Access to Livelihood Assets and Vulnerability to Lower Levels of Well-Being in Kakuma Refugee Camp, Kenya

Abstract

This paper investigates the role that access to livelihood assets plays in reducing vulnerability to lower levels of well-being, especially for camp-based refugees. We develop the multidimensional vulnerability index using the 2019 Kakuma socioeconomic survey to provide a comprehensive and holistic approach to measuring vulnerability. The fractional regression results suggest that the household head’s age and education level determine the vulnerability of refugees to lower levels of well-being. In addition, access to finance and employment substantially reduces refugees’ vulnerability. Although remittances from abroad are a prevalent source of finance among refugees, we find that remittances from abroad only lessen the prevalence of vulnerability by 1.1%. Therefore, we recommend camp refugees adopt more self-reliant ways of accessing sustainable finance. The multidimensional vulnerability index reveals a high level of food insecurity in camps caused by the influx of refugees over the years. We recommend the inclusion of refugees in farming and training on climate change to provide sustainable solutions around food security to them and the host community.

1. Introduction

Africa continues to lead in hosting refugees and displaced persons amidst the global surge of forced displacement. According to the UNHCR, it will host close to 27.2 million displaced persons by the end of 2025, which is an increase from 26 million at the end of 2024. Kenya alone hosted 819,686 refugees and asylum seekers by late November 2024, with 87% residing in camps and 13% in urban areas (UNHCR, 2024). The UNHCR collaborates with the Government of Kenya to manage the development and execution of protection and the implementation of targeted support programs for refugees and asylum seekers. This is backed by an elaborate policy environment and regulatory framework that guides the management of refugees’ affairs. Foremost, these global efforts aim to improve humanitarian and development assistance for refugees through the Global Compact of Refugees (GCRs), which was influenced by the Comprehensive Response Refugee Framework (CRRF) (World Bank, 2022). These strategies for development have been designed to integrate refugees, promote economic inclusion, and create self-reliance for refugees, which are key efforts towards reducing their vulnerability.

Despite these efforts, refugees face challenges related to coping mechanisms and socioeconomic vulnerability, particularly in employment opportunities. Although there has been progress in granting refugees legal rights to work, only 67% have such rights (GCR, 2023). A total of 45% of these reside in countries with practical access to formal employment, revealing a 22 percentage point gap perpetuated by ongoing barriers. The refugee employment rate in Turkana remains low (20%) compared to that of the host community (62%) and the national rate (71%) (UNHCR, 2023a).

Refugees often encounter substantial barriers when seeking employment due to a mismatch between their skills and the local job market, stemming from a lack of relevant skills, skill obsolescence, and restrictive legal frameworks limiting their access to work permits and hindering the recognition of their qualifications. As a result, refugees tend to rely on their social networks.

Social networks play a vital role in job searching and employment as they provide access to information on the available opportunities (Betts et al., 2019). Betts et al. (2019) explain that the social networks established by refugees in Kakuma create reluctance to relocate for fear of losing their connections. Strengthening social networks as a coping mechanism can improve self-reliance and the ability of refugees to navigate the available opportunities. The importance of social connections in facilitating socioeconomic integration cannot be overstated. Social connections, including relationships with specialist refugee-supporting organizations, friends, and informal contacts, play a crucial role in providing practical and emotional support, accessing essential resources, and navigating statutory services. These connections are essential for refugees to achieve their long-term employment, educational, and housing goals.

The impact of forced displacement on physical and mental health can severely affect refugees’ employability, as mental health challenges such as trauma and stress can hinder an effective work performance, emphasizing the need for health-focused interventions. Furthermore, access to essential assets significantly influences the vulnerability of refugees and their overall well-being; the loss of financial resources during displacement severely restricts their ability to invest in skill training, education, and entrepreneurship, necessitating carefully designed financial assistance programs that consider their specific economic behaviors and risk aversion.

Practical barriers, such as the lengthy administrative processes for obtaining permits and recognizing qualifications, alongside language proficiency issues, further complicate refugees’ access to employment; thus, providing tailored language training linked to job opportunities can significantly enhance their employment prospects. Ultimately, economic inclusion is crucial for enabling refugees to contribute as consumers, taxpayers, and employers in their host economies. This calls for deliberate efforts from host countries to stimulate economic growth, raise the living standards, and address unemployment and underemployment to create decent work opportunities for refugees.

Research has shown that refugees are generally more vulnerable compared to the host communities. Chapman (2021) argues that while the host urban population and urban refugees faced difficulties during the COVID-19 pandemic, the Kenyan (host) population was not as asset-vulnerable. In particular, camp-based refugees have less access to livelihood assets than urban refugees.

Most refugees face significant challenges in achieving socioeconomic integration. For instance, research highlights that refugees often experience difficulties in catching up with natives in terms of employment probability, earnings, and other economic outcomes, particularly in advanced economies.

