced. The model can be represented as follows: 1 →Root causes →2 Dynamic pressures →3 Unsafe conditions →Disaster ← Hazards

The PAR model proposes a ‘progression’ of vulnerability with three main levels: root causes, dynamic pressures, and unsafe conditions. Vulnerability begins with root causes, which are economic, demographic, and political processes. These root causes interact with dynamic pressures such as population growth, rapid urbanization, and deforestation to produce unsafe conditions. Unsafe conditions are the specific forms in which the vulnerability of a population is expressed in time and space in conjunction with a hazard. Examples of unsafe conditions are people living in fragile physical environment, like dangerous locations or unprotected buildings and infrastructure, weak local economy with low income and uncertain livelihoods, population categories at risk such as the old and disabled, prevalence of endemic disease and lack of disaster preparedness. All of these factors change

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over time, sometimes rapidly. They also interact with each other in complex ways. The outcome can be unpredictable (Twigg, 2001). The PAR model takes a structural view of vulnerability. It explains the systemic pressures contributing to vulnerability, but does not suggest a strategy for reducing it. It also does not provide insight into what constitutes vulnerability at the household level. It is the access model, which explains the household vulnerability. The model suggests that it is the level of access to resources that determines the vulnerability of people and turns some natural events into disasters for some people. Each household has a range or profile of resources and assets that represent their particular access level. These may include land of various qualities, livestock, tools and equipment, capital and stock, reserves of food, jewelry, as well as labor power and specialist skills. Non-material ‘resources’, qualities, or qualifications such as gender, and membership of caste or kinship-based organizations may also be included. Access to all the resources that each individual or household possesses can collectively be called its access profile. Those who possess access qualifications for a large number of income opportunities have more flexibility in securing a livelihood under generally adverse conditions, command considerable resources, have reserves of food, and can be said to have a well-resourced profile. On the other hand, those whose access profiles are limited usually have little choice in income opportunities, less store of value to draw upon, and have the least flexibility in adverse conditions (Blaikie, et.al., 1994). However, even ‘Access’ model provides just an abstract framework. It is not modeled on empirical observations in the field, nor has it been validated through actual experiences. Besides, the model is not sufficiently dynamic to explain vulnerability. A household economy is not isolated or disconnected; it is connected strongly to the regional, national and international economy. These connections, which enable households to reduce their vulnerability, have not been incorporated in the model. Further, the model does little further than explaining vulnerability. It does not specify the instruments or programs, which could be used for reducing or mitigating disaster risks. Vulnerability requires a broader and dynamic framework,

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which includes an instrumental perspective too. It is not only necessary to explain what constitutes vulnerability, but also how vulnerability could be reduced. A model, which is based on a critical mass of empirical observations, will also provide a choice of strategies, measures and programs, for reducing vulnerability. 4.2 Assessing Vulnerability Several methods of vulnerability assessment have evolved in line with the requirements of a particular discipline or organization. These methods are applied at different levels—households, communities, countries, and regions. Vulnerability at one level influences vulnerability at other levels of aggregation (Ribot, 1996). While a detailed review of these issues could the subject of an independent discussion, we present here a brief review of different methods of vulnerability assessment (VA) in the field of natural disasters. 4.2.1 Vulnerability Assessment in the US In the US, the Project Impact8 carries out an assessment, which includes both hazard identification and VA. The stated purpose of hazard identification is to gather existing information about areas with a high likelihood of hazard occurrences and compile the information into a useful format. Similarly, the purpose of VA is to gather and organize existing information about the location and vulnerability of buildings, utilities, and transportation systems serving the community. The National Oceanic and Atmospheric Administration (NOAA) goes one step further with the tool it has developed for comprehensive community-wide VA.9 It specifies a series of steps through which this assessment is conducted. Though the NOAA methodology includes societal analysis in its vulnerability framework, this too focuses more on hazard identification and prioritization, built environment, and economic centers. 4.2.2 Vulnerability Assessment in Developing Countries Famine Early Warning System (FEWS) and Vulnerability Analysis and Mapping (VAM): In developing countries, communities’ vulnerability has been assessed first in terms of food security, due to incidence of droughts

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and famine and high levels of mortality. The USAID has developed a distinct methodology for conducting VA in the context of improving food security in sub-Saharan Africa under the Famine Early Warning System (FEWS).10. However, the concept and methodology of VA applied in the FEWS has the perspective of a donor organization, and it is used primarily as a tool to assist decision-makers faced with the responsibility of responding to any potential threat of famine. As is the case with FEWS, food security is the leading perspective in the Vulnerability Analysis and Mapping (VAM) conducted by the World Food Program (WFP), a UN agency.11 Participatory Rural Appraisal (PRA)-based Vulnerabilities and Capacities Analysis (VCA): The Participatory Rural Appraisal (PRA) methods, extensively practiced in development activities, have been used for carrying out the Vulnerabilities and Capacities Analysis (VCA). Developed in the context of relief work undertaken by NGOs, the VCA undertakes an assessment by dividing societal capacities and vulnerabilities into three categories: physical/material; social/organizational; and motivational/ attitudinal (Anderson and Woodrow, 1998). The International Federation of Red Cross and Red Crescent Societies (IFRC) has adopted the Vulnerability and Capacity Analysis (VCA) as a diagnostic tool to assess institutional capacity and evaluate the effectiveness of current programs. The IFRC national societies have preferred VCA over needs-based assessment approach, as it emphasizes capacity building and community participation, making their mitigation programs more adaptive and responsive (IFRC, 1999). Given the multi-dimensionality of vulnerability, not all of the assessment can be encompassed in a single model. Instead, a number of analytical techniques could be used to assess vulnerability, which includes quantitative data of different measures of vulnerability, qualitative information upon different vulnerable groups, descriptive details of spatial and geographical situation, and multivariate modeling of vulnerability with respect to outcome indicators such as consumption (Tesliuc and Lindert, 2002).

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4.3 Measuring and Indexing Vulnerability Can vulnerability be measured? At what level is it feasible to measure vulnerability? According to the World Development Report 2000/1, it is especially difficult to measure vulnerability at the household level. It observes as follows: “…since the concept is dynamic, it cannot be measured by observing households once. Only with household panel data—that is, household surveys that follow the same households over several years—can the basic information be gathered to capture and quantify the volatility and vulnerability that poor households say is so important. Moreover, people’s movements in and out of poverty are informative about vulnerability only after the fact. The challenge is to find indicators of vulnerability that can identify at-risk households and populations beforehand.”

