THE RELATIONSHIP BETWEEN LENGTH OF RESIDENCE AND VOTING BEHAVIOR IN THE UNITED STATES

Cole Gessner

Abstract: Prior research has identified a number of factors that are related to voter turnout, including socio-economic status, race, age, and sex. A substantial literature also suggests the existence of a positive relationship between length of residence and likelihood of voting.  However, these studies use data from before 2016. The present study fills that gap in the literature by estimating the relationship between length of residence and the probability of voting using the most recent data from the United States Census Bureau Current Population Survey Voting Supplement. More specifically, I estimate the influence of length of residence on the probability of voting in the 2020 U.S. general election. Consistent with earlier studies, I find evidence of a small, positive, and statistically significant association between length of residence in the same home and the likelihood of voting in the November 2020 elections. Given that political participation is widely regarded as an indicator of a healthy and fully functioning democracy, policymakers interested in preserving American democracy should explore the potential for a causal relationship between length of residence and voting.

Introduction

More than two-thirds of Americans recently surveyed by American National Election Studies (ANES 2021) believe that public officials in the United States do not care what their constituents think. Almost as many respondents believe that American citizens do not have a say in public policy decisions or in what their government does (ANES 2021). Perhaps because of these concerns, the United States is an outlier among its democratic peers in terms of voter turnout (Hill 2006). Some 67% of eligible Americans voted in the 2020 presidential election, and only half of eligible voters participated in the 2018 midterm elections (United States Election Project 2020). While these turnout figures represented historic highs for the United States (Desilver 2021), the country still ranks relatively low in voter turnout when compared to other democratic countries (Desilver 2020). A total of 56% of the United States voting age population (VAP) participated in the 2016 presidential election (Desilver 2021). In comparison, during recent national elections, 80% of VAP participated in Australia, 77% participated in South Korea, 77% participated in The Netherlands, and 69% in Germany. More than 80% of VAP participated in Australia’s 2019 election (Desilver 2020).[1]

Low voter turnout has potentially important implications. For example, multiple studies have found that American voters tend to be of higher socioeconomic status than non-voters (Leighley and Nagler 1992; Lijphart1997; Nielson 2015). This finding suggests that, in the American political system, the poor and other groups could be underrepresented (Hill 2006). Low turnout also has implications for electoral outcomes. Wattenberg and Brians (1998) estimated that, in the 1994 midterms, the Republican Party may have lost nearly three percent of its vote because registered Republican voters decided to not participate.

In addition, low turnout levels are related to a variety of policy outcomes and to the overall health of a democracy. In his study of the impacts of compulsory voting on public policy outcomes in Australia, Fowler (2013) found that the increase in voting after the adoption of the country’s compulsory voting laws was linked to increased public spending on pensions. Relatedly, Anzia (2012) found that changes in voter turnout in Texas school board elections were linked to changes in teacher salaries.[2] Other studies have shown that, in the United States, voting is a clear indicator of democratic collective action (Chapman 2016), and that high voter turnout supports democratic values such as popular sovereignty, legitimate elections, and majority rule (Hill 2006).[3]

Given the implications of voter turnout for the healthy functioning of government, it is important to understand its determinants. One potential determinant is voters’ sense of connectedness to their communities, which may be related to how long they have resided in their homes. A considerable literature on this subject provides evidence of a positive relationship between length of residence and likelihood of voting. However, the data used in this research dates from before 2016.  However, these studies are limited to data collected before 2016, leaving a gap in the research from 2016 to the present. In this study, I use the most recently available (2020) release of the United States Census Bureau’s Current Population Survey (CPS) to study this relationship.

Background

Prior research has come to differing conclusions regarding the significance and direction of the relationship between length of residence and voting. Since the 1980s, interstate migration within the United States has been on the decline (Molloy et al. 2014). This trend is particularly true for those who rent their homes. One study finds that 21.7% of renters in the United States moved to a different state in 2017, a lower rate than in any other year since 1988 (U.S. Census Bureau 2017). This decreasing trend has been found to be associated with lower rates of job turnover and decreases in the wage gains associated with such job changes, among labor market outcomes (Molloy et. al.  2014). 

However, a number of recent studies have shown that while the population as a whole is less likely to migrate, younger, college-educated Americans are more likely to move in order to find new economic opportunities (Kodrzycki 2001; Kelly 2010; Sapra 2014). These demographic correlates on interstate migration may also have implications for voter turnout, as studies have shown that those with more education and higher incomes are more likely to vote (Pew Research Center 2006; Nielson 2015). In other words, those in the United States who are most likely to vote may also be the most likely to migrate. 

The United States is also experiencing a decline in homeownership (GAO 2020) and a rise in rent prices (U.S. Census Bureau 2021), both of which may be related to migration patterns. A 2020 report from the Government Accountability Office (GAO) found that, between 2004 and 2016, the rate of U.S. homeownership decreased from approximately 69% to 62% and that the ratio of rented to vacant household units had increased compared to the ratio of rented to owned housing units. Additionally, the GAO report found that, between 2010 and 2018, homeownership in nine major cities had either declined or remained relatively constant.[4] This factor, combined with the Census Bureau’s (2021) finding that rent levels have increased steadily since 1997, could have important implications for intra-state migration. Given that residential leases tend to be set for a particular length of time and that renters in the United States are typically more mobile than homeowners (Joint Center for Housing Studies of Harvard University 2020), Americans who rent may be incentivized to relocate from neighborhood to neighborhood within their communities in search of more affordable rent levels. Such highly mobile Americans who move from lease to lease may be less likely to register to vote in their new places of residence.

In addition, the Joint Center for Housing Studies (2020) reported that an increasing number of renters in the United States are younger, college-educated, and white. This demographic group is also highly likely to vote (Wattenberg 1998; Pew Research Center 2006), which suggests that a demographic group important to voter turnout is also more likely to rent rather than own and, therefore, to have higher residential mobility levels than other Americans. If the demographic groups that are more likely to vote are also more likely to relocate, registration and voting rates could be affected.

Literature Review

A substantial literature suggests that there is a positive relationship between the length of time that an individual resides in his or her home and that individual’s likelihood of voting (Wolfinger and Rosenstone 1980; Squire et al. 1987; Rosenstone and Hansen 1993; Highton 2000). Most importantly, Squire et al. (1987) found that living in a community for two or fewer years is associated with a significantly lower probability of voting. Relatedly, Ansolabehere and Lovett (2008) found that moving across state lines has a significant, negative relationship with a mover’s opinions of the destination state’s senators, which the authors consider to be a proxy for political engagement. In other research, Burke et al. (2019), in their analysis of data on North Carolinians who moved to a new voting precinct between the 2012 and 2016 elections, found that a change in polling station was associated with a decrease of nearly one percentage point in the probability of voting. 

Researchers have advanced two theories to explain the relationship between length of residence and voting behavior. The “social cost” school of thought posits that moving disrupts one’s social network, and that these disruptions in turn have implications for an individual’s political participation. The “administrative cost” school suggests that the administrative burdens associated with moving, such as finding a new polling place and re-registering to vote, reduce an individual’s likelihood of voting. I describe both theories in more detail below.  

The Social Cost School

Several studies examine the relationship between social networks and political participation. For example, Fieldhouse and Cutts (2018) find that sharing those who identify with the same political party as others in their social networks are more motivated to vote. Field experiments have also provided evidence of a positive relationship between social pressure and the motivation to vote (Gerber, Green, and Larimer 2008; Panagopoulos et al. 2014).  Magre et al. (2016) found that the longer individuals live at their residences, the more likely they are to participate in local community activities. More specifically, the authors found that community engagement increases significantly after five years of residence in one’s community.

Researchers who study the impact of residential mobility on political behavior often argue that moving disrupts social networks that serve as important sources of political information and motivation to engage in politics (Wolfinger and Rosenstone 1980; Rosenstone and Hansen 1993). For instance, in his analysis of panel data from Danish elections between 2009 and 2013, Hansen (2016) finds evidence of a negative relationship between moving and political participation, even among groups of voters who maintain the same polling station after a move—and who therefore do not need to re-register. Hansen interprets this as evidence that the social value of voting decreases when an individual moves to a new residence. This research directly supports the social cost school’s argument that disruptions to social networks, such as those caused by a move from one community to another, could reduce one's likelihood of voting.

The Administrative Cost School

Other studies of the relationship between length of residence and voting focus on the administrative burdens that are created when one moves to a new residence, including the costs associated with registering to vote (Ortiz 2009). In essesnce, the greater the administrative burden associated with moving to a new residence, the greater the potential impact on voter behavior. Using data from the 1980 National Election Study, Squire et. al. (1987) analyzes the impact of the ease of registration on voter turnout among American citizens who have recently moved. The authors find that, among those who had lived in their residence for six months or less, voter turnout was 18% higher in states with more permissive voter registration laws than in states with more restrictive laws; related research has arrived at similar conclusions (Highton 2000, 2004; McDonald 2008).[5]

In addition, Highton (2000) makes an important distinction between the impact of moving within one’s community (i.e., maintaining one’s social networks, while potentially facing administrative barriers to voting) versus moving to an entirely new community (i.e., disrupting social networks and facing administrative barriers to voting). The author finds that both forms of moving are negatively associated with the likelihood of political participation. Moreover, he finds that the administrative barriers to voting after a move have a larger negative association with political participation than disruptions to social networks. Using Current Population Survey (CPS) and American National Election Studies (ANES) data from people who move within the same county, Ortiz (2009) similarly finds that barriers to registration are more closely related to voting behavior than any other factor. 

