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. 2021 Apr 22;16(4):e0249315. doi: 10.1371/journal.pone.0249315

Willingness to help climate migrants: A survey experiment in the Korail slum of Dhaka, Bangladesh

Rachel Castellano 1, Nives Dolšak 2, Aseem Prakash 1,*
Editor: Bernhard Reinsberg3
PMCID: PMC8062004  PMID: 33886603

Abstract

Bangladesh faces a severe rural to urban migration challenge, which is accentuated by climate change and the Rohingya crisis. These migrants often reside in urban slums and struggle to access public services, which are already short in supply for existing slum dwellers. Given the inadequacy of governmental efforts, nonprofits have assumed responsibility for providing essential services such as housing, healthcare, and education. Would local slum-dwellers in Dhaka be willing to support such nonprofits financially? We deploy an in-person survey experiment with three frames (generic migrants, climate migrants, and religiously persecuted Rohingya migrants) to assess Dhaka slum-dwellers’ willingness to support a humanitarian charity that provides healthcare services to migrants. Bangladesh is noted as a climate change hotspot and its government is vocal about the climate issue in international forums. While we expected this to translate into public support for climate migrants, we find respondents are 16% less likely to support climate migrants in relation to the generic migrants. However, consistent with the government’s hostility towards Rohingya, we find that respondents are 9% less likely to support a charity focused on helping Rohingya migrants. Our results are robust even when we examine subpopulations such as recent arrivals in Dhaka and those who have experienced floods (both of which could be expected to be more sympathetic to climate migrants), as well as those who regularly follow the news (and hence are well informed about the climate and the Rohingya crisis).

Introduction

Climate change is an important global policy issue. Increasingly, leading policymakers, business leaders, celebrities, and non-governmental organizations emphasize the need for quick and substantial efforts to tackle the crisis. While policy changes such as a transition from coal to renewables in electricity generation are critical, such profound changes will eventually require citizen cooperation as well. This holds for policies targeted at climate mitigation and climate adaptation. The former pertains to policies to reduce the emissions of greenhouse gases, while the latter pertains to policies that increase the resilience to or protect from the effect of climate change [1, 2].

To what extent are citizens in a developing country willing to expend private resources to support an important climate adaptation policy, namely climate migration? Climate change is increasing the severity and frequency of extreme weather events. Because this is making some areas unfit for human habitation, individuals could adapt to climate change by migrating to a more hospitable area [3]. There is a rich literature examining support for climate mitigation policies such as carbon taxes and cap and trade, especially in developed countries [46]. This is among the first papers to examine public support for non-governmental organizations that work on climate adaptation by providing public services to climate migrants. We focus on Bangladesh, which is among the world’s most densely populated countries, and is often identified as a climate change hotspot [7]. It faces risks from rising sea-level, increased frequency of floods and droughts, and salt-water intrusion [8].

Theoretically, our paper speaks to the broader debate on citizen perceptions of salient global issues and how they form an opinion about actors, both governmental and non-governmental, that work domestically on these issues [9]. We offer several different perspectives on why respondents might or might not be willing to support an organization that supports migrants, such as empathy-driven giving and competition over scarce services. Thus, we do not have a theoretical position on which perspective will prevail and address this question empirically.

International treaties obligate domestic governments to translate them in domestic policies and enforce them. A government’s willingness to enforce international treaties as domestic policies depends, in part, on domestic support for these policies. However, citizens are unlikely to support policies that they view as an elite imposition because these policies do not address their concerns or sometimes militate against their core beliefs, as in the issue of gender equality [10] or same-sex marriage [11]. Governments fear high political costs when citizens believe that new policies clash against their interests and beliefs [12]. In some countries, international trade agreements are also viewed as elite impositions that enrich multinational corporations at the expense of workers [13]. Broadly, the populist rhetoric against globalization falls in this category. Climate change is an important global issue, but policies such as carbon taxes have invited populist backlash even in developed countries (such as the “yellow vest” protests [14] or the defeat of two carbon tax initiatives in the state of Washington [15]).

In addition to the concern about elite impositions, there is an emerging literature in development studies on “democracy recession.” In the last two decades, there has been a massive crackdown against NGOs worldwide. Governments have incentives to crack down on foreign aid when they perceive NGOs are working with their political opponents and when they perceive that NGOs do not have citizen support (therefore, the political costs of cracking down are low) [16]. Sometimes citizens believe, often abetted by autocratic governments that control the media, that NGOs work for western agendas instead of local concerns. Scholars term this as the NGOization of civil society [17]. The literature noted that as foreign donors route aid through NGOs as opposed to local governments, NGOs became visible in public service delivery–sometimes even more than the local government [18]. For example, NGOs flooded Haiti after the 2010 earthquake. Not surprisingly, Haiti has subsequently acquired the label of the “Republic of NGOs”. Competition among NGOs for funding meant that NGOs were perceived as working on agendas dictated by their donors [19]. Thus, citizens sometimes become wary of even local humanitarian NGOs, especially when they work on “global” agendas.

The extent to which support in developing countries for climate action measures up with international concern is unclear, especially if it involves citizens incurring private costs. Moreover, while the threats of the climate crisis are visible, most developing countries do not have the resources to address the climate challenge. Given the level of poverty and other pressing needs, it is unclear whether citizens in developing countries view climate change as their top policy priority. If citizens perceive climate change as an elite “western” issue, their lack of support could spill over to even non-governmental climate action. In the context of Bangladesh, this paper examines citizen support (in terms of willingness to incur private costs) for a charitable organization that serves climate migrants.

Climate migration is a form of ex situ adaptation [20]. Riguad et al. estimate that by 2050, the number of climate migrants in Latin America, sub-Saharan Africa, and Southeast Asia alone will reach 143 million, and that environmental migration in Bangladesh will outpace other internal migrations. Under the pessimistic reference scenario, they predict that 13.3 million people will become climate migrants by 2050 [21]. The National Geographic declared that while Bangladesh is “already grappling with the Rohingya crisis, it now faces a devastating migration problem as hundreds of thousands face an impossible choice between battered coastlines and urban slums” [22]. Scholars expect large-scale migration from Bangladesh’s coastal areas to its capital city Dhaka [23]. This poses a policy challenge because Dhaka is already overcrowded, with a population of 18 million that is expected to increase to about 50 million by 2050. Dhaka is the most densely populated city in the world [24], and the living conditions in Dhaka slums are getting worse as about 2,000 people move to Dhaka every day [22, 24].

New migrants require substantial private assistance, given the government’s widespread failure to provide basic public services [25]. Family networks certainly help but given the widespread poverty, this help is often inadequate. Consequently, local charities have stepped in [26], often mobilizing substantial funds from the local community. We assess individuals’ willingness to contribute to a (fictitious) charity, Bengal Humanitarian Organization, that provides healthcare to migrants. We expect a higher level of support for a charity that serves climate migrants (in relation to generic migrants) given the global advocacy of the climate problem by the Bangladesh government. The local media also reports high levels of concerns in international forums about climate issues. If local residents take cues from the global discourse, we should expect to see higher support levels for climate migrants.

In contrast to climate migrants, we expect a lower level of support (in relation to generic migrants) for a charity that serves Rohingyas, refugees from neighboring Myanmar. While there is widespread global sympathy for Rohingya refugees, the Bangladesh government treats them harshly, and the local media portrays them negatively, often blaming them for rising local crimes. In international forums, Bangladesh demands quick repatriation of the migrants to Myanmar. As we explain further in our Methodology section, we choose to use the term ‘religiously persecuted migrants’ in our survey experiment to elicit responses about the Rohingya because of the emotional saliency the term Rohingya carries in Bangladesh.

Our findings are mixed. As per our expectations, we find lower support (9% lower than the reference group) for a charity that serves Rohingyas. Much to our surprise, we find a lower willingness (16% lower than the reference group) to support climate migrants as well. Our results are robust even when we examine subpopulations such as recent arrivals in Dhaka and those who have experienced floods (both of which could be expected to be more sympathetic to climate migrants), as well as those who regularly follow the news (and hence are well informed about the climate crisis).

Migration and climate change

An alarming increase in climate-related natural disasters is leading to population dislocation. Consequently, policymakers increasingly recognize the emerging challenge of climate migration. While developed countries are responsible for the bulk of accumulated emissions driving climate change, developing countries, particularly in the global south, are disproportionately affected by climate change and are already experiencing large-scale climate migration [2729]. The majority of climate-induced displacement is typically internal to the migrant’s home country, though cross border climate migration is also expected to increase [30].

A key debate around climate migration with important theoretical and political implications is about who counts as a climate migrant. Biermann and Boas [31] argue against subsuming ‘climate refugee’ under the 1951 Geneva Convention Relating to the Status of Refugees. Instead, they advocate for a new international framework dedicated to the specific needs of climate refugees. Betts [32] argues for creating a category of ‘survival migrants’, defined as those who move outside their country of origin for threats to which there is no domestic remedy. Drawing on the experiences of climate-induced displacement in the Pacific Island of Tuvalu, some scholars reject the image and discourse of climate refugees [33, 34] because it is politically charged.

We also recognize that the term “climate migrant” is problematic since it could emphasize the “pull” of the destination more than the “push” of the source region as the driver of human movement. In addition to the negative connotations, this could also reduce the implied responsibility of the international community for their welfare. Indeed, The International Organization for Migration encourages the use of the term ‘environmental migrant’ defined as:

“A person or group(s) of persons who, predominantly for reasons of sudden or progressive changes in the environment that adversely affect their lives or living conditions, are forced to leave their places of habitual residence, or choose to do so, either temporarily or permanently, and who move within or outside their country of origin or habitual residence [35].” Due to our focus on climate change, and the contested nature of the climate refugee label, we use the term climate change migrant in this study, while recognizing its limitations.

Bangladesh is identified among the first countries to face the consequences of climate change, including migration [30, 36, 37], and ND-GAIN Country Index ranks Bangladesh as the 20th most vulnerable to climate change among 181 ranked countries [38]. About 40% of Bangladesh’s land area and 46% of its population are located in the Low Elevation Coastal Zone areas that are between 1 to 20 meters above sea level [39]. In fact, as per Raigud et al., a one-meter rise in sea level is estimated to result in a loss of more than 4,800 square kilometers of land area [21]. Because the Bangladesh government faces resource problems in constructing the “hard” adaptation infrastructure, such as seawalls, migration could be viewed as an individual-level climate adaptation strategy [4042]. Hassani-Mahmooei and Parris [37] predict changes in migration from the west, which is drought-prone, and the south, which is vulnerable to cyclones and floods, towards the northern and eastern regions. Their model predicts between 3 and 10 million internal migrants over the next 40 years in Bangladesh.

Historically, there is a steady stream of rural migrants relocating to cities in search of livelihood [43, 44], particularly in Dhaka. Climate migration is a continuation of an existing trend of rural-urban population movement. Newly arrived migrants require basic public services such as healthcare. However, governmental resources are already stretched thin with existing obligations. As scholars have noted, nonprofits often emerge to correct governmental failures in public service delivery [45]. While nonprofits secure funds from various sources, local nonprofits often rely on local funding. In this Tocquevilian [46] model of local level voluntary action, nonprofits raise resources from the communities they serve. Further, recent work suggests that climate migrants might be perceived differently from other migrants. In the context of Germany, Helbling (2020) reports that German respondents are more supportive of climate change migrants, in relation to economic migrants [47]. Hence, we examine whether Dhaka’s slum dwellers are willing to contribute to healthcare services for climate migrants who have joined their community.

Poverty is not always a barrier to philanthropy. As a percentage of income, the poor donate more to charities than the rich [48, 49]. In the United States, those in the top 20 percent of incomes contribute, on average, 1.3 percent of their income to charity while the bottom 20 percent donated 3.2 percent of their income [50]. The reason may be that empathy often drives charitable giving [51].

However, migrant reception by local communities is complex. Weber and Peek [52] report that while there was a general warm and compassionate reception of Hurricane Katrina evacuees, community leaders expressed concern that evacuees were moving ahead of local people in need of public assistance on lengthy waitlists. Ishtiaque and Mahmus [53] find that rural-urban migrants primarily move to Dhaka to access the informal economy, find a job, or earn money, and 70% of respondents believed that their migration objectives had been fulfilled. This inevitably results in increased competition for resources, particularly in areas that already face resource scarcities. Dhaka slums are overcrowded and lack adequate public services, such as housing and health [25]. Thus, this study contributes to the literature on the reception of different types of migrants among communities that are already experiencing economic struggles.

Bangladesh was the first South Asian country to formulate a Climate Change Strategy and Action Plan. In 2011, climate protection was given a stronger legal status by an amendment to the constitution, although its impact on domestic policy remains unclear. In recognition of Bangladesh’s climate leadership, Prime Minister Sheikh Hasina was awarded the 2015 United Nations Champions of the Earth award. Given the extensive focus on climate change in media and the strong advocacy by the Bangladesh government in global forums, we hypothesize:

  • H1: Survey respondents will be more willing to support climate migrants in relation to generic migrants.