There has been some research at measuring vulnerability at household level using panel and cross-sectional data. A number of country-based studies have attempted to measure vulnerability on the basis of variability of consumption, expenditure, and household characteristics in Pakistan, Indonesia; and Guatemala (Mansuri and Healy, 2000; Chaudhary, Jalan, and Suryahad, 2002; Tesliuc and Lindert, 2002). Another study uses longitudinal data on rainfall in Ethiopia to estimate the vulnerability to poverty arising from variation in rainfall (Dabelen, Poupart, and Kline, 2002).12 These studies are part of the economic research, and are primarily concerned with the future risk of households falling below poverty line. Many indices of losses associated with natural disasters are not included in these studies. At the country level, there have been recent initiatives to measure and index vulnerability. The South Pacific Applied Geoscience Commission (SOPAC) is in the process of developing an Environmental Vulnerability Index (EVI), which will provide a general sense of the environmental condition and vulnerability of a country, particularly for small island developing countries (SIDS). It has included 54 indicators, covering natural hazards and information on national eco-system. The EVI has been developed and is now undergoing testing and refinement in order to make it a globally applicable tool.13

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The United Nations Development Programme (UNDP) is preparing a World Vulnerability Report. As part of the report, it is developing a Global Risk and Vulnerability Index at the national level. The index, which will rank countries in terms of their vulnerability to natural disaster losses, is based on a wide range of data, drawn from different sources. Among the data it has taken into consideration is the data on hazards, disaster losses, and socio-economic information. Social vulnerability is reflected through a number of indicators such as economic aggregates, resource endowments, demography, health and sanitation, capacity for disaster response, and corruption.14 These and similar other initiatives at indexing vulnerability at the national and sub-national levels are in progress. However, there is still a distance to go before there is a consensus on indices of vulnerability and their measurement. It is likely that these efforts at national indexing will provide the necessary framework for measuring and indexing vulnerability at the sub-national and community levels. V. Asset-based Approach to Disaster Risk Management 5.1 Evolving Mitigation Strategies In the last few decades, the nature of disaster mitigation has changed significantly. In the mid-20th century, the US, traditionally the world leader in disaster mitigation, was still almost entirely dependent on engineering measures. However, the structural approach generally failed to reduce the scale and cost of damages. In developing countries too, mitigation began with structural measures, particularly the construction of dams and embankments to reduce floods. These measures did not produce intended results; their consequences in terms of environment and displacement of settlements were indeed adverse. The failure of structural approach led to a steady shift towards non-structural approaches, which included land use planning, zoning restrictions, building codes and insurance schemes. Despite the emphasis on the management of human systems, these non-structural measures predominantly represent a technocratic model, focusing on hazards. It does not take into account social and economic vulner-

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ability of communities in developing countries, nor does it heed the cultural aspect of community life (Alexander, 1997). The alternative to these standard notions of mitigation planning is provided by community-based mitigation plans. However, despite all the rhetoric, the examples of successful community-based mitigation plans in developing countries are difficult to identify (Vatsa, 2000). Besides, community projects too do not address the central issue: how to provide more resources and information to households and communities and build more assets with a view to reduce their endemic vulnerability? While there is a greater agreement among experts and academics on reducing vulnerability, the literature on disaster management does not offer many ideas about how to reduce vulnerability. Interventions that are generally recommended for disaster risk reduction are from the conventional menu, borrowed from the literature of urban and regional planning and architecture. There is a surfeit of rhetoric about linking disaster management with development, but again there is no road map about securing the linkage. The interventions and instruments, which effectively link disaster management with development, have not been identified, let alone practiced. 5.2 Asset-based Approach to Mitigation Against this backdrop, an asset-based approach promises to be an innovative way of pursuing disaster mitigation and providing a bridge to development. The main premise of this approach is that the assets play a central role in reducing vulnerability. “The more assets people have, the less vulnerable they are. And the greater the erosion of their assets, the greater their insecurity” (Moser, 1997 p.2). By using a wider definition of assets, the approach establishes links with programs related to livelihood, human rights, social protection and social capital. It thus represents a comprehensive approach to risk management, drawing from different disciplines. Assets may be defined as the stock of wealth in a household, representing its gross wealth. Assets can be tangible, such as land, house, jewelry, savings, and education and skills, or intangible assets such as household relations, social capital, proximity to markets and health and education facilities, and empowerment. The economic literature emphasizes productive

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tangible assets as they generate financial returns. Sociologists and anthropologists often focus on intangible assets. However, there is growing consensus that both tangible and intangible assets, and their interplay, are important in the context of risk management of vulnerable households (Shearraden, 1991; Siegel and Alwang, 1999). The household asset-based approach traces its beginnings to Amartya Sen’s “entitlement” approach, developed in the context of famine. Sen in his classic book, Poverty and Famines (Sen, 1981), showed that famines could be attributed to failures in securing individual entitlements, which emanates from all the endowments (assets)—their labor, cash crops, or animals— at her or his command. The value of these endowments and related production activities is liable to collapse in relation to staple food prices, denying individuals and households the capacity to purchase food. A household’s failure to secure its entitlement is thus primarily a failure in exchange rate or terms of trade rather than crop or production failure. Though Sen’s concept of entitlements includes all the productive resources and tangible assets owned by a household, he has analyzed famine predominantly in terms of exchange and terms of trade failures. It does not always explain differential vulnerability within some communities and between similar communities apparently facing similar production or exchange failures. How can a particular community cope longer and better than other communities? Jeremy Swift (1989) therefore employs a wider meaning of assets as consisting of investments, stores and claims (Figure 3). “Assets in this broad sense are created when production leads to a surplus beyond immediate consumption requirements, and households use this surplus, willingly or unwillingly, to invest (including investment in better education or health), to build up physical stores of all sorts, and to “invest in claims’ by putting more resources into the community or government (p.11).” Investments, stores, and claims together build the asset profile of an individual or household. Asset-based approach was incorporated into the sociological / anthropological literature by the late 1980s, which expanded the concept of assets (Moser, 1998; Bebbington, 1999). It also came to be applied to the analysis

