Show Summary Details

Page of

Printed from Oxford Research Encyclopedias, Natural Hazard Science. Under the terms of the licence agreement, an individual user may print out a single article for personal use (for details see Privacy Policy and Legal Notice).

Subscriber: null; date: 02 March 2021

Politics and Policies for Managing Natural Hazardsfree

  • Timothy Mulligan, Timothy MulliganWayne State University, Department of Political Science
  • Kristin TaylorKristin TaylorWayne State University, Department of Political Science
  •  and Rob A. DeLeoRob A. DeLeoBentley University

Summary

Policies to manage natural hazards are made in a political context that has three important characteristics: local preferences and national priorities, short-sighted political decision-making, and policy choices informed by experience instead of future expectations. National governments can set broad policy priorities for natural hazard management, but it is often local governments, with conflicting policy priorities and distinctive hazard profiles, that have the authority to implement. Moreover, legislators who are tasked with passing laws to put policies into force are rewarded with reelection by voters who are only concerned with issues that have an immediate impact on their day-to-day lives (e.g., the economy) as opposed to hazards that may or may not occur until some undetermined point in the future. Finally, legislators themselves face challenges making policies to mitigate and manage hazards because they fail to see the longer-term risks and instead make decisions based on past experiences. This article broadly lays out the challenges of the policy environment for natural hazards, including intergovernmental concerns, policy myopia, and shifting policy priorities. It also describes the politics shaping the management of natural hazards, namely, electoral politics, the social dynamics of blame assignment, and the various political benefits associated with disaster relief spending.

Introduction

Disasters are political events (Platt, 2012). As such, natural hazard management does not occur in a vacuum. Instead, it is shaped by a dynamic and complex political context that can either promote or, more often than not, inhibit, effective disaster governance. From the electoral goals of incumbent politicians to the degree of structural fragmentation within a political system, emergency managers must contend with many political factors when advocating for and adopting policies aimed at reducing the risks associated with human-made and naturally occurring hazards.

The idea of a political context for policies to manage natural hazards implies that these so-called “public risk” policy domains entail characteristics that make them discernable from other areas of policymaking, such as economic or social policy. Policy domains describe components of the political system “organized around substantive issues” (Burstein, 1991, p. 328). Each domain differs in terms of its subject matter, patterns of interest group interaction, and even key decision-making venues. Moreover, whereas some domains garner significant and sustained media attention, others tend to operate outside of the watchful eye of the public, at least until some sort of focal event or controversy sheds light on problems within the policymaking system (Birkland, 1998). Nor are domains static. Instead, they are marked by intense internal competition as competing subsystems or constellations of like-minded interest groups, experts, and politicians are constantly trying to reconfigure a domain’s internal power dynamics in ways that accentuate their own goals and priorities (Baumgartner & Jones, 2009).

In short, each domain is different and therefore warrants special attention. Disaster management resides within the category that policy scholars refer to as “public risk domains.” Public risks domains are distinctive in that they lack an organized public. Specifically, very few organized interest groups readily mobilize and advocate for policy to prepare for or recover from disaster. The domain of policymaking on natural hazards is dominated by bureaucrats, scientists, and other individuals with a high level of technical expertise (Burby & May, 1998; May & Koski, 2013).

This is not to say that elected officials are somehow irrelevant. On the contrary, elected officials at all levels of government play a critical role in shaping policymaking outcomes in public risk domains. From formulating policy to allocating funds, to executing laws to overseeing administration, elected officials are the dynamos of any political system. Effective hazard management hinges on decisions rendered in the political arena.

Hazard and disaster management occur in other countries with different approaches, political ideologies and values, and systems of government and governance. And in some instances, international and financial institutions help shape hazard and disaster policies that sovereign countries formulate and adopt (Coppola, 2006). It is within this context that this article investigates the political dimensions of hazard management in the United States. The United States is a federal system of government, where lessons about layered or nested government structure can be extended to other counties with similar governance systems. The United States also faces a wide variety of natural hazards and disasters that make its experience formulating and adopting policies to manage natural hazards insightful for other countries. This article highlights other countries as appropriate in the discussion of the concepts.

Close attention is paid to the various impediments to effective disaster management. Chief among these concerns is the inherent strain between preparing for emerging hazards and responding to existing crisis. Hazard management is typically characterized as being reactive, meaning policymakers rarely invest in programs that aim to stave off or prepare for future threats. Instead, substantive policy change typically occurs in the wake of disaster, a policy sequence that has been shown to result in an unnecessary loss of economy and, at times, life. Not only does this curious policy sequence expose citizens to risk, but it is also an inefficient use of resources. For example, studies suggest that every $1 dollar spent on disaster preparedness could offset nearly $15 in future damages (Healy & Malhotra, 2009).

