JohannaWedholm Policychangeafternaturalhazards UPPSALAUNIVERSITET

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UPPSALA UNIVERSITET

Policy change after natural hazards

A systematic large-N study using narrative analysis

Johanna Wedholm

Bachelor thesis

Department of Government

Political Science C, Spring 2020

Supervisor: Daniel Nohrstedt

Words: 11660

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Abstract

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List of Figures

1 Mentions of policy change as a result of natural hazards . . . . 22

List of Tables

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Introduction

Climate change is a reality and the observed impact of climate change on physical and ecological systems the past century is a precursor of things to come (McCharthy et. al 2001). As the world’s climate changes, climate-related extremes are probable to become even more widespread. Regions of the world are expected to experience more natural hazards such as floods, storms, extreme temperatures, and severe droughts (IPCC 2020). As these natural hazards strike and affect communities and societies, they can become focusing events by engaging both policymakers and the public leading to policy changes by revealing the possibility of potential future harms (Birkland 1997). In 2005, a framework for disaster risk reduction called Hyogo Framework for Action (HFA) was adopted with the expected outcome of hazard losses, in lives and in the social, economic and environmental assets of communities over a 10-year timeframe (UNDRR 2005). Coordinated through the United Nations Disaster Risk Reduction (UNDRR) the HFA provide a set of achievable policies to develop and strengthen institutions, mechanisms, and capacities to build resilience to natural hazards (UNDRR 2005). But statistics published by the International Disaster Database (EM-DAT) tell that the number of people killed by natural hazards and the number of people affected and the associated economic losses have remained high since the 1990s (EM-DAT 2020).

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or aim to understand the variability in hazard losses rather than providing systematic large-N studies on the connection on policy change in the wake of natural hazards (Birkmann et. al 2010; Pasquini et. al 2014; Becker and Reusser 2016).

There is also a need for studies using methods other than case studies as the knowledge on the connection on natural hazards and policy change is almost entirely built on case studies. The method of narrative analysis puts focus on happenings characterized by causality and temporality (Labov and Waletzky 1997) which enables for large-N studies to view the connection of natural hazards and policy change from another perspective. This study sets out with the ambition to study data on natural hazards from the International Disaster Database (EM-DAT) for 2011-2013 by searching for citations on these natural hazards mentioning them as drivers for policy changes in the national progress reports on the implementation of the HFA 2013-2015.

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1.1 Main purpose and research questions

The main purpose of this thesis is to empirically describe the extent to which and how countries affected by natural hazards refer to these natural hazards as drivers for policy change. In order to realize this, a systematic large-N extensive study with the innovative method of narrative analysis will be used to analyze the national progress reports on the implementation of the Hyogo Framework for Action 2013-2015. Meeting this goal by searching for men-tions of policy changes implemented after natural hazards will add important knowledge and cumulation to the research field of disaster risk reduction and the connection of natural hazards and policy change. In order to meet the main purpose, two empirical research questions will be examined:

(1) How many countries refer to earlier natural hazards as drivers for policy change?

(2) Are there any natural hazards that can be classified as focusing events?

The extent to which and how countries affected by natural hazards refer to these natural hazards as drivers for policy change is studied through a selection of countries that had major natural hazards recorded in the International Disaster Database (EM-DAT) from 2011-2013 and a narrative analysis of their national progress reports on the implementation of the Hyogo Framework for Action 2013-2015.

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citations describing how and to which extent the countries in the material mention natural hazards as drivers for policy change.

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Theoretical framework

This section deals with the theoretical impacts of disaster risk reduction (DRR) policy change after natural hazards. Previous research is first discussed and is then followed by a discussion regarding the components derived from the previous research that make up theories on policy change, focusing events, and policy windows. The section is concluded with contradictions in the previous research that have been divided into two positions, one that argues for natural hazards as drivers for policy change and one that argues the opposite.

2.1 Previous research on disaster risk reduction policy

change after natural hazard events

During the last decade and after the introduction of the UN International Decade for Natural Disaster Reduction in the 1990s the focus of DRR and management has been put towards a wider and broader understanding of the underlying causes of natural hazard vulnerability. Another focal point has been the development of forward-looking and longer-term strategies for anticipating and managing risk rather than just short-term ad hoc solutions (Thomalla et. al 2006). This allowed research on DRR to grow wider in the fields of social science and more specifically, political science. With the increasing climate changes in the world, there is a rapidly growing literature on climate adapta-tion, resilience, and DRR since it has been argued that policy changes usually are triggered by recent events (Adger et. al 2005). Recent research and pol-icy priorities driven by climate change and major natural hazards affecting multiple regions of the world have generated a greater understanding of how natural hazard impact and reconstruction have the potential of reshaping po-litical policies and entire systems (Pelling and Dill 2010). As a consequence, DRR policies and strategies are now well established in most countries in the world and in most societal levels in order to reduce vulnerability towards all kinds of natural hazards.