The Present Study

A number of the studies that provide evidence of a positive relationship between length of residence and political participation use data from before 2016 (Wolfinger and Rosenstone 1980; Squire et. al. 1987; Rosenstone and Hansen 1993; Highton 2000; Ortiz 2009; Hansen 2016; Burke et. al. 2019). While scholars from both the administrative and social cost schools widely cite these studies, it is important to reexamine the relationship as society continues to change. As noted in my Background section, the United States is experiencing declining homeownership (GAO 2020) and rising rent rates (U.S. Census Bureau 2021). Many of the citizens most likely to vote are also the most likely to rent homes with set leases; these individuals must contend with the social and administrative costs described above as they move from apartment to apartment (Joint Center for Housing Studies 2020; Wattenberg 1998). By using the most current (2020) data, I provide updated research into this relationship.

Conceptual Framework

Based on the findings detailed in my Literature Review, I hypothesize that length of residence in one’s current home will have a positive correlation with one’s likelihood of voting in the 2020 election. My model will control for economic, demographic, and geographic factors that are plausibly related to my dependent and key independent variables. These factors are diagrammed in Figure 1 and discussed further below.

Demographic Factors

Previous studies have linked several demographic factors to voter turnout. Age, sex, and race are commonly included demographic controls in a number of these studies, which have typically found them to be associated with political participation (Wolfinger and Rosenstone 1980; Squire et al. 1987; Highton 2000, 2004; Ortiz 2009; Burke et al. 2019). In addition, previous research has shown that marital status is associated with voter turnout: adults who never marry are less likely to vote than married adults (Wolfinger 2008).

Economic Factors

A relationship has also been found between economic factors and voter turnout. For instance, research suggests that educational attainment is positively related to the likelihood of voting (Wolfinger and Rosenstone 1980; Squire et al. 1987; Pew Research Center 2006). Socioeconomic status, as measured by family income, has also been positively associated with political participation and voter turnout (Wolfinger and Rosenstone, 1980; Highton 2000, 2004; Ortiz 2009, Pew Research Center 2006). In prior research, occupation or industry of employment have been included as socioeconomic controls (Wolfinger and Rosenstone 1980). 

Geographic Factors

Finally, prior studies of voter participation have controlled for geographic factors. For example, when analyzing voter turnout, researchers frequently control for differences between states (Highton 2004; McDonald 2008; Ansolabehere and Lovett 2008; Ortiz 2009). Additionally, widely-cited prior research has controlled for the differences in metropolitan status – i.e., whether a residence is in an urban area, a suburban area, or a rural area (Wolfinger and Rosenstone 1980).

Data and Methods

My empirical analysis uses individual-level data collected monthly by the U.S. Census Bureau’s Current Population Survey (CPS).[6]  Using both an online questionnaire and person-to-person interviews, the survey gathers data on all members of the sampled household over the age of 15. In most cases, the owner of the household or primary renter responds on behalf of each of the household’s eligible members.[7]  The CPS collects data on a wide array of subjects, including general demographic information, education outcomes, employment, and income and wealth. These data points are used by federal agencies, such as the Bureau of Labor Statistics to create annual reports.

For my analyses, I use the November 2020 Voting Supplement to the CPS, which is the  most recent version of this survey.[8] In addition to the base set of survey questions, the Voting  Supplement includes questions on voter behavior, such as whether respondents voted in the  election earlier in the month, whether and how they registered to vote, and how long they have  lived in their place of residence (IPUMS 2021). Respondents below the age of 18 are not included in my analysis as they are not of legal voting age in the United States. Non-citizens are also removed from my analysis since they cannot participate in American elections. As discussed in my Conceptual Framework section, I control for several demographic, economic, and geographic factors that have been found in prior studies to be related to voter turnout. Data for these controls are all drawn from the 2020 CPS Voting Supplement. 

Due to the binary nature of my dependent variable, I estimate a linear probability model (LPM) to analyze the relationship between length of residence and the likelihood of voting. My primary specification is as follows, with the individual as the unit of analysis:

Pr⁡(Voted) = β0+ β1 Residence + β2Age + β3Sex + β4Race + β5MaritalStatus + β6Education + β7FamilyIncome + β8Industry + β9Metro + State + ε

 where State represents a vector of state fixed effects terms, ε is an error term, and β1 is my coefficient of interest. My dependent variable is a dichotomous measure of whether the respondent voted in the most recent (November) election. My key independent variable is a continuous measure of how long CPS respondents have lived at their current address (measured in months). The inclusion of state-fixed effects in the regression reduces the extent of bias in my estimates by controlling for all unobserved factors that are common to residents in each respective state. My data set contains information on 35,109 individuals who were surveyed for the November 2020 CPS Voting supplement. Table 1 provides definitions for all of the variables included in my model.

Descriptive Statistics

Table 2 reports descriptive statistics for my dependent, key independent, and control variables. All my results have been weighted using a variable created by the U.S Census Bureau to facilitate analysis of their monthly surveys. My analytic sample includes 35,109 individuals from all 50 states and the District of Columbia.[9]  Approximately 81% of the sample group reported that they voted in the November 2020 elections. As discussed in my Introduction, the national voting turnout in the 2020 election was 66.8% (United States Election Project 2020). Thus, the members of my sample have higher levels of political engagement than the U.S. population at large. Respondents’ average length of residence at their current address is 64 months. Sample members are 44 years old on average, and their average household income is $98,778 per year. The average family income in my sample is $31,257 higher than the U.S. family median income reported by the US Census Bureau ($65,521) in 2020 (Shrider et al. 2021). 

 Table 2 also shows that a plurality of participants is categorized as working in the “Professional Services” industry, which is a broad category defined by the Census Bureau to include occupations such as healthcare, education, management, and accounting service professionals. Additionally, a substantial majority of respondents have at least a high school diploma and live in either an urban or a suburban setting. 

Results

Table 3 reports my weighted regression results.[10] Given the dichotomous nature of my dependent variable; I estimate linear probability models (LPM).[11] I report robust standard errors beneath each coefficient. Table 3 presents results for five different specifications. Model (1) is a simple bivariate specification that estimates the relationship between the length of residence in one’s home (measured in years) and the likelihood of voting in the November 2020 election.  Model (2) includes several control variables to reduce the extent of bias in my estimates.  These controls include demographic factors (i.e., age, sex, marital status, and race), economic factors (i.e., income, educational attainment, and industry of employment), and geographic factors (i.e., metropolitan status and state of residence). Model (3) adds state-fixed effects to account for unobserved differences between residents of different states, such as civic engagement or the ease of voting registration.

As I originally hypothesized, the results of Models (1), (2), and (3) suggest that there is a small, positive association between length of residence and voting. These correlations are all statistically significant at the 1% level. More specifically, the results of Model (1) indicate that a one-year increase in the length of residence is associated with a 1.6 percentage point increase in the likelihood of voting in November 2020. As indicated by Table 2 above, the average length of residence in my sample is about 5 years, and about 81% of sample members voted in the 2020 election. Thus, in practical terms, a one-year increase in length of residence is an approximate 20% increase relative to the mean, while a 1.6 percentage point increase in the likelihood of voting reflects an approximate 2% increase relative to the base proportion in my sample. In other words, a relatively large increase in the length of residence corresponds with only a small increase in the likelihood of voting. The addition of control variables in Model (2) results in a decrease in the estimated magnitude of this relationship. The results of this specification suggest that a one-year increase in length of residence is associated with an increase of just under one percentage point in the likelihood of voting; this estimate remains statistically significant at the 1% level. The addition of state-fixed effects in Model (3) has little impact on my estimate of interest.

Models (4) and (5) report the results of my subgroup analyses. Model (4) examines the role that age plays in the relationship of interest. This consideration is potentially important, given the homeownership and renting trends among young Americans discussed in previous sections. For this specification, I created a dichotomous age measure that indicates whether respondents are 30 years old or younger. I then interacted this dummied version of the age variable with the length of residence variable. Similarly, Model (5) examines the role that income plays in the relationship between length of residence and likelihood of voting. Income may moderate my relationship of interest because wealthier individuals could, as discussed earlier, be better able to overcome barriers to voting such as re-registration after migration. I dichotomized the income variable based on the within-sample median, then interacted this dummied version of the income variable with the length of residence variable.

Model (4) produces unexpected results, suggesting that there is a very small and positive, but statistically insignificant, difference in the association of length of residence and voting when examining the interaction of age. More specifically, a one-year increase in the length of residence is associated with a statistically significant 0.93 percentage point increase in the likelihood of voting (0.009 + 0.0003) among those who are 30 or younger, while comparable increase in length of residence is associated with a statically significant 0.9 percentage point increase in the likelihood of voting among those older than 30.[12] However, the difference between these two groups in terms of the association between length of residence and voting is very small and statistically insignificant. These results are not aligned with my expectation that increased length of residence would have a meaningfully greater impact on young people’s voting behavior.  

Model (5) is more aligned with my expectations. I find that there is a small, negative, and statistically significant difference between high and low-income individuals when examining the association between length of residence and likelihood of voting. More specifically, Model (5) suggests that a one-year increase in length of residence is associated with a statistically significant 0.51 percentage point increase (0.0115 - 0.0064) in the likelihood of voting for those with incomes greater than $87,000 per year. In comparison, a one-year increase in the length of residence is associated with a statistically significant 1.2 percentage point increase in the likelihood of voting for the lower income category.[13] The magnitude of this relationship is very small for both groups and there is little practical difference in the association between length of residence and voting when examining the difference across income groups.