We also test for public support in the context of another migration crisis that Bangladesh is facing: Rohingya who have fled neighboring Myanmar due to religious persecution. This issue has gained considerable international attention. Myanmar leader and Nobel Laureate Aung San Suu Kyi appeared before the International Court of Justice in The Hague to defend her country against the charge of genocide. However, the regional politics of the issue are complex. Although Rohingyas share the Islamic faith with most Bangladeshis, Rohingya have not been well received in Bangladesh. Ullah [54] highlights the systematic brutality towards the Rohingya population, which spans decades in Myanmar and Bangladesh. For the domestic audience, the Bangladesh government often portrays Rohingyas negatively, highlighting their criminality and illegality. The government seeks to confine them in camps, located around the Cox Bazaar area. It is very keen to repatriate them back to Myanmar; indeed, recently, it even cut off mobile phone connections to these camps [55]. In addition to the law and order issue, citizens fear that Rohingya refugees’ cheap labor depresses wages in the local job market [56]. The government is also starting to implement its plan on relocating Rohingya to an island called Bhashan Char, off the southern coast of Bangladesh. This is an incredibly controversial decision because of its vulnerability to cyclones [57]. Because of these negative narratives about Rohingyas, we hypothesize:

  • H2: Respondents will be less willing to support Rohingyas in relation to generic migrants.

Methodology

We focus on the charitable giving of slum dwellers, who constitute the majority of the Bangladeshi population and compete with new migrants for valuable public and private resources. Hence, their willingness to donate to healthcare services for new migrants sets a high bar for us to assess the level of domestic support for climate issues. After receiving permission from the University of Washington’s Human Subject Division (IRB ID: STUDY00009013), we interviewed (over Skype) several well-established survey firms in Bangladesh. We hired Sustainability Services Limited, located in Dhaka, and compensated them for administering the survey. We informed them about the ethics guidelines, including respect for the local law as well as the issue of prior, informed consent. Consequently, all respondents were adults (18+) and their verbal consent was taken before administering the survey. The payment to this firm was facilitated through University of Washington.

With the survey firm, we discussed in length about the sampling strategy and survey methodology (including sending women surveyors to interview female respondents, given the traditional nature of the Bangladesh society). We also consulted the survey firm to ensure that the survey (see S1 Appendix) in the Bengali language was both culturally appropriate and informative. For example, we had an extensive discussion on the appropriate name for the charity and what amount we should ask for in the question about donating. The firm managers also encouraged us to employ the phrase persecuted minority instead of Rohingyas in the survey instrument because the phrase Rohingya is extremely volatile in Bangladesh. Thus, while the persecuted minority clearly signals that we are asking about Rohingya, it will not unleash an emotional reaction from the respondent.

We recognize that Buddhists and Hindus could also be considered persecuted minorities in Bangladesh (although the prevalence of this persecution has decreased under the current Awami League regime) and we raised the issue with the survey firm in Bangladesh. We were advised that Hindus and Buddhist tend not to migrate to Dhaka but instead migrate to other places, like India. Furthermore, there are no media reports of large-scale violence against Hindus and Buddhists under the current Awami League regime. Indeed, this regime has cracked down on Islamic fundamentalist groups that worked with Pakistani Army during the Liberation war and were often in the forefront of fomenting violence against minorities. Thus, to guard against any confusion on the nature of religiously persecuted minorities, we chose the language in the treatment frame carefully: “religious violence is causing a large displacement of people.” Hence, we are confident that respondents interpret the term “persecuted minority” as referring to Rohingyas.

We first piloted the survey with about 200 participants to ensure that our questions were clearly understood. Then, the survey firm conducted a 1,800 in-person survey of individuals, exposing them to three different frames describing a fictitious charity’s work. Our firm administered the survey in the Korail slum in Dhaka. The survey team collected data from almost the entire Korail slum. They started with identifying five blocks based on the scoping study. The entire slum was then grouped into 20 clusters based on these blocks. Employing a single-stage cluster sampling considering gender, religion and occupations, the team interviewed 100 respondents in each cluster. When respondents did not give their consent to take part in the interview, the survey team moved to another respondent. Only one household member in each family was interviewed in this study.

Given that Dhaka has more than 3,300 slums, we recognize the issue of generalizability. These slums differ on many aspects, including the percentage of slum dwellers receiving medical services from NGOs (47% in Korail) and the composition of slum population in terms of areas/regions they come from. Based on our extensive discussion with the survey firm, we decided that given the heterogeneity among slums on different dimensions, Korail provided an appropriate survey site. However, we hope that our paper will motivate additional work in different sites to empirically assess the generalizability of our findings. Further, our regression analysis does control for some issues such as prior experience with extreme weather events, a dimension on which the composition of slum populations might differ.

Among the respondents, 97.3 percent identified at Muslim, 2.5 percent identified as Hindu, and 0.2 identified as Christian (see S6 Appendix for a table on demographics of survey participants). The national averages are 89.1 percent Muslim, 10 percent Hindu and 0.9 percent other (including Buddhist and Christian). We have a slightly higher representation of Muslims. This makes our estimates more conservative because Muslims could be expected to be more sympathetic to their co-religionists, Rohingyas, who are facing religious persecution in the neighboring country.

Our sample was equally split among men and women which approximates the national average. 46.7 percent were employed, 21.5 percent were homemakers, and 12.2 percent were unemployed but looking for work. The national unemployment rate is much lower at about 4.4 percent, further supporting the claim about the lack of economic opportunities in Dhaka slums [58].

The survey experiment follows a between-subjects design, where individuals were randomly assigned to one of the three groups (see Table 1). The groups were asked for their willingness to donate to a fictitious charity, Bengal Humanitarian Organization, which provides healthcare to migrants. Depending on the group, respondents were told that the Bengal Humanitarian Organization provides healthcare to migrants generally, climate migrants, or religiously persecuted migrants.

Table 1. Experimental frames.

Charity Recipient
Charity provides healthcare to migrants Charity provides healthcare to climate migrants Charity provides healthcare to religiously persecuted migrants
Generic Group X
Climate Frame X
Persecuted Minority (Rohingya) Frame X

Migrants have different characteristics. The vast literature on migration studies has examined public support when specific characteristics of the emigrant such as religion, gender, skill level, etc. are highlighted. We contribute to this literature by focusing attention to a specific characteristic that the literature has overlooked: climate change as a migration driver. Thus, the generic frame does not highlight any migration driver unlike the two treatment frames. Consequently, this research design allows us to assess the change in public support when one specific migrant characteristic (migration driver: climate change or religious persecution) is highlighted in the two treatment frames while all other information remains the same as the generic frame. This is also why we do not have any open-ended questions to investigate what types of migrants the respondents had in mind after reading the generic frame because we are not examining how respondents perceive generic migrants. Rather, we want to see how support for migrants might shift (in relation to the generic migrant) when one specific migration driver is highlighted.

To further elaborate, the generic migrant frame in our survey experiment is intended to capture migrants who move because of any reason including economic and/or educational opportunities. Thus, in the generic frame, the driver of the migration is not identified. In contrast, in the treatment frame, the migration driver is identified. While there is potential overlap between the generic frame and the other two frames, the objective of the generic category is to provide a benchmark (or reference category) to assess if the willingness to support the charity changes when a specific migration driver is identified in the treatment frames. Thus, in our survey experiment, frames are identical, except for one factor—the information about the migration driver. Therefore, they are not mutually exclusive. If the migration driver does matter (because it generates empathy or fear) in generating public support, then it has important policy implications.

Surveyors read a brief summary of the charity to respondents before asking them if they would be willing to donate 100 takas (the local currency) to the Bengal Humanitarian Organization. As per Mahumud et al. [59], on average, Bangladeshi households spend $1.4 per month on medicines, which amount to about 120 takas. Based on the advice of the survey company, we rounded it off to 100 takas.

To ensure that respondents understood (and were attentive to) the questions, we then asked them a set of comprehension questions. We limit this analysis to only those respondents (1,443 of the 1,800) who correctly answered all the three comprehension questions. Of the individuals who were excluded, 118 were in the generic group, 161 received the climate treatment, and 77 received the Rohingya treatment (our results hold when we examine the full sample, as shown in in Fig 2). Finally, the surveys asked questions about demographic information, media consumption, crime in Bangladesh, time spent in Dhaka, and experiences with floods.

Fig 2. Differences in willingness to donate between the generic frame and both experimental frames, all else equal (Full sample).

Fig 2

Note: This plot shows the change in the willingness to give for each frame. The generic frame is the baseline (0%). 95% confidence intervals also shown.

Our dependent variable, willingness to donate, is a five-level scale (no, probably not, maybe, probably yes, and yes). We discussed this possibility of using some sort of a slider scale to ask respondents for their support for 100-taka donation on say 1–5 scale. Because this was an in-person survey (as opposed to an online one), the survey firm thought that the logistical issues will be difficult if we were to ask respondents to use the slider on the smartphone and might even be distracting. Hence, we decided to work with a 5-point Likert scale–which is consistent with most survey experiments in the climate policy field. In S2 Appendix, we also provide an OLS estimation where we treat the dependent variable as continuous as a robustness check. Our results about the lower support for both climate migrants and Rohingya (with the generic group as the reference category) remain unchanged.

Given the categorical and ordered nature of the dependent variable, we estimate ordered probit models using the full scale. We combine the predicted probabilities of donating (combining “probably yes” and “yes”, as well as “probably no” and “no”) in post-estimation simulations [60, 61]. Following Dolšak et al., [62], we only combine the predicted probabilities of donating in post-estimation simulations in order to avoid losing precision in our results (as would occur if we collapsed the scale prior to estimation). Our ordered probit results are sample average treatment effects (SATEs), which average the expected percentage change of respondents offering support [62]. Because ordered probit coefficients are on a log-odds scale, they are more difficult to interpret then coefficients in a linear regression. Therefore, we run a simulation 10,000 times to obtain first differences between predicted values. This method requires the construction of alternative scenarios and is more useful for interpreting log-odds than trying to calculate odds or odds ratios [63].

Results

Among all respondents, 75 percent answered “probably yes” or “yes” to whether they were willing to donate. For the remainder of this paper, we report the results for willingness to donate by combining the “probably yes” and “yes” categories. 86 percent of respondents in the generic group were willing to donate. However, 61 percent of respondents receiving the climate change migrant frame were willing to donate, while 77 percent of the respondents receiving the persecuted migrant frame were willing to donate. Despite the discrepancies between these numbers, it appears that survey respondents were very generous. Even though many live in poverty, a high percentage were willing to donate to a charity they had never heard of before. While these results are encouraging, it is possible that our results suffer from social desirability bias, one of the most common biases in survey research [64]. In this case, we suspect that social desirability bias manifests in the respondent’s desire to appear charitable. We hope that future research will test this bias by observing what individuals say they will give to migrants compared to what they will actually give.

Fig 1 shows the estimated average effect of both climate and Rohingya frames on our sample of respondents. Much to our astonishment, the data not only fail to support our hypothesis of higher support for climate migrants (H1) but instead indicate lower support. As the figure below shows, the probability of giving to the climate migrants is about 16 percent less than the probability of giving to the generic group. We speculate that this finding could reflect the disconnect between elite discourse and grassroots perceptions about the importance of climate migration. Further, respondents might view that because climate migration is a “western” issue, they might assume that migrants are probably receiving help from rich international actors. After all, the Bangladesh government is vocally asking for international assistance for climate change.

Fig 1. Differences in willingness to donate between the generic frame and both experimental frames, all else equal (Attentive sample only).

Fig 1

Note: This plot shows the change in the willingness to give for each frame. The generic frame is the baseline (0%). 95% confidence intervals also shown.

Alternatively, Bangladesh citizens might harbor some sort of skepticism about the anthropogenic nature of the climate crisis. For example, a survey conducted in Bangladesh reports that 52% of respondents (and 93% of Muslims in the study) believe that climate change is due to sinful activities and the wish of God [65]–which also implies that any help rendered to climate migrants goes against the wishes of God. While we do not have the data to arbitrate among different explanations for a decreased support for climate migrants in relation to generic migrants, our results are worrisome because grassroots perceptions are particularly important when mobilizing political action around climate change [66].

Another explanation for this surprising result could be the threat of economic competition. It is possible that our respondents might conceptualize climate migrants as permanent residents who will not be able to return home, while conceptualizing generic migrants as seasonal or temporary. Therefore, the opposition to climate migrants in relation to generic migrants could be because of the potential economic threats they pose to a community where resources are already scarce. Indeed, in their study of urban-rural migrants in India, Gaikwad and and Nellis [67] find that city residents belonging to the majority religious group (in the Indian case, Hindus) do not discriminate again rural-to-urban migrants based on religious profiles. Instead, they appear to care mainly about the economic impact of migration.

In line with our expectations, as Fig 1 shows, we find support for Hypothesis 2 that the Rohingya frame will elicit less support than the generic migrant frame. The probability of giving to Rohingyas is about 9 percent less than the probability of giving to a generic migrant. This is in line with our theory that the media and the Bangladesh government have perpetuated harmful narratives about these migrants, resulting in hostility among Bangladeshis.

The results for the sample average treatment and interaction effects discussed below and are provided in tabular form in S4 Appendix.

Our results hold when we include the full sample as respondents as well. As Fig 2 shows, both the Rohingya frame and the climate change frame elicit less support than the reference group (see S5 Appendix for interaction results in tabular form).

Sub population analysis

News consumption

The news media might shape opinions about new migrants (see Question 15 in S1 Appendix). Because the Rohingya are portrayed negatively while climate change is deemed a worthy issue, those with higher media exposure levels might show more support for climate migrants and less for Rohingyas. We do not find support for the conditioning effect of media consumption. The interaction between a respondent’s frame and their answers about media does not alter the basic results and is consistent across news sub-categories (Fig 3). We suspect that this may be the case because if media is saturated with negative stories, then media might not have a conditioning effect on willingness to give.