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of poverty (Reardon and Vosti, 1995; Attanasio and Székely, 1999). In the US, Michael Sherraden (1991) applied asset-based approach to social policy. According to Sherraden, assets exert impacts in ways that cut across economic, psychological, and institutional effects. Siegel and Alwang (1999) provide the most detailed exposition of asset-based approach in the context of social risk management. 5.3 Classification of Assets Assets can be classified in many ways. Distinctions may be made between enterprise assets and individual and household assets; productive and nonproductive assets; tangible and intangible assets; and the ease with which assets can be liquidated. Moser (1998) offers a five-fold classification of assets: labor, human capital, productive assets, household relations, and social capital. Another scheme of classification —natural, financial, physical, human and social assets—is more straight and clear as presented below (Siegel and Alwang, 2000; Sebstad and Cohen, 1999, p.15): Natural assets: Pasture, forests, fisheries, water: quality and quantity Financial assets: cash, savings, loans and gifts, regular remittances or pensions, other financial instruments; Physical assets: housing; buildings and land, and improvements to these; land and other physical items that maintain or increase in value, such as gold jewelry; and physical items that decrease in value, including consumer durables such as household appliances, shoes, clothing, and vehicles; and productive assets, including fixed-enterprise assets; Human assets: skills and knowledge, ability to labor, good health, selfesteem, bargaining power, autonomy, and control over decisions; and Social assets: networks, group memberships, relationships of trust, access to wider institutions of society, and freedom from violence.

Each category of assets has specific relevance for reducing vulnerability. Natural assets help households in reducing environmental stress, in addition to providing the necessary wherewithal for the physical assets (e.g., provision of water for irrigation of lands, and pastures for cattle). Financial

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assets can be used to smooth consumption, or they can be invested in a variety of ways that help smooth incomes. Physical assets can be pawned or mortgaged or turned into productive assets to increase household income. Human assets form the basis for labor mobilization, a key strategy for coping with shocks and stress events. Social assets are a critical source of financial and non-financial support in times of need, and clients place high priority on building and maintaining these assets (Sebstad and Cohen, p. 72). Depletion of assets in a certain category would have a corresponding impact on the associated vulnerability. An asset vulnerability matrix, which identifies indicators of increasing and decreasing vulnerability associated with a certain category of assets at the household level, has been presented below (see Figure 4): Figure 4: Asset Vulnerability Matrix Type of Assets

Indicator of Increasing Vulnerability

Indicator of Decreasing Vulnerability

Financial Assets

Withdrawal of savings

Sustained level of savings

Rise in indebtedness

Diversified financial investments

Loans for consumption

Credit for productive assets

Default or postponement of loan repayment

Loan repayment on schedule

Dependence on remittances

Availability of insurance

Lack of insurance

Availability of a wide array of financial instruments

Crop failure

Diversified cropping

Soil erosion and degradation of land

Soil and water conservation

Damaged and destroyed houses

Structural reinforcement of houses

Disruption or closure of businesses

Business continuity plans

Distress sale of household consumer durables

Increased level of security for house, crops, business and household goods

Physical Assets

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Illnesses and loss of health

Good health

Deaths and disability

Physical capacity to work

Poor nutrition

Availability of nutrition

Withdrawal from schools

Educational opportunities for children

Primary concern with coping strategy

Opportunities for learning skills

Bonded and child labor

Independence and self-esteem

Discrimination based on race, sex, caste or ethnicity

Relief and assistance based on equity and special needs of different social groups

Social disintegration and lack of trust

Community solidarity, cohesion, reciprocity and presence of social networks

Lack of participation in community Participation in community initiatives and volunteerism organizations Dependence on charity

Self-help and mobilization of community resources

Looting and criminal activities

Mutual support and cooperation

5.4 Household Assets, Risk, and Vulnerability A household’s level of assets has a positive, if not direct, relationship with its ability to deal with risks. The greater the household’s level of assets, more the capacity to cope with risk and the lower its level of vulnerability. A household must have a minimum level of assets to cope with risks. If the household does not have the bare essential assets, it slips to situation where it cannot cope with risks and reaches a breakdown point. The assetlevel of a household corresponds to its poverty level. Extremely poor households have lower level of assets. Moderate and vulnerable non-poor households have increasingly higher level of assets (Sebstad and Cohen, 1999). The interaction of assets with risk is always complex. It is not just the level of assets, but also the mix of assets that influence the capacity to manage risks. While the importance of financial, physical assets is obvious, hu-

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Figure 5: Relationship between Household Assets and Vulnerability

Capacity

Less Vulnerable

to

More Vulnerable

Asset Mix and Least Risk

Extreme Poor

BREAKDOWN

Moderate Poor

Vulnerabl e

POINT BARE ESSENTIAL ASSETS

Househol d

Source: Sebstad and Cohen, 1999

man and social assets have also emerged as important variables in risk management. Education, skills, and information equip households in dealing with risks in a more balanced way. Similarly, social cohesion, community networks, gender relations, and participation in social organizations, which are considered to be the expressions of social capital or assets, play important roles in responding to risks and crisis situations. A great deal of transactions, involving reciprocal arrangements, gifts, and loans, take place on the basis of expectations and obligations, helping households and communities. For example, human and social assets are more important for extremely poor households, while the moderate and vulnerable non-poor may find physical and financial assets more important (Vatsa and Krimgold, 2000; Sebstad and Cohen, 1999).

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Disasters can drastically alter a household’s portfolio of assets by either destroying them physically, or by dramatically reducing its value due to prolonged collapse of asset markets (Vosti, 1999). In Malawi, the food shock of 2001 is relatively small compared to 1991, yet its impact is far more severe in the country. Recent research evidence suggests that the current situation in rural Malawi, where three quarters of households corresponded to the poorest households in Tanzania and Uganda, is due to an erosion of Malawi’s assets over the last 10 years (Stevens, et.al. 2002). Households reallocate their assets in response to risks. They use their savings or insurance, draw down their physical stocks, borrow, sell or pawn assets, reduce expenditures, modify their consumption, or seek help from friends and relatives. A popular strategy is to make claims upon governments, NGOs, and international organizations, though such claims have their own limits. Reducing assets (including claims) makes households and communities more vulnerable, and its impact could be extended to processes within households, particularly in respect of gender and intergenerational assets and claims (Swift, 1989). For instance, it may result into withdrawal of children from schools, reduced nutrition for women, migration, or other desperate measures. Wealthier households allocate their assets more efficiently in dealing with their risks, and manage their risks with minimal welfare loss. Research findings collected during drought of 1999-2000 in Ethiopia indicate that well-off households achieve or maintain higher asset holdings (livestock, cash, equipment) due to their ability to fully respond to economic opportunity, purchase devalued assets from poorer households, and keep their assets and products off a devalued market. Asset-poor households find their accumulation constrained by an inefficient asset-mix (abundant land, but insufficient labor), declining values for their meager assets as markets for these goods also collapse, declining wages for their labor while costs of borrowing increase, and declining access to social networks and support institutions during periods of massive depletion (Little, 2002, p.2). However, differential vulnerability between communities may always vary. For exam-