In summary, my regressions provide evidence of a relatively weak, but positive and statistically significant, relationship between the length of residence in one’s home and the likelihood of participating in the November 2020 election. The small magnitudes of my estimates are not unexpected, considering the complex motivations for voting in American elections. I also find little evidence of meaningful variation in the relationship between length of residence and likelihood of voting according to age, and only limited evidence of variation according to income. The implications of my results are discussed in the conclusion, along with limitations of my analysis and recommendations for policy and future research.

Conclusion

My results suggest that there is a small, positive, and statistically significant association between length of residence in one’s home and the likelihood of voting in the November 2020 elections. Specifically, after controlling for a number of demographic, economic, and geographic factors, I find that an additional year of residence is associated with an increase of slightly less than a percentage point in the likelihood of voting. My estimates of this relationship are consistently significant at the one percent level. As discussed earlier, there is substantial literature supporting the positive relationship between the length of residence at a person’s address and her or his likelihood of political participation (Wolfinger and Rosenstone 1980; Squire et al. 1987; Rosenstone and Hansen 1993; Highton 2000). My results are consistent with these earlier findings when examining political participation in the November 2020 elections.

I also find that there is little variation in my relationship of interest according to age. This result is at odds with Wolfinger and Rosenstone’s (1980) finding that changes in political participation after a move tend to be more limited among young adults, compared to older adults. The authors suggested that moving in young adulthood is less disruptive than moving later in life because older adults usually have greater familial, financial, and material interests that complicate the moving process, all of which may have implications for political participation. I also find that my relationship of interest is modestly larger among those with lower incomes than among those with higher incomes.

My study has at least two limitations. The first is bias created by missing variables.  Previous studies that examined my relationship of interest (Squire et al. 1987; Highton 2000) controlled for the individual owning or renting their address of residence. These studies found that homeownership is positively associated with the likelihood of voting in elections. Owning a home is associated with longer lengths of residence, and therefore my coefficient is impacted by upward omitted variable bias (Haurin and Rosenthal 2004). In other words, because this source of bias is increasing the magnitude of the coefficients in my results, my small coefficients may be even smaller. Unfortunately, the 2020 edition of the Voter Supplement data from the CPS did not include data on homeownership, so I was unable to control for this potentially important variable; future research should attempt to include this variable. 

Similarly, in their study on the impact of residential mobility on political participation, Squire et al. (1987) controlled for individuals’ levels of political interest. The authors argue that being more politically interested is associated with higher levels of political participation.[14] However, there is limited research on the association between political interest and how long one resides at their address, making the direction of this omitted variable bias difficult to determine. The November 2020 CPS Voting Supplement did not include data on levels of political interest or engagement, so I was unable to include and control for this potentially impactful variable. 

The second limitation of my study is the likelihood of measurement error in my length of residence variable. As discussed in Table 1, my length of residence variable was created by taking the midpoint of a series of categories contained in the underlying variable available in the CPS, and I took the fairly conservative step of assigning a value of eight years for the “Longer than 5 years” category. This likely caused measurement error in the length of residence variable, which subsequently biased the resulting coefficients.

Future Research and Policy Implications

My results warrant additional exploration. First, future researchers should consider examining the relationship between length of residence and political participation during off-year election cycles. American society’s level of interest and engagement in the 2020 election was higher than any other point in the 21st century (Galston 2020), as evidenced by the approximately seven percentage point increase in voter turnout between the 2016 and 2020 elections (DeSilver 2021). Pew Research Polling indicated that 83% of Americans thought that the winner of the 2020 election would have important consequences for American policy and progress, compared to just 50% in 2000 (Galston 2020). Political engagement and participation are typically lower during mid-term and off-cycle elections (DeSilver 2014). Therefore, political participation may be more sensitive to individual-level factors in election years when society-level factors are less pronounced. In other words, individual-level factors, such as a person’s length of residence or a person’s level of education, may have greater influence on political participation in years when society as a whole is less interested in the election. Individual-level factors like my variable of interest may have had less influence in 2020 given the high levels of societal interest in the election. 

Second, future research should examine and control the impact of the COVID-19 pandemic on the association between length of residence and political participation. COVID-19 had considerable influence on the way in which the 2020 election was carried out. Mail-in ballots became much more prevalent, which may have contributed to the surge of participation across the country (DeSilver 2021). Future researchers should attempt to control for this impact. 

As previously discussed, political participation is a hallmark of a functioning and healthy democracy, and it supports democratic values such as popular sovereignty, majority rule, and legitimate elections (Hill 2006; Anzia 2012; Fowler 2013; Chapman 2016). My results suggest that length of residence is associated with increased political participation in the most recent U.S.  general election. This association is worth further exploration. If future research can establish a causal relationship between length of residence and voting, policymakers would benefit from promoting policies that facilitate length of residence, incentivize home ownership or long-term leases as a tool in their arsenal to increase political participation. Such policies could provide stability for American citizens, to engage with the needs of their community on a deeper level, and ultimately to increase their political participation and engagement in the American political system.

Appendix

MINTING ENDS MEET: CASH TRANSFERS AS A DISASTER RELIEF TOOL

Denton A. Cohen

Abstract: While cash transfer programs (CTPs) have shown impressive efficacy in empowering marginalized populations and building resilience to economic shocks, CTPs have yet to be adopted in the United States as a disaster tool. Weaving together three separate literatures on the production of social vulnerability and inequity in coping capacity, on procedural vulnerability and FEMA, and on the utility of cash transfers – this paper makes the case that CTPs possess valuable, untapped potential in a disaster resilience context. This paper proposes two alternate and overlapping program designs, and discusses multiple paths forward for the study and implementation of disaster-based CTPs. Additionally, by exploring their benefits for disaster resilience, this paper contributes to the growing body of support for the adoption of Universal Basic Income (UBI) programs by local, state, and federal governments.

Introduction

Cash transfers – periodic provisions of small, standard amounts of cash, typically to low-income families – have won widespread recognition as a powerful tool to combat poverty and poor health outcomes, particularly in the developing world (Banerjee et al. 2019; Bastagli et al. 2019; Ivaschenko et al. 2018). As a substitute for (or an addition to) more restrictive welfare programs such as food stamps or housing vouchers, cash transfer programs (CTPs) allow recipients to spend funds freely and according to their needs (Kabeer and Waddington 2015). While some CTPs are means-tested – conditioned on certain criteria, such as an income threshold or disability status – they can also be designed to be universal and non-means-tested in nature (Banerjee et al. 2019; Standing 2008). Beyond their everyday benefits, CTPs have displayed effectiveness in helping people and communities withstand economic shocks by increasing coping capacity, alleviating the impact of employment loss, and generating better health outcomes (Aizer et al. 2016; Kabeer and Waddington 2015; Ranganathan and Lagarde 2012).

While poverty, social isolation, and job insecurity are often cited as drivers of disaster vulnerability, CTPs are yet to receive significant attention as a disaster mitigation and preparedness tool (Cutter et al. 2006; Elliott and Pais 2006; Fothergill and Peek 2004; Ivaschenko et al., 2020). Household- and individual-focused disaster relief efforts instead center around targeted restrictive programs, such as property insurance, funeral assistance, and crisis counseling (Currie 2018). Taken together, these relief programs fall short in building coping capacity and in many cases widen pre-existing wealth gaps present in target populations (Howell and Elliott 2019; Reid 2013; Rivera et al. 2021).

Still, the COVID-19 pandemic has dramatically shifted the window of possibility for CTPs in the United States. In the year following the first cases of community spread of the virus in the U.S., Congress authorized hundreds of billions of dollars of direct cash assistance in the form of so-called stimulus checks – an unprecedented action in both nature and scale. Not only did this cash assistance program enjoy broad political support and help millions of families ease economic strife, it demonstrated the ability of the federal government to deliver direct aid during times of crisis (Buckles 2020; Han et al. 2020). While disasters triggered by natural hazards typically (though not always) generate more geographically acute impacts, they levy the most sizable burden on minority and low-income communities, and their economic impacts can be just as dire as the direct impacts of the hazard itself. Given the success and popularity of national CTPs during COVID-19, the window of opportunity for further adoption of CTPs in disaster (and non-disaster) settings has been cracked open, if not more.

In this paper, I explore two potential models for disaster-focused cash transfer programs in the U.S.: rapid-response cash transfers and continuing cash transfers. Above all, I argue that CTPs have the potential to a) build bottom-up resilience by increasing coping capacity and reducing procedural vulnerability and b) constitute a transformative method of disaster-based structural reform, resituating power and resources in the hands of those who would normally be at risk of being shut out of disaster relief and recovery programs. At their best, cash transfers can provide a baseline of support that makes it easier for disaster victims to absorb the economic shock of a disaster – even when traditional disaster recovery programs fail to do so. I also argue generally that, as a universal CTP design, universal basic income (UBI) programs possess immense and underappreciated potential in the disaster realm.

To do so, I begin with a thorough review of the literature on social vulnerability, first critiquing the concept of social vulnerability for its passive framing, and then demonstrating how disparities in coping capacity produce social vulnerability before, during, and after disasters. Then, I present the literature on existing Federal Emergency Management Agency (FEMA) disaster relief programs and their failure to adequately reach marginalized peoples and communities. I follow this by establishing cash transfers as an innovative and transformational resilience tactic when instituted alongside more traditional programs. I conclude with an overview of the limitations of cash transfer programs in the disaster planning realm and a discussion of possibilities for CTP design.

Literature Review

Disaster Outcomes and Social Vulnerability

While the field of disaster vulnerability had previously focused more on the physical and logistical side of planning, a new generation of scholarship began to emerge in the 21st century, particularly following Hurricane Katrina (Jacobs 2019). This new era of vulnerability scholarship broke ground in systematically naming and measuring the many social factors – such as gender, race, class, and age – that drive unequal post-disaster outcomes, ranging from mortality rates to mental health issues (Cutter et al. 2003; Flanagan et al. 2020; Peacock et al. 2012).