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The many case studies has contributed to a broad spectrum in the re-search on policy change, disaster risk reduction (DRR) and natural hazards. The state of knowledge on policy change and DRR after natural hazards can be divided into two dimensions.

The first dimension is the research on policy change and the connec-tion to DRR. Disaster risk reducconnec-tion is defined by the UNDRR as ”the sys-tematic development and application of policies, strategies, and practices to minimize vulnerabilities, hazards and the unfolding of natural hazard impacts throughout society, in the broad context of sustainable development” (UN-DRR 2004:3). For many scholars, building resilience is the ultimate purpose of any DRR policy change (Djalante et. al 2011). Strategies for policy changes to reduce risk include hazard vulnerability and capacity assessments and the strategies usually highlight communities’ ability to reduce their disaster risks induced by hazards as the best placed to identify solutions for risk reduction (Wisner et. al 2004). Previous research on DRR embraces that climate adap-tation is particularly important for reducing vulnerability and the impacts of natural hazards (Schipper 2009; Thomalla et. al 2006; Yohe and Tol 2002). Adaptation is often described as ”a process of deliberate change in anticipation of or in reaction to external stimuli and stress” (Nelson et. al 2007:395). In this context, it could mean that adaptation takes place after natural hazards. As the frequency of natural hazards is increasing in the world, researchers and policy makers are currently working to provide the tools necessary for analyz-ing adaptations after natural hazards in the light of current and future climate change (Nelson et. al 2007).

The second dimension of the state of knowledge on policy change and DRR after natural hazards are specific studies on the connection explaining how policy changes after natural hazards can be implemented in practice. There are many interesting studies in the research field showing the poten-tial effects of natural hazards on policy change and to illustrate the state of knowledge, two studies will be used as examples in this section.

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by analyzing national laws and policies. The main findings of the study that are of interest for this thesis are that shocks, such as natural hazards, may encourage the redistribution of political resources and motivate policy change by casting doubt on the dominant policy core belief system. She found that, for major policy core changes to occur, changes in the political system and the occurrence of extreme floods were necessary for major policy changes to take place in the government’s flood management program (Albright 2011:507).

The second study is written by Anna Scolobig et. al (2014) on drivers of transformative change in the Italian landslide risk policy through a desk-top study of the published disaster literature ranging from books to media articles (Scolobig et. al 2014). The authors also performed expert interviews to gain insights on major policy changes. One of the main findings of the study is that the transformation reallocating resources from reactive hazard aid to proactive disaster risk-management has far to come in the management of landslide risk in Italy. Policies are implemented for emergency interven-tion and reconstrucinterven-tion rather than risk preveninterven-tion, but they do conclude that policies after landslide events have changed importantly through Italy’s recent history (Scolobig et. al 2014).

2.2 Theory derived from previous research

2.2.1 Policy change, focusing events and policy windows

The last two decades have seen great activity in the explanation of policy change in general. Debates have centered on the roles of ideas and institutions as competing and coordinating events have been put in place (Beland and Hacker 2004). Policy changes can be defined as ”incremental shifts in existing structures, or new and innovative policies” (Bennet and Howlett 1992). This means that a policy change does not have to be a change in existing policy, it could also be the addition of a new policy. Although this is not a study on policy changes in general, it is vital to define policy change. It is necessary to understand what a policy change is to examine the extent to which and how natural hazards works as drivers for policy changes.

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or suggests potential harms that are or could be concentrated on a definable geographical or community of interest, and that is known to policymakers and the public virtually simultaneously” (Birkland 1997:2). There is a difference between a potential focusing event and a focusing event in the definition that a focusing event always leads to a policy change (Michaels et. al 2006:983). According to Birkland (2006), it depends on where the hazard strikes if the potential focusing event becomes a focusing event since a hurricane that fails to strike populated areas is still a hurricane in a meteorological sense, but it will not be worth mentioning in the history books. He argues that the distribution of damage and deaths in natural hazards and accidents differ given that the largest storms, on the scale of for example Hurricane Katrina overwhelming the American emergency management system, have the best chance for policy learning and change (Birkland 1997).