The gap in socioeconomic integration is further exacerbated by the limited access to livelihood assets, which increases the level of vulnerability among refugees. Some studies have documented that refugees’ economic prospects are hindered by various factors besides their living conditions, limiting their engagement with local economies.

In the context of Venezuelan migrants and refugees, research has emphasized the need to improve economic inclusion, access to healthcare and education, and social cohesion to enhance socioeconomic integration. These measures are critical for benefiting migrants and the host communities by strengthening economic development, public health, and social equity.

This paper provides a comprehensive approach to how access to assets for sustaining livelihoods affects refugees’ vulnerability to lower levels of well-being. We achieve this by focusing on two objectives:

(i)

To ascertain the determinants of vulnerability among the refugees in the Kakuma refugee camp;

(ii)

To assess the influence of access to finance and employment on vulnerability to lower levels of well-being among the refugees in Kakuma.

This study develops the multidimensional vulnerability index (MVI), which provides a contextual overlay of the vulnerability of the refugees in Kakuma across three dimensions and fifteen indicators of well-being. The recommendations from this study aim to address the refugee population’s vulnerability to lower levels of well-being, emphasizing the need for effective policies that facilitate socioeconomic integration and reduce the disparities between the refugees and the native population.

1.1. Livelihood Assets of Refugees in Kakuma

Refugees residing in camps exhibit heightened vulnerability, largely due to their increased dependence on direct aid and small-scale trade. While camp-based refugees are more likely to possess bank accounts, their likelihood of accessing loans is 22% lower (Pape et al., 2021). Forsen et al. (2016) note that despite the seasonal nature of remittances, these transfers account for one-third of the cash income in the Kakuma refugee camp. In response, the Government of Kenya, the UN Refugee Agency, and other key stakeholders have initiated efforts to foster self-reliance among refugee populations.

Refugees face barriers in accessing jobs locally mainly due to a lack of documentation and skill mismatch. The language barrier, legal restrictions, and skills mismatch majorly result in employment among refugees (Ginn, 2023). However, the UNHCR has scaled up the employment opportunities in Kakuma by providing accessible online jobs for youths. These initiatives have had a significant impact, as businesses in Kakuma and Kaloboyei account for 30% of the businesses in Turkana County (UNHCR, 2023b).

Chambers and Conway (1992) identify five essential assets for creating sustainable livelihoods: human capital, social capital, natural capital, physical capital, and financial capital. This analysis focuses on human and financial capital as the key assets since they are measurable and directly impact livelihoods. We seek to assess how access to these assets affects refugees’ vulnerability to poverty.

The major pathways to self-reliance for refugees lie in access to livelihood assets, initiatives that advocate for their interests, and partnerships with the private sector. The UNHCR has made efforts in socioeconomic profiling, identifying and documenting refugees with skills upon arrival for ongoing monitoring.

Given this context, there is a need to explore the extent to which access to livelihood assets has reduced vulnerability among refugees. Furthermore, examining these livelihood assets will enhance our understanding of the labor market dynamics for refugees, facilitating the effective utilization of their skills and competencies.

1.2. Vulnerability of Refugees in Kakuma

Refugees face poverty vulnerability associated with their health, societal structures, and capabilities to cope with threats. More than half of the households in Kakuma are headed by women compared to 32% in Kenya. Such households are typically larger and viewed as more vulnerable than those led by men (UNHCR & World Bank, 2019). Women refugees with disabilities are particularly vulnerable to discrimination, violence, and exploitation. According to the UNHCR and other international organizations, women and girls with disabilities are at a higher risk of discrimination, violence, and exploitation in refugee settings (UNHCR, 2020). Few refugees in the Kakuma camp can sustain themselves without any support (Forsen et al., 2016). Refugees are especially vulnerable to diseases, often due to poor healthcare in the host countries and exposure to infections in transit (WHO, 2018). The Turkana community faces problems ranging from marginalization, low income, and limited access to livelihood assets. Based on the nature of the economic activities of the Turkana community, the refugees in Kakuma are likely to face vulnerability to lower levels of well-being due to the constraints in socioeconomic factors accorded by the host communities.

Most refugees survive off remittances from friends and family, employment in informal sectors, and trade. The World Bank (2022) reports low-level asset ownership and access to employment among the refugees in Kakuma; most incentive workers who work for the UNHCR and its partners are paid approximately USD 65 per month rather than a salary. Only 10% of households reported receiving income from employment or businesses.

In addition to access to employment opportunities, some of the potential pathways to reducing vulnerability lie in access to finance, which has been promoted through the efforts of financial providers through account-opening services among refugees.

2. Literature Review

2.1. Theoretical Framework

Two theories have been adopted to consider refugees’ vulnerability: the vulnerability theory and the sustainable livelihood theory. These two theories are important in addressing the multidimensional nature of vulnerability and the livelihood assets to define vulnerability thereof.

The vulnerability theory highlights that exposure to risks, functionality, and coping mechanisms shape the vulnerability of a population. Fineman (2005) envisions vulnerability as a universal condition shaped by social systems and resource allocation. This emphasizes the role of societal structures in accelerating or reducing vulnerability. In the context of refugees, we adopt documentation, coping mechanisms, and food indicators as the key dimensions to measure vulnerability.