Politics for Managing Natural Hazards,” outlines the intergovernmental context for hazard management, including the distribution of authority within public risk domains. And the following section, “Electoral Politics and Natural Hazards: Myopic Voters, Retrospective Voting, and Anticipatory Policymaking in Hazard Management,” examines the effect of myopia, or shortsightedness, in natural hazards policy. Myopic behaviors are considered by political scientists to be one of the one of the most significant barriers to preparedness policy, at least within the context of emergency management policy. Myopic voting refers to the tendency of voters to reward politicians for relief policy, but not preparedness policy. “The Politics of Blame and Responsibility in Hazard Policies” then examines the systemic political bias that U.S. government institutions have to favor disaster relief over preparedness. Finally, the “Conclusion” considers a number of gaps in the existing literature on the politics of hazard management and reactive policymaking.

Policies for Managing Natural Hazards

In the United States the patchwork of federal, state, and local policies to manage hazards has been conceived in terms of “pre-disaster” activities in the mitigation and preparedness stages that are not triggered by a specific disaster and in the “after-impact” stages of the cycle that include response and recovery, which are reactive in nature (Lindell & Perry, 2000). It is useful to consider these activities as interrelated and to some extent mutually reinforcing. In the political and policymaking context, the dominant paradigm for hazard management has been one of federal support and local responsibility, with periods of national policy activism (Taylor & Birkland, 2019). The effect of this paradigm for hazard management and mitigation has been to create policies that at times increase hazard risk (Miletti, 1999) or policies that provide relief at the expense of preparedness and mitigation (Cooper & Block, 2007; Platt, 2012).

An example of federal activism in the “local responsibility–federal support” paradigm is evident in the case of the Biggert-Waters Flood Insurance Reform Act (PL 113-89), which Congress passed and President Obama signed into law in 2012. The legislation passed both houses by wide bipartisan margins (i.e., 406-22 in the U.S. House of Representatives). After major provisions of the Biggert-Waters Act were implemented in October 2013, there was significant public concern about the increasing premiums and the relative fairness of the increases (Alvarez & Robertson, 2013). Congress subsequently acted to reverse major provisions of the Biggert-Waters Act by passing the Homeowner Flood Insurance Accountability Act (HFIA) of 2013 (replacing Biggert-Waters as PL 113-89). The legislation was signed into law in March 2014, and it capped premium increases at 18% per year.

Biggert-Waters is noteworthy because it was an important step toward reforming hazard mitigation by reducing federal subsidies insurance for flood-prone property. But, in this context the quick reversal and step-back of the legislation sent signals to states that federal policy was inconsistent under political pressure at best and incoherent in terms of commitment to policy priorities at worst. This reversal represents the present-day time horizon biases of legislators and their electorates toward short-term risks and hazard management in their actions to keep present-day insurance costs low.

Even when policymakers do fashion preparedness policy, they are often hampered by limited knowledge and uncertainty about the future. The term “policy myopia” was coined to describe the myriad of pitfalls associated with appropriately identifying the bounds and range of these future uncertainties (Nair & Howlett, 2017). In the face of incomplete information about the future, policymakers are often forced to devise imperfect policy that only partially remedies the problem it originally set out to address. Worse yet, policy myopia can introduce unforeseen—and often negative—externalities that further complicate the governance process (Lindblom & Cohen, 1979; Simon, 1991).

Policy myopia is, of course, associated with all policy areas, although it is an especially vexing issue in the hazards management and national security domains. Low-probability but high-consequence hazard events, like disasters, are notoriously difficult to forecast and, when they do occur, rarely follow a scripted pattern. This dynamic can play out across a variety of time horizons. Consider, for example, the enormous difficulties associated with pandemic influenza preparedness. Effective pandemic preparedness often requires bold and decisive action in response to a relatively small number of disease cases that are assumed to portend a looming public health crisis. These decisions often need to be rendered within a relatively short time frame in order to give public health officials adequate time to stockpile vaccines and be ready for an event (Foreman, 1994).

History tells us this process is wrought with pitfalls. Fearing that the outbreak of swine flu influenza on a military base in New Jersey in 1976 foreshadowed a larger pandemic event, former president Gerald Ford order a mass immunization. Although the pandemic never came to be, the hastily made swine flu vaccine used to inoculate the public against the disease resulted in more than 400 cases of Guillain-Barré syndrome, a potentially deadly condition that causes a person’s immune system to attack his or her nerves (Neustadt & Fineberg, 1978).

Other hazards unveil themselves across a much longer time horizon but are no less challenging to legislate. Projections about the scope and severity of climate change, for example, are predicated on imperfect greenhouse gas emissions scenarios that often fail to capture interactions between rising temperatures and various environmental and ecological systems. Nor are the effects of climate change evenly distributed, meaning climate-related hazards have differential impact on different regions (Cass, 2006; Dessler & Parson, 2006). Complicating matters further, opponents on policy change exploit these uncertainties as an opportunity to muddy the debate, even in the face of decisive scientific evidence suggesting the need for robust climate mitigation and adaptation policy (Cass, 2006).