Fig 3. Predicted differences in willingness to donate based on news consumption within the last 24 hours, all else equal.

Fig 3

Note: These points display the stimulated average effect of both treatments. For example, respondents who received the climate change migrant treatment are 11.7 percent less likely to donate if they had read the news in a newspaper and 16.4 less likely than the generic group to donate if they had not read the news in a newspaper. 95% confidence intervals are also included as horizontal lines.

Our findings raise a broader issue of how individuals access information on policy issues.

In this survey, we did not ask directly about how respondents learn about policy issues in general or about government’s positions on climate migrants. This is for two reasons. First, people typically get much of their policy information from different types of mass and social media. Of course, we do not know if this information is authoritative and if they comprehend this information. Indeed, we are not making any claim on how well informed or poorly informed individuals are about climate change, migration, or any national policies. We recognize that as boundedly rational actors, individuals develop opinions about issues based on incomplete information. Yet, no matter how incomplete or poorly informed individuals are, public opinion matters. And this is what we examine in the context for public support for a charity that provides health services to climate migrants and Rohingyas (in relation to generic migrants).

Because the media plays a crucial role in shaping public opinion, we asked questions about each respondent’s exposure to different types of mass media (Q15 of the survey) and analyzed if exposure to different mass media might influence respondent’s support for climate migrants or Rohingyas in relation to generic migrants. We have not subsumed all types of media into one category because some respondents might rely on newspapers to access policy information, while others might rely on radio. In addition, it is possible that some media might cover climate issues more extensively or effectively than others. For example, television might provide more content about challenges faced by climate migrants in relation to radio. Or, the television footage might create more empathy for climate migrants. If so, those with higher exposure to television might reveal higher support for the charity supporting climate migrants. Our model does control for factors such as prior experience with floods, which might make them more prone to access or pay attention to specific type of climate information. Finally, because this is a survey experiment in which respondents are randomly assigned to different frames, unobserved heterogeneity in respondents’ characteristics should not influence support for any frame.

When we rerun the analysis for each media type separately, our results do not change (i.e. support for climate migrants or Rohingyas in relation to the generic frame). This gives us additional confidence that the medium through which respondents might receive information is not changing the support for climate migrants in relation to generic migrants.

Experience with floods

Might respondents with similar life experiences be more supportive of climate migrants? The “linked-fate” theory [68] suggests that individuals tend to help fellow community members with whom they share life experiences. Because climate migrants of Bangladesh are often escaping rising sea level, the willingness to support climate migrants depends on whether respondents had experienced floods themselves (see Question 17 in S1 Appendix). After all, those who have experienced a natural disaster might have more empathy [50] for those who have had to suffer it as well. Though we can expect respondents to appreciate the monsoon season for replenishing water supplies and help farmer, climate change is likely to accentuate the frequency and severity of even regularly occurring weather events such as the annual flooding. Here as well, as presented in Fig 4, our results remain unchanged.

Fig 4. Predicted differences in willingness to donate based on experiencing floods, all else equal.

Fig 4

Note: These points display the estimated average effect of both treatments. For example, respondents who received the Rohingya treatment are 11.2 percent less likely to donate if they experienced floods in the last year and 9.6 percent less likely to donate if they did not experience floods in the last year. 95% confidence intervals are also included as horizontal lines.

Recent migrants

Finally, to further explore the empathy argument, we asked respondents how long they have lived in Dhaka because there might be a difference between those who had recently migrated to the city and those who have lived there for a longer time (15 years). Arguably, recent arrivals might also have stronger connections with their relatives in villages and, therefore, show a higher level of empathy for climate migrants because of the increase in environmental degradation in Bangladesh’s rural areas. However, similar to other interaction terms, respondents are still much less likely to support climate refugees (and Rohingyas) in relation to generic migrants (Fig 5).

Fig 5. Predicted differences in willingness to donate based on years lived in Dhaka, all else equal.

Fig 5

Note: These points display the estimated average effect of both treatments. For example, respondents who received the Rohingya treatment are 10.2 percent less likely to donate if they have lived in Dhaka for less than 15 years and 9.9 percent less likely to donate if they have lived in Dhaka for more than 15 years. 95% confidence intervals are also included as horizontal lines.

Conclusion

We expected that Bangladesh citizens will support NGOs providing humanitarian services to climate migrants. After all, Bangladesh is directly impacted by climate change. Hence, our survey findings are contrary to our theoretical expectations. There could be several reasons. First, we suggest that perhaps this is because citizens have already formed their opinion about climate change and NGOs working on this issue. Given the media publicity on climate issues and the constant refrain about its global implications, citizens may feel that it is an elite issue or that NGOs have foreign funding. Second, respondents might believe that because climate change is a global issue caused predominantly by developed countries, the developed North should bear the cost of helping climate migrants, as opposed to citizens of developing countries. Third, the lower rate of willingness to give among climate change migrants in relation to the generic migrants could be related to perceived economic threats about permanent versus temporary migrants. Because we do not specifically explore the reasons for distrust in NGOs, we hope future work will explore this issue in greater detail.

The subject of public support for climate migration (in relation to other types of migration) is relatively new in the climate policy literature (although as we point out in the paper, there is extensive literature on levels of climate migration and whether climate migrants should be recognized as refugees). We hope this paper will contribute to this growing field given an increased focus on climate migration, especially in the context of migration as a climate adaptation strategy.

Climate change has emerged as an important global public policy issue. However, it is not clear whether climate concerns are equally salient at the domestic level, especially in developing countries that struggle with the challenges of poverty and development. In addressing this question, this paper speaks to the broader issue of why domestic support for some international treaties tends to be spotty. Governments might sign treaties as a way of virtue signaling and ingratiate themselves with important global audiences that have championed these treaties [6971] but they may not have the local support to implement it. This sort of implementation gap might reflect the fact that international norms are not cohering with local priorities and customs [9, 72]. Worse still, some domestic audiences might view these norms as international and elitist fads that do not address pressing domestic concerns [73]. Indeed, the issue of disconnected elites that are pandering to global audiences figures prominently in the populist discourse [7476]. While much work pertains to the lack of domestic support to governmental action in response to global policy commitments, this paper extends this argument to the sphere of local support for non-governmental action.

Our paper raises an important question about the lack of political attention to climate issues within developing countries, although many will face severe consequences. In the United States, Canada and Australia, a strong fossil fuel lobby has created a climate countermovement [77]. This sort of industry-inspired backlash to climate issues tends to be missing in many developing countries; although countries such as Malaysia and Indonesia have pushed back against policies to limit deforestation, they have not questioned the science of climate change. Climate change seems to suffer from policy neglect in domestic politics because public attention tends to be focused on either bread and butter issues such as jobs, or cultural issues that often lead to religious or ethnic mobilization. This is worrisome because climate policies and rapid decarbonization will require large-scale mobilization and citizen participation, which could be impeded if citizens view climate change as a “western” issue championed by (elite) individuals and organizations that often depend on foreign funding.

While the Bangladesh government is vocal on climate issues in global forums and has formulated many national-level policies, the salience of climate change in domestic politics remains unclear. Neither the Awami League (the ruling party) or the Bangladesh Nationalist Party (the main opposition party) focuses on climate migrants’ issue. This is not limited to Bangladesh only. Its neighboring country India stakes out a climate leadership position in international forums. However, election manifestos of the two major political parties barely contained the mention of climate issues in the recent 2019 elections [78].

We hope our unexpected findings on lower-than-expected local support for climate migrants, even in a climate hotspot country, will spark new research to understand domestic support for climate adaptation. Bangladeshis are very generous despite the level of poverty in Bangladesh. As part of their religious faith, many Muslims regularly provide some sort of zakat or a religious contribution [79]. However, their support for both Rohingyas and climate migrants is below that for generic migrants. This should raise concerns about how Bangladesh will mobilize citizens to address the high level of population displacement that climate change is expected to cause.

This survey experiment has limitations, which highlight areas for further research. First, the high percentages of individuals willing to donate to the charity suggest that the results may suffer from social desirability bias [64]. A future project could compare how individuals say they will give and what they will actually give. Additionally, this study is specific to one slum in Dhaka. It would be worthwhile to examine whether survey results would differ based on geographic location and proximity to migrant populations. Third, our research design examines whether respondents are willing to donate100 takas. To further validate our study, future work could look at different “price points,” especially which are substantially higher than 100 Takas. The reason is that as the financial commitments of the donation increase, respondents might view their support for generic migrant as opposed to the climate migrant and Rohingyas differently.

Supporting information

S1 Appendix. Survey questionnaire.

(DOCX)

S2 Appendix. OLS regression.

(DOCX)

S3 Appendix. Balance table.

(DOCX)

S4 Appendix. Ordered probit results.

(DOCX)

S5 Appendix. Ordered probit results–full sample.

(DOCX)

S6 Appendix. Demographic profile of survey participants.

(DOCX)