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ple, the urban poor, though often very poor, make more effective claims upon the government assistance compared to the urban poor (Swift, 1989). Diversification of household assets and income-generating opportunities improves risk management at the household level. Multiple assets can increase creditworthiness of a household, thereby improving their ability to borrow during a crisis. Households can engage in small businesses, off-farm employment, and seasonal migration arrangements. The rural poor engage in farming and livestock husbandry, in gathering wild food and fuel, and in the nonagricultural sector (Vosti, 1999). Reardon, et.al. (1988) document the practices of poorer households in Burkina Faso to spread income risks across occupations and across space (cited in Seigel and Alwang, 1999). Pastoralists of East Africa increasingly pursue non-pastoral strategies to meet consumption needs and to buttress against shocks caused by climatic fluctuations, animal disease, market failures, and insecurity (Little, et.al., 1999). As stated earlier, the poorest households are characterized by low asset endowment, and therefore, they tend to reach the threshold of collapse much faster. Poorer households also tend to adopt risk management strategies that concentrate in lower risk and lower return assets, trapping them in the vicious cycle of poverty (Swift, 1989; Jalan and Ravallion, 1998). 5.5. Level of Assets and their Interaction The capacity to reduce risk and vulnerability depends not only upon the initial assets and endowments, but also by the ability to transform such assets into income, food, or other basic necessities in an effective manner. Factors at household, intra-household, community and extra-community levels determine both the use of assets and the strategies adopted during the periods of crisis and disasters. At the level of households, factors which influence its response to a major shock are changes in household structure, composition, and headship, care of children and the elderly, and domestic violence. Intrahousehold factors basically refer to gender-based differences, which influence the process of resource allocation within a household. Within a household, the distribution of impact and resources in a crisis or disaster situation are different for men and women, and boys and girls. At the community

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level, the extent to which a disaster or crisis has increased or eroded social capital may have long-term consequences for recovery strategies (Moser, 1997). At the extra-community level, labor, commodity and financial markets determine the economic returns, and political and institutional factors determine relief, assistance and security. There are strng linkages between different levels which allow household assets to draw on community and extra-community assets. Households seek community and government’s help in strengthening flood control measures at the local level. Flood and cyclone shelters, which are community assets, can protect many household assets. Governments may provide financial assistance to households for undertaking seismic strengthening of their houses. These strategies may then create cross-boundary asset pools and broaden the risk pool. Assets enlarge the risk pool, creating incentives for households to contribute to the risk pool and draw upon its resources. The asset-based approach, by using assets in a broader sense, embodies elements of sustainable livelihoods and rights-based approaches, which have been advanced by many stakeholders in international development. Its strength lies in using multiple levels of assets—tangible and intangible—for managing risks. However, asset-risk interaction needs to be investigated more empirically to ascertain how different categories of assets correlate with outcomes of risky events at the household level. Research on these issues will provide better information on the component or a mix of assets required for dealing with a certain type of risk. VI. Asset-building Strategies for Disaster Management The discussion above underscores the importance of following a more comprehensive approach to reducing risk and vulnerability. Such a strategy needs to connect the conventional measures of disaster management to the world of development: financial assets, livelihoods, social protection, community networks, housing, and information sharing. Interventions that promote these issues could be used effectively for managing disaster risks. Different components of the strategy and their application for ex-ante and ex-post risk management are presented in a matrix below, followed by a discussion:

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Figure 6: Asset-building and Risk Management Asset-building Strategy

Ex-ante Risk Management

Ex-post Risk Management

Building Financial Assets

· Flexible savings

· Withdrawal of savings

· Credit for asset-building

· Re-scheduling loan repayment

· Affordable insurance

· Insurance payments

· Diversification of income-earning opportunities

· Assistance for business recovery

· Provision of training in skills

· Assistance for resumption of economic activities

· Management of natural and common property resources

· Commence large-scale public works

Promoting Livelihoods

· Reconstruction as an opportunity for employment generation Investing in Housing

· Improvement in sites and services

· Post-disaster reconstruction

· Wind- and seismic-resistance housing

· Application of disaster-resistant technology in reconstruction

· Relocation Supporting Social · Microfinance for vulnerability Protection and deduction Safety Nets · Social / calamity Funds · Public works (Employment Generation) programs

· Cash transfer · Food distribution · Social insurance · Public works (Employment Generation) programs

Strengthening Community Networks

· Community-based mitigation Programs

· Community participation in recovery and reconstruction

·Special programs for vulnerable social groups such as women

· Group insurance payment

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· Risk and vulnerability mapping

· Information upon post-disaster recovery and reconstruction

· Early warning · Household and community-level Preparedness

· Information upon mitigation solutions financial mechanisms for mitigation investment

6.1 Providing Financial Services Households need to avail of financial services to the households—savings, credit, and insurance—to reduce the impact of a major shock. Many households borrow, more do save, and all seek informal, if not formal, insurance. The choice of these services depends upon the household situation. Credit is obtained more for economic activities, and helps to reduce risk (income smoothing). Savings can provide more efficient self-insurance to help mitigate and cope with risk (consumption smoothing). Formal insurance may not be affordable for the households, but they seek insurance through their savings and other physical assets (Siegel, 2000). In developing countries, government is the primary source of disaster assistance for households. Governments provide assistance through their own resources or by borrowing from international financial institutions. In the private sector, formal banking sector, insurance companies, and microfinance institutions can provide a wide array of financial services and products, specifically designed for disaster risks. Flexibility and heterogeneity of financial services and instruments offer more alternatives to households in managing their risks. 6.2 Promoting Livelihoods One of the important steps is to expand livelihood opportunities for the people living in vulnerable situations. It may involve different strategies suited to particular hazards. For example, those likely to be affected by drought may be assisted for preventing soil erosion, water resource management, dry land farming, social forestry, and common property resource management. Households facing floods, cyclones and earthquakes may be assisted with productive assets such as restoration of their business premises, resumption of fishing operations, or replacement of their agricultural imple-