With insights from the vulnerability theory that vulnerability is a multidimensional concept, we integrate the Alkire and Foster (2011) approach, which develops a flexible measure of poverty by incorporating a variety of indicators adopted from a specific context. First, Alkire and Foster (2011) propose identifying specific forms of deprivation that a population has, and further developing indicators of the selected dimensions of deprivation. The Alkire–Foster method proceeds to combine indicators and dimensions and calculate the average number of people facing deprivation and the average intensity of deprivation in each dimension. The method accords flexibility in weighting. We accord equal weights to the dimensions and indicators selected using the identification method. Nguefack-Tsague et al. (2011) argue that equal weight provides a simplistic interpretation and ensures that no single dimension dominates the index. Therefore, policymakers can focus on improving all the dimensions of well-being holistically. The product of the components is weighted to form a weighted average across all forms of deprivation, which acts as the poverty measure, such that the following is true:

MPI = H × A

(1)

where, MPI is the multidimensional index, H is the incidence or percentage of poor people, and A is the average percentage of dimensions in which people are poor.

The sustainable livelihoods theory, on the other hand, is suitable for assessing how development decisions fit the livelihoods of marginalized and poor populations. We adopt the framework by Chambers and Conway (1992) to assess how refugees mobilize assets and how their access influences vulnerability. Figure 1 represents assets in a pentagon that changes based on the availability of each asset: human capital, natural capital, social capital, physical capital, and financial capital. Chambers and Conway (1992) note difficulties in measuring and comparing livelihood assets because they vary based on the local context, such that a given population might be able to satisfy their needs with more social capital than financial capital. The sustainable livelihood theory is of importance to this study since it builds the foundation for the relationship between livelihood assets and vulnerability. This theory illustrates that transforming processes and structures enables a population to create changes with the available livelihood assets (DFID, 1999). Our findings confirm this as refugees who engaged in farm work, salaried employment, and had access to finance showed reduced multidimensional vulnerability.

2.2. Empirical Literature

Food security is a critical aspect of refugee well-being on a path to reducing vulnerability. Nisbet et al. (2022) examine food security interventions among refugees around the globe. The study seeks to identify the existing gaps in food security interventions among refugees. The studied variables include food transfers, animal husbandry, nutrition education, providing cash and cash vouchers, animal husbandry, and gardening. The study aligns with the United Nations’ Sustainable Development Goals (SDGs) of reducing food insecurity. Gender consideration is essential in the interventions regarding refugee food security, while including the host communities in decisions about food security is effective and enhances the interactions between refugees and host communities (Nisbet et al., 2022). While the reviewed study provides direct impacts on food security, the current study examines a broader perspective of how institutional factors such as documentation interplay with access to livelihood assets. In addition, Nisbet et al. (2022) emphasize that reliance on food aid reduces vulnerability; this study establishes that reliance on aid from abroad reduces vulnerability to a small extent, thus proposing the need for more self-reliant and sustainable ways of reducing vulnerability among refugees.

The geographic location of refugees influences their access to livelihood assets. Chapman (2021) compared asset vulnerabilities among urban refugees and the Kenyan urban population in the Kibera settlement in Nairobi during the COVID-19 pandemic. The comparative study establishes that both the populations faced difficulties during the pandemic, but the Kenyan population was not as asset-vulnerable. The results by Chapman (2021) align with Mosser’s Asset Vulnerability Framework, which notes that access to capital for urban refugees builds resilience and reduces poverty (Moser, 1998). In addition, Chapman (2021) underscores the extent to which shocks can worsen the existing vulnerabilities of refugees as compared to those of host communities. This current analysis adopts a quantitative approach and the MVI to show how access to human and financial capital affects vulnerability to the lower levels of well-being.

Coping mechanisms define adaptive capacity, resilience, and the strategies a population uses to deal with stressors. Nabulsi et al. (2020) provide an in-depth analysis of coping mechanisms and livelihood strategies for food security and access to health care among Syrian refugees in Lebanon. The study evaluates the livelihood strategies and coping mechanisms of refugees, particularly about formal assistance and registration status. This is emphasized by Dyer and Burchardt (2016) by identifying the role of social support systems, optimism, and the importance of fostering resilience among refugees. While Nabulsi et al. (2020) suggest that systematic challenges in Lebanon’s healthcare increase the vulnerability of refugees with financial access, this study shows that financial access reduces overall vulnerability. This analysis could be more targeted by incorporating insights on gender, as illustrated by Fliethmann et al. (2024) who argue that gendered stereotypes influence the access to assets among refugees. Building on this foundation, the current study seeks to fill this gap by exploring gendered geographic dynamics and their interplay with the vulnerability of the refugees in Kakuma, Turkana, Kenya.

The political environment and the integration of refugees with host communities significantly impact the socioeconomic well