Data Availability

Relevant data has been uploaded to the Harvard Dataverse (https://dataverse.harvard.edu) with the following DOI: https://doi.org/10.7910/DVN/HTV3DT.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Moser SC. Adaptation, mitigation, and their disharmonious discontents: an essay. Climatic Change. 2012;111(2):165–175. [Google Scholar]
  • 2.Haden VR, Niles MT, Lubell M, Perlman J, Jackson LE. Global and local concerns: what attitudes and beliefs motivate farmers to mitigate and adapt to climate change?. PloS One. 2012;7(12), p.e52882. 10.1371/journal.pone.0052882 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Mirza MMQ. Climate change and extreme weather events: can developing countries adapt?. Climate Policy. 2003;3(3):233–248. [Google Scholar]
  • 4.Mills S, Rabe BG, Borick CP. Cap-and-trade support linked to revenue use. Issues in Energy and Environmental Policy. 2015;23. [Google Scholar]
  • 5.Drews S, Van den Bergh JC. What explains public support for climate policies? A review of empirical and experimental studies. Climate Policy. 2016;16(7): 855–876. [Google Scholar]
  • 6.Baranzini A, Carattini S. Effectiveness, earmarking and labeling: testing the acceptability of carbon taxes with survey data. Environmental Economics and Policy Studies. 2017;19(1): 197–227. [Google Scholar]
  • 7.Vidal J. From heatwaves to hurricanes, floods to famine: seven climate change hotspots. The Guardian. 2017 June 23 [Cited 2020 May 7]. Available from: https://www.theguardian.com/environment/2017/jun/23/from-heatwaves-to-hurricanes-floods-to-famine-seven-climate-change-hotspots
  • 8.Barbier E. Climate change impacts on rural poverty in low-elevation coastal zones. World Bank Group Policy Research working paper; no. WPS 7475. 2015.
  • 9.Bob C. The marketing of rebellion: Insurgents, media, and international activism. Cambridge University Press; 2005. [Google Scholar]
  • 10.Price A. How national structures shape attitudes toward women’s right to employment in the Middle East. International Journal of Comparative Sociology. 2016;56(6): 408–32. [Google Scholar]
  • 11.Van Klinken AS, Gunda MR. Taking up the cudgels against gay rights? Trends and trajectories in African Christian theologies on homosexuality. Journal of Homosexuality. 2012;59(1):114–138. 10.1080/00918369.2012.638549 [DOI] [PubMed] [Google Scholar]
  • 12.Fearon JD. Domestic political audiences and the escalation of international disputes. American Political Science Review. 1994;1:577–92. [Google Scholar]
  • 13.Shaffer ER, Brenner JE. International trade agreements: hazards to health?. International Journal of Health Services. 2004;34(3):467–81. 10.2190/FB79-G25U-DWGK-C3QK [DOI] [PubMed] [Google Scholar]
  • 14.Fisher E. Unearthing the Relationship Between Environmental Law and Populism. Journal of Environmental Law. 2019;31(3):383–7. [Google Scholar]
  • 15.Karceski SM, Dolšak N, Prakash A, Ridout TN. Did TV ads funded by fossil fuel industry defeat the Washington carbon tax?. Climatic Change. 2020;158(3):301–7. [Google Scholar]
  • 16.Dupuy K, Ron J, Prakash A. Hands off my regime! Governments’ restrictions on foreign aid to non-governmental organizations in poor and middle-income countries. World Development. 2016;84:299–311. [Google Scholar]
  • 17.Hearn J. The ‘NGO‐isation’of Kenyan society: USAID & the restructuring of health care. Review of African Political Economy. 1998;25(75):89–100. 10.1002/ps.5176 [DOI] [PubMed] [Google Scholar]
  • 18.Edwards M, Hulme D. Too close for comfort? The impact of official aid on non-governmental organizations. World development. 1996;24(6):961–73. [Google Scholar]
  • 19.Kristoff M, Panarelli L. Haiti: A republic of NGOs?. InPeace brief 2010. April 26 (Vol. 23). United States Institute of Peace. [Google Scholar]
  • 20.Nawrotzki RJ, Hunter LM, Runfola DM, Riosmena F. Climate change as a migration driver from rural and urban Mexico. Environmental Research Letters. 2015;10(11): 114023. 10.1088/1748-9326/10/11/114023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Rigaud K, Sherbinin A, Jones B, Bergmann J, Clement V, Ober K, et al. Groundswell: Preparing for Internal Climate Migration. The World Bank. 2018. Available from: https://openknowledge.worldbank.org/handle/10986/29461 [Google Scholar]
  • 22.McDonnell T. Climate change creates a new migration crisis for Bangladesh. National Geographic. 2019. January 24. Available from: https://www.nationalgeographic.com/environment/2019/01/climate-change-drives-migration-crisis-in-bangladesh-from-dhaka-sundabans/ [Google Scholar]
  • 23.These are the world’s most crowded cities. World Economic Forum. 2017. Available from: https://www.weforum.org/agenda/2017/05/these-are-the-world-s-most-crowded-cities/
  • 24.McPherson P. Dhaka: the city where climate refugees are already a reality. The Guardian. 2015. December 1. Available from: https://www.theguardian.com/cities/2015/dec/01/dhaka-city-climate-refugees-reality#:~:text=%E2%80%9CWithin%20a%20week%2C%20we%20moved,and%20women%20escaping%20rural%20poverty. [Google Scholar]
  • 25.Afsar R. Internal migration and the development nexus: the case of Bangladesh. In Regional Conference on Migration, Development and Pro-Poor Policy Choices in Asia. 2003;22–24.
  • 26.Ahsan R, Kellett J, Karuppannan S. Climate Induced Migration: Lessons from Bangladesh. The International Journal of Climate Change: Impacts and Responses. 2014;5(2): 1–15. [Google Scholar]
  • 27.Connell J. Soothing breezes? Island perspectives on climate change and migration. Australian Geographer. 2013;44(4): 465–480. [Google Scholar]
  • 28.Marino E, Ribot J. Adding insult to injury: climate change and the inequities of climate intervention. Global Environmental Change. 2012;22: 323–328. [Google Scholar]
  • 29.Nishimura L. ‘Climate change migrants’: Impediments to a protection framework and the need to incorporate migration into climate change adaptation strategies. International Journal of Refugee Law. 2015;27(1): 107–134. [Google Scholar]
  • 30.McAdam J. Swimming against the tide: Why a climate change displacement treaty is not the answer. International Journal of Refugee Law. 2011;23(1): 2–27. [Google Scholar]
  • 31.Biermann F, Boas I. Preparing for a warmer world: towards a global governance system to protect climate refugees. Global Environmental Politics. 2010;10(1): 60–88. [Google Scholar]
  • 32.Betts A. Survival Migration: A New Protection Framework. Global Governance. 2010;16(3): 361–382. [Google Scholar]
  • 33.Farbotko C, Lazrus H. The first climate refugees? Contesting global narratives of climate change in Tuvalu. Global Environmental Change. 2012;22(2): 382–390. [Google Scholar]
  • 34.McNamara KE, Gibson C. ‘We do not want to leave our land’: pacific ambassadors at the United Nations resist the category of ‘climate refugees’. Geoforum. 2009;40(3): 475–483. [Google Scholar]
  • 35.Key Migration Terms. International Organization for Migration [cited 2021 January 15]. Accessed from: https://www.iom.int/key-migration-terms.
  • 36.Barnett J. Security and climate change. Global Environmental Change. 2003;13(1): 7–17. [Google Scholar]
  • 37.Hassani-Mahmooei B, Parris BW. Climate change and internal migration patterns in Bangladesh: an agent-based model. Development Economics. 2012;17(6): 763–780. [Google Scholar]
  • 38.Notre Dame Global Adaptation Initiative. ND-GAIN Country Index. 2007. Accessed from: http://index.gain.org/. Accessed through PREPdata, [date]. www.prepdata.org.
  • 39.McGranahan G, Balk D, Anderson B. The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environment and Urbanization. 2007;19(1): 17–37. [Google Scholar]
  • 40.McLeman R, Smit B. Migration as an adaptation to climate change. Climatic change. 2006;76(1–2): 31–53. [Google Scholar]
  • 41.Perch-Nielsen SL, Bättig MB, Imboden D. Exploring the link between climate change and migration. Climatic change. 2008;91(3–4): 375. [Google Scholar]
  • 42.Kartiki K. Climate change and migration: a case study from rural Bangladesh. Gender and Development. 2011;19(1): 23–38. [Google Scholar]
  • 43.Todaro M. A model of labour migration and urban unemployment in less developed countries. American Economic Review. 1969;59: 138–148. [Google Scholar]
  • 44.Harris J, Todaro M. Migration, unemployment and development. American Economic Review. 1970;60: 126–142 [Google Scholar]
  • 45.Weisbrod B. The nonprofit economy. Boston: Harvard University Press; 1988. [Google Scholar]
  • 46.Tocqueville A. Democracy in America, ed Mayer J. P. and trans. Lawrence, George. Doubleday Anchor Book; 1969. [Google Scholar]
  • 47.Helbling M. Attitudes towards climate change migrants. Climatic Change, 2020; 1–14. [Google Scholar]
  • 48.Egan B. The Widow’s Might: How Charities Depend on the Poor. London: Allen Lane; 2001. [Google Scholar]
  • 49.Wiepking P. The Philanthropic Poor: In Search of Explanations for the Relative Generosity of Lower Income Households. Voluntas. 2007;18: 339–358. [Google Scholar]
  • 50.Stern K. Why the Rich Don’t Give to Charity. The Atlantic. 2013. April. Available from: https://www.theatlantic.com/magazine/archive/2013/04/why-the-rich-dont-give/309254/ [Google Scholar]
  • 51.Piff PK, Kraus MW, Côté S, Cheng BH, Keltner D. Having less, giving more: the influence of social class on prosocial behavior. Journal of Personality and Social Psychology. 2010;99(5): 771. 10.1037/a0020092 [DOI] [PubMed] [Google Scholar]
  • 52.Weber L, Peek LA. Displaced: Life in the Katrina diaspora. University of Texas Press; 2012. [Google Scholar]
  • 53.Ishtiaque A, Mahmud MS. Migration objectives and their fulfillment: a micro study of the rural-urban migrants of the slums of Dhaka city. Geografia: Malaysian Journal of Society & Space. 2011; 7(4): 24–29. [Google Scholar]
  • 54.Ullah AA. Rohingya refugees to Bangladesh: Historical exclusions and contemporary marginalization. Journal of Immigrant & Refugee Studies. 2011; 9(2): 139–161. [Google Scholar]
  • 55.Bangladesh cut mobile internet access in Rohingya camps. AFP Deccan Herald. September 2019 10. Available from: https://www.deccanherald.com/international/bangladesh-cut-mobile-internet-access-in-rohingya-camps-760546.html (accessed May 7, 2020).
  • 56.Rahman U. The Rohingya refugee: A security dilemma for Bangladesh. Journal of Immigrant & Refugee Studies. 2010; 8(2): 233–239. [Google Scholar]
  • 57.Bangladesh: Rohingya Refugees in Risky COIVD-19 Quarantine. Human Rights Watch. May 2020 5. Available from: https://www.hrw.org/news/2020/05/05/bangladesh-rohingya-refugees-risky-covid-19-quarantine# (accessed April 26, 2020)
  • 58.Bangladesh. Central Intelligence Agency. The World Factbook 2017. [Cited May 2020 4]. Available from: https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html
  • 59.Mahumud R, Sarker A, Sultana M, Islam Z, Khan J, Morton A. Distribution and Determinants of Out-of-pocket Healthcare Expenditures in Bangladesh. Journal of Preventive Medicine and Public Health. 2017; 50(2): 91–99. 10.3961/jpmph.16.089 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Hanmer M, Kalkan K. Behind the curve: Clarifying the best approach to calculating predicted probabilities and marginal effects from limited dependent variable models. American Journal of Political Science. 2013; 57(1): 263–277. [Google Scholar]
  • 61.King G, Tomz M, Wittenberg J. Making the Most of Statistical Analyses: Interpretation and Presentation. American Journal of Political Science. 2000;44(2): 341–355. [Google Scholar]
  • 62.Dolšak N, Adolph C, Prakash A. Policy Design and Public Support for Carbon Tax: Evidence from a 2018 U.S. National Online Survey Experiment. Public Administration; 2020. [Google Scholar]
  • 63.Ward M, Ahlquist J. Maximum Likelihood for Social Science. Cambridge: Cambridge University Press; 2018. [Google Scholar]
  • 64.Nederhof AJ. Methods of coping with social desirability bias: A review. European Journal of Social Psychology. 1985;15(3): 263–280. [Google Scholar]
  • 65.Haq SM, Ahmed KJ. Does the perception of climate change vary with the socio-demographic dimensions? A study on vulnerable populations in Bangladesh. Natural Hazards. 2016. 1;85(3):1759–85. [Google Scholar]
  • 66.Gaikwad N. and Nellis G. The majority‐minority divide in attitudes toward internal migration: Evidence from Mumbai. American Journal of Political Science, 2017; 61: 456–472. [Google Scholar]
  • 67.Rootes C, Zito A, Barry J. Climate change, national politics and grassroots action: An introduction. Environmental Politics. 2012; 21(5): 677–690. [Google Scholar]
  • 68.Dawson MC. Behind the Mule: Race and Class in African-American Politics. Princeton, NJ: Princeton University Press; 1994. [Google Scholar]
  • 69.Goldsmith JL, Posner EA. The Limits of International Law. Oxford, UK: Oxford University Press; 2005. [Google Scholar]
  • 70.Hafner-Burton EM. Trading Human Rights: How Preferential Trade Agreements Influence Government Repression. International Organization. 2005; 59(3): 593–596. [Google Scholar]
  • 71.Vreeland J. Political Institutions and Human Rights: Why Dictatorships Enter into the United Nations Convention Against Torture. International Organization. 2008;62 (1):65–101. [Google Scholar]
  • 72.Reimann K. A view from the top: International politics, norms and the worldwide growth of NGOs. International Studies Quarterly. 2006;50(1): 45–67. [Google Scholar]
  • 73.Matejova M, Parker S, Dauvergne P. The politics of repressing environmentalists as agents of foreign influence. Australian Journal of International Affairs. 2018;72(2): 145–162. [Google Scholar]
  • 74.Rodrik D. Populism and the Economics of Globalization. Journal of international business policy. 2018;1(1–2): 12–33. [Google Scholar]
  • 75.Patana P. Changes in local context and electoral support for the populist radical right: Evidence from Finland. Party Politics. 2018: 1–12. [Google Scholar]
  • 76.Guiso L, Helios H, Massimo M, Sonno T. Global crises and populism: the role of Eurozone institutions. Economic Policy. 2019;34(97): 95–139. [Google Scholar]
  • 77.Brulle RJ. Institutionalizing delay: foundation funding and the creation of US climate change counter-movement organizations. Climatic change. 2014;122(4): 681–694. [Google Scholar]
  • 78.Dolšak N, Prakash A. Are India’s Political Parties Ignoring Climate Change? April 2019. 13. Forbes.com. 10.1016/j.ejmech.2019.06.030 [DOI] [Google Scholar]
  • 79.Sohag K, Mahmud K, Alam F, Samargandi N. Can zakat system alleviate rural poverty in Bangladesh? A propensity score matching approach. Journal of Poverty. 2015;19(3): 261–277. [Google Scholar]

Decision Letter 0

Bernhard Reinsberg

16 Dec 2020

PONE-D-20-35549

Willingness to Help Climate Migrants: A Survey Experiment in Bangladesh

PLOS ONE

Dear Dr. prakash,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both reviewers raise serious concerns about the paper. While Reviewer 1 has serious doubts and cannot recommend an invitation to revise, Reviewer 2 is more positive. My own reading is closer to Reviewer 2, which is why I would like to invite you to revise and resubmit the paper. I would like to stress that the changes necessary to make the paper publishable are significant.

In particular, I would like you to

* sharpen the theoretical expectations by engaging more closely with the literature on ‘climate migrants’

* better motivate case selection and discuss issues of external validity

* enhance internal validity by doing appropriate balance tests and address attrition issues

* improve the presentation of findings along the lines suggested by the Reviewers

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: PONE-D-20-35549

Willingness to Help Climate Migrants: A Survey Experiment in Bangladesh

My general assessment is that the paper contains an interesting idea, which unfortunately has been executed poorly and unconvincingly. In particular, I have some serious concerns regarding the lack of theory and the insufficient execution of the empirical analysis, in particular the survey experiment. This paper needs a lot of work in many areas. I have suggested some but do not feel that a revise and resubmit is appropriate.

Specific comments

Title: I wonder whether the results could be generalized to other slums in Dhaka, let alone to the country as a whole. The title does not even mention that the focus of this study is on a Dhaka slum, and thereby implicitly suggests a broader applicability of the findings at the national level. Hence, given that there is not much in the paper to suggest the findings are more widely applicable, the title should probably be adjusted accordingly.

Abstract: I find the conclusion in the abstract regarding the implications of the findings for support for global policy agendas a little fuzzy and somewhat farfetched, especially, since the main document does not deduce these implications from the empirical evidence.

Introduction

The introduction contains several statements that need better elaboration and/or justification. For instance it is not clear how this paper “…speaks [theoretically] to the broader issue of public support for global policy agendas” (ll. 73-75), when the paper empirically addresses citizens support for a local humanitarian organization aiming at providing health services to ‘climate’ migrants. Furthermore, it is not clear why citizens’ perception in less developed countries of climate change as an elite ‘western’ issue could lead to their lack of support to non-governmental climate action (ll. 83-85).