A great deal of research has uncovered and mapped the disparate impacts of disasters on a variety of populations. Across the board, low-income and low-wealth populations experience not only greater mortality and injury risk, but also systematically slower emergency response and job recovery, lower rates of return to housing, and worse long-term physical and mental health outcomes (Fothergill and Peek 2004; Howell and Elliott 2019; Lim et al. 2017). Scholars have observed parallel and compounding disaster impacts based on race and ethnicity, with Black and Hispanic communities often experiencing the greatest harms (Adams and Boscarino 2005; Bolin and Kurtz 2018; Fothergill et al. 1999; Luft 2016; Peacock and Girard 1997; Rivera and Miller 2007). Similarly, disproportionate disaster impacts have also been uncovered for women (Enarson 1998; Enarson et al. 2018; Peacock et al. 2012), disabled people (Peek and Stough 2010; Wolbring and Leopatra 2012), immigrants (Horton 2012), and the elderly and children (Heagele and Pacquiao 2018; Peek 2008). Many scholars have advocated for an intersectional approach to understanding social vulnerability, situating race and class as interacting variables that can combine to create specific types of vulnerability (e.g., for low-income Black mothers) (Cutter et al. 2003; Elliott and Pais 2006; Fussell and Harris 2014; Luft 2016).

The idea of class as a threat multiplier is a major throughline in the social vulnerability field; at every level, those with lower incomes are found to have lower levels of coping capacity. Drakes et al. (2021) define coping capacity as “an individual or group’s use of available resources and opportunities to absorb impacts, manage needs, and overcome the immediate and short-term effects of hazard-related losses” (1). Coping capacity is directly tied to an individual’s or a community’s financial resources and social capital, meaning systemic inequality in wealth and power translates into inequality in disaster outcomes (Parsons et al. 2016). While wealthier communities will be able to independently fund disaster resilience projects, communities that have experienced disinvestment and thus own less capital will possess diminished ability to fund disaster mitigation, preparedness, response, and recovery initiatives on their own (Pais and Elliott 2008). Wealth-based inequity in recovery is measurable on an individual level, too; research tells us that wealthier individuals are more likely to be able and willing to leverage their own savings to prepare for disasters ahead of time, evacuate to a safe place, and reconstruct property following a disaster (Fothergill and Peek 2004). Meanwhile, these class differences routinely interact with race, disability status, age, citizenship status, and other factors that may ease or worsen disaster outcomes.

Despite progress made in the disaster planning field to recognize the interaction of pre-existing inequalities and disaster outcomes, the identity-based framing of social vulnerability – as opposed to identification based on systems of oppression – remains a concept of great controversy. Deploying Black feminist theory, Jacobs (2019) argues that disaster planners and scholars have largely shied away from naming systems of oppression as drivers of inequity, instead preferring to focus on the disaster-specific effects of such inequities. Specifically, Jacobs (2019) contends that disaster scholars should be “naming sexism, racism and classism as the problems as opposed to gender, race and class (or gender, race and class in specific situations)” (33). In Jacobs’s (2019) view, which Wisner and Luce (1993) agree with, it is not sufficient to say that people with certain identities fare worse during the disasters. Without naming and tracing the structures that create these outcomes, disaster planners risk advancing the narrative that there is something inherent about the concept of social vulnerability, rather than it being socially constructed.

More importantly, the Black feminist critique of social vulnerability allows us to reframe disaster planning solutions. If the inequalities endemic to disaster outcomes stem from actively produced oppression, then deconstructing the oppressive structures governing disaster planning is a policy imperative. Short of changing national and global structures that drive inequality and maintain oppressive economic relations, altering disaster programs themselves (or social programs that have direct disaster-related implications) provides a promising avenue for change. As the next section explains, the current state of disaster relief deploys a top-down approach designed with a certain type of disaster victim in mind. This approach would shift dramatically with the advent of cash transfer programs.

FEMA Disaster Aid and Procedural Vulnerability

While we have reviewed the disparate impacts of disasters on oppressed peoples, it is also important to understand how procedural vulnerability borne out of disaster programs itself contributes to the production of oppression. Much of the literature on the limitations of existing disaster relief programs overseen by FEMA centered around how the design of structures and systems produces procedural vulnerability. Hsu et al. (2015) define procedural vulnerability as vulnerability that “arises from people’s (and peoples’) relationships to power rather than environment, and the ways that power is exercised” (309). Put differently, Rivera et al. (2021) posit that procedural vulnerability stems from not only overly complex and inaccessible program design, but from power imbalances that allow resources to be leveraged in favor of certain types of people.

In addition to direct food and temporary housing aid, the federal government – by far the largest provider of disaster response and recovery funding – relies on an assortment of programs to provide indirect financial assistance to individual disaster victims (Currie 2018; Webster 2022a; Webster 2022b). These “opt-in” programs, which require extensive paperwork to take part in, are primarily overseen by the Federal Emergency Management Agency (FEMA), and provide limited funding for specific needs, such as housing reconstruction, crisis counseling, legal services, and funeral assistance (Webster 2022a). The only national FEMA program that provides direct cash payments to individuals is the Disaster Unemployment Assistance program, which operates on a small scale, requires extensive paperwork to obtain, and phases out after      a few months (Federal Emergency Management Agency 2020; Webster 2022b).

Many researchers have quantified and criticized the shortcomings of this patchwork approach. Scholars have found that programs such as the National Flood Insurance Program (NFIP) and FEMA-funded buyout programs actually worsen inequality by functioning as de facto wealth-protection programs (Howell and Elliott 2019; Nelson and Molloy 2019; Pais and Elliott 2008; Peacock et al. 2014). By setting far higher coverage limits for homeowners than renters and making it a mandatory and standard practice for property owners to purchase insurance, programs such as the National Flood Insurance Program steer the vast majority of funding away from non-homeowners. Others find immense racial and socioeconomic inequality in the provision of services such as temporary shelters and housing repair grants (Craemer 2010; Emrich et al. 2021). Drakes et al. (2021) demonstrate how renters are systematically shut out of FEMA’s Individuals and Households Program (the federal government’s largest disaster recovery program for individual assistance) because only property owners are eligible for the Repair and Replacement grant program.

Crucially, some scholars find that, even for those who are theoretically eligible for relief programs, the overly complicated, highly restrictive, deeply unaccountable, and sometimes intimidating application process prevents many low-income, Black and brown and/or immigrant disaster victims from applying (Clark-Ginsberg et al. 2021; Hooks and Miller 2006; Horton 2012; Laska et al. 2018; Mendez et al 2020; Rivera et al. 2021). In one egregious case after Hurricane Harvey, FEMA denied a low-income, elderly Black woman’s request for housing reconstruction funds because the agency erroneously claimed the flooding damage to her house was not caused by the disaster (Fernandez and Panich-Linsman 2018). Unable to obtain legal assistance, the woman moved in with her son and joined a Habitat for Humanity waitlist (Fernandez and Panich-Linsman 2018). This woman’s experience was far from an aberration; Hamel et al. (2018) uncover massive disparities in assistance provision and recovery speed post-Harvey, with low-income, immigrant, and Black and brown residents of Texas experiencing the worst outcomes.

This trend far supersedes just Hurricane Harvey. Drakes et al. (2021) demonstrate how the FEMA Individuals and Households Program, which manages a Rental Assistance Program intended to help renters replace their property and belongings, consistently falls short in serving the renter population. The IHP fails renters both by making it difficult to apply in the first place (eligible renters apply at much lower rates than homeowners) and by disbursing roughly 40% less to the average renter recipient than the average home-owning recipient.

One could make the argument that, if these programs were merely tweaked in ways that expanded the program or made it easier to navigate, that it would sufficiently cover the needs of disaster victims. However, in a case study highlighting the challenges of colonia residents in the Río Grande Valley, Rivera et al. (2021) argue that incremental changes to existing programs would still fall short. Specifically, because of fundamental and pre-existing inequities in wealth, infrastructure quality, health conditions, and political power – the result of decades of disinvestment, segregation, and disempowerment – the current array of FEMA programs further entrenches current imbalances (Rivera et al. 2021). They are designed to restore wealth; not to redistribute it.

Similarly, Reid (2013) argues that the provision of funds on a restrictive, top-down basis that provides little opportunity for legal recourse is, per se, an unequal process. Reid (2013) connects these outcomes to prevailing political attitudes that govern public spending, citing the neoliberal state’s insistence that recipients of aid prove that they are deserving of help. Much like the American welfare system, Reid (2013) claims, FEMA’s individual and household assistance programs are designed to be something that the needy must actively seek out and prove they are worthy of, and which may be restrictive in nature in that they authorize assistance only for certain goods or services (such as housing) that the state deems acceptable. In effect, conditional and restrictive aid is designed, intentionally or not, to serve a particular type of disaster victim – one who has the time, support system, legal standing, and informational wherewithal to actively seek out aid, even after a disaster.

Take this excerpt from Reid’s (2013) study:

FEMA's policies follow in a long line of “middle-classist” policies that employ implicit definitions about what constitutes a deserving assistance recipient. Middle-classist policies are designed around a particular model of person or family that reflects certain characteristics such as a nuclear family household structure and financial savings or resources to draw on … Though the programs were designed to operate the same for everyone, they had the effect of disenfranchising and further disadvantaging poor survivors, especially those not living in single-family households. This was especially true for black survivors, who tended to be members of both groups. (760-61)

The failure of disaster relief programs to reach the neediest disaster victims not only compounds the overarching social and economic structures that produce social vulnerability in the first place; it arguably constitutes one of those structures in itself. If Jacobs (2019), Rivera et al. (2021), and Reid (2013) are correct that structural issues render “vulnerability-blind” programs ineffectual, structural changes that break the production cycle of inequality are in order. The next section details how the adoption of cash transfer programs as a disaster mitigation and relief tool can serve these transformational goals.