In his book After Disaster (1997), Birkland holds that focusing events get so much attention because they highlight policy failures by elevating the policy agenda. After a sudden hazard event, attention increases on the pol-icy agenda, leading to an increased discussion of ideas, and in turn, polpol-icy changes (Birkland 2006). Focusing events are usually very hard for policy-makers to ignore since they receive great interest and coverage in the media. Birkland (2006) holds that media attention, policy issues, and a difference of interest groups involved may encourage policy learning and the creation of policy changes whereas political constraints and confusion over the underlying causes of a hazard may hinder learning and policy change.

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windows, Michaels et. al (2006) exemplifies with Hurricane Hazel in Ontario that arrived with short notice and caused great harm. It is a good example of how a policy window opens because public policymakers had to address a ”new” problem with the potential of another strike. The aftermath of the hurricane resulted in organizational learning and policy change (Michaels et. al 2006:988).

As mentioned in the introduction, there are two sides to the theory on the connection between natural hazards and policy change. To provide an understanding of both sides, they have been divided into two different positions presented below.

2.2.2 The position on natural hazards as a driver for policy changes

The research by Fred Cuny (1983) suggests that natural hazards could activate civil societies and hence push for policy changes through new leaders replacing the previous ones who have proved ineffective leadership or not being able to cope with the aftermath of natural hazards (Cuny 1983). Pelling and Dill (2010) seek to identify tipping points that make policy change happen after natural hazards. They present two arguments with the first one being that natural hazards produce an ”accelerated status quo” since change is path-dependent and limited to a concentration of hazard directions that remain under the influence of the political elite both before and after natural hazard events. The other argument is that hazards can catalyze a ”critical point” where change is inevitable in the direction or composition of a political regime (Pelling and Dill 2010:22).

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effects (Pelling and Dill 2010:24). Drury and Olson (1998) confirmed Albala-Bertrand’s conclusions by concluding that prior political crisis was positively correlated with the post- natural hazard crisis for major natural hazards be-tween 1966 and 1980 (Drury and Olson 1998).

There is also evidence that major natural hazard events create a pol-icy window for large scale investments to take place for action on adaptation measures to adapt to climate change. A study by Adger (2005) holds that adaptation in response to climate change is triggered by past extreme natural hazard events. A natural hazard can open a policy window by raising the con-sciousness of climate change within policymaking and in turn, give legitimacy for governmental action (Adger 2005:85). Without major natural hazards, adaptation requiring big investments tends to be episodic and staggered. Ma-jor natural hazards can spur policy change and redistribute political resources for these investments to take place (Adger 2005). Legitimacy in governmental action is central to the resilience and ultimately the perceived success of adap-tation, fair public action defines both the relationship to the natural world, and it is a component of long-term sustainability (Low and Gleeson 1998).

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due to a lack of capacity, funding and the government’s desire to maintain command over the post-hazard situation (Becker and Reusser 2016:86). The authors conclude that the use of multi-level perspectives allows for the recog-nition of which societal levels are of importance for DRR after natural hazard events and where obstacles occur (Becker and Reusser 2016:86).

2.2.3 The position on natural hazards as a non-driver for policy changes

Boin and Hart (2003) question the above-presented arguments that natural hazards works as drivers for policy change. Their core argument is that haz-ard events can also become portrayed as policy failures, creating an atmosphere where policy changes are hindered (Boin and Hart 2003). With this in mind, they argue that the opportunities for reform in the wake of hazards are smaller than what might be expected (Boin and Hart 2003:544). In times of hazard events striking society, it is natural to look at leaders expecting them to do something, and successful performance is often well rewarded by the people (Boin and Hart 2003:544). However, there is a substantial gap between ex-pectation of the citizens and leadership efforts in preventing and containing hazards where leaders seldomly meet up to the demand for prevention, pre-paredness, and response (Boin and Hart 2003). To implement policy changes in the aftermath of hazards leaders must have a clear idea about the most vital societal functions to avoid immediate decisions with irreversible consequences (Boin and Hart 2003).

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capacities in the studied regions are unevenly distributed among regions and populations.

The literature arguing that natural hazards do not lead to policy changes can be summarized into two main arguments.

The first is that some initial events and actions can be perceived as suc-cesses, and in turn block insights that major changes after natural hazards are necessary (Eisenack et. al 2014). Eisenack et. al (2014) hold that the grow-ing number of case studies and theoretical work on adaptation has produced a large collection of commonly reported barriers which are institutional frag-mentation, lack of awareness and communication, and lack of resources among other barriers. They further explain that most of these barriers apply to policy change and management processes too (Eisenack et. al 2014:868). For exam-ple, they mention that investments to intensify the buoyancy of infrastructure to more frequent natural hazard events might be delayed due to a deficiency of economic resources (Eisenack et. al 2014:867). To further complicate mat-ters, barriers to policy change on adaptation or disaster risk reduction are not static but change over time and adaptation investments are strongly shaped by expectations about the future (Pechan 2014).