The authors cite Rigaud et al (2018) to emphasize the effects of climate on future migration flows (ll. 88-90). Given that the focus of the paper is on Bangladesh, the authors could instead mention the Rigaud et al study, which contains a sub- chapter on Bangladesh and estimates that climate induced migration will outpace other internal migrations and predicts that 13.3 million people will be force to move by 2050 under the pessimistic reference scenario. Furthermore, while it is stated that “…[Dhaka] is expected to increase to about 50 million by 2050” (l.95; also a reference is needed here), the Rigaud et al study predicts that climate change will dampen population growth in urban areas such as Dhaka and the river delta south of the city, which will constitute ‘climate’ outmigration hotspots.

The authors state: “Dhaka is the most densely populated city in the world, and the living conditions in Dhaka slums are getting worse as new refugees arrive, about 2,000 a day [The Gardian (15)]” (ll. 95-97). However, it seems that the authors have misquoted the article in the Guardian, since it never mentions ‘climate refuges’, and simply states: “Every day, another 2,000 people move to the Bangladeshi capital. It’s nothing new – for generations Dhaka has been a magnet for those escaping rural poverty – but now climate change is accelerating the race to the city”.

The authors distinguish between three types of migrants, namely ‘religiously persecuted’ ‘climate’, and ‘generic’ (ll. 103-109). While the two first categories could be easily –relatively speaking- defined, the generic one needs to be clarified. That is, what exactly does this category include? Only people, who moved in search for better jobs, economic and educational opportunities as well as standards of living? Or also people, who moved in order to save their lives from political/religious persecution as well as natural disasters? (more on this below)

It is not clear what type of migration the authors study. On the one hand, they talk about climate migrants moving to Dhaka (internal migration) and on the other, refugees from neighbouring Myanmar (Rohingyas) fleeing to Dhaka (international/cross boarder migration) (ll. 103-109). However, in the ‘persecuted migrants treatment’, the Rohingyas are never mentioned and as a result, the respondents were never treated to this specific type of migration (ll. 598-6006). (more on this below)

Migration and Climate Change

The authors do not need to discuss the debate about ‘who counts as a climate migrant (ll.129-141), this debate is well known in the literature. Furthermore, they chose to use the term ‘climate change migrant’ instead of ‘climate refugee’ due to the latter’s contested nature (ll.140-141). Unfortunately, the term “climate migrant” is also problematic since it implies the “pull” of the destination more than the “push” of the source region and carries negative connotations, which reduce the implied responsibility of the international community for their welfare. I believe that the authors should use the term ‘environmental migrant’, which was put forward by IOM in 2007 and is widely used in the relevant literature. That is, “Environmental migrants are persons or groups of persons who, predominantly for reasons of sudden or progressive change in the environment that adversely affects their lives or living conditions, are obliged to leave their habitual homes, or choose to do so, either temporarily or permanently, and who move either within their country or abroad”.

In describing the vulnerability of Bangladesh to climatic changes (ll. 142-150), the authors should use better and more recent references such as the ND-GAIN country Index or the Climate Change Vulnerability Index as well as the Groundswell Report (2018).

The authors state: “Hence, we examine whether Dhaka’s slum dwellers are willing to financially support climate migrants who have joined their community” (ll.158-160). However, a donation to a humanitarian organization, which provides only healthcare services, does not qualify as ‘financial support’ to climate migrants.

Overall, I miss a theoretical argument why “Survey respondents will be more willing to support climate migrants in relation to generic migrants” (H1, LL.183-184), and “Respondents will be less willing to support Rohingyas in relation to generic migrants” (H2, l.204). Especially since the authors state contradictory arguments: on the one hand, respondents might be will to support climate migrants due to empathy (ll.161-165), and on the other, they might not be willing to support them due to competition over scarce public services such as health (ll. 172-174). The authors hence need to develop the arguments more thoroughly, thereby directing the reader to the hypotheses that are tested afterwards. In addition, the survey experiment is not appropriate for testing H2 since it did not explicitly mention the Rohingyas, but rather people who were displaced by religious violence!

Methodology

Selection of the survey site: The survey took place in the Korail slum in Dhaka. Given that Dhaka city has more than 3,300 slums (inhabited by an estimated 6.5 million people), a justification of the selection of this site is needed in order for the findings to be generalized to other slums and to allow for the conclusions the authors reach regarding the lack of support for global policy agendas. In other words, would the authors obtain similar results if they conducted their survey experiment in, say, the Sattola slum instead? Both Korail and Sattola are established slums in the North Dhaka City Corporation, situated beside elite, residential areas of Dhaka city, where land prices are high and there is high potential for urban development. However, in Korail slum, about 47% slum dwellers obtain medical service from NGOs, which is much higher compared to the Sattola slum dwellers where only 33% get medical services from NGOs. In addition, while many Korail dwellers have been relocated there due to major eviction drives in other Dhaka slums (Korail has never fallen victim to evictions owing to its strong political backing), in Sattola most migrants come from different disaster-prone and river-eroded areas such as the northern chars and the coastal belt.

Selection of respondents: the reader should know more about the procedure and criteria how respondents were selected. E.g. did the data collection cover the entire Korail slum or only specific neighbourhoods (which ones)? was cluster sampling used? The authors, hence, need to describe better the survey design. I know how challenging it is to reach and interview people especially in challenging locations, such as Bangladesh. I do not mean to imply that one needs to have the same level of sophistication in sampling procedures as we would expect from survey research in OECD countries. However, it is important to communicate just how the sample was constructed, beyond and above, showing that it is balanced in sex and closely matches national averages in religion and occupation.

Frame experiment (Appendix S1)

Generic Frame: the ‘generic frame’ includes ‘people, who for a variety of reasons are forced to leave their homes and move to other areas in search for a better future or a safer place’ (ll. 589-591). However, this category of migrants presents severe identification problems for the frame experiment, since it is not mutually exclusive from the other two categories of migrants. Take for instance the ‘climate’ migrant frame: since, it is extremely difficult to disentangle the environmental from the economic reason of migration, it is possible that for many respondents the ‘generic’ frame contains also climate induced migration. Furthermore, and perhaps more importantly, the ‘generic’ frame contains information, i.e., “They are in urgent need of humanitarian assistance.” (l. 592), which is missing in the two treatment frames. This information makes the ‘generic’ frame much stronger than the two treatment frames, affecting hence the responses and the empirical results.

‘Persecuted Migrants Treatment’: given that ‘persecuted migrants treatment’ never mentioned the Rohingyas, it is very likely that the respondents perceived the ‘religious violence’ to apply to the domestic religious/ethnic minorities. In Bangladesh, even though the government publicly supports(ed) freedom of religion, still Hindu, Christian, and Buddhist minorities experience(d) discrimination and sometimes violence from the Muslim majority. Hence, it is not surprising that the survey respondents, who are mostly Muslims (98%), would not support giving to a charity that aims at helping these minority groups.

‘Climate Migrants Treatment’: the authors state that heavy flooding is associated with climate change (ll. 610). Why? Bangladeshis know that the monsoon season always brings heavy rainfall to the country, which is critical for replenishing water supplies and helps farmers, but it can also cause great damage! Furthermore, the mentioning of climate change might lead to biased responses, as rightly the authors point out (ll. 293-297).

Results

The authors need to discuss the possibility that the ‘high willingness to donate’ observed in their data ((ll.274-282)) might be due to social desirability bias.

The interpretation of the finding of low support for climate migrants is quite superficial (ll.287-292).

There are also some contradictions. For instance, they authors attribute the low probability of giving to the ‘persecuted migrants’ (i.e., Rohingyas) to the media and the Bangladesh government, which have perpetuated harmful narratives about these migrants (ll. 301-305), even though they do not find any support for the conditioning effect of media consumption! (ll. 312-317).

Conclusion

A large part of this section is quite unrelated to the research question of this paper and confusing (ll. 347-379).

Reviewer #2: This manuscript sets out to investigate the preferences of slum dwellers in Dhaka, Bangladesh regarding three categories of migrants: generic migrants, climate migrants, and religiously-persecuted refugees. Specifically, the researchers embedded a survey experiment in a survey of 1,800 respondents. Respondents were provided vignettes about a fictitious humanitarian group seeking to raise funds for migrants who were randomly described as belonging to one of the three categories above. Respondents were then asked whether they were willing to donate funds to support the charity. The authors find high levels of support for willingness to contribute funds when the migrants in question were generic migrants: 86 percent of this treatment arm agreed to support the humanitarian charity. Against expectations, support plummeted for climate migrants (61 percent) as well as for religiously persecuted migrants (77 percent).

Overall, this is a nicely conceptualized and executed study, and it contributes to scholarly knowledge in an important domain where empirical research is scarce. Nevertheless, I would urge the authors to address the following questions and suggestions:

1. The manuscript could do more to theoretically motivate its predictions regarding climate migrants (H1) and its interpretations of the empirical tests of H1. The authors argue that poor Dhaka residents should theoretically be more in favor of climate migrants since the Bangladeshi government has prioritized climate change and has highlighted the plight of climate refugees in the past. That government actions shape citizen preferences is a plausible conjecture. At the same time, the literature on migration (both cross-border and internal) has clearly identified economic competition to be an important predictor of nativist preferences toward migrants. Both job market competition and fiscal pressures (e.g., competition for public housing, education, employment, etc.) can lead locals to oppose the entry of migrants. Climate migrants are likely a special category of migrants, since presumably they are permanent migrants who have little ability to return to their “homes.” Hence, they might produce pronounced economic threats to locals. By contrast, it is quite possible that generic migrants are conceptualized as temporary or seasonal migrants (or at the very least not as permanently dependent on the welfare state in Dhaka as climate migrants). In this theoretical light, the pronounced opposition to climate migrants (compared to the generic migrants) that the manuscript documents might appear to be quite reasonable and rational. These are the types of migrants who plausibly pose the starkest economic threats to the poor slum-dwellers in the study’s sample. I encourage the authors to discuss and probe this possibility, both theoretically and in their analysis of the results. One idea would be to analyze whether the treatment effects vary by respondents’ household monthly incomes.

2. The manuscript should do more to interpret the “willingness to donate” outcome measure that is used in all of the primary analyses. Since this is a self-reported measure that does not have a behavioral component (i.e., an observed measure of how much subjects would have actually donated if given the option), it is a bit unclear how readers should interpret this measure. Clearly, the baseline levels of professed support are very high. Given the low socio-economic status of the sample, it is unlikely that such a high proportion of respondents (75 percent across all treatment arms) would in reality donate funds to charities. Are the authors concerned about survey response bias? Of particular concern is the possibility that survey response bias is lower for religiously persecuted migrants and climate migrants, which may explain why subjects are more willing to deny donating funds to support these particular types of migrants. The authors could comment on these possibilities and ideally offer some kinds of empirical evidence to explore and rule them out. More broadly, the manuscript would be stronger if it provided guidance to readers on how to interpret the self-reported willingness to pay measure.

3. The manuscript repeatedly describes the frame regarding religiously persecuted migrants as the Rohingya frame. In Appendix S1, however, the “Persecuted Migrants Treatment” does not appear to specifically mention that these migrants are Rohingya migrants. Of course, in the Bangladesh context the Rohingya are indeed the main type of religiously persecuted migrants. But if the treatment frame did not use the term Rohingya, it is not immediately clear that respondents would have assumed that the migrants in the survey vignette were Rohingya. It is fine if the authors want to retain the Rohingya terminology, but they should make clear to readers their rationale for doing so and explain why respondents would likely not have considered any other types of religiously persecuted migrants in this context.

4. Because the manuscript limits its analysis to only those respondents (1,443 of the 1,800) who correctly answered three comprehension questions, it ends up dropping subjects in what appears to be an unbalanced manner (see p. 12). Appendix S3 presents summary statistics of key variables but does not present formal statistical tests of balance. I would recommend presenting formal tests of balance. If unbalanced, it may make sense to present the results in the appendix of all of the primary analyses utilizing the full sample in the study.

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PLoS One. 2021 Apr 22;16(4):e0249315. doi: 10.1371/journal.pone.0249315.r002

Author response to Decision Letter 0


29 Jan 2021

Rebuttal Memo

Willingness to help climate migrants:

A survey experiment in the Korail Slum of Dhaka, Bangladesh

PONE-D-20-35549

We thank the reviewers for their exceptionally detailed, thoughtful, and constructive feedback. We are enclosing a rebuttal memo detailing the reviewers’ suggestions and outlining specific ways we address them in the revised manuscript.

Sincerely,

Authors

Reviewer 1

1. Title: I wonder whether the results could be generalized to other slums in

Dhaka, let alone to the country as a whole. The title does not even mention that the focus of this study is on a Dhaka slum, and thereby implicitly suggests a broader applicability of the findings at the national level. Hence, given that there is not much in the paper to suggest the findings are more widely applicable, the title should probably be adjusted accordingly.

Response:

Thank you. The new title is: “Willingness to help climate migrants: A survey experiment in the Korail Slum of Dhaka, Bangladesh”.

2. Abstract: I find the conclusion in the abstract regarding the implications of the

findings for support for global policy agendas a little fuzzy and somewhat farfetched, especially, since the main document does not deduce these implications from the empirical evidence.

Response:

Fair point. We have removed this sentence from the abstract.

3. Introduction: The introduction contains several statements that need better

elaboration and/or justification. For instance it is not clear how this paper “…speaks [theoretically] to the broader issue of public support for global policy agendas” (ll. 73-75), when the paper empirically addresses citizens support for a local humanitarian organization aiming at providing health services to ‘climate’ migrants. Furthermore, it is not clear why citizens’ perception in less developed countries of climate change as an elite ‘western’ issue could lead to their lack of support to non-governmental climate action (ll. 83-85).