Cash Transfer Programs

Although their popularity in the academic and political arenas is a relatively recent phenomenon, cash transfer programs in the U.S. are not a novel concept. Aizer et al.  (2016) trace the advent of American CTPs back to the Mother’s Pension Program. Established in 1911, the program was designed to help single and/or widowed mothers care for their children, and it provided monthly cash transfers with no spending restrictions. Similarly, the largest welfare program in the U.S., the Social Security program, provides unrestricted cash transfers to elderly and disabled people (and their families). While the American welfare state has much more commonly focused on non-cash restricted aid (means-tested food stamps, housing vouchers, healthcare reimbursement, etc.), unrestrictive cash transfers are not without precedent.

CTPs have wide-ranging economic and social benefits. Cash transfers allow recipients to increase their savings, normalize consumption patterns, and pursue more stable labor force participation (Fiszbein and Schady 2009; Kabeer and Waddington 2015; Ranganathan and Lagarde 2012). However, their benefits extend far beyond economic activity. Cash transfers lead to better mental and physical health outcomes (and higher utilization of healthcare services more generally) and increase social ties within and between families (Aguila et al. 2017; Attanasio et al. 2015; Bastagli et al. 2018; Courtin et al. 2018; Marinescu 2018). In other words, CTPs increase both financial resources and social capital, and by proxy, coping capacity in shock settings. Moreover, if designed to be universal, CTPs can decrease procedural vulnerability by eliminating the need to navigate a complicated screening process to receive benefits and removing the power of state actors to deny or delay benefits. Even if partially means-tested and not entirely universal, CTPs reduce procedural vulnerability by removing restrictions on expenditures and removing government from the process post-transfer.

Thus, when we consider the compounding drivers of unequal disaster outcomes – low coping capacity and high procedural inequity – it is unsurprising that cash transfer programs have proven to be useful in a disaster setting, albeit primarily in developing countries (Creti and Jaspars 2006). In a groundbreaking study of cash transfers in a disaster recovery context, Ivaschenko et al. (2020) find promising evidence that these programs can significantly improve outcomes for low-income disaster victims. The authors make use of a “natural experiment” in the small island nation of Fiji, where in 2014 Tropical Cyclone Winston caused widespread destruction across the country, killing forty-four people and causing over $1 billion in damage (Ivaschenko et al. 2020). A crucial plank of Fiji’s disaster recovery effort was to distribute one-time “top-up” transfers (roughly three times greater than the typical monthly amount) to low-income disaster victims one month after the tropical cyclone, using an existing cash transfer program and scaling up both the benefits and recipient pool (Ivaschenko et al. 2020). Ivaschenko et al. (2020) find highly encouraging results: recipients overwhelmingly spent the cash transfer on critical goods and services such as food, medicine, home repairs, and clothing and furniture replacements. More importantly, program beneficiaries rebuilt their homes significantly more quickly than the control sample – evidence that cash transfers can produce not just a tangible but a transformative impact on the disaster recovery stage (Ivaschenko et al. 2020).

Ivaschenko et al.’s (2020) research builds on a growing body of work studying cash transfers in international disaster contexts. Venton et al. (2015) posit that cash transfer programs allow recipients to access crucial goods and services that they would not have been able to otherwise, such as shelter, clothing, food, medicine, and transport. More broadly, several scholars find that CTPs have great utility before, during, and after shocks of all kinds – not just disasters triggered by natural hazards (Bailey and Harvey 2011; Independent Evaluation Group 2011; Lehmann and Masterson 2014). Ivaschenko et al. (2020) note that cash transfers will not be effective without functioning markets and/or an intact supply chain, and thus not in the immediate aftermath of a disaster. Rather, the “sweet spot” for CTPs appears to be in the critical stage when supply chains have been partially restored and when there exists no mass shortage of staple goods, but when there still exists a great need for rebuilding of structures and institutions, as well as responding to humanitarian needs.

While an effective disaster measure, the most transformational aspect of CTPs may lie in their reframing and re-situation of power in both a pre- and post-disaster context. Rather than treating disaster survivors as program subjects (instead of program participants), forcing them to spend time and resources applying for aid and relying solely on government programs to get by, CTPs empower those affected by disasters to reclaim agency over rebuilding efforts. For example, typically, a family whose place of residence is made unlivable by a disaster would have to rely on a temporary housing arrangement (whether government-provided or with friends or family) while applying to a litany of relief programs to move to another permanent residence or start rebuilding their old one. This place of residence might be located far from their home, place(s) of employment, and/or social network. They may have very few of their belongings with them or may be forced to be separated from a pet (or from each other) based on shelter rules. The family may be multigenerational, responsible for the care of elderly, disabled, and/or child dependents, for whom temporary housing is inadequate.

With a CTP in place, this family could use the funds provided to them to start rebuilding their lives on their terms, to the extent possible based on market conditions. While waiting for other forms of relief, the family could replace clothing, stock up on medicine, help out needy friends, family, or community members, and purchase culturally and allergy- appropriate foods that may not be available at shelters or food banks. They may even be able to conduct      maintenance on their original place of residence – their home may only need a minor repair (such as replacing water-damaged flooring or repairing broken windows), which the CTP may allow them to pay for entirely. In other words, cash transfers allow people to access the goods and services they know they need, without the lengthy and paternalistic process of convincing the government they need them. While CTPs would not and could not replace programs that provide direct, in-kind emergency aid (and thus would not be a panacea for the delays and denials endemic to the current system), they would provide a baseline of support – and agency – to those who would ordinarily be left to fend for themselves.

Discussion

Given the inadequacy of restrictive, reactive disaster relief programs, and the urgency of the need to reduce disaster vulnerability, CTPs present a compelling opportunity to proactively shift power and resources into the hands of those who need it the most. Below, I discuss two distinct (but non-mutually exclusive) models for what a cash transfer program could look like in a disaster context.

Rapid Response Transfers

A rapid-response transfer program would leverage existing welfare and disaster relief programs to provide direct cash assistance to people affected by disasters. In the absence of a pre-existing basic income program, where the vast majority of households are already enrolled in a program that provides monthly cash transfers, rapid-response transfers would allow governments to improvise payments to all people within certain geographic boundaries. The structure of rapid-response transfers is outlined in Figure 1 below.

Similar to the COVID-19 stimulus program, direct deposits could be provided using geographically defined tax return information, and cash could be provided at shelters, temporary housing facilities, and community centers such as places of worship, food banks, recreation centers, and parks. Pre-registration could also be achieved through leveraging everyday contact points between people and government agencies such as the U.S. Postal Service or local motor vehicle bureaus. Another set of channels through which to register participants and provide benefits is through pre-existing programs such as Temporary Assistance for Needy Families (TANF) and the Supplemental Nutrition Assistance Program, which already provide cash or cash-like benefits to low-income households. Depending on the type and severity of the disaster, payments could be distributed at regular (weekly or monthly) intervals, phasing out over certain time horizons.

For example, in the case of a wildfire that causes evacuation orders to be issued for 10,000 households spanning two municipalities and four ZIP codes, FEMA could authorize direct transfers to households with addresses (or, for those without addresses, stated residences) within those defined boundaries, and hand out cash payments at shelters and temporary housing facilities. The “application process” would consist of a simple attestation to living at a certain address (or an equivalent attestation for unhoused individuals), and for those with direct deposits tied to eligible addresses, there would be no application process at all. Such a database could be compiled by FEMA by cooperating horizontally (with other federal agencies such as the Internal Revenue Service and the U.S. Department of Agriculture) and vertically (with local and state agencies such as welfare agencies, taxation agencies, and motor vehicle departments).

By providing a low-effort way to access the program on the front end and full autonomy over spending on the back end, rapid response transfers would decrease procedural vulnerability for all disaster victims, even where other programs failed. Unlike other disaster programs contingent on lengthy reviews of eligibility, rapid-response transfers could kick in instantaneously and scale up quickly, providing a baseline of support to the most marginalized populations, for whom other forms of disaster aid may never materialize.

This type of transfer program would not, however, overcome the challenges that many other disaster programs encounter with reaching eligible participants. Moreover, a rapid-response design comes with considerable weaknesses in its ability to increase coping capacity, compared to alternate designs. Because the preparedness stage is crucial for determining disaster outcomes, and because rapid-response transfers would be focused on the recovery phase, this design would fall short in providing relief in the preparedness stage. Its design is more reactive than proactive, and a superior design would involve a standing cash transfer program, designed to scale up during times of disaster.

Continuing Transfers

A continuing transfer program would be a basic income program with built-in disaster protections. Using a pre-existing cash transfer program, such as a basic income program, that is already providing periodic and regular transfers to recipients, the government agency overseeing the program could scale it up to meet seasonal disaster needs (in flood- or wildfire-prone areas), and/or acute post-disaster needs. The structure of continuing transfer programs is outlined in Figure 2 below.