Policy myopia is problematic because it can result in policy failure or situations wherein policy fails to meet its stated objectives and/or results in negative outcomes (Newman & Head, 2015). Indeed, the climate change case suggests it induces political gridlock. Cognizant of this reality, emergency managers have increasingly called for policy to promote “great resilience,” a term that broadly denotes the ability of a community or organization to bounce back from disaster (Aldrich, 2012; Nair & Howlett, 2017). A focus on resilience to all hazards allows for a degree of flexibility that is simply not possible if we narrowly focus on one or a handful of threats, many of which are falsely assumed to mirror previous disasters.

But some policies to manage hazards may not be conducive to long-term risk reduction. For example, the U.S. Army Corps of Engineers is responsible for managing wetlands in the United States. The approach of the Corps has effectively increased risk and hazard in locations like New Orleans, where the dredging and excavating of the Mississippi River Gulf Outlet destroyed fragile wetlands over decades, thereby increasing the impact of strong storms like Hurricane Katrina (Freudenburg, Gramling, Laska, & Erikson, 2008). Policy prerogatives at the national level, like dredging a shipping lane to promote commerce, deter effective management of risk at the local level.

In this example, the U.S. Army Corps of Engineers represents an instance of specific policy priorities at the federal level, not necessarily reflecting local preferences. Beyond the statutory authority granted to them, government bureaucracies are policymakers with discretion to implement policies (Ripley & Franklin, 1987). Once policymakers have struggled with the concerns of their voters and districts, worked with the caucuses, and navigated risks over times, policies become laws that are implemented by bureaucrats. Particularly in the context of natural hazards and disasters, bureaucrats make a series of similar political decisions about how to implement (O’Donovan, 2018). With incomplete information and constrained decision-making ability, the focus on keeping shipping channels like the Mississippi River Gulf Outlet clear obscured the larger ramifications for preserving wetlands that serve as a barrier to storm surge and coastal erosion in a hurricane.

Other approaches to hazard management that that involve fewer infrastructure-specific policy tools pose their own set of local political challenges. For example, after catastrophic tornadoes in Oklahoma, Missouri, and Kansas, local governments struggled with balancing risk reduction, economic development, and affordable housing (O’Donovan, 2017). However, policymakers are presented with policy tools to address risk and hazard in their community and tend to discount the risk. Importantly, policymakers can ignore the risk a hazard presents until a disaster is at their doorstep (DeLeo, 2016). So, in spite of having a range of options to manage a natural hazard that do not require large-scale infrastructure projects, policymakers tend to have a distorted time horizon when thinking about the risks posed to their communities.

Politics of Managing Natural Hazards

As previously noted, there are three key elements to the politics of managing natural hazards: the electoral politics, including myopic voters and retrospective voting; the politics of blame; and the political rewards for preparedness and relief. This article describes each of these political factors in natural hazard policy formulation, management, and governance.

Electoral Politics and Natural Hazards: Myopic Voters, Retrospective Voting, and Anticipatory Policy Making in Hazard Management

Retrospective voting has, since the 1960s, provided political scientists with a mechanism through which voters may process information and cast sufficiently informed ballots. Retrospective voting provides a useful lens for examining the electoral politics of natural hazard management in practice. Natural disasters represent an exogenous shock to the local social and economic status quo. Although disasters are not randomly distributed, their incidence is exogenous to the economic-political system. As such, elected officials exercise no power over the incidence of natural disasters. Yet, elected officials may reasonably be blamed for the public response to a disaster or to the threat of a disaster. Myopic-retrospective voters thus over-reward (or over-punish) incumbent politicians for election-year disaster responses and under-reward (or under-punish) incumbents for their off-year responses.

Key (1966) suggests voters cast ballots not by prospectively evaluating policy alternatives as being in accordance with their policy preferences or ideologies, but by either punishing or rewarding candidates for past failures or successes in implementing policy that improves the voter’s personal welfare. For natural hazards policy, this reliance on retrospective, as opposed to prospective, considerations has meant that elected officials are under more pressure from their electorate to respond to natural disasters after the fact, by publicly providing disaster relief, than they are to proactively create policy that minimizes the risk posed by natural disasters in the first place.

Numerous studies have found evidence that, in the United States, myopic and retrospective voters punish incumbents for disaster and weather damages (Achen & Bartels, 2016; Gasper & Reeves, 2011; Healy & Malhorta, 2010; Healy, Kuo, & Malhorta, 2014). In India, studies examining government’s responses to rainfall damages and famine have revealed the Indian electorate to reward or punish incumbent politicians in a similarly myopic fashion (Besley & Burgess, 2001, 2002; Cole, Healy, & Werker, 2012).