The second argument is that the beliefs of policy actors are so strong that a natural hazard cannot change them. In his dissertation on crisis and policy reformcraft, Nohrstedt (2007) turns the attention to the debate on the relative role of interests compared to policy-oriented beliefs by specifying the conditions that might help explain why and how interests become important motivations in policymaking. He argues that policy core beliefs are resistant to change with the consequence that major policy changes are rare events (Nohrstedt 2007:14). By focusing on the decision making by the Social Democrats during the Three Mile Island crisis in 1979, he discovered that they did not change their policy beliefs on nuclear power after the accident. Instead, they chose to take strategic action which indicates that policymakers prioritize strategic action to prevent the loss of political capital above the ambition to realize policy core beliefs (Nohrstedt 2007).

2.3 Theoretical framework summary

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haz-ards as drivers for policy change holds that natural hazhaz-ards can activate the civil society and hence provide legitimacy for governmental action and policy change. The position on natural hazards as a non-driver for policy change holds that initial events can be perceived as a success at first and in turn block the opportunities for major policy changes. It also takes a stand in the idea that the beliefs of policy actors are so rigid that a natural hazard cannot change these beliefs.

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Methodology

In this section, the methodology of the thesis will be presented. Narrative analysis will be discussed at first and how it will be used in this study, fol-lowed by a discussion regarding the collected data in terms of the databases for natural hazards and DRR policies. Then, an operationalization will be presented and lastly, limitations with the chosen method, the data, and the overall methodology will be discussed.

3.1 Narrative analysis

During the last decades, the interest in narrative analysis has been growing in the field of social science, and political science specifically (Johansson 2005). The idea that the social reality is constructed through discourse is reaching bigger acceptance among researchers and many agree on that language creates the reality we experience. According to sociologist Rimmon-Kernan (1983), it is the story and the chronological succession of events that provide the basis for a narrative. A common definition of the conception of a narrative is that it concentrates on the accounting of happenings characterized by causality and temporality (Labov and Waletzky 1997). Another definition could be that it is the main tool to organize our understanding of time and at the same time give our experiences meaning through structure and context (Johansson 2005:16,84).

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the connection of natural hazards and policy change almost entirely built on case studies. This implicates the need for studies with other methodological approaches.

The second argument lies in the realization that a narrative analysis can provide an opportunity to understand the connection between natural hazards and policy changes from another perspective. Narrative analyses are used to find a form of causality through the connection between events in the past and actions in the present (Johansson 2005). To reach one of the criterion’s of causality, events need to be connected in the order of temporality (Johansson 2005) meaning that the natural hazards need to precede the policy changes. According to Somers and Gibson (1994), the parts of the narrative must be put in an intrigue for the narratives to reveal structured patterns of causal logic. They argue that it is through this intrigue that isolated events transform into a sequence of episodes creating casual relationships and patterns (Somers and Gibson 1994).

By studying data on natural hazards from 2011-2013 and policy changes induced after these events in the national progress reports on the implemen-tation of the HFA 2013-2015, one can be assured that the national hazards percede the policy changes and hence reach the criteria of temporality which is one of the four criterion’s of causality. However, as the aim is not to reach all criterion’s of causality, it is important to clarify that the methodological con-tribution lies in the innovative way of using this narrative analysis as the start of building the bridge of causal mechanisms through the paving of temporality. To pave temporality the national progress reports on the implementation of the HFA 2013-2015 will be analyzed with a tool for qualitative text analysis to find citations mentioning how and to what extent the countries refer to natu-ral hazards as drivers for policy changes. When they mention policy changes 2013-2015 as a result of natural hazards 2011-2013, one can be sure that the temporality has been paved.

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the authors still choose what, and what not to mention in the reports. For validity concerns related to this, see section 3.4. The focus of this thesis is thus put on the authors’ understanding of the social reality in terms of prevention measures after natural hazards and hence what they mention in the national progress reports of the implementation of the HFA 2013-2015. Natural haz-ards data from EM-DAT will be used to make a selection of countries struck by major natural hazards during 2011-2013.

3.2 Data collection

Natural hazards database. The data on natural hazards used in this thesis is retrieved from the often-used International Disaster Database (EM-DAT) which is a global data set containing essential core country-level data on the occurrence and effects of over 22 000 mass hazards in the world from 1900 to the present day (EM-DAT 2020). The database provides information on the human impact of hazards such as the number of killed and affected, the severity of the natural hazard event and hazard related economic damage estimates (DAT 2020). More on this in section 3.4. With these measures, the EM-DAT only includes major hazards, and smaller hazards are thus automatically excluded from the database. The information in the database is compiled from various sources such as UN agencies, research institutes, non-governmental organizations, and research institutes (EM-DAT 2009). To meet the aim of this thesis data from the years 2011-2013 will be retrieved and then sorted to exclude the countries affected by natural hazards events that did not submit national progress reports on the implementation of the HFA 2013-2015.