Response:

Thanks for raising these issues, which we have clarified in the revised paper. There are two issues: why should citizens oppose global agendas, and second why should they oppose NGOs that are involved in climate action.

Our paper speaks to a broader debate on citizen perceptions of salient global issues, and how they form opinion about actors, both governmental and nongovernmental, that work domestically on these issues. Why should this matter? International Relations scholars have examined whether international treaties require domestic support (for example, see the literature on “two-level” games as well as “audience costs”). The reason is that international treaties obligate governments to enact and enforce policies domestically. Governments fear high political costs when citizens believe that new policies militate against their interests and beliefs. Citizens might entertain the perception that their government signed on to these treaties because it succumbed to international (often viewed as, Western or elite) pressure. Recent examples of citizen opposition include the issues of gender equality, same-sex marriage, the migration crisis in Europe, and Brexit. In some countries, international trade agreements are also viewed as elite impositions that enrich global corporations at the expense of workers. Broadly, the populist rhetoric against globalization falls in this category. Climate change is an important global issue but policies such as carbon taxes have (unfortunately) invited populist backlash even in developed countries (see the “yellow vest” protests or the defeat of two carbon tax initiatives in the state of Washington). The issue of climate migration is even more complex, given the political opposition to migration in many countries.

Why should citizens not support non-governmental organizations (NGOs) that work on humanitarian issues, irrespective of whether their action is motivated by a global policy concern? The literature suggests that citizens may sometimes think of NGOs as the part of the establishment, and not as local organization that help local communities. There is an emerging literature in development studies on “democracy recession.” In the last two decades, there has been a massive crackdown against NGOs across countries. Governments have incentives to crackdown when they perceive NGOs are working with their political opponents. They feel emboldened to crack down when they perceive that NGOs do not have citizen support (in other words, the political costs of cracking down are low).

Why the lack of support for NGOs? Sometimes citizens believe that NGOs work for western agendas instead of local concerns. Scholars term this as the “NGOization” of the civil society. In the 1990, as foreign donors began routing aid through NGOs as opposed to local governments, NGOs became visible in public service delivery –sometimes even more than the local government. For example, NGOs flooded Haiti after the 2010 earthquake. Not surprisingly, Haiti has acquired the label of the “Republic of NGOs.” Competition among NGOs for funding meant that NGOs were perceived as working on agendas dictated by their western donors. And there are also cases of NGO misconduct such as the recent Oxfam scandal. The lavish lifestyle of some NGOs also contributed to the perception among some citizens that NGOs are elites. Thus, citizens sometimes become wary of even local humanitarian NGOs especially when they work on “global” agendas.

Nevertheless, it is not clear whether Bangladesh citizens will support NGOs providing humanitarian services to climate migrants. After all, Bangladesh is directly impacted by climate change. Further, unlike Haiti where the citizen anger is often directed at foreign (and rich) NGOs, the hypothetical NGO in our survey experiment was dependent on local resources (as opposed to foreign funding). Hence, our survey findings are contrary to our theoretical expectations, as we note in the paper. We suggest that perhaps this is because citizens have already formed their opinion about climate change and NGOs working on this subject. In particular, given the media publicity on climate issues and the constant refrain about its global dimensions, citizens probably feel that it is an elite issue or that NGOs in fact have foreign funding. Because we do not specifically explore the reasons for distrust in NGOs, we hope future work will explore this issue in greater detail.

We have incorporated the above discussion both in the introduction and conclusion. In addition, we have included new citations to support our argument:

Bob, C. (2005). The Marketing of Rebellion: Insurgents, Media and Transnational Support. Cambridge University Press.

Dupuy, K., Ron, J. & Prakash, A. (2015). Hands off my regime! Governments’ restrictions on foreign aid to non-governmental organizations in poor and middle-income countries. World Development, 84: 299-311.

Edwards, M. & Hulme, D. (1996). Too close for comfort? The impact of official aid on non-governmental organizations. World Development, 24: 961-973.

Hearn, J. (1998). The ‘NGO‐isation’ of Kenyan society: USAID & the restructuring of health care. Review of African Political Economy, 25(75): 89-100.

Kristoff, M., & Panarelli, L. 2010. Haiti: A Republic of NGOs? Peace Brief 23. Washington, DC: United States Institute of Peace.

4. The authors cite Rigaud et al (2018) to emphasize the effects of climate on future

migration flows (ll. 88-90). Given that the focus of the paper is on Bangladesh, the authors could instead mention the Rigaud et al study, which contains a sub- chapter on Bangladesh and estimates that climate induced migration will outpace other internal migrations and predicts that 13.3 million people will be force to move by 2050 under the pessimistic reference scenario. Furthermore, while it is stated that “…[Dhaka] is expected to increase to about 50 million by 2050” (l.95; also a reference is needed here), the Rigaud et al study predicts that climate change will dampen population growth in urban areas such as Dhaka and the river delta south of the city, which will constitute ‘climate’ out-migration hotspots.

Response:

Thank you. We have included a citation of Raigaud et al. to note that climate induced migration will outpace other internal migrations.

5. The authors state: “Dhaka is the most densely populated city in the world, and

the living conditions in Dhaka slums are getting worse as new refugees arrive, about 2,000 a day [The Gardian (15)]” (ll. 95-97). However, it seems that the authors have misquoted the article in the Guardian, since it never mentions ‘climate refuges’, and simply states: “Every day, another 2,000 people move to the Bangladeshi capital. It’s nothing new – for generations Dhaka has been a magnet for those escaping rural poverty – but now climate change is accelerating the race to the city”.

Response:

Thank you; we have corrected the text.

6. The authors distinguish between three types of migrants, namely ‘religiously

persecuted’ ‘climate’, and ‘generic’ (ll. 103-109). While the two first categories could be easily –relatively speaking- defined, the generic one needs to be clarified. That is, what exactly does this category include? Only people, who moved in search for better jobs, economic and educational opportunities as well as standards of living? Or also people, who moved in order to save their lives from political/religious persecution as well as natural disasters? (more on this below)

Response:

Great point – we have expanded the discussion on generic migration, including those who migrate in search of any factor including better economic and educational opportunities. The objective of the generic category is to provide a benchmark (or reference category) to assess if the willingness to support the charity changes when a specific migration driver is identified in the treatment frame. We have noted this point in the revised manuscript.

7. It is not clear what type of migration the authors study. On the one hand, they

talk about climate migrants moving to Dhaka (internal migration) and on the other, refugees from neighbouring Myanmar (Rohingyas) fleeing to Dhaka (international/cross boarder migration) (ll. 103-109). However, in the ‘persecuted migrants treatment’, the Rohingyas are never mentioned and as a result, the respondents were never treated to this specific type of migration (ll. 598-6006). (more on this below)

Response:

In consultation with local survey firm, we employed the phrase “persecuted minority” instead of Rohingyas in the survey instrument. The local firm felt that the phrase Rohingya is extremely volatile in Bangladesh. Indeed, the government is seeking to relocate Rohingyas on an island which is prone to storms. Thus, while the persecuted minority clearly signals that we are asking about Rohingya, it will not unleash the passion of the respondent.

We recognize that Buddhists and Hindus could also be considered to be persecuted minorities (although less under the current Awami League regime of Sheikh Hasina) and we raised the issue with the survey firm. We were advised that Hindus and Buddhist tend not to migrate to Dhaka but instead head to say India. We have included this brief discussion in the revised paper.

8. Migration and Climate Change:

The authors do not need to discuss the debate about ‘who counts as a climate migrant (ll.129-141), this debate is well known in the literature. Furthermore, they chose to use the term ‘climate change migrant’ instead of ‘climate refugee’ due to the latter’s contested nature (ll.140-141). Unfortunately, the term “climate migrant” is also problematic since it implies the “pull” of the destination more than the “push” of the source region and carries negative connotations, which reduce the implied responsibility of the international community for their welfare. I believe that the authors should use the term ‘environmental migrant’, which was put forward by IOM in 2007 and is widely used in the relevant literature. That is, “Environmental migrants are persons or groups of persons who, predominantly for reasons of sudden or progressive change in the environment that adversely affects their lives or living conditions, are obliged to leave their habitual homes, or choose to do so, either temporarily or permanently, and who move either within their country or abroad”.

Response:

In the revised paper, we have noted the debate on climate refugees and climate migration more generally. Since the paper is focused on climate change, we believe that the use of the phrase climate migrant is appropriate. We have, however, incorporated your point about IOM, suggesting the use of the term environmental migrant.

9. In describing the vulnerability of Bangladesh to climatic changes (ll. 142-150),

the authors should use better and more recent references such as the ND-GAIN country Index or the Climate Change Vulnerability Index as well as the Groundswell Report authored by Raigud et al. (2018).

Response:

Thank you! We have referenced these indexes in the revised version.

10. The authors state: “Hence, we examine whether Dhaka’s slum dwellers are

willing to financially support climate migrants who have joined their community” (ll.158-160). However, a donation to a humanitarian organization, which provides only healthcare services, does not qualify as ‘financial support’ to climate migrants.

Response:

Fair point. We have modified the language to make clear that the support is for healthcare services.

10. Overall, I miss a theoretical argument why “Survey respondents will be more

willing to support climate migrants in relation to generic migrants” (H1, LL.183-184), and “Respondents will be less willing to support Rohingyas in relation to generic migrants” (H2, l.204). Especially since the authors state contradictory arguments: on the one hand, respondents might be will to support climate migrants due to empathy (ll.161-165), and on the other, they might not be willing to support them due to competition over scarce public services such as health (ll. 172-174). The authors hence need to develop the arguments more thoroughly, thereby directing the reader to the hypotheses that are tested afterwards. In addition, the survey experiment is not appropriate for testing H2 since it did not explicitly mention the Rohingyas, but rather people who were displaced by religious violence!

Response:

We offer several different perspectives on why respondents might or might not be willing to support an organization that supports migrants, such as empathy-driven giving and competition over scarce services. Thus, we do not have a theoretical position on which perspective will prevail; this eventually needs to be resolved empirically. We clarify these points as they relate to our hypotheses. Regarding Rohingyas, see please the response to point 7.

11. Methodology

Selection of the survey site: The survey took place in the Korail slum in Dhaka. Given that Dhaka city has more than 3,300 slums (inhabited by an estimated 6.5 million people), a justification of the selection of this site is needed in order for the findings to be generalized to other slums and to allow for the conclusions the authors reach regarding the lack of support for global policy agendas. In other words, would the authors obtain similar results if they conducted their survey experiment in, say, the Sattola slum instead? Both Korail and Sattola are established slums in the North Dhaka City Corporation, situated beside elite, residential areas of Dhaka city, where land prices are high and there is high potential for urban development. However, in Korail slum, about 47% slum dwellers obtain medical service from NGOs, which is much higher compared to the Sattola slum dwellers where only 33% get medical services from NGOs. In addition, while many Korail dwellers have been relocated there due to major eviction drives in other Dhaka slums (Korail has never fallen victim to evictions owing to its strong political backing), in Sattola most migrants come from different disaster-prone and river-eroded areas such as the northern chars and the coastal belt.

Response:

Thank you for bringing up the issue of generalizability. We expanded the discussion in the “Methodology” section that addresses the case selection of the Korail slum. We also comment on this limitation in our conclusion and discuss the need for further research in other parts of Dhaka and Bangladesh.

12. Selection of respondents: the reader should know more about the procedure and

criteria how respondents were selected. E.g. did the data collection cover the entire Korail slum or only specific neighbourhoods (which ones)? was cluster sampling used? The authors, hence, need to describe better the survey design. I know how challenging it is to reach and interview people especially in challenging locations, such as Bangladesh. I do not mean to imply that one needs to have the same level of sophistication in sampling procedures as we would expect from survey research in OECD countries. However, it is important to communicate just how the sample was constructed, beyond and above, showing that it is balanced in sex and closely matches national averages in religion and occupation.

Response:

We have included the following information in the revised manuscript. “The survey team collected data from almost entire Korail slum. They started with identifying five blocks based on the scoping study. The entire slum was grouped into 20 clusters based on these blocks. Employing a single-stage cluster sampling considering gender, religion and occupations, the team interviewed 100 respondents in each cluster. When respondents did not give their consent to take part in the interview, the survey team moved to another respondent. Only one household member in each family was interviewed in this study.”

13. Frame experiment (Appendix S1)

Generic Frame: the ‘generic frame’ includes ‘people, who for a variety of reasons are forced to leave their homes and move to other areas in search for a better future or a safer place’ (ll. 589-591). However, this category of migrants presents severe identification problems for the frame experiment, since it is not mutually exclusive from the other two categories of migrants. Take for instance the ‘climate’ migrant frame: since, it is extremely difficult to disentangle the environmental from the economic reason of migration, it is possible that for many respondents the ‘generic’ frame contains also climate induced migration.

Response:

Our objective is to assess if the support for the NGO changes if specific drivers of migration are identified. Frames are identical, except for one factor—the information about the migration driver. Therefore, they are not supposed to be mutually exclusive. In the generic frame we do not provide information of any specific migration driver: it merely assesses public support for an NGO that is providing health services to any migrant which would serve as the reference category or benchmark to assess other frames. But if the migration driver does matter (because it generates empathy or fear) in generating public support, then it has important policy implications. For example, if migration is caused by climate change, then the governments will need to sensitize the public that migrants are “victims” of exogenous factors which are beyond their control. We have briefly elaborated on this issue in the revised paper.