Incumbent politicians seem aware of this perverse incentive structure. U.S. presidents and state governors are more likely to approve or request emergency relief after a natural disaster during an election year (Garrett & Sobel, 2003; Gasper & Reeves, 2010; Kriner & Reeves, 2012; Reeves, 2011). Boudreau (2016) similarly found that Mexican governors were more likely to request disaster relief during election years. However, retrospective voting can be mitigated by other political context such as clarity of responsibility (Achen & Bartels, 2016; Gasper & Reeves, 2011) as well as by political factors, such as partisanship (Anderson, 2000; Garrett & Sobel, 2003; Healy et al., 2014).

Moreover, a growing body of literature underscores the ways in which government institutions and the policymaking process itself might contribute to the gulf between disaster relief and preparedness spending. Roberts (2013) correctly points out the ways in which federalism, for example, muddies emergency management and disaster planning. He notes that under such conditions no politicians and government officials are responsible for all aspects of a passing and/or implementing policy. As a result, politicians and government officials are able to take advantage of this ambiguity and claim credit for policy successes for which they bore little responsibility and shirk responsibility for policy failures for which they bear substantial responsibility.

Of course, greater centralization does not automatically equate to more effective disaster management. McLuckie’s (1975) work on comparative public administration shows that in the case of highly centralized states, like Japan and Italy, subnational officials are often reluctant to implement important disaster preparedness and response initiatives for fear of usurping the national government’s authority. This dynamic in turn leads to a slowing down of the decision-making process. This arrangement stands in stark contrast to the U.S. example, where subnational units are not only empowered to act but are excepted to bear most of the burden in terms of disaster preparedness and response.

Although policy change is never a foregone conclusion, the policy process literature suggests public risks often require some nudge from a potential focusing event before cracking the crowded policy agendas. Many events fail to even capture media, public, and policymaker attention, let alone induce actual policy change. Some disasters, however, come to symbolize powerful examples of policy failure, meaning they help reveal flaws in existing policy regimes. Policy scholars often refer to this process of assigning meaning to social issues, including disasters, as problem definition. In this respect, disasters are social constructs in that their larger political and policy implications are less a reflection of the scale and scope of the damage they cause and more a byproduct of the ways in which they are framed and described by organized interests (Birkland, 1997; Nohrstedt, 2008).

Policy change is occurring in the aftermath of an event, as opposed to in anticipation of some sort of emerging hazard in a common phenomenon. However, a handful of studies suggest this need not always be the case. For example, the public health domain is often characterized as being indicator driven in that policymaking occurs in response to an accumulation of disease cases and deaths across time. In theory (and as noted herein), gradually accumulating instances of disease can point to a much larger, culminating event, in turn prompting policymakers to take anticipatory measures like preparedness planning and the stockpiling of vaccines and other measures (DeLeo, 2010, 2018).

Anticipatory policymaking has been used to assist with the management of technological hazards, namely, the various health and environmental risks associated with nanotechnology engineering. In this instance, U.S. policymakers mandated that the various government agencies proactively consider the various social, health, and environmental dangers associated with the new technology during the research and development process. This novel approach to hazard governance was seen as a way of not only promoting public health and safety but also staving off public backlash against the promising yet potentially disruptive new technology (Doubleday, 2007; Guston & Sarewitz, 2002; Lindquist, Mosher-Howe, & Lui, 2010).

The Politics of Blame and Responsibility in Hazard Policies

Numerous studies have found evidence that myopic and retrospective voters punish incumbents for disaster damages (Achen & Bartels, 2016; Cole, Healy, & Werker, 2012: Gasper & Reeves, 2011; Healy et al., 2014). However, the process of blame assignment varies based on the type of loss. For example, Healy and Malhotra (2010) found voters blame incumbents for economic losses but are reticent to blame incumbents for deaths caused by tornados. It appears that voters will hold government officials responsible for mitigating the economic losses caused by a natural disaster rather than for the loss of life caused by disasters. Such reasoning holds that deaths are more likely to be viewed by the electorate as “acts of God,” not a failure of government action.

Clarity of responsibility and blame assignment also varies by level of government. After Hurricane Katrina, most effected voters were generally able to determine which level of government was most appropriately suited for the job and correctly blamed local, as opposed to state and federal, officials for failing to adequately prepare for and respond to the disaster (Malhotra, 2008; Schneider, 2008). The presence of multiple overlapping levels of government makes it easier for politicians and government officials to avoid blame for poor responses. Birkland and Waterman (2008) argue that federalism itself may have contributed to policy failure in the wake of Hurricane Katrina.