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which was chosen as it is the most recent time frame for the framework, a total of 92 countries submitted national progress reports on the implementation of the HFA 2013-2015 to the United Nations Disaster Risk Reduction (UNDRR). 32 of these national progress reports are written in languages other than En-glish and will thus be excluded from the results of this thesis due to language barriers. Of the remaining 60 reports, 6 countries did not have any natural hazards reported in the EM-DAT database of natural hazards 2011-2013 and hence they are not of interest to the main purpose. The remaining 54 country reports on the national progress on disaster risk reduction is providing the ground for the result and analysis of this thesis.

3.3 Operationalization

In order to analyze all 54 national progress reports a tool for qualitative data analysis (NVIVO) will be used to search for natural hazard events mentioned in the reports connected to policy changes. NVIVO, which is a software by Alphasoft from 2020, is used to cope with the big material of the national progress reports on the implementation of the HFA 2013-2015 by searching for citations mentioning natural hazards and a connection to policy changes. The UN Space-based Information for Disaster Management and Emergency Re-sponse (UN-SPIDER 2020) is listing six types of natural hazards that are oc-curring in the world. Each category has different types of specifications which made the list over a hundred variables long. With the attempt to find all nat-ural hazards mentioned in the national progress reports all six categories will be included in the results: biological (insect infestation, epidemic, harmful al-gae), climatological (forest fire, drought, glacial lake outburst), extraterrestrial (near-earth objects, space weather), geophysical (tsunami, earthquake, mass movement, volcanic eruption, subsidence), hydrological (flood, landslide).

In order to meet the main aim to describe how and to what extent coun-tries affected by natural hazards refer to these hazards as drivers for policy change the national progress reports on the implementation of the HFA 2013-2015 will be analyzed.

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(2) Are there any events that can be classified as focusing events? will be answered by measuring the number of mentions of policy change after natural hazards and citations on how the countries describe the policy changes induced by natural hazards.

An example of a citation that was coded as a policy change induced by a natural hazard is from the national progress report on the implementation of the HFA 2013-2015 by Pakistan:

”A comprehensive Disaster Damages and Needs Assessment exercise have been undertaken after the floods 2010 and also after floods 2011, with the tech-nical assistance and validation of World Bank and the Asian Development Bank. The Government of Pakistan accordingly formulated its recovery and reconstruction plans and implemented projects and programmes in the affected areas.”

The citation was coded as a policy change following a natural hazard event since the national progress report mention floods and policy changes that have been undertaken in terms of an exercise and reconstruction projects and programs in the areas affected by the floods. In accordance with the broad definition of policy change, this shows a major shift in how floods are handled. Although there were many clear examples of when natural hazards worked as drivers for policy change there were citations that were challenging to code since the policy changes were either vaguely expressed or difficult to judge whether they were implemented or not.

This is a constraint with the method of narrative text analysis since the categories must be mutually exclusive, meaning that a citation regarding policy change and natural hazards cannot be put into two categories. In order to answer the research questions, the reports have to be coded as either Yes= policy change after natural hazards or No= absence of policy change after natural hazards. The few citations that were vague were therefore coded in the category of no policy change after natural hazard events. Continuing, there are many examples in the reports when a natural hazard is mentioned without a policy change or the other way around. One example is found in the national progress report on the implementation of the HFA 2013-2015 by Bhutan:

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farmers. There is therefore an urgent need to strengthen forecasting capabili-ties and build early warning and information communication channels between technical/government agencies and to the community level.”

This was not coded as a policy change following a natural hazard event since no policy change is mentioned, only that there is a need for a policy change to prevent further losses after storms in the area. Following the defi-nition of a policy change, it requires ’incremental shifts in existing structures, or new and innovative policies’ (Bennet and Howlett 1992) which is not men-tioned in this report by Bhutan.

3.4 Limitations

The main limitation of this study is that the national progress reports on the implementation of HFA 2013-2015 are self-reported. When narratives of natural hazards and policy changes are of interest there will always be some aspects of subjectivity since it is the narrator’s social construction of reality. The reports are hence subjective. The narrator can choose how to tell the story and that comes with validity problems since the narrator can choose to either exaggerate or restrain their version of the truth. This validity concern might lead to an under- or overrating of the extent to which and how countries refer to natural hazards as drivers for policy changes based on the information assessed in the national progress reports.