14. Furthermore, and perhaps more importantly, the ‘generic’ frame contains

information, i.e., “They are in urgent need of humanitarian assistance.” (l. 592), which is missing in the two treatment frames. This information makes the ‘generic’ frame much stronger than the two treatment frames, affecting hence the responses and the empirical results.

Response:

We cross-checked the survey and confirm that following sentence is identical in the generic frame and the two treatment frames: “There is a very large number of poor people in urgent need of humanitarian assistance.” Hence, generic frame is not stronger than the two treatment frames.

15. ‘Persecuted Migrants Treatment’: given that ‘persecuted migrants treatment’

never mentioned the Rohingyas, it is very likely that the respondents perceived the ‘religious violence’ to apply to the domestic religious/ethnic minorities. In Bangladesh, even though the government publicly supports(ed) freedom of religion, still Hindu, Christian, and Buddhist minorities experience(d) discrimination and sometimes violence from the Muslim majority. Hence, it is not surprising that the survey respondents, who are mostly Muslims (98%), would not support giving to a charity that aims at helping these minority groups.

Response:

Thank you, this is an important point! After much discussion with our research partners in Dhaka, we chose not to include the term Rohingya because of the emotional salience the term currently carries in Bangladesh. Indeed, the level of hostility towards Rohingya, encouraged by the government, is quite high. The local survey firm felt that Rohingya could become a trigger word and provoke an extreme negatively emotional reaction. Hence, they advised that we could still talk about Rohingyas in terms of “religious persecuted” minority without mentioning them directly. Thus, arguably, if we had employed the phrase Rohingya as opposed to a religious persecuted minority, the decline in support in this frame (in relation to the generic frame) might have been even higher. Thus, we consider our results for this frame to be conservative.

We recognize that several minorities in Bangladesh have experienced religious persecution. Yet, there are no media reports of large-scale violence against Hindus and Buddhists under the current Awami League regime. Indeed, this regime has cracked down on Islamic fundamentalist group that worked with Pakistani Army during the Liberation war and were often in the forefront of fomenting violence against minorities.

Thus, to guard against any confusion on the nature of religiously persecuted minorities, we chose the language in the treatment carefully: “religious violence is causing a large displacement of people.” We are confident that respondents recognized this as Rohingya.

As a practical matter, the out-migration of Hindus has tended to flow towards India (where it has become a political issue in the context of the Citizenship Bill) and is therefore not a major political issue within Bangladesh. We have elaborated on this issue in our “Introduction” as well as the Methodology section.

15. ‘Climate Migrants Treatment’: the authors state that heavy flooding is

associated with climate change (ll. 610). Why? Bangladeshis know that the monsoon season always brings heavy rainfall to the country, which is critical for replenishing water supplies and helps farmers, but it can also cause great damage! Furthermore, the mentioning of climate change might lead to biased responses, as rightly the authors point out (ll. 293-297).

Response:

Fair point. As scholars note, climate change is likely to accentuate the frequency and severity of even regularly occurring weather events such as the annual flooding. We have noted this in the revised paper.

16. Results:

The authors need to discuss the possibility that the ‘high willingness to donate’ observed in their data ((ll.274-282)) might be due to social desirability bias.

Response:

Fair point. We have noted this in the paper.

17. The interpretation of the finding of low support for climate migrants is quite

superficial (ll.287-292). There are also some contradictions. For instance, they authors attribute the low probability of giving to the ‘persecuted migrants’ (i.e., Rohingyas) to the media and the Bangladesh government, which have perpetuated harmful narratives about these migrants (ll. 301-305), even though they do not find any support for the conditioning effect of media consumption! (ll. 312-317).

Response:

If media is saturated with negative stories, then media will not have a conditioning effect as along as people have a baseline exposure. We have clarified this point in the revised paper.

17. Conclusion

A large part of this section is quite unrelated to the research question of this paper and confusing (ll. 347-379).

Response:

Thank you for your feedback. We reworked the conclusion and expanded upon many of the points and limitations that you commented on.

Reviewer #2

1. This manuscript sets out to investigate the preferences of slum dwellers in

Dhaka, Bangladesh regarding three categories of migrants: generic migrants, climate migrants, and religiously-persecuted refugees. Specifically, the researchers embedded a survey experiment in a survey of 1,800 respondents. Respondents were provided vignettes about a fictitious humanitarian group seeking to raise funds for migrants who were randomly described as belonging to one of the three categories above. Respondents were then asked whether they were willing to donate funds to support the charity. The authors find high levels of support for willingness to contribute funds when the migrants in question were generic migrants: 86 percent of this treatment arm agreed to support the humanitarian charity. Against expectations, support plummeted for climate migrants (61 percent) as well as for religiously persecuted migrants (77 percent).

Overall, this is a nicely conceptualized and executed study, and it contributes to scholarly knowledge in an important domain where empirical research is scarce. Nevertheless, I would urge the authors to address the following questions and suggestions:

Response:

Thank you!

2. The manuscript could do more to theoretically motivate its predictions

regarding climate migrants (H1) and its interpretations of the empirical tests of H1. The authors argue that poor Dhaka residents should theoretically be more in favor of climate migrants since the Bangladeshi government has prioritized climate change and has highlighted the plight of climate refugees in the past. That government actions shape citizen preferences is a plausible conjecture. At the same time, the literature on migration (both cross-border and internal) has clearly identified economic competition to be an important predictor of nativist preferences toward migrants. Both job market competition and fiscal pressures (e.g., competition for public housing, education, employment, etc.) can lead locals to oppose the entry of migrants. Climate migrants are likely a special category of migrants, since presumably they are permanent migrants who have little ability to return to their “homes.” Hence, they might produce pronounced economic threats to locals. By contrast, it is quite possible that generic migrants are conceptualized as temporary or seasonal migrants (or at the very least not as permanently dependent on the welfare state in Dhaka as climate migrants). In this theoretical light, the pronounced opposition to climate migrants (compared to the generic migrants) that the manuscript documents might appear to be quite reasonable and rational. These are the types of migrants who plausibly pose the starkest economic threats to the poor slum-dwellers in the study’s sample. I encourage the authors to discuss and probe this possibility, both theoretically and in their analysis of the results. One idea would be to analyze whether the treatment effects vary by respondents’ household monthly incomes.

Response:

Thank you for this insightful comment and for highlighting a plausible explanation of our results. We agree that climate migrants may pose the largest economic threat because of perceived permanence. We have included this point in the revised paper.

3. The manuscript should do more to interpret the “willingness to donate” outcome

measure that is used in all of the primary analyses. Since this is a self-reported measure that does not have a behavioral component (i.e., an observed measure of how much subjects would have actually donated if given the option), it is a bit unclear how readers should interpret this measure. Clearly, the baseline levels of professed support are very high. Given the low socio-economic status of the sample, it is unlikely that such a high proportion of respondents (75 percent across all treatment arms) would in reality donate funds to charities. Are the authors concerned about survey response bias? Of particular concern is the possibility that survey response bias is lower for religiously persecuted migrants and climate migrants, which may explain why subjects are more willing to deny donating funds to support these particular types of migrants. The authors could comment on these possibilities and ideally offer some kinds of empirical evidence to explore and rule them out. More broadly, the manuscript would be stronger if it provided guidance to readers on how to interpret the self-reported willingness to pay measure.

Response:

Thank you for bringing this up. We elaborate on our discussion of potential social desirability bias in the revised paper.

4. The manuscript repeatedly describes the frame regarding religiously persecuted

migrants as the Rohingya frame. In Appendix S1, however, the “Persecuted Migrants Treatment” does not appear to specifically mention that these migrants are Rohingya migrants. Of course, in the Bangladesh context the Rohingya are indeed the main type of religiously persecuted migrants. But if the treatment frame did not use the term Rohingya, it is not immediately clear that respondents would have assumed that the migrants in the survey vignette were Rohingya. It is fine if the authors want to retain the Rohingya terminology, but they should make clear to readers their rationale for doing so and explain why respondents would likely not have considered any other types of religiously persecuted migrants in this context.

Response:

Thank you for bringing this up. We discuss our rationale for not using the term ‘Rohingya’ in the “Methodology” section.

5. Because the manuscript limits its analysis to only those respondents (1,443 of

the 1,800) who correctly answered three comprehension questions, it ends up dropping subjects in what appears to be an unbalanced manner (see p. 12). Appendix S3 presents summary statistics of key variables but does not present formal statistical tests of balance. I would recommend presenting formal tests of balance. If unbalanced, it may make sense to present the results in the appendix of all of the primary analyses utilizing the full sample in the study.

Response:

Thank you for bringing this up. Our results hold when utilizing the full sample in the study. We have included both results in the revised manuscript.

Attachment

Submitted filename: PLOS ONE Response to reviewers.docx

Decision Letter 1

Bernhard Reinsberg

17 Feb 2021

PONE-D-20-35549R1

Willingness to help climate migrants:  A survey experiment in the Korail Slum of Dhaka, Bangladesh

PLOS ONE

Dear Dr. prakash,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

As you notice, the reviewers are more positive about your manuscript following your revisions. I agree with them but insist that you resubmit a revised paper addressing their remaining comments and concerns. Especially Reviewer 2 has some important questions that need to be addressed. Specifically, you should back up your assumptions about how individuals learn about policy positions of their government regarding climate migrants. Furthermore, you should check your survey for cues from respondents in the control group about what they think when thinking about migrants in general. This would help further increase the validity of your study.

Please submit your revised manuscript by Apr 03 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Bernhard Reinsberg, Ph.D

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: This is a strong revision and I would be delighted to see this research published, pending a few minor revisions listed below. I paid particular attention to the author(s)’ responses to the prior referee reports, and to their alterations of the manuscript to reflect their adjustments to critiques. In particular, the theoretical framework in the revised manuscript is considerably strengthened, the link between theory and empirics is more focused, and the empirical evidence remains robust to the different sensitivity checks that the author(s) have now introduced. Overall, I am impressed by the constructive revisions undertaken by the author(s) and see the author(s) as admirably responsive to the prior concerns raised in review.

Minor revisions:

1. In l.106 “especially if it involves citizens to incur private costs” would read better as “especially if it involves citizens incurring private costs.”

2. In response to R1’s excellent comments, the author(s) now address the issue of religious similarities and differences between the migrants and respondents quite extensively in the manuscript, noting that the Rohingya share the same Islamic faith as the majority of Bangladeshis (e.g., p.10), that respondents would likely not have associated the migrants with religious minorities like Hindus (p.12), and that respondents could have been expected to be “sympathetic to their co-religionists” (p.14, l.304). In neighboring India, which is frequently referenced in the manuscript, existing public opinion work shows that city residents belonging to the majority religious group (in the Indian case, Hindus) do not discriminate again rural-to-urban migrants based on religious profiles. Instead, residents from the dominant religious group appear to care mainly about the economic impact of migration. This is in fact consistent with what the author(s) find in the Bangladesh context: slum residents do not appear to heed religious concerns in responding to migration. The manuscript would be strengthened by citing and referencing these points as it would link the manuscript to broader debates in comparative politics.

Citation: Gaikwad, N. and Nellis, G. (2017), “The Majority‐Minority Divide in Attitudes toward Internal Migration: Evidence from Mumbai.” American Journal of Political Science, 61: 456-472.

3. In l.343, the sentence is missing a closed parenthesis mark.

Overall, I continue to believe that this manuscript tackles a very important subject, and I expect it to foreshadow new work on climate change and migration.

Reviewer #3: Review of:

Willingness to Help Climate Migrants: A Survey Experiment in Bangladesh

This paper examines individuals’ willingness to provide assistance to climate migrants as compared to other types of migrants by means of a survey-embedded experiment conducted in a slum in Dhaka. The paper is well-written and addresses an important and very timely question. I believe that this study can make a contribution to the literature after addressing the issues below.

Theory

I think the authors need to provide a more specific discussion of the mechanism(s) underlying their main hypothesis, especially “H1: Survey respondents will be more willing to support climate migrants in relation to generic migrants.” The arguments that the authors provide (line 222: “extensive focus on climate change in media and the strong advocacy by the Bangladesh government in global forums”) are based on the assumption that citizens of Korail slum take their cues from the media and policymakers and will formulate their willingness to support (climate) migrants accordingly. However, this not only requires that slum residents have access to these specific information, but are also well-informed about what their national politicians advocate in global policy arenas. I think the authors could expend more efforts to provide more micro-level arguments as to why they think climate migrants might be perceived in more favorable lights than other (generic) migrant types.

Methodology

My main issue with this manuscript is the design of the generic frame. The problem is that the lack of a specific driver of migration in this frame introduces the possibility for survey respondents to think about all sorts of migrant type, including climate migrants as well as both domestic and international migrants. I think this heterogeneity, but more importantly, the impossibility to identify what type of migrant the respondent is thinking about when answering whether they’d like to help that group of migrants, makes it very hard to interpret the outcome variable itself. What is the level of support we are benchmarking support for climate migrants against? We know from the literature that different types of migrants are seen in very different ways (as this manuscript also argues). Therefore, it is important to know how individuals perceive climate migrants compared to other (specific) types of migrants. I wonder whether the authors asked some open-ended questions about what types of migrants (or general thoughts) the respondents had in mind after reading the frames. This may give us some hint about the type of migrant (and potential biases/associations) people had in mind when reading the respective treatment text. At the least, this shortcoming should be addressed in greater detail in the manuscript.