Consider this excerpt from Ivaschenko et al. (2020), which explains why this approach is advantageous:

Long-term social protection programmes are increasingly being linked with emergency cash transfer projects to make them shock-responsive. This can protect vulnerable households from shocks ex ante through predictable cash transfers that help them to build resilience; they can be scaled up ex post to respond to extreme events. In addition, this is an efficient way of getting emergency cash to people, [utilizing] existing delivery systems and beneficiary databases. [Programs] can be scaled up vertically (providing additional resources to existing beneficiaries) or horizontally (adding more beneficiaries), depending on the needs and capacity of the prevailing system. (459)

Take, for example, a catastrophic hurricane affecting a coastal town in South Carolina that had a pre-existing basic income program for low-income residents. The program could be proactively designed with a modest scale-up during hurricane season (June to November), or, alternatively, simply designed to scale up in the aftermath of a hurricane. After a brief disruption immediately following the storm, the town could – likely with the assistance of state or federal aid – restore service and take advantage of the basic income program to provide even greater benefits to program participants. The town could choose to enroll greater numbers of people in the program, recruiting participants at disaster shelters and temporary housing facilities, and phasing out benefits later in the process as recovery needs are increasingly met.

The continuing transfer design’s advantage over the rapid-response design lies not only in its more straightforward ability to reach program participants after a disaster, but also in its ability to build coping capacity before a disaster occurs. With extra savings and social capital in hand, those enrolled in the program would have greater resources with which to install protective infrastructure in their place of residence, greater ability to collectively evacuate (via leveraging financial resources and social ties), and enhanced capability to help family, friends, neighbors, and strangers during times of crisis. While rapid-response transfers could help in the recovery stage, a continuing transfer design builds resilience throughout the entire process.

Still, although the rapid-response transfer design is inferior in many ways, it represents the more politically feasible way to institute a disaster CTP. Slimmer in cost because of its more temporary nature, and perhaps more amenable to a pilot program design, rapid-response programs – or even a hybrid CTP design that leverages pre-existing non-cash transfer welfare programs – may be the most feasible path forward. The next section discusses the multiple avenues through which CTPs can be further studied and implemented in disaster settings.

The Path Forward

Because of the scarce usage of disaster-specific CTPs such as the one implemented by Fiji, disaster-focused CTP literature is still in its nascent stage globally, and literature on the topic is non-existent in a U.S. context. The growing popularity of basic income programs – and the potential for low-cost pilot programs – means that cash transfers’ absence in disaster policy discussions should soon change.

The most likely path forward for further study of CTPs in a disaster context lies with the cash transfer programs that already exist. According to an index maintained by Business Insider, as of December 2021, at least thirty-three cities and states have implemented limited basic income programs, most of which are pilot programs that provide periodic cash transfers to relatively small numbers of low-income participants (Lalljee, 2021). Most of these projects are being implemented with the help of researchers (with control groups already identified), and many have been undertaken by cities and states where disasters are relatively common, such as Los Angeles, Shreveport, Louisiana, New York State, and New Orleans. These projects vary in size and benefit level, but if a major disaster were to occur in an area with a basic income program, it is highly likely that they would lend themselves conveniently to a quasi-experimental study, where the effects of the program on disaster outcomes could be tested and quantified.

Another option along these lines would be to construct a pilot program, similar to the aforementioned programs, with the key differences being the incorporation of disaster planning from the ground up and location in a disaster-prone area. By formulating plans for scaling up benefits, ensuring continuity of post-disaster cash provision, and collecting key disaster-related data points (such as physical condition of residence, mental and physical health indicators, etc., both pre- and post-disaster), the program could provide illuminative information on the effectiveness of CTPs in an American disaster context. An example could be a disaster cash transfer pilot program in a community lying in a major coastal floodplain and hurricane hotspot, in anticipation of a major storm happening sometime in the near future.

Finally, the ultimate realization of cash transfers in a disaster context would be a permanent UBI program, administered across an entire state or locality – or the entirety of the United States. The state of Alaska is the only jurisdiction in the U.S. with anything resembling a permanent UBI program. The Alaska Permanent Fund, established using oil revenues, provides an annual payment to all adult Alaska residents (apart from incarcerated people) between roughly $1,000 and $2,500, although it varies year to year (Goldsmith 2012; Jones and Marinescu 2022). This program deviates from a traditional UBI format in that its provision is annual rather than monthly and that benefits are not fixed but rather fluctuate based on oil prices and drilling trends. Even so, the Alaska Permanent Fund provides a rough blueprint for what statewide or national UBIs could look like. UBI programs provide a best-case scenario in terms of procedural equity – enrollment would ideally be automatic and universal – and coping capacity, by providing transfers before and after disasters, and maintaining continuity between disasters to build resilience. As outlined in the continuing transfer design section, the only disaster-specific steps necessary for powerful disaster resilience effects would be to design logistical and financial plans for benefit scale-ups.

Limitations

It is important to come to terms with CTPs’ limitations in assisting disaster victims in the immediate aftermath of a disaster. While cash transfers may help residents prepare in the run-up to a disaster and then recover on the back end, transfers do not produce the same effect in the period immediately following a disaster. In fact, CTPs could have an undesired inflationary impact in cases where markets are dysfunctional or have already failed, inundating supply-constrained markets with a flood of demand (Bailey and Harvey 2011; Gentilini 2007; Ivaschenko et al. 2020). Cash transfers lose their utility when people have nothing to purchase or when immediate survival is the only consideration, which makes disaster response planning, including for search-and-rescue efforts and direct food and shelter aid, so important (Ivaschenko et al. 2020; Bailey and Hedlund 2012).

Beyond in-kind aid that provides direct disaster response resources, CTPs should also not be designed as a substitute for inequity-ridden disaster programs housed under FEMA. Cash transfers would never be able to fully cover the costs of catastrophic damage to residences and personal property. Rather, CTPs merely serve as a baseline that diminish the effect of procedural barriers set up in other relief programs. Even in the presence of a generous disaster CTP, existing recovery aid programs should be overhauled to reduce procedural inequity and more comprehensively respond to the needs of its most disenfranchised target populations.

Additionally, cash transfers may still struggle to reach marginalized populations. Especially among unhoused and/or undocumented people in the U.S., problems persist in delivering aid even to those who would be eligible. Although programs could be designed to be opt-out rather than opt-in (by automatically registering participants), such a design would still struggle to reach populations who avoid contact with government agencies and have such low levels of trust in government that they would actively avoid enrolling even if they knew about the program. It follows, then, that without fixing wide-ranging social problems and remedying long-standing state-imposed harms, many of the problems endemic to current disaster programs would arise with CTPs as well.

Even so, a disaster setting has features that may allow governments to reach typically inaccessible and marginalized people. First, disasters bring a fleet of bureaucrats, first responders, social workers, and volunteers to at-risk areas: these public servants can be mobilized to deliver aid directly to needy populations. Additionally, disasters often result in people being concentrated in common spaces such as community centers, shelters and temporary housing, and food banks, making it less labor-intensive and more cost-effective to provide rapid assistance to large numbers of people. The literature also tells us that it is possible to leverage existing welfare supply chains and government data to reach as many people as possible. At the very least, all recipients of some form of government cash assistance (such as unemployment, disability, welfare, etc.) living in a disaster-impacted area could instantly receive benefits if the provision of one or more of these services uses direct deposit technology. Even tax returns could be utilized in a similar way to the COVID-19 stimulus program; all residents who had filed taxes for addresses within a certain ZIP code could receive their cash transfer deposit from the IRS (Carlisle, 2020). Current disaster aid programs are unable to automatically provide benefits because of strict eligibility requirements contingent on the nature of each program, such as having to document and prove that one’s place of residence underwent damage. Non-means-tested CTPs would skip the expensive and exclusionary step of eligibility screening altogether.

Finally, a major limitation is the cost necessary to design, implement, and maintain a cash transfer program. Although non-means-tested CTPs are cost-effective to administer by virtue of spending far less time and resources on screening participants, they would still generate substantial costs by providing direct cash benefits to a large number of people. The costs may make it politically difficult to secure the funds necessary for CTPs, whether as a rapid-response design or as a much more ambitious continuing transfer program. Despite this, a Cash Transfer Program’s many social and economic benefits could far outweigh its costs.

Conclusion

The utility of this assessment of CTPs is twofold. First, to suggest that disaster-specific cash transfer programs should be considered by government agencies (namely, FEMA) as a redistributive, resilience-building, transformative addition to the current regime of relief programs. Second, to contribute more theoretical support for the adoption of Universal Basic Income programs. While UBIs would produce an array of socially and economically desirable effects, an unforeseen and yet profoundly impactful effect may be their efficacy in helping oppressed and marginalized peoples withstand disasters.

As climate change makes disasters both more common and more extreme, policymakers and planners must respond. Thinking transformatively and radically is a policy imperative, not just in a disaster context, but in the context of the political, economic, and social engines that power inequality and injustice. Cash transfer programs may play a critical role in the future of American disaster planning, but only if researchers and policymakers alike begin to treat them as a legitimate disaster tool instead of a fringe safety net fad.

CHILD LABOR: CONTINUOUS EXPLOITATION AND ABUSE

Jennifer Smith

Abstract: On September 27, 2020, The New York Times reported that the closing of schools and decrease of jobs and income during the coronavirus pandemic forced millions of poor children to leave education behind and pursue careers to support their families. Despite nearly 100 million children being removed for child labor between 2000 and 2016, 152 million children are laborers with nearly half currently working in hazardous jobs in agriculture, mining, construction, manufacturing, and other sectors. The conventional wisdom is that the United Nations is effective in reducing global child labor, yet this belief does not explore how international organizations can respond to global issues. This paper will use qualitative methodology in the form of case study research to demonstrate how the International Labor Organization can respond to the threat of increasing child labor by evaluating two case studies from the 1990s: the Pakistan soccer ball industry and the Bangladesh garment industry. My research demonstrates that the International Labor Organization can respond to the threat of increasing child labor by raising awareness of the industries profiting off child labor. The findings demonstrate how removing children from child labor and placing them in education programs both provides better human rights for children and has the possibility of stimulating better economic growth in the future as more children become educated.