With this in mind, this study can only draw conclusions on the results of the extent to which countries affected by natural hazards refer to earlier catastrophes as drivers for policy change in the national progress reports on the implementation of the Hyogo Framework for Action 2013-2015 submitted to the UNDRR. However, this method and material is still motivated to use since it is the best option available giving a good insight in how countries submitting their national progress reports to the UNDRR and hence providing a systematic study on a larger scale than most studies currently published.

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possible. Hence, an intracoder reliability test, meaning that the author of this thesis coded the material two times, was the best option at hand. Although the EM-DAT database is one of the most well-used and comprehensive databases and presents similar numbers as other databases on natural hazards such as Sigma and NatCat that are constructed a bit differently, it has its limitations. A recent study shows that EM-DAT has missing data on damage in terms of deaths and affected in about 16 percent of the natural hazard events which strongly indicated an urgent need for improvement (Guha-Sapir et. al 2017). Despite its limitation, the EM-DAT is still the best option of a database for this study since it is open for public access, unlike the other major databases. The insufficient information data on damage is not affecting the analysis since the focus is on the number of natural hazard events rather than the effects of them.

As the countries submitting their reports on the national progress on the implementation of the HFA 2013-2015 are responsible for reporting their own results of policy change during the period it opens up for problems with countries not providing all policy changes that have been taking place, or exaggerated results. Furthermore, the period of 2013-2015 excludes policy changes undertaken in the HFA reports from 2005-2013. Many countries might have adopted and implemented policies in efforts to reduce risks after natural hazard events during 2011-2013 in the reports from 2011-2013 that will be missed out in this analysis.

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Results and analysis

In this section, the results of the study will be presented and analyzed. A summary of the natural hazards affecting the countries in the data set will be presented at first to provide a basis of information for the countries that are being analyzed. Then the result and analysis of the extent to which and how countries refer to natural hazards through the empirical research questions: (1) How many countries refer to earlier natural hazards as drivers for policy change? and (2) Are there any natural hazards that can be classified as focus-ing events? will follow. A discussion and highlightfocus-ing of the main findfocus-ings of the study and future outlooks close the section.

The number and type of natural hazards measured in the International Disaster Database EM-DAT 2011-2013 differ from country to country and from region to region giving that some countries are more affected than others. See Appendix 1 for details on numbers and type of natural hazards. The three countries with the biggest frequency of natural hazards; the Philippines, Indonesia, and India, are all Asian countries. Another pattern that can be seen is that floods and storms followed by extreme temperatures are by far the most frequent natural hazard events hitting almost every country in the data set. When floods and storms are affecting all continents of the world, extreme temperatures are most frequent in European countries. And hardly surprising, earthquakes and volcanic activities are more frequent in countries in earthquake-prone areas.

27 of 54 countries have had less than 5 natural hazards during 2011-2013 and for the remaining 27, the number of natural hazards varies from 5 up to 68. With the relatively high numbers of natural hazards for half of the data set, one could think that it would result in many policy changes if they are windows of opportunities to become focusing events.

4.1 How many countries refer to earlier natural hazards

as drivers for policy changes?

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reports are emphasizing natural hazards as drivers for policy changes and some countries that do not. Out of the 54 countries affected by natural hazards ac-cording to EM-DAT, 25 countries reported policy changes in the aftermath of a natural hazard event and 29 did not. The countries that did not mention any natural hazards events as drivers for policy changes are represented in most continents and a common denominator seems to be that they are not affected by more than 5 natural hazard events during 2011-2013. Examples of coun-tries not mentioning policy change after natural hazards are Norway, Rwanda, Kenya, and Lao people’s Democratic Republic. But having few catastrophes is not equivalent to a total absence of policy changes in the aftermath of natural hazard events. 9 of the 25 countries that did report natural hazards as drivers for policy changes also had 5 or fewer catastrophes during 2011-2013; Sweden, Austria, Fiji, and Bhutan for example. For a list of all countries mentioning and not mentioning policy change, see Appendix 1.

Figure 1: Mentions of policy change as a result of natural hazards

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non-policy changes after natural hazards could be a lot. Given this, it can never be excluded that these policy changes would have been implemented even without these natural hazards. But the result that a common denominator for countries not mentioning policy changes after natural hazards are that they have 5 or less natural hazards indicate that natural hazards are the drivers for policy changes in the wake of natural hazards.