Voters are most able to identify the correct office for blame if they are relatively knowledgeable about politics and when government’s role is clear. Gomez and Wilson (2008) found that residents in New Orleans who were more politically knowledgeable were less likely to blame the federal government for policy failure following Hurricane Katrina than less politically sophisticated residents were. Similarly, Arceneaux and Stein (2006) found that overlapping local government proved to be a difficult barrier for voters to overcome with respect to correctly assigning blame. They found that although voters were generally willing to erroneously hold mayors accountable for damages in the wake of Tropical Storm Allison, they only did so if they believed the mayor is responsible for flood prevention. Voters who were best informed, specifically about local politics, were much more likely to correctly identify the county government most responsible for flood prevention and deserving of credit or blame.

Correctly identifying which government to blame or credit for disaster damages is made more difficult by politicians in the federalist system hoping to shift blame in the media for policy failures and to conversely claim credit for policy successes. Despite most people—including many Republicans—initially blaming the Bush administration for failing to adequately respond to Hurricane Katrina, the administration was able to successfully shift much of the blame from the administration onto the state government, the Federal Emergency Management Agency (FEMA), and the Department of Homeland Security (Birkland & Waterman, 2008; Maestas, Atkenson, Croom, & Bryant, 2008). In part, they were able accomplish this by publicly “scapegoating” the director of FEMA, Michael Brown, by portraying him in the media as bumbling and incompetent. Malhotra and Margalit (2014) additionally found that incumbent politicians during the Hurricane Katrina period were able to minimize their chances of being blamed for policy failures without too adversely hurting their ability to claim credit. They found that incumbents who set low expectations were less likely to be punished by voters, but were still rewarded for successful responses.

One heartening finding of the natural hazards and blame literature is in how seriously voters consider federalism in their estimations of blame and how much they value cues about the respective government offices. Rather than acting as partisan automatons and simply blaming opposing government partisans, voters instead try to blame the office—or level of government—which they believe is the “best fit” for the problem. And the voters update their opinions consistently after receiving new information about the various actors’ responsibilities. However, partisanship plays a clear role in determining voters’ initial allocation of blame. Immediately after Hurricane Katrina, more than 60% of Democrats believed that the Bush administration was most to blame for policy failure in that case, whereas fewer than 25% of Republicans agreed (Maestas et al., 2008). Moreover, when exposed to information about the responsibilities of various governments and offices, the opinions held by both Democrats and Republicans were reinforced (Malhotra, 2008). And in a survey experiment, both Democrats and Republicans responded more to cues about the office held by various figures than they did to cues about party affiliation (Malhotra & Kuo, 2008, 2009).

So, although voters are generally able to correctly suss out which office is responsible for providing disaster relief, their myopia means that they systematically over-reward recent disaster relief after the fact and under-reward disaster preparation, which minimizes the damages caused by disasters. As a result, incumbents are faced with the perverse incentive to ignore disaster preparedness in favor of disaster relief (Healy & Malhotra, 2009).

Political Rewards for Preparedness and Relief

Gasper and Reeves (2011) found evidence that although voters punished executives for weather damage, they also rewarded them for timely response by way of state-of-emergency declarations. However, because the voter is short-sighted and therefore fails to punish the incumbent for a lack of preparedness, Gasper and Reeves (2011) found that the positive effect of claiming credit for making an emergency declaration on public opinion was approximately 20 times greater than the negative effect of having sustained weather damages at all because of a lack of preparation. Thus, we can infer that the electoral incentives for executives are structured in a way to cause them to prioritize disaster relief (disaster declarations) above disaster preparedness (weather damage mitigation). They found similar incentives exist for governors, who are frequently blamed more for weather damages than are presidents, because they are closer to the problem (Schneider, 2008). As such, incumbent governors receive even larger election-day boosts than does the president in the counties where a disaster declaration has been declared (Gasper & Reeves, 2010, 2011). Governors even benefit if the president declines to release federal assistance in response to a disaster declaration made by the governor—indicating that governors benefit from the attempt to secure federal relief grants even if they are unable to provide them (Gasper & Reeves, 2011; Gaspar 2015).

Incumbent politicians appear to be aware of their reelection incentive to politicize disaster relief in election years. State governors in both the United States and Mexico are more likely to declare an emergency and request disaster relief during gubernatorial election years (Boudreau, 2016; Gasper & Reeves, 2011). Reeves (2011) found evidence that presidents utilize disaster relief strategically by responding to more disaster declarations, on average, in the fourth years of their term. Even first-term presidents are responsive to electoral pressures and are more likely to accept a request for disaster relief for competitive districts (Garrett & Sobel, 2003; Reeves, 2011). Conversely, presidents are more likely to decline state requests for disaster assistance in relatively “safe” states (Gasper, 2015). However, even among the more competitive, “partisan-leaning” states presidents distribute slightly more FEMA dollars to Democrat-leaning states than to Republican-leaning states (Vogel, 2012). Further, research is necessary to determine whether this disparity in FEMA spending in electorally competitive blue and red states is the rational response to preference for disaster relief within the electorate, the result of partisan bias, or something else. Moreover, it has long been documented that members of Congress manipulate public spending to produce better election-year economies and thus achieve improved outcomes for incumbents (Kriner & Reeves, 2012, 2015; Levitt & Snyder, 1997; Nordhaus, 1975). Congress similarly politicizes FEMA funding despite being less able to clearly claim credit for disaster declarations (Wamsley & Schroeder, 1996). Garrett and Sobel (2003) find that FEMA disaster expenditures are generally higher in election years because of both presidential and congressional influences.