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ments. Training in different trades can also be organized for the people who have to seek alternative sources of employment. Governments may begin large-scale public works, which could provide employment to the people affected by a disaster event. Poor households have labor as their greatest asset. In face of a disaster, a frequent response by poor households is to migrate or mobilize additional labor—principally women’s labor and sometime even children’s labor. These strategies have their own welfare losses. If households have more diversified livelihood opportunities, they may avoid these losses, and maintain their level of economic and social well-being. A number of international agencies such as the DFID, UNDP, CARE International and Oxfam are working on sustainable livelihood approaches. These organizations have also underscored the importance of including livelihood strategies in their disaster-related interventions (Carney et al. 1999, cited in Sanderson, 2002). 6.3 Investing in Housing Housing is an important productive asset that can cushion households against most of the big and small shocks. When households have secure ownership of houses, they often use this asset with particular resourcefulness when other sources of income are reduced. Homeowners use their housing as a base for enterprises or rent it to raise income. They sell part of their plot or, as a last resort, all of their property. They save “imputed rent” that would otherwise be added to household expenditure. And they use their housing as a tool for extending personal relationships and generating social capital (Moser, 1997, p. 7). Housing can be promoted through infusion of public and private resources. These resources need to be mobilized for the construction of new and better houses, strengthening of existing houses, and improvement in sites and services. People who live in unsafe conditions could be assisted to move in safe and better houses. For instance, people living in flood-prone areas could be helped with simple flood prevention measures such as rising of plinths or building on stilts or even relocating. Insurance schemes could be tied to specific mitigation measures. These policies could be pursued through building incentives, and developing adequate legal and institutional

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frameworks. The government alone cannot promote housing. Financial institutions and non-governmental organizations need to partner with the government in encouraging housing sector. 6.4 Supporting Social Protection and Safety Nets Social protection or safety net programs assist individuals, households, and communities to better manage a wide range of risks that leave people vulnerable. These programs deal with both the absolute deprivation and vulnerability of the poorest people and also with the need of the currently non-poor for security in the face of shocks and life-cycle events. A number of safety net programs are in nature of income support or social insurance. In view of its equity-enhancing and social investment functions, it has received widespread support from governments and development agencies. Despite its growing portfolio worldwide, the agenda of social protection has not yet been linked very effectively to disaster risk reduction. Though the literature recognizes the potential of safety nets for disaster risk reduction, in practice, there have not been many successful examples (IDB, 2000). Applying social protection programs for disaster management will mean introducing both ex ante and ex post measures, with a view to reduce disaster risks. In practice, ex ante measures will include credit, subsidy and assistance for improvement in shelter, flood protection, crop management, and diversification of livelihoods, whereas ex post measures will mean using the financial services for resumption of economic activities, reconstruction, and even consumption. Among the instruments and services, which could be used for both ex ante and ex post risk management, are microfinance, social funds, insurance, and public works program. Safety net programs involve targeting of the people who are the most vulnerable or most affected. However, in very low-income countries, such as Ethiopia, Nepal and Malawi, almost everyone is poor or affected. Besides, in these poor countries too, there is a group of ultra-poor, which needs to be supported very directly. Some of the options that could be used for these groups involve cash transfers (selected / universal), food programs (free distribution, food stamps, school-feeding, etc.), food subsidies, agricultural inputs (subsidies, free packs), and health and education fee waiver

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programs (Smith and Subbarao, 2002). In almost all the low-income countries, underlying vulnerability and institutional weaknesses are so serious that a simple intervention would not work. It would require multiple interventions, encompassing both short- and long-term measures. 6.5 Strengthening Community Networks The importance of community networks in mobilizing human, social and financial assets has been demonstrated in recent disasters. A generous international assistance for the Gujarat earthquake in 2001 could be attributed to the political and commercial strength of the non-resident Gujarati community in a number of developed countries (Vatsa, 2002). Similarly, El Salvador tapped a large amount of resources through remittances from millions of expatriates after the earthquake in 2001. These social networks could be strengthened through participatory programs. Group-based insurance programs and community-based mitigation programs could be among the interventions required to promote community networks. An important component of community programs is to support women with special programs. In Honduras, women coped with hurricane Mitch by mobilizing formal and informal social networks and organizing women’s groups to meet needs, organize temporary shelters, and coordinate relief efforts. They also used kin networks to take in affected family members (Corrieia, 2001). Women also participated in construction of shelter and digging of wells and ditches. In Maharashtra, India, after the Latur earthquake of 1993, women’s participation in the seismic repairs and strengthening program facilitated successful completion of owner-driven earthquake reconstruction program. 6.6 Sharing Information and Knowledge One of the valuable assets is information and knowledge that could be used for risk management at the household and community level. Through electronic media and Internet, one can immediately get an access to data, and see how a river is rising, track a tornado or hurricane, or observe the likely extent of damage caused by an earthquake that just occurred. One can access the latest information on disaster resistant design, regions of high and low

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risk, sources of emergency supplies, preparedness plan, and more. A risk and vulnerability mapping can be undertaken to inform the people of their risks and how to deal with these risks. The information could also be used to seek the attention of decision-makers and enhance claims upon national and international resources. Several factors influence the value of information and knowledge. The credibility of source, clarity of the message, and simplicity of solutions are some of the important factors that help households to act upon the information. Risk communication strategy is thus an essential part of the risk management strategy. Though in the recent times, the global connectivity has increased significantly, a digital divide still exists in developing countries. An important challenge lies in widening the channels of communication and providing relevant information to the individuals, households and communities for taking more informed decisions. 6.7 Conclusion An increasing concern about vulnerability in disaster management has reflected into programs that concentrate on households and communities. The above-mentioned strategies form the integral part of these programs and interventions, helping households and communities in accumulating assets, and thus increasing their resilience and capacity to manage risks. With a balanced mix of assets at their disposal, households are empowered to address all kinds of risks: health and employment risks which arise frequently, lifecycle risks related to old age and loss of income, and infrequent disaster risks causing major losses. It provides a sense of personal and social security, which is critical to households’ well-being. The relative importance of these strategies would depend upon the risk exposure and coping strengths of households and communities. While certain households or communities can prepare or recover through access to financial resources, there would be many others who would require social protection measures and safety nets. Similarly, housing would be a critical asset for reducing the risk of floods and earthquakes. It could, however, be said that while access to financial resources, and sharing information and

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knowledge are emerging as the transformative strategies for reducing vulnerability, other strategies are more relevant for coping and sustenance. Whether governments would extend the necessary support to households for building their assets or these should be driven by market incentives, is an extremely important issue. A policy choice would be guided by the context in which these interventions are called for. In respect of access to financial services and housing, market institutions can implement a more feasible strategy, while governments are more effective in implementing social protection and safety net measures and encouraging community networks. Both governments and market institutions can play a mutually supportive role in creating livelihood opportunities and improving public access to information and knowledge. A strong public policy support for asset-based approaches would encourage both the governments and market institutions to increase their commitment of resources for risk management at the household and community level.