As mentioned in the theory section on the position on natural hazards as non-drivers for policy change, Thomalla et. al (2006) argue that countries frequently exposed to major natural hazards tend to allocate resources to recovery and rebuild what was destroyed rather than developing policies of DRR to reduce the vulnerability for future natural hazards. This could be another potential explanation to why some countries do not mention policy changes after natural hazards, but it does not suit these results very well as all countries frequently affected by natural hazards during 2011-2013 mention policy change as a result of natural hazards.

4.2 Are there any natural hazards that can be classified

as focusing events?

For the countries that did mention policy changes in the wake of natural hazard events in the national progress reports on the implementation of the HFA 2013-2015, there are some interesting observations to be made. As to be seen in table 1, in most cases the number of natural hazard events is higher than the reported policy changes undertaken as a result of natural hazards during 2013-2015. The exceptions are New Zealand, Bhutan, and Sweden with more policy changes as a result of natural hazards than the number of natural hazards during 2011-2013. None of the countries mentioned have many natural hazard events compared to the Philippines, India, and Indonesia which are the most vulnerable countries in the selection, yet their ratio of policy changes relative to natural hazard events is very high.

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a magnitude of 7.1, followed by a highly devastating magnitude 6.3 aftershock, led to a range of reviews on the efficiency of the emergency response and risk reduction practices highlighting the importance of resilience (New Zealand national progress report on the implementation of the HFA 2013-2015). Table 1: Number of mentions of policy change as a result of natural hazards and number of natural hazards

Country Number of mentions of policy change as a result of a natural hazards Number of natu-ral hazards Afghanistan 1 21 Australia 1 8 Austria 1 2 Denmark 1 2 Georgia 1 6 India 1 35 Indonesia 1 41 Nigeria 1 6 Philippines (the) 1 68 Serbia 1 5 Switzerland 1 5 Viet Nam 2 19

Czech Republic (the) 2 3

Fiji 3 3 Sweden 2 1 Thailand 2 10 Turkey 2 6 United Kingdom 2 10 Germany 3 7 Mozambique 3 3 Nepal 3 12 Bangladesh 4 13 Bhutan 6 1 Pakistan 7 11 New Zealand 11 6

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that are implemented as results of natural hazards and what types of natural hazards that works as drivers for policy change, it had to be excluded from this study due to constraints in time and space.

Birkland (1997) defined a potential focusing event as ”an event that is sudden, relatively rare, can be reasonably defined as harmful or revealing the possibility of greater potential future harms, inflicts harms or suggests poten-tial harms that are or could be concentrated on a definable geographical or community of interest, and that is known to policymakers and the public vir-tually simultaneously”. As potential focusing events become focusing events when they lead to policy changes (Michaels et. al 2006:983) it becomes clear that the earthquakes in New Zealand during 2010 and 2011 were focusing events. Not only were they sudden and harmful inflicting the possibility of future harms, but they also struck in New Zealand’s second-largest metropoli-tan area and affected the everyday life of many people (New Zealand national progress report on the implementation of the HFA 2013-2015).

The national progress report on the implementation of the HFA 2013-2015 by Bhutan is another interesting case since they report six policy changes with only one natural hazard measured in the EM-DAT during 2011-2013. The national progress report on the implementation of the HFA 2013-2015 mentioned the earthquake events in 2009 and 2011 working as the drivers for policy changes such as School Disaster Preparedness Day on the anniversary of the earthquake in 2009 that struck the province of the capital in Bhutan to ensure a culture of disaster resilience in schools (Bhutan national progress report on the implementation of the HFA 2013-2015). They also formulated the Bhutan Disaster Assessment Tool to receive humanitarian assistance and relief for future earthquakes. Bhutan has put a major focus on making policy changes to strengthen their resilience and to integrate DRR in post-natural hazard activities. According to EM-DAT the 2011 earthquake measured a magnitude of 6,9 and affected 20 000. Both Bhutan and New Zealand are cases supporting the hypothesis on natural hazards as drivers for policy changes and they are potential focusing events that became focusing events according to the definition by Birkland (1997).

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2011-2013. The authors of the HFA report for 2013-2015 mention that there is no national recovery plan and that ad hoc arrangements have been put in place, but not institutionalized. It is also described how the main challenge is to cope with the increasing frequency and severity of natural hazards that are constantly testing the limits of its institutions and preparedness mechanisms that have been put in place (the Philippines national progress report on the implementation of the HFA 2013-2015).

The ideas by Thomalla et. al (2006) explaining why countries do not implement policy changes after natural hazards because they need to allocate resources to recovery and reconstruction rather than implementing DRR pol-icy changes to reduce vulnerability to future hazards could be an explanation for the absence of focusing events in the Philippines compared to their high number of natural hazards. The pattern of having more natural hazards than policy changes connected to them is continuing throughout the material and it cannot be concluded that the countries submitting their national progress reports on the HFA 2013-2015 refer to earlier catastrophes to a very big ex-tent. Although many countries have focusing events like the ones mentioned in Bhutan and New Zealand, they are not many relative to the number of natural hazards.