Introduction

On September 27, 2020, The New York Times reported that closing schools and loss of jobs and income during the coronavirus pandemic forced millions of poor children globally to leave their education and begin working to support their families (Pérez-Peña 2020). Increases due to the pandemic demonstrate a new disruption to the efforts to end child labor, which have been prevalent since the founding of the International Labor Organization (ILO) in 1919. In the early twentieth century, the ILO established the Conventions and Recommendations on child labor and children’s work, introducing international legally binding instruments for children’s rights (Quinn 2019). From 2000 to 2016, the ILO decreased the number of child laborers from 246 million to 152 million, resulting in nearly 100 million children being removed from child labor (ILO News 2021). As the number of child laborers decreases, the ILO argues that helping the remaining children, especially those living in remote areas, situations of conflict and disaster, and poor communities continue to be the most challenging demographic to reach (Quinn 2019). To prevent vulnerable families from resorting to child labor, the ILO and UNICEF urge governments to bolster or develop social safeguard measures that guarantee secure access to health care and reinforce employment, income, and food security (Buchner 2020).

The critical issues that increase child labor pose numerous ramifications for vulnerable populations. For many low- and middle-income countries, such as Myanmar, Bangladesh, and India, fighting coronavirus also involves a fight to save children from forced labor that disrupts their childhoods and impedes their right to a fruitful future (Buechner and Ferguson 2020). Child labor goes beyond education, resulting in harmful outcomes that last lifetimes as schools provide children with health, immunization, and nourishment services in a secure, supportive environment (Buchner 2020). Prevalent poverty results and enforces child labor, further feeding social discrimination and inequality. Without urgent and effective measures to protect and remove children from child labor, years of educational gain and anti-child labor actions will falter. This paper examines the enduring manifestations of child labor and its impact on global and local prosperity. By utilizing the theoretical framework of international positivism, the research explores whether child labor can be eradicated through international pressure from economies like the United States and advocacy and implementation work by global entities like the International Labor Organization. With specific evidence from Pakistan and Bangladesh, the study finds that international pressure and subsequent response by international organizations can play a crucial role in beginning to dismantle child labor practices across the world.

Conventional Wisdom

While there is no available non-partisan polling data from the United States regarding child labor, we can determine American beliefs by looking at international organizations dealing with child labor, such as the ILO under the United Nations (UN). According to a 2016 poll from the Pew Research Center, 65 percent of Americans say the UN is doing a poor job of attempting to solve the global issues it faces (Pew Research Center 2016). Likewise, a 2020 Gallup poll shows that 57 percent of Americans believe the UN is doing a poor job of attempting to solve the global issues it faces (Brenan 2020). These polls reveal that most Americans think the UN needs to solve global problems more sufficiently. While these polls did not explicitly ask for American’s perspectives on the UN’s effectiveness in solving issues related to child labor, based on overall negative reviews of the UN’s lack of effectiveness in addressing and solving global issues, it is plausible to assume that Americans do not obtain a favorable opinion on the UN’s handling of and effectiveness in reducing global child labor either.

While Americans believe the UN is doing a poor job of attempting to solve the global issues it faces, this conventional wisdom is incomplete. Several factors need consideration about individual UN organizations, including their historical effectiveness, before understanding how individual organizations like the ILO respond to international child labor. General disapproval of the UN’s effectiveness does not provide a full picture of the approval of each of these UN organizations. Furthermore, this conventional wisdom does not explore how international organizations can respond to global issues, such as the rise in child labor. Specifically, the ILO can look at previous actions and precedents they have conducted to determine the best method of responding to an increase in child labor on an individual country basis. By overlooking individual factors and demonstrating generic disapproval of the UN, the conventional wisdom fails to address how international organizations can improve global conditions.

Methodology and Evidence

This paper will use case study research to demonstrate how the ILO can respond to the threat of increasing child labor. These case studies will look at the use of child labor in 1990s Pakistan and Bangladesh and how the ILO has intervened to eliminate child labor. Case studies were limited to the 1990s as they provided a significant amount of time to determine the effectiveness of their programs. Additionally, case studies occurring prior to the ILOs adoption of Convention No. 182 in 1999, which declares that UN member countries commit themselves to take immediate and effective measures to secure the prohibition and elimination of the worst forms of child labor, including slavery, prostitution, and forced labor, were chosen to evaluate the effectiveness of the UN's policies without an established global support and accountability measure (International Labor Organization 1999). The prevalence of Pakistan and Bangladesh industries in the 1990s global market, which further prompted the hiring and forced labor of children, made them ideal representative countries for this case study. The evidence utilized in this paper is a combination of primary and secondary evidence. The paper predominantly relies on primary evidence, including ILO and UN reports, U.S. Department of Labor documents, international law journals, and news sources like The Atlantic and The Economist.

Theoretical Paradigm

International positivism accentuates states as primary actors, prominent within international organizations such as the Permanent Court of International Justice. The theory focuses on implementing global standards through positive practices commonly found in treaties and unspoken customs included in legal matters. It asserts the significance of state consent, in which a state adheres to a legal standard due to affirmatively consenting to the norm (Murphy 2012). International positivism concentrates on what the law is and says by studying ratified treaties and state practices rather than focusing on what the law should be according to equity, justice, and fairness. Its theory of precedent and implementing global standards through positive practices helps frame the ILO's actions when determining how to eliminate child labor.

The concept that international law focuses on studying ratified treaties and state practices rather than working towards equal and fair laws makes it difficult for the ILO to establish action plans to eliminate child labor. As child labor limits the lifelong potential for child laborers perpetuating a cycle of poverty, efforts to eliminate child labor are essential to protecting and saving lives and entire communities. Therefore, international organizations must focus on creating plans that incentivize states to change based on state desire rather than emphasizing plans based on equity, justice, and fairness. The global acceptance of adhering to the legal norm due to state affirmative consent makes it increasingly difficult for international organizations to conceive and implement change.

Case Study: Pakistan

According to the U.S. Department of Labor, Pakistani children are engaged in some of the worst forms of child labor, leading to commercial sexual exploitation and domestic work linked to human trafficking (Bureau of International Labor Affairs 2020b). Much of this child labor is implemented under forced labor conditions such as debt bondage, sexual assault, and physical abuse. In addition to debt bondage, many poor rural families sell their children as domestic servants or rely on paid agents to arrange servitude, often misinformed that their children work under decent conditions (Bureau of Democracy, Human Rights and Labor 2020). Furthermore, child labor has continued to thrive in Pakistan due to police corruption which includes taking bribes and being unwilling to conduct investigations into child labor crimes, including receiving bribes from presumed perpetrators to overlook criminal child labor and a lack of motivation to conduct investigations (Bureau of International Labor Affairs 2020b). Despite the lack of experience, trade knowledge, and maturity, employers continue to utilize child labor as children are less expensive, highly motivated, efficient, and obedient as they do not form labor unions or strike, unlike adult laborers (Smith 2005). However, many employers defend their actions by arguing that the lack of economic stability prevents the country from addressing social concerns.

One of the prominent issues leading to child labor in Pakistan is the weakness of the education system. A 2004 Congressional Research Service Report (CRS) lists Pakistan's primary education system among the least effective globally (Kronstadt 2004). As of 1999, over half of Pakistan's country was illiterate, including 21.5 million children (Ahmed and Becker 1999). Due to poor education systems, many parents prefer their children to develop practical skills rather than attend low-quality schools without additional employment opportunities. In rural countries, poor-quality schools do not necessarily provide students with better opportunities for developing jobs and personal growth, making it natural for children to join the labor market instead. For those children who do attend school, most decide to drop out before completing primary school. According to a 2020 Human Development report from the UN Development Reports, Pakistan has an average of 5.2 years of schooling compared to the United States, which averages 13.4 years of schooling (Conceição 2020).

The UN and ILO began targeting large Pakistan-based industries profiting from child labor. In 1997, the ILO began targeting the soccer ball industry for using bonded child laborers in Sialkot, Pakistan. In the early 1990s, Pakistan produced 75 percent of the global supply of soccer balls and 71 percent of imports to the United States (International Labor Rights Fund 1999). Child laborers aged 5 to 14 stitched soccer balls for 11 hours daily, making only $0.50 to $0.55 per ball, with an average of two to three balls per day. Other children were forced into bonded labor to pay off their parent’s debts. As a result, children remained out of school. Along with their families, they continued to be bound by labor obligations, possibly continuing an intergenerational cycle of poverty and debt bondage.

In the late 1990s, negative publicity in the United States regarding Pakistani child labor and the stitching of soccer balls provoked a change in soccer ball retailers and influenced concerned activists to ensure that manufactured soccer balls did not contain child labor (International Labor Rights Fund 1999). Many soccer ball manufacturers agreed to comply with monitoring programs sponsored by the ILO to combat adverse exposures. One program was the Partners’ Agreement to Eliminate Child Labor in the Soccer Ball Industry in Pakistan, also called the Atlanta Agreement. Formed on February 14, 1997, the agreement established a partnership between the ILO, the Sialkot Chamber of Commerce and Industry, and UNICEF. The project aimed to eliminate child labor in the soccer ball industry and other industries through industry monitoring of child labor and establishing social protection initiatives for impacted children and families (Ahmed & Becker 1999). By targeting multiple industries, the partners hoped that the project's establishment would influence other work sectors in Sialkot, the Pakistani Government, and other vital Pakistani institutions to analyze their potential to contribute to eradicating child labor (Independent Monitoring Association for Child Labour 1997). However, a notable concern was ensuring the elimination of child labor in Pakistan does not generate new dangers for child laborers and their families.