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Endnotes 1. A household is a unit of social production with common eating arrangements. 2. The Royal Society’s report in 1983, which strengthened the international orthodoxy on the subject of risk, became a major work of reference. In 1992 when the Society returned to the subject with a new report entitled Risk: analysis, perception and management, it was a significant deviation from the earlier formulation of risk, sparking differences between physical and social scientists. The Royal Society disowned the report, stating therein that the “views expressed are those of the authors alone” and that it was merely “a contribution to the ongoing debate”. 3. In Germany, Beck had a major impact on environmentalist politics and thinking, but in the English-speaking world that impact has been considerably lessened by the gap between original publication and translation (Beck’s book was published in Germany in 1986; the English translation appeared in 1992). 4. Most of the papers produced by the The Risk Management and Decision Processes Center, Wharton School and International Institute for Applied Systems Analysis (IIASA), Austria on the subject of catastrophic risk do not refer to social vulnerability. 5. For a detailed discussion, see Alwang, Siegel and Jørgensen, 2001. It presents a review of perspectives on vulnerability provided by different disciplines. 6. http://www.guardian.co.uk/naturaldisasters/story/0,7369,439143,00.html 7. http://www.ecu.edu/coas/floyd/papers/floyd007.pdf 8. The Project Impact was a community-based mitigation program launched by the Federal Emergency Management Agency (FEMA) in 1997. The program was recently discontinued. 9. Information on NOAA’s vulnerability assessment method is available on www.csc.noaa.gov/products/nchaz/htm/step1.htm.

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10. The FEWS project conducts annual assessments of the ability of populations within numerous countries to meet their consumption requirements since 1988. Steps involved in FEWS are preseason VA, season monitoring, special alerts and warning, and contingency planning. More information is available on www.fews.net. 11. More information on VAM is available on www.wfp.it/vam_documents/. 12. These papers were presented in a workshop organized by the World Bank and International Food Policy Research (IFPRI) on “Risk and Vulnerability”. 13. The information on EVI is available on the following site: http://cobalt.sopac.org.fj/Evi/. 14. The World Vulnerability is under preparation.

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References Adams, John. 1995. Risk. London: UCL Press. Alexander, David. 2000. Confronting Catastrophe, New Perspectives on Natural Disaster. New York: Oxford University Press. Alexander, David E. 1997. “The Study of Disasters 1977-1997: Some Reflections on a Changing Field of Knowledge.” Disasters 21(4): pp.284-304. Alexander, David E. 1993. Natural Disasters. University College London Press, London, and Kluwer Academic Publishers, Dordrecht and Boston, p. 632. Alwang, Jeff, Paul Siegel, and S. Jorgensen. 2001. “Vulnerability: A View from Different Disciplines.” SP Discussion Paper No. 0115. Social Protection Unit. The World Bank. Anderson, Mary B. and Woodrow, Peter J. 1998. Rising from the Ashes, Development Strategies in Times of Disaster. Lynne Rienner Publishers. Boulder, Colorado. Arnold, Christopher. 1984. “Techniques of Vulnerability Assessment.” Proceedings of the International Conference on Disaster Mitigation Program Implementation. Ocho Rios, Jamaica. November 12-16. Virginia Polytechnic Institute and State University. Attanasio, Orazio and Szekely, Miguel. 1999. “An Asset-Based Approach to the Analysis of Poverty in Latin America.” IDB-OCE Working Paper No. R-376. Posted on www.cofi.ecn.ulaval.ca/privdom/PDocs/R-376.pdf. Bass, Batjargal, and Swift. 2001. “Pastoral Risk Management for Disaster Prevention and Preparedness in Central Asia with Special Reference to the case of Mongolia.” Paper presented in Asia-Pacific Conference on Early Warning, Prevention, Preparedness and Management of Disasters in Food and Agriculture, Chiangmai, Thailand. 12-15 June. Mimeo. Bebbington, A. (1999). “Capitals and Capabilities: A Framework for Analyzing Peasant Viability, Rural Livelihoods and Poverty.” World Development. 27: pp.2021-2034.

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Beck, U.(1992a). Risk Society: Towards a New Modernity. London: Sage Publications, 1992. Blaikie, P., T. Cannon, I. Davis, I. and B. Wisner.1994. At Risk - Natural Hazards, People’s Vulnerability, and Disasters. London: Routledge. Bolin, Robert and Stanford, Lois. 1999. “Constructing Vulnerability in the First World: The Northridge Earthquake in Southern California, 1994.” In. Anthony Oliver-Smith and Susanna M. Hoffman (eds.). The Angry Earth, Disaster in Anthropological Perspective. New York and London: Routledge. Canon, Terry. 1994. “Vulnerability Analysis and the Explanation of “Natural’ Disasters”. In A. Varley (ed.) Disasters, Development and Environment. Chichester: John Wiley & Sons. Cannon, Terry.1993. “A Hazard Need Not a Disaster Make: Vulnerability and the Causes of Natural Disasters.” In P. A. Merriman and C. W. A. Browitt. (Eds). Natural Disasters, Protecting Vulnerable Communities. Proceedings of the Conference held in London, 13-15 October 1993. London: Thomas Telford. Chambers, Roberts. 1989. “Vulnerability, coping and policy.” IDS Bulletin 20(2): 1-7. Chaudhuri, Shubham, Jalan, Jyotsna, and Suryahadi, Asep. 2002. “Assessing Household Vulnerability to Poverty from Cross-sectional Data: A Methodology and Estimates from Indonesia.” Columbia University, Department of Economics, Discussion Paper Series. New York, NY: April 2002. Posted on http://www.ifpri.org/events/conferences/2002/092302/chaudhuri.pdf. Coburn, Andrew, Spence, Robin, and Pomonis, A. 1994. “Disaster Mitigation.” 2nd Edition. Disaster Management Training Programme. UNDP. Comerio, Mary. 1998. Disaster Hits Home, New Policy for Urban Housing Recovery. Berkeley: University of California Press. Correia, Maria. 2001. “Hurricane Mitch-the Gender Effects of Coping and Crisis.” PREM Notes, World Bank, Posted on http://www1.worldbank.org/prem/PREMNotes/premnote57.pdf.