I have two concerns with the way that the outcome variable was formulated. First, the reference “a typical family spent about 1,500 takas on medicine last month” may have exacerbated social desirability bias, since it conveys the information that compared to what a typical family spends on healthcare, 100 takas are not much. Second, the way that this question is formulated, I wonder whether it may also have tapped into people’s support for NGOs more generally rather than just capturing people’s support for the specific migrant group described in the treatment text.

As an additional comment, I am curious why the authors did not use a continuous variable by asking respondents how much of the 100 takas they’d be willing to donate.

The authors discuss how much the average Bangladeshi household spends on healthcare. Is this the same amount that the average slum resident in Korail spends on healthcare? In general, I would like to hear more about in what way the survey site (the Korail slum) differs from other slums, or the country.

**********

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Reviewer #2: No

Reviewer #3: No

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PLoS One. 2021 Apr 22;16(4):e0249315. doi: 10.1371/journal.pone.0249315.r004

Author response to Decision Letter 1


7 Mar 2021

Rebuttal Memo

Willingness to help climate migrants:

A survey experiment in the Korail Slum of Dhaka, Bangladesh

PONE-D-20-35549R1

Reviewer #2

1. This is a strong revision and I would be delighted to see this research published, pending a few minor revisions listed below. I paid particular attention to the author(s)’ responses to the prior referee reports, and to their alterations of the manuscript to reflect their adjustments to critiques. In particular, the theoretical framework in the revised manuscript is considerably strengthened, the link between theory and empirics is more focused, and the empirical evidence remains robust to the different sensitivity checks that the author(s) have now introduced. Overall, I am impressed by the constructive revisions undertaken by the author(s) and see the author(s) as admirably responsive to the prior concerns raised in review.

Response:

Thank you.

Minor revisions:

1. In l.106 “especially if it involves citizens to incur private costs” would read better as “especially if it involves citizens incurring private costs.”

Response:

Done.

2. In response to R1’s excellent comments, the author(s) now address the issue of religious similarities and differences between the migrants and respondents quite extensively in the manuscript, noting that the Rohingya share the same Islamic faith as the majority of Bangladeshis (e.g., p.10), that respondents would likely not have associated the migrants with religious minorities like Hindus (p.12), and that respondents could have been expected to be “sympathetic to their co-religionists” (p.14, l.304). In neighboring India, which is frequently referenced in the manuscript, existing public opinion work shows that city residents belonging to the majority religious group (in the Indian case, Hindus) do not discriminate again rural-to-urban migrants based on religious profiles. Instead, residents from the dominant religious group appear to care mainly about the economic impact of migration. This is in fact consistent with what the author(s) find in the Bangladesh context: slum residents do not appear to heed religious concerns in responding to migration. The manuscript would be strengthened by citing and referencing these points as it would link the manuscript to broader debates in comparative politics.

Citation: Gaikwad, N. and Nellis, G. (2017), “The Majority‐Minority Divide in Attitudes toward Internal Migration: Evidence from Mumbai.” American Journal of Political Science, 61: 456-472.

Response:

Thanks for suggesting this article which we have referenced in the revised paper.

3. In l.343, the sentence is missing a closed parenthesis mark.

Response:

Corrected.

Overall, I continue to believe that this manuscript tackles a very important subject, and I expect it to foreshadow new work on climate change and migration.

Response:

Thank you.

Reviewer #3

1. This paper examines individuals’ willingness to provide assistance to climate migrants as compared to other types of migrants by means of a survey-embedded experiment conducted in a slum in Dhaka. The paper is well-written and addresses an important and very timely question. I believe that this study can make a contribution to the literature after addressing the issues below.

Response:

Thank you.

Theory

2. I think the authors need to provide a more specific discussion of the mechanism(s) underlying their main hypothesis, especially “H1: Survey respondents will be more willing to support climate migrants in relation to generic migrants.” The arguments that the authors provide (line 222: “extensive focus on climate change in media and the strong advocacy by the Bangladesh government in global forums”) are based on the assumption that citizens of Korail slum take their cues from the media and policymakers and will formulate their willingness to support (climate) migrants accordingly. However, this not only requires that slum residents have access to these specific information, but are also well-informed about what their national politicians advocate in global policy arenas.

Response:

In this survey, we did not ask directly about how respondents learn about policy issues in general or about government’s positions on climate migrants. This is for two reasons. First, people typically get much of their policy information from different types of mass and social media. Of course, we do not know if this information is authoritative and if they comprehend this information. Indeed, we are not making any claim on how well informed or poorly informed individuals are about climate change, migration, or any national policies. We recognize that as boundedly rational actors, individuals develop opinions about issues based on incomplete information. Yet, no matter how incomplete or poorly informed individuals are, public opinion matters. And this is what we examine in the context for public support for a charity that provides health services to climate migrants and Rohingyas (in relation to generic migrants).

Because mass and social media plays a crucial role in shaping public opinion, we have asked questions about respondent’s exposure to different types of media (Q15 of the survey):

a. Read a daily newspaper?

b. Watch the news or a news program on television?

c. Listen to any news on radio or FM radio?

d. Read/watch news on your phone (e.g., Facebook, online portal etc.) or computer?

We have analyzed if exposure to different media might influence respondent’s support for climate migrants or Rohingyas in relation to generic migrants. Anticipating some of concerns of the reviewer, we have not subsumed all types of media in category: we have examined them separately. The reason is that some respondents might rely on newspapers, and others on Facebook, to access policy information. Also, it is possible that some media might cover climate issues more extensively or effectively than others. For example, television might provide more content about challenges faced by climate migrants in relation to, say radio. Or, the television footage might create more empathy for climate migrants. If so, those with higher exposure to television might reveal higher support for the charity supporting climate migrants.

Also, please note that our model controls for factors such as prior experience with floods that might make respondents more (or less) prone to access or pay attention to specific type of climate information in any media. Finally, because this is a survey experiment in which respondents are randomly assigned to different frames, unobserved heterogeneity in respondents’ characteristics should not influence support for any frame.

When we rerun the analysis for each media type separately, our results do not change (i.e. support for climate migrants or Rohingyas in relation to the generic frame). This gives us additional confidence that the medium through which respondents might receive information is not changing the support for climate migrants in relation to generic migrant. We have included this discussion in the revised paper.

3. I think the authors could expend more efforts to provide more micro-level arguments as to why they think climate migrants might be perceived in more favorable lights than other (generic) migrant types.

Response:

Fair point. The subject of public support for climate migration (in relation to other types of migration) is relatively new in the climate policy literature (although as we point out in the paper, there is extensive literature on levels of climate migration in parts of the world, and whether climate migrants should be recognized as refugees). We have identified a recent paper which investigates whether respondents might perceive climate migrants differently from other migrants. In the context of Germany, Hebling (2020) reports that German survey respondents are more supportive of climate change migrants, in relation to economic migrants. We have referenced this paper in the revised manuscript.

Helbling, M. (2020). Attitudes towards climate change migrants. Climatic Change, 1-14.

3. My main issue with this manuscript is the design of the generic frame. The problem is that the lack of a specific driver of migration in this frame introduces the possibility for survey respondents to think about all sorts of migrant type, including climate migrants as well as both domestic and international migrants. I think this heterogeneity, but more importantly, the impossibility to identify what type of migrant the respondent is thinking about when answering whether they’d like to help that group of migrants, makes it very hard to interpret the outcome variable itself. What is the level of support we are benchmarking support for climate migrants against? We know from the literature that different types of migrants are seen in very different ways (as this manuscript also argues). Therefore, it is important to know how individuals perceive climate migrants compared to other (specific) types of migrants. I wonder whether the authors asked some open-ended questions about what types of migrants (or general thoughts) the respondents had in mind after reading the frames. This may give us some hint about the type of migrant (and potential biases/associations) people had in mind when reading the respective treatment text. At the least, this shortcoming should be addressed in greater detail in the manuscript.

Response:

Migrants have different characteristics. The vast literature on migration studies has examined public support when specific characteristics of the emigrant such as religion, gender, skill level, etc. are highlighted. We contribute to this literature by focusing attention to a specific characteristic that the literature has overlooked: climate change as a migration driver. Thus, the generic frame does not highlight any migration driver unlike the two treatment frames. Consequently, this research design allows us to assess the change in public support when one specific migrant characteristic (migration driver: climate change or religious persecution) is highlighted in the two treatment frames while all other information remains the same as the generic frame.

This is also why we do not have any open-ended questions to investigate what types of migrants the respondents had in mind after reading the generic frame because we are not examining how respondents perceive generic migrants. Rather, we want to see how support for migrants might shift (in relation to the generic migrant) when one specific migration driver is highlighted. We have included a discussion on this subject in the manuscript.

4. I have two concerns with the way that the outcome variable was formulated. First, the reference “a typical family spent about 1,500 takas on medicine last month” may have exacerbated social desirability bias, since it conveys the information that compared to what a typical family spends on healthcare, 100 takas are not much. Second, the way that this question is formulated, I wonder whether it may also have tapped into people’s support for NGOs more generally rather than just capturing people’s support for the specific migrant group described in the treatment text.

Response:

We have acknowledged the issue of social desirability bias in the previous revision. If there is a bias, because respondents are randomly assigned to different groups, it cannot explain the difference in support between the generic and treatment frames.

Similarly, we do not have data to speculate whether respondents were responding to support for NGOs. All respondents were given the same information cues with only difference between the generic and treatment frames: drivers of migration. Again, because respondents were randomly assigned to different frames, how respondents interpreted the information cue is not important for this study.

5. As an additional comment, I am curious why the authors did not use a continuous variable by asking respondents how much of the 100 takas they’d be willing to donate.

Response:

We discussed this possibility of using some sort of a slider scale to ask respondents for their support for 100-taka donation on say 1-5 scale. Because this was an in-person survey (as opposed to an online one), the survey firm thought that the logistical issues will be difficult if we were to ask respondents to use the slider on the smartphone and might even be distracting. Hence, we decided to work with a 5-point Likert scale – which is consistent with most survey experiments in the climate policy field. In the Appendix, we also present our results using the OLS estimator, where the dependent variable is treated as continuous. We have noted this in the revised paper.

6. The authors discuss how much the average Bangladeshi household spends on healthcare. Is this the same amount that the average slum resident in Korail spends on healthcare? In general, I would like to hear more about in what way the survey site (the Korail slum) differs from other slums, or the country.

Response:

We do not have data on healthcare spending in Korail slum in relation to other slums. Also, the issue of level of healthcare expenditure is not critical to our research design. Across all frames, generic frame and the treatment frame, we had the same ask for donation, 100 takas. In the revised manuscript, we have noted that this research design pertains to only one “price point,” namely 100 takas. To further validate our study, future work could look at different price points. Also, our paper already acknowledges that this study should be replicated in other locations/slums to validate its findings.

Attachment

Submitted filename: PLOS ONE Response to reviewers march 7 2021.docx

Decision Letter 2

Bernhard Reinsberg

16 Mar 2021

Willingness to help climate migrants:  A survey experiment in the Korail Slum of Dhaka, Bangladesh

PONE-D-20-35549R2

Dear Dr. prakash,

I am pleased to inform you that your manuscript has been judged scientifically suitable for publication. Both reviewers are satisfied with the changes you made to respond to their concerns. I recommend that you still incorporate the minor suggestions from Reviewer 3. Your manuscript will then be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Bernhard Reinsberg, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The authors have successfully addressed my earlier concerns and suggestions in the revised version of the paper.

Reviewer #3: I'm pleased to see this revised version of the manuscript. I'm also glad to see that the authors had taken my suggestions and questions seriously and have sought to address most of the points that I have raised. With regards to point 3, however, I remain concerned about the formulation of the generic frame (and the non mutual exclusiveness of the treatment and generic frame), but also appreciate the fact that this the survey experiment has already been conducted and that there is no room for changes of the experimental design at this stage. I would have, however, welcomed a more critical self-reflection in the discussion.

Another minor point: In addition to the Helbling study the authors have identified, there is another study on the perception of environmental migrants in Vietnam and Kenya (Spilker et al;. 2020: Attitudes of urban residents towards environmental migration in Kenya and Vietnam), which might be even more relevant to this study given the geographical scope of the paper.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #2: No

Reviewer #3: No

Acceptance letter

Bernhard Reinsberg

6 Apr 2021

PONE-D-20-35549R2

Willingness to help climate migrants: A survey experiment in the Korail Slum of Dhaka, Bangladesh

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Appendix. Survey questionnaire.

    (DOCX)

    S2 Appendix. OLS regression.

    (DOCX)

    S3 Appendix. Balance table.

    (DOCX)

    S4 Appendix. Ordered probit results.

    (DOCX)

    S5 Appendix. Ordered probit results–full sample.

    (DOCX)

    S6 Appendix. Demographic profile of survey participants.

    (DOCX)

    Attachment

    Submitted filename: PLOS ONE Response to reviewers.docx

    Attachment

    Submitted filename: PLOS ONE Response to reviewers march 7 2021.docx

    Data Availability Statement

    Relevant data has been uploaded to the Harvard Dataverse (https://dataverse.harvard.edu) with the following DOI: https://doi.org/10.7910/DVN/HTV3DT.


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