In the Atlanta Agreement, the ILO was responsible for determining programs and implementing agents, enlisting the participation of the Pakistani government, and providing financial and technical support. Additionally, the agreement created an awareness-raising initiative to target Siaklot communities that provide child workers and educate community and religious leaders, parents, and children about the importance of education and the detrimental consequences of permitting children to work (Independent Monitoring Association for Child Labour 1997). Children in rural, poverty-stricken areas engaged in unprotected employment, and any improvements required a holistic legal framework and viable actions and awareness (Khan 2019). Manufacturing companies volunteered to take part in the agreement and agreed to stop child labor and allow international organizations to monitor their actions. Following the conclusion of the agreement, the ILO explained that international advocacy towards pressure groups is an essential factor in interventions (Ahmed & Becker 1999). International pressure from the United States caused interest and change in societal norms regarding child labor in Pakistan. Due to allegations of inadequate work rights protection involving nationwide child labor, the United States partially suspended Pakistan from the Generalized System of Preferences in 1996 (Bureau of International Labor Affairs 2003). The suspension adversely impacted Pakistan’s trade privileges, removing $40 million in GSP benefits from Pakistani surgical instruments, sporting goods, and handmade rugs (U.S. Department of State 1997).  Changing societal norms puts pressure on manufacturers and governments to incite change for the benefit of the people. It also led international organizations like the ILO to begin taking action to solve global problems and improve the lives of some of the world’s most vulnerable populations.

According to an article published in 2000 by The Economist, three years after implementing the Atlanta Agreement, Sialkot's soccer industry is primarily history, and 66 manufacturers accounting for 90% of the district's exports consented to inspection by the ILO (The Economist Historical Archive 2000). However, despite the best efforts of the Atlanta Agreement, the effects have also been adverse. To ensure a lack of child labor in soccer ball manufacturing, employers needed to move stitching into centers made of sheds along village roads that the 14 ILO monitors could visit. As a result, overall costs increased, leading customers to buy from competitors, like China, which produces machine-stitched soccer balls. Between 1996 and 1998, as the program's establishment occurred, Pakistan's share of the American soccer-ball market dropped from 65% to 45% (The Economist Historical Archive 2000). While adverse outcomes have occurred due to the Atlanta Agreement, the ILO has proven effective in eliminating child labor by inciting change through international pressure.

Case Study: Bangladesh

Currently, children in Bangladesh partake in some of the worst forms of child labor, including producing dried fish, bricks, garments, and leather goods (Bureau of International Labor Affairs 2020a). Many of these children work in manual labor industries where they must work without protective gear to shield them from toxic materials and insecticides. Additionally, long workloads force many children to remain at their factories, often surrounded by water pollution, to eat, bathe, and sleep. Bangladeshi children are subject to domestic servitude and bonded labor involving limited mobility, wage holdings, threats, and abuse (Bureau of Democracy, Human Rights and Labor 2017). The government does not provide oversight in the agriculture and other informal sectors, leading to the employment of large numbers of children. Nearly all labor sectors utilized child labor except for ready-made garments aimed at exports. However, the lack of government presence regarding the elimination of child labor has allowed it to flourish in most industries.

One of the prominent issues leading to child labor in Bangladesh is the utilization of refugee camps. BBC News reported in 2020 that several thousand Rohingya Muslims fled across the border into Bangladesh after a crackdown by Myanmar’s army in August 2017 (BBC News 2020). Dubbed one of Myanmar’s largest ethnic minorities, the Rohingya people were attempting to escape alleged communal violence and abuses by Myanmar’s security forces. During his visit to Cox’s Bazar, Bangladesh on July 2, 2018, UN Secretary-General António Guterres stated, “I have no doubt that the Rohingya people have always been one of, if not the, most discriminated people in the world, without any recognition of the most basic rights starting by the recognition of the right of citizenship by their own country” (UN Secretary General 2018). However, 350,000 Rohingya children live in refugee camps exposed to forced labor and commercial sexual exploitation in Bangladesh, India, and Nepal (Bureau of International Labor Affairs 2020a). Though promised monthly wages equivalent to USD 18 to USD 24, children are paid significantly less, if at all, despite working excessive hours (IOM 2018). Additionally, they are forbidden from communicating with their families and are further sold into bonded labor.

To combat child labor, the UN and ILO began targeting some of Bangladesh's largest industries profiting from child labor. In the mid-1990s, the ILO and UNICEF focused on the garment industry. In 1992, Bangladesh was one of the world’s major garment exports and employed over a million workers (Bellamy 1997). However, between 50,000 and 75,000 of these workers were children under 14, primarily young girls. In 1992, the textile and garment industry accounted for roughly 75 percent of Bangladesh’s total exports (World Integrated Trade Solution n.d.). Bangladesh's total exports reached USD 1.942 billion in 1992, with roughly USD 1.46 billion USD resulting from textiles and clothing.

While Bangladesh's national law indicated illegal child employment, the issue did not gain attention until the United States uncovered child labor practices. In 1992, the United States was Bangladesh's largest trading partner, accounting for roughly 34 percent of all trade in Bangladesh (World Integrated Trade Solution n.d.). However, as the uncovering of the use of child labor continued, the pressure from Americans to buy products made ethically threatened Bangladesh's economy. On October 1, 1992, the House Ways and Means Committee, sponsored by Representative Donald J. Pease, introduced the Child Labor Deterrence Act of 1992. This act urged the President to form an agreement with the United States’ global trade partners to create a ban on trade in child labor-made products (Pease 1992). It also called for the prohibition of imported products produced through child labor by creating civil and criminal penalties.

An article posted on December 24, 1992, by The New York Times highlights Americans' pressure to avoid child labor. After the NBC News program “Dateline” accused Wal-Mart Stores Inc. of purchasing clothing from Asian suppliers using illegal child labor, many Americans became more aware of the lack of ethical business practices in the products they were purchasing (Hayes 1992). The program, watched by 14 million Americans, showed eleven-year-old children stitching Wal-Mart labels onto garments in a Bangladesh factory, which experienced a fire two years prior that killed 25 workers, including several children. Wal-Mart remained under fire for purchasing unethically made products from China as well. Hongda Harry Wu, a research fellow at the Hoover Institution at Stanford University, stated, “My view is they are aware of the problems, but they just don’t care... they shouldn’t purchase blood products. This is against the basic principles of the United States” (Hayes 1992). While Wal-Mart did not face any negative economic impacts, primarily due to the scandal occurring during the holiday season, it raised awareness for child labor and the issues large American companies were facing in maintaining standards and monitoring the production of the products they purchase.

With new global pressure to eliminate the use of child labor, the garment industry in Bangladesh swiftly laid off between 40,000 to 50,000 children in 1992 (International Program on the Elimination of Child Labor 2004). As a result, many children took up other work, often more hazardous and less protected. However, continuous international pressure compelled the ILO and UNICEF to step in. On July 4, 1995, the Bangladesh Garment Manufacturers and Exporters Association (BGMEA), the International Labor Organization (ILO), and the United Nations Children’s Fund (UNICEF) signed a Memorandum of Understanding (MOU). It stated that all children should be removed from factories and enrolled in schools; however, they should not be removed from work until an appropriate school program is available. It also prevented factories from hiring new or returning child laborers once placed in appropriate school programs. This Memorandum marked the first time an industry closely worked with international organizations to eliminate child labor by creating and providing appropriate alternatives. Following the MOU, the first school was established in January 1996 by UNICEF, with 2,200 children enrolled in schools by August. The BGMEA created a verification and monitoring system in July 1998 to construct a monitoring and validation system according to the agreements specified in the MOU. Despite the MOU's positive progress in Bangladesh, as of 2004, the child labor monitoring system was only sustainable with support from the ILO and had an uncertain future.

Policy Implications

Based on the research findings demonstrated in this paper, international pressure is the most effective method of inciting change in child labor. As opposed to the conventional wisdom that Americans believe the United Nations is not doing a good job solving global problems, my research demonstrates that the International Labor Organization can respond to the threat of increasing child labor by raising awareness of the industries profiting off child labor. By increasing global awareness, the public becomes more aware of the type of labor used to produce the projects they import from overseas. As seen in the Pakistan case study, Americans desire products that are made ethically and refrain from importing goods with negative press. The pressure to eliminate child labor due to economic threats influenced manufacturers to comply with monitoring programs sponsored by the ILO. Likewise, the Bangladesh case study demonstrates the pressure child labor awareness places on big American companies allowing the industry to flourish by purchasing unethically sourced products. The threat to economic stability for the United States, Bangladesh’s largest export, forced the country to create programs to move students from factories to schools.

The ILO needs to raise more awareness around goods profiting from child labor so that countries profiting off it will receive negative backlash from the countries purchasing. As mentioned in the international positivism theoretical paradigm, international organizations must focus on creating plans that incentivize states to change based on state desire rather than emphasizing plans based on equity, justice, and fairness. Both case studies exemplify how international pressure influences global industries to comply with UN organizations to eliminate child labor in the workforce. It further demonstrates how removing children from child labor and placing them in education programs provide better human rights for children and can stimulate better economic growth in the future as more children become educated. With schools closing due to the coronavirus pandemic, the UN must help children return to school to prevent them from entering or re-entering child labor. Based on these findings, global disdain over product manufacturing and the threat to economic growth is a suitable catalyst for change.

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