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Cunningham, Wendy, and William Maloney. 2000. Measuring Vulnerability: Who Suffered in the 1995 Mexican Crisis? Latin America and Caribbean Sector Management Unit for Poverty Reduction and Economic Management. The World Bank. Dabalen, Andrew, Poupart, Nadine and Kline, Patrick. 2002. Vulnerability to Rainfall Shock in Ethiopia. Posted on http://www.ifpri.org/events/conferences/2002/092302/dabalen.pdf. Dercon, S. (1999). Income Risk, Coping Strategies and Safety Nets. Mimeo prepared for the 2000/1 World Development Report. Katholieke Universiteit Leuven. Devereux, Stephen. 2002. State of disaster: Causes, consequences & policy lessons from Malawi. ActionAid. Posted on http://www.actionaid.org/newsandmedia/the_malawi_famine_of_2002.pdf. Downing, Thomas E., and Karen Bakker. 2000. “Drought discourse and vulnerability.” In. Donald A. Wilhite (ed.). Drought: A global assessment, vol. 2, 213-230. London: Routledge. Enarson, Elaine. 2000. Gender and Natural Disasters. Recovery and Reconstruction Department. International Labor Organization. Geneva. Posted on http://www-ilo-mirror.cornell.edu/public/english/employment/recon/crisis/download/criswp1.pdf. Erdik, Mustafa. 2001. “Recovery after 1999 Kocaeli and Duzce (Turkey) Earthquakes.” Paper presented in the International Workshop on Earthquake Safer World in the 21 st Century, January 29-31. Posted on http://www.hyogo.uncrd.or.jp/ws2001/proceedings/ws_cdrom/6_symposium/6-4_panel3/6-4-3_erdik/erdik.pdf. Fafchamps, Marcel. 1999. Rural Poverty, Risk and Development. Report Submitted to Food and Agriculture Organization. Posted on http://www.econ.ox.ac.uk/members/marcel.fafchamps/homepage/fao3.pdf. Giddens, A. 1990. The Consequences of Modernity. Cambridge, UK: Polity Press.

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Glewwe, P. and G. Hall. 1998. “Are Some Groups More Vulnerable to Macroeconomic Shocks than Others? Hypothesis Tests Based on Panel Data from Peru,” Journal of Development Economics. Vol 56, pp 181-206. Hewitt, Kenneth. 1997. Regions of Risk, A Geographical Introduction to Disasters. Essex: Longman. Holzmann, Robert and S. Jorgensen. 1999. “Social Protection as Social Risk Management: Conceptual Underpinnings for Social Protection Sector Strategy Paper.” SP Discussion Paper No. 9904. Washington, D.C.: World Bank. Holzmann, Robert. 2001. Risk and Vulnerability: The Forward looking Role of Social Capital in a Globalizing World. Paper prepared for The Asia and Pacific Forum on Poverty—Policy and Institutional Reforms for Poverty Reduction, Asian Development Bank, Manila, February 5-9. 2001. International Federation of Red Cross and Red Crescent Societies (IFRC). 1999. World Disaster Report. Geneva. International Federation of Red Cross and Red Crescent Societies (IFRC). 1999. Vulnerability and Capacity Assessment. An International Federation Guide. Geneva Inter-American Development Bank (IDB). 2000. Social Protection for Equity and Growth. Washington, DC. Jalan, J. and M. Ravallion (1998). “Transient Poverty in Postreform China.” Journal of Comparative Economics. Vol 26, pp. 338-357. Kunreuther, Howard. 2002. “Risk Analysis and Risk Management in an Uncertain World.” Risk Analysis. Vol. 22 No. 4 pp. 655-64. Kunreuther, Howard. and Slovic, Paul. 1996. “Science, Values and Risk.”. Annals. AAPSS, 545. May. pp. 116-25. Little, Peter D. 2002. “Building Assets for Sustainable Recovery and Food Security.” BASIS Brief No. 5. Posted on http://www.basis.wisc.edu/live/basbrief05.pdf. Little, P.D., Cellarius, B., Barrett, C., and Coppock, D.L.. 1999. “Economic Diversification and Risk Management among East African Herders: A Pre-

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liminary Assessment and Literature Review.” Pastoral Risk Management Research Brief 01-08-PARIMA. Utah State University, Logan. Posted on http://glcrsp.ucdavis.edu/project_subpages/PRMP_folder/Research%20Briefs/PARIMA8_Little.pdf. Mansuri, G. and A. Healy (2000). “Vulnerability Prediction in Rural Pakistan.” Development Research Group. The World Bank. Posted on http://www.ifpri.org/events/conferences/2002/092302/mansuri.pdf. Miller, Kristen and Nigg, Joanne M. 1993. “Event and Consequence Vulnerability: Effects on the Disaster Recovery Process.” Paper presented at the annual meeting of the Eastern Sociological Society, Boston, MA. March 25-28. Posted on http://www.udel.edu/DRC/preliminary/217.pdf. Morduch, Jonathan. 1999. “Between the state and the Market: Can informal insurance patch the safety net?” The World Bank Research Observer 14 (2): pp. 187-207. Morduch, Jonathan. 1995. “Income Smoothing and Consumption Smoothing.” Journal of Economic Perspectives 9 (3): pp. 103-14. Moser (1998), “The Asset Vulnerability Framework: Reassessing Urban Poverty Reduction Strategies”, World Development vol.26, no.1, pp. 1-19. Moser, Caroline. 1997. Household Responses to Poverty and Vulnerability. Volume 1: Confronting Crisis in Cisne Dos, Guayquil, Ecuador. Urban Management Programme, Report 21 Washington, D.C.: The World Bank. Narayan, Deepa, Robert Chambers, Meera K. Shah, and Patti Patesch. 2000. Voices of the Poor. Crying Out for Change. New York: Oxford University Press for the World Bank. ODI. 2002. Famine and the Failure of Development, Southern Africa 2002. Posted on http://www.odi.org.uk/southern_africa/report.html. Quarantelli, E. L. 2000. Urban Vulnerability to Disasters in Developing Societies: The Need for New Strategies and for Better Applications of Valid Planning and Managing Principles. Mimeo.