Conclusion

From myopic voters to federalism, to blame attribution, to term limits, the American political system is, in many respects, structurally biased against proactive policy change. Elected officials are neither rewarded for nor encouraged to proactively plan for emerging hazards, and as result, policy change is often the byproduct of a disastrous event that was simply too great to ignore. This policy sequence is not only injurious to our collective safety but also results in enormous sunken costs and wasted resources.

This said, although the political science literature has done an excellent job detailing and documenting the various barriers to preparedness policy, it has said surprisingly little about potential strategies for overcoming voter myopia and reactive decision-making. What, if any, strategies exist for combating reactive policymaking? For example, Healy and Malhotra (2009, p. 400) suggest it is possible that “voters reward relief spending but not preparedness spending because relief spending generally comes in the form of direct, individual-level payments, whereas preparedness usually comes in the form of collective goods.” Repackaging preparedness policy as an individual rather than a collective good may very well be an antidote for myopic voting, but this contention has yet to be tested.

Moreover, the literature has devoted relatively little attention to those instances where policymakers do, in fact, enact preparedness policy—however uncommon they may be. A more sustained focus on policy change in response to fluctuations in indicators may very well provide important insights into when and under what conditions policymakers are more likely to pay attention to emerging hazards. Indeed, one could argue that the literature falsely silos public health risks (e.g., emerging disease outbreaks and drug epidemics), natural hazards (e.g., earthquakes, hurricanes, and tornadoes), and environmental risks (e.g., drinking water, aging infrastructure, storm and waste water management).

The importance of the political context for natural hazard management policy cannot be understated. Students, scholars, and professionals who work in disaster preparedness and hazard management grow frustrated at the lack of policy change in light of mounting evidence of the risk of a natural disaster. Based on the political science and public policy literature, the authors of this article conclude that our natural hazard management system is one that is highly constrained by political factors that do not reward policymakers for disaster risk reduction.

Further Reading

  • Albright, E. A., & Crow, D. (2019). Beliefs about climate change in the aftermath of extreme flooding. Climatic Change, 155(1), 1–17.
  • Anderson, S. E., DeLeo, R. A., & Taylor, K. (2019). Policy entrepreneurs, legislators, and agenda setting: Information and influence. Policy Studies Journal, March 22.
  • Ansell, C., & Baur, P. (2018). Explaining trends in risk governance: How problem definitions underpin risk regimes. Risk, Hazards & Crisis in Public Policy 9(4), 397–430.
  • Gasper, J. T., & Reeves, A. (2011). Make it rain? Retrospection and the attentive electorate in the context of natural disasters. American Journal of Political Science, 55(2), 340–355.
  • Healy, A., & Malhotra, N. (2009). Myopic voters and natural disaster policy. American Political Science Review, 103(3), 387–406.
  • May, P. J., & Koski, C. (2013). Addressing public risks: Extreme events and critical infrastructures. Review of Policy Research, 30(2), 139–159.
  • Platt, R. H. (2012). Disasters and democracy: The politics of extreme natural events. Washington, DC: Island Press.
  • Sadri, A. M., Ukkusuri, S. V., Lee, S., Clawson, R., Aldrich, D., Nelson, M. S., . . . Kelly, D. (2018). The role of social capital, personal networks, and emergency responders in post-disaster recovery and resilience: A study of rural communities in Indiana. Natural hazards, 90(3), 1377–1406.

References

  • Achen, C. H., & Bartels, L. (2016). Democracy for realists: Why elections don’t produce responsive governments. Princeton, NJ: Princeton University Press.
  • Aldrich, D. P. (2012). Building resilience: Social capital in post-disaster recovery. Chicago, IL: University of Chicago Press.
  • Alvarez, L., & Robertson, C. (2013). Cost of flood insurance rises, along with worries. New York Times, October 12.
  • Anderson, C. (2000). Economic voting and political context: A comparative perspective. Electoral Studies, 19(2), 151–170.
  • Arceneaux, K., & Stein, R. M. (2006). Who is held responsible when disaster strikes? The attribution of responsibility for a natural disaster in an urban election. Journal of Urban Affairs, 28(1), 43–53.
  • Baumgartner, F. R., & Jones, B. D. (2009). Agendas and instability in American politics (2nd ed.). Chicago, IL: University of Chicago Press.
  • Besley, T., & Burgess, R. (2001). Political agency, government responsiveness and the role of the media. European Economic Review, 45(4–6), 629–640.
  • Besley, T., & Burgess, R. (2002). The political economy of government responsiveness: Theory and evidence from India. Quarterly Journal of Economics, 117(4), 1415–1451.
  • Birkland, T. A. (1997). After disaster: Agenda setting, public policy, and focusing events. Washington, DC: Georgetown University Press.
  • Birkland, T. A. (1998). Focusing events, mobilization, and agenda setting. Journal of Public Policy, 18(1), 53–74.
  • Birkland, T., & Waterman, S. (2008). Is federalism the reason for policy failure in Hurricane Katrina? Journal of Federalism, 38(4), 692–714.
  • Boudreau, L. (2016). Discipline and disasters: The political economy of Mexico’s Sovereign Disaster Risk Financing Program. Fondation pour les Etudes et Recherches sur le Développement International (FERDI) policy brief 128.
  • Burby, R., & May, P. J. (1998). Intergovernmental environmental planning: Addressing the commitment conundrum. Journal of Environmental Planning and Management, 41(1), 95–110.
  • Burstein, P. (1991). Policy domains: Organization, culture, and policy outcomes. Annual Review of Sociology, 17(1), 327–350.
  • Cass, L. R. (2006). The failures of American and European climate policy: International norms, domestic politics, and unachievable commitments. Albany: State University of New York Press.
  • Cole, S., Healy, A., & Werker, E. (2012). Do voters demand responsive governments? Evidence from Indian disaster relief. Journal of Development Economics, 97, 167–181.
  • Cooper, C., & Block, R. (2007). Disaster: Hurricane Katrina and the failure of homeland security. New York, NY: Henry Holt.
  • Coppola, D. P. (2006). Introduction to international disaster management. Oxford, U.K.: Elsevier.
  • Dalle Nogare, C., & Ricciuti, R. (2011). Do term limits affect fiscal policy choices? European Journal of Political Economy, 27(4), 681–692.
  • DeLeo, R. A. (2010). Anticipatory-conjectural policy problems: A case study of avian influenza. Risk, Hazards, & Crisis in Public Policy, 1(1), 147–184.
  • DeLeo, R. A. (2016). Anticipatory policymaking: When government acts to prevent problems and why it is so difficult. London, U.K.: Routledge.
  • DeLeo, R. A. (2018). Indicators, agendas, and streams: Analysing the politics of preparedness. Policy & Politics, 46(1), 27–45.
  • Dessler, A. E., & Parson, E. A. (2006). The science and politics of global climate change: A guide to the debate. Cambridge, U.K.: Cambridge University Press.
  • Doubleday, R. (2007). Risk, public engagement, and reflexivity: Alternative framings of the public dimensions of nanotechnology. Health, Risk & Society, 9(2), 211–227.
  • Foreman, C. H., Jr. (1994). Plagues, products & politics: Emergent public health hazards and national policymaking. Washington, DC: The Brookings Institution.
  • Freudenburg, W. R., Gramling, R., Laska, S., & Erikson, K. T. (2008). Organizing hazards, engineering disasters? Improving the recognition of political-economic factors in the creation of disasters. Social Forces, 87(2), 1015–1038.
  • Garrett, T. A., & Sobel, R. S. (2003). The political economy of FEMA disaster payments. Economic Inquiry, 41(3), 496–509.
  • Gasper, J. T. (2015). The politics of denying aid: An analysis of disaster declaration turndowns. Journal of Public Management & Social Policy, 22(2), 7.
  • Gasper, J. T., & Reeves, A. (2010). Governors as opportunists: Evidence from disaster declaration requests. APSA 2010 Annual Meeting Paper. Social Science Research Network, July 19.
  • Gasper, J. T., & Reeves, A. (2011). Make it rain? Retrospection and the attentive electorate in the context of natural disasters. American Journal of Political Science, 55(2), 340–355.
  • Gomez, B. T., & Wilson, J. M. (2008). Political sophistication and attributions of blame in the wake of Hurricane Katrina. Publius: The Journal of Federalism, 38(4), 633–650.
  • Guston, D. H., & Sarewitz, D. (2002). Real-time technology assessment. Technology in Society, 23(4), 93–109.
  • Healy, A., Kuo, A. G., & Malhorta, N. (2014). Partisan bias in blame attribution: When does it occur? Journal of Experimental Political Science, 1(2), 144–158.
  • Healy, A., & Malhotra, N. (2009). Myopic voters and natural disaster policy. American Political Science Review, 103(3), 387–406.
  • Healy, A., & Malhorta, N. (2010). Random events, economic losses, and retrospective voting: Implications for democratic competence. Quarterly Journal of Political Science, 5(2), 193–208.
  • Key, V. O. (1966). The responsible electorate. Cambridge, MA: Harvard University Press.
  • Kriner, D. L., & Reeves, A. (2015). Presidential particularism and divide-the-dollar politics. American Political Science Review, 109(1), 155–171.
  • Kriner, D. L., & Reeves, A. (2012). The influence of federal spending on presidential elections. American Political Science Review, 106(2), 348–366.
  • Levitt, S. D., & Snyder, J. M., Jr. (1997). The impact of federal spending on house election outcomes. Journal of Political Economy, 105(1), 30–53.
  • Lindblom, C. E., & Cohen, D. K. (1979). Usable knowledge: Social science and social problem solving. New Haven, CT: Yale University Press.
  • Lindell, M. K., & Perry, R. W. (2000). Household adjustment to earthquake hazard: A review of research. Environment and behavior, 32(4), 461–501.
  • Lindquist, E., Mosher-Howe, K. N., & Liu, X. (2010). Nanotechnology . . . What is it good for? (Absolutely everything): A problem definition approach. Review of Policy Research, 27(3), 255–271.
  • Maestas, C. D., Atkeson, L. R., Croom, T., & Bryant, L. A. (2008). Shifting the blame: Federalism, media, and public assignment of blame following Hurricane Katrina. Publius: The Journal of Federalism, 38(4), 609–632.
  • Malhotra, N. (2008). Partisan polarization and blame attribution in a federal system: The case of Hurricane Katrina. Publius: The Journal of Federalism, 38(4), 651–670.
  • Malhotra, N., & Kuo, A. G. (2008). Attributing blame: The public’s response to Hurricane Katrina. Journal of Politics, 70(1), 120–135.
  • Malhotra, N., & Kuo, A. G. (2009). Emotions as moderators of information cue use: Citizen attitudes towards Hurricane Katrina. American Politics Research, 37(2), 301–326.
  • Malhotra, N., & Margalit, Y. (2014). Expectation setting and retrospective voting. Journal of Politics, 76(4), 1000–1016.
  • May, P. J., & Koski, C. (2013). Addressing public risks: Extreme events and critical infrastructures. Review of Policy Research, 30(2), 139–159.
  • McLuckie, B. F. (1975). A study of functional response stress in three societies. (Doctoral dissertation). Ohio State University, Columbus, OH.
  • Miletti, D. (1999). Disasters by design: A reassessment of natural hazards in the United States. Washington, DC: John Henry Press.
  • Nair, S., & Howlett, M. (2017). Policy myopia as a source of policy failure: Adaptation and policy learning under deep uncertainty. Policy & Politic, 45(1), 103–118.
  • Neustadt, R. E., & Fineberg, H. V. (1978). The swine flu affair: Decision-making on a slippery disease. Washington, DC: U.S. Government Printing Office.
  • Newman, J., & Head, B. W. (2015). Categories of failure in climate change mitigation policy in Australia. Public Policy and Administration, 30(3), 342–358
  • Nohrstedt, D. (2008). The politics of crisis policymaking: Chernobyl and Swedish nuclear energy policy. Policy Studies Journal, 36(2), 257–278.
  • Nordhaus, W. D. (1975). The political business cycle. Review of Economic Studies, 42(2), 169–190.
  • O’Donovan, K. (2017). Policy failure and policy learning: Examining the conditions of learning after disaster. Review of Policy Research, 34(4), 537–558.
  • O’Donovan, K. (2018). Bureaucratic policymaking on natural hazards. In Oxford encyclopedia of natural hazard science. Oxford, U.K.: Oxford University Press.
  • Platt, R. H. (2012). Disasters and democracy: The politics of extreme natural events. Washington, DC: Island Press.
  • Reeves, A. (2011). Political disaster: Unilateral powers, electoral incentives, and presidential disaster declarations. Journal of Politics, 73(4), 1142–1151.
  • Ripley, R. B., & Franklin, G. A. (1987). Congress, the bureaucracy, and public policy. Chicago, IL: Dorsey Press.
  • Roberts, P. S. (2013). Disasters and the American state: How politicians, bureaucrats, and the public prepare for the unexpected. Cambridge, MA: Cambridge University Press.
  • Schneider, S. K. (2008). Who’s to blame? (Mis)perceptions of the intergovernmental response to disasters. Publius: The Journal of Federalism, 38(4), 715–738.
  • Simon, H. A. (1991). Bounded rationality and organizational learning. Organization Science, 2(1), 125–134.
  • Taylor, K., & Birkland, T. A. (2019). The politics and governance of mitigation. In M. Lindell (Ed.), The Routledge handbook of urban disaster resilience: Mitigation, preparedness, and recovery planning. Abingdon, U.K.: Taylor & Francis/Routledge.
  • Vogel, R. M. (2012). Politics, diversity and the distribution of federal disaster assistance. Economics and Business Letters, 1(2), 37–42.
  • Wamsley, G. L., & Schroeder, A. D. (1996). Escalating in a quagmire: The changing dynamics of emergency management policy subsystem. Public Administration Review, 56(3), 235–244.