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4.3 Discussion

The results presented in this thesis show many interesting findings. One among many is that it seems like there is no general pattern regarding how countries refer to natural hazards as drivers for policy change based on the information retrieved in the national progress reports on the implementation of the Hyogo Framework for Action 2013-2015.

Two positions on the connection of policy change and natural hazards were presented in the theoretical framework; one position on natural hazards as drivers for policy change and one position on natural hazards as non-drivers for policy change. With the result that some countries mention policy changes after natural hazards, and some do not, this thesis cannot provide strong support for any of the two positions. It can rather give a limited support to both positions.The absence of a general pattern is reoccurring in a large-N working paper by large-Nohrstedt et. al (2020) where they find no empirical evidence connecting policy change to hazard frequency. They argue that their finding that natural hazards did not spur improved DRR policy globally is consistent with institutional inertia predicting that enduring policy legacies sustain rigid beliefs and practices that prevent policy renewal (Nohrstedt et. al 2020) which could be a likely explanation to the absence of policy changes after natural hazards.

Another interesting finding is that the number of natural hazards seems to be of importance for whether countries refer to natural hazards as drivers for policy changes or not. This is drawn from the finding in that a common denominator for countries not mentioning any policy change after natural haz-ards at all is that they had less than five natural hazhaz-ards during 2011-2013. As the countries not mentioning any policy changes after natural hazards vary from rich countries such as Norway and Portugal to poor countries such as Zimbabwe and Malawi, GDP might not be the main factor explaining why policy changes take place after natural hazards. Instead, this indicates that the frequency of natural hazards could be an explanation for the occurrence of policy change after natural hazards which is an interesting opening for a study with explaining ambitions.

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not many seen to the total number of 54 countries in this study. This an interesting finding in the sense that if the idea of focusing events does not apply to a broad extent in a material with countries selected on the basis that they had natural hazards large enough to be listed in the EM-DAT, it opens up for other large-N studies to examine if the same pattern goes for countries with smaller natural hazards or not. A possibility for generalization of these results lies in the research of climate adaptation and mitigation since it has been argued that DRR and climate adaptation and mitigation in many ways can be described as two sides of the same coin (Thomalla et. al 2006). Policy aspects of climate adaptation and mitigation would have been very interesting and relevant to include in the aim of this thesis, but due to the limited time frame, a limit to DRR policies was necessary. Both research on climate adaption and DRR have been actively focusing on reducing vulnerability to natural hazards and with this thesis providing new knowledge on the area of DRR, a seed has been planted for future studies on adaption and mitigation to grow on these results.

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Conclusion

The main aim of this thesis was to empirically describe to which extent and how countries affected by natural hazards refer to natural hazards as drivers for policy change. In order to meet this aim, a systematic large-N study using narrative analysis set out with two empirical research questions: (1) How many countries refer to earlier natural hazards as drivers for policy change? and (2) Are there any natural hazards that can be classified as focusing events? A the-oretical starting point to answer these questions was drawn from the different positions on the connection on natural hazards and policy change and the the-ory on policy change, focusing events and windows of opportunity. Research question (1) was answered by the result that 25 of the selected countries men-tioned natural hazards as policy change while 29 did not. Research question (2) on focusing events in the national progress reports on the implementation of HFA 2013-2015 was answered by the results that there are focusing events following the definition by Birkland (1997), especially in New Zealand and Bhutan.

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countries mentioned policy change after natural hazards. In order to give full support to any of these positions the results would have had to show that either all countries mentioned policy change after natural hazards, or no country did. This thesis makes two contributions to the research on disaster risk re-duction policy change. First, it provided a large-N systematic study on the connection on natural hazards and policy change revealing general patterns as a contrast to the many small-N case studies in the research field on disas-ter risk reduction policy change. As the research field is almost entirely built on knowledge from case studies, this study generated new knowledge on the connection of natural hazards and policy change on a larger scale. Second, it also provided a methodological contribution through the innovative use of narrative analysis. By using narrative analysis, this study reached a form of causality in terms of temporality that prior large-N studies on DRR have been missing. It reaches the criterion of temporality by proving that major natural hazards recorded in EM-DAT 2011-2013 were mentioned as drivers for policy changes in the national progress reports on the implementation of HFA 2013-2015 to a major extent in some cases, a smaller extent in some cases and not at all in some cases.

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Appendix 1

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