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Reardon, Thomas and Stephen A. Vosti. 1995. “Link Between Rural Povety and the Environment in Developing Countries: Asset Categories and Investment Poverty,” World Development. Vol. 23: 9, pp. 1495-1506. Reardon, Thomas., Matlon P., and Delgado C.. 1988. “Coping with Household- level Food Insecurity in Drought-Affected Areas of Burkina Faso,” World Development, 16 (9): pp. 1065-1074. Ribot, Jesse C., A.R. Magalhaes, and S. Panagides. 1996. Climate Variability, Climate Change and Social Vulnerability in the Semi-Arid Tropics. Cambridge: Cambridge University Press. Sanderson, David. 2000. “Cities, disasters and livelihoods,” Environment and Urbanization, October. Volume. 12, No. 2, pp. 93-102. Sebstad Jennefer. and Monique Cohen. Editors. 1999. Microfinance, Risk Management, and Poverty, Synthesis Report. Draft. USAID. Washington, D.C. Sen, Amartya. 1981. Poverty and Famines: An Essay on Entitlement and Deprivation. Oxford: Oxford University Press. Sherraden, Michael. 1991. Assets and the Poor. Armonk, N.Y.: M.E. Sharpe. Slovic, Paul and Weber Elke U. 2002. “Perception of Risk Posed by Extreme Events.” Paper prepared for discussion at the conference “Risk Management strategies in an Uncertain World,” Palisades, New York, April 12-13. Posted on http://www.ldeo.columbia.edu/CHRR/Roundtable/slovic_wp.pdf. Swift, Jeremy. 1989. Why are Rural People Vulnerable to Famine? IDS Bulletin. Vol. 20 (2): pp. 8-15. Siegel, P. 2000. “Towards an Integrated Approach for Risk Management in Rural Areas: Guiding Principles”. Paper Presented at the UNDP-World Bank Sponsored Colloquium on Microfinance: Disaster Risk Reduction for the Poor. February 2. The World Bank.

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Siegel and Alwang. 1999. An Asset-based Approach to Social Risk Management: A Conceptual Framework. Social Protection Discussion Paper 9926. World Bank. Sinha, S. and M. Lipton (2000). Undesirable Fluctuations, Risk and Poverty: A Review. University of Sussex. Mimeo. Smith, Jim and Subbarao Kalanidhi. 2002. Safety Nets in Very Low-Income Countries. Posted on http://www.worldbank.org/wbi/socialprotection/srm/parisone/pdfpaper/incomeeng.pdf. Stevens, Christopher, Devereux, Stephen, and Kennan, Jane. 2002. The Malawi Famine of 2002: More Questions than Answers. Posted on http://www.odi.org.uk/southern_africa/devereux.pdf. Tesliuc, Emil D. and Lindert, Kathy. 2002. “Vulnerability: A Quantitative and Qualitative Assessment.” Guatemala Poverty Assessment Program. The World Bank. Posted on http://www.ifpri.org/events/conferences/2002/092302/tesliuc.pdf. Toothill, Jane. 2002. “Central European Flooding.” August 2002. An EQECAT Technical Report. Posted on http://www.absconsulting.com/EQECAT%20flood/flood_rept.pdf. Oxfam, 1995. The Oxfam Handbook of Development and Relief. Vol. 1 Oxford: Oxfam.. Twigg, John. 2001. Sustainable Livelihoods and Vulnerability to Disasters. Posted on http://www.benfieldhrc.com/DMU/WorkingPapers/workingpaper2.pdf. Udry, C., (1994), “Risk and insurance in a rural credit market: An empirical investigation of Northern Nigeria" Review of Economic Studies, 61, no.3, pp. 495-526. Udry, Christopher 1990. “Credit Markets in Northern Nigeria: Credit as Insurance in a Rural Economy.” The World Bank Economic Review. 4 (3): pp. 251-69. Varley, Ann (ed.) 1994. Disasters, Development and Environment. Chichester: John Wiley & Sons.

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Vatsa, Krishna 2002. “Government Response and Socio-economic Impacts.” Spectra. Supplement A to Volume 18 Earthquake Engineering Research Institute. Oakland. Vatsa, Krishna. and F. Krimgold. 2000. “Financing Disaster Mitigation for the Poor”. In. Managing Disaster Risk in Emerging Economies. Eds. A. Kreimer and M. Arnold. World Bank. Vatsa, Krishna. 2000a. Notes on Vulnerability. Department of Engineering Management, George Washington University, Washington, D.C. Mimeo. Vosti, Stepehen. 1999. Understanding and Coping with Natural Disasters: El Nino in Latin America and the Caribbean. Mimeo. Westgate, K. N., and P. O’Keefe. 1976. “Some Definitions of Disaster.” Disaster Research Unit Occasional Paper 4. University of Bradford, Department of Geography. U.K. White, Gilbert F. 1961. Papers on Flood Control. Chicago: University of Chicago Department of Geography. Winchester, Peter. 1992. Power, Choice and Vulnerability, A Case Study in Disaster Management in South India. London: James and James Science Publishers, Ltd. Wisner, Ben. 1993. Disaster Vulnerability: Scale, Power and Daily Life. Posted on http://online.northumbria.ac.uk/geography_research/radix/resources/dailylife93.doc. World Bank. 2000. World Development Report 2001/2. Oxford: Oxford University Press for the World Bank.

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Web Sites http://www.udel.edu/DRC/preliminary/217.pdf www.csc.noaa.gov/products/nchaz/htm/step1.htm. www.usaid.gov/fews/va/vaterms.html#fews&va www.wfp.it/vam_documents/ http://www.guardian.co.uk/naturaldisasters/story/0,7369,439143,00.html http://www.ecu.edu/coas/floyd/papers/floyd007.pdf http://cobalt.sopac.org.fj/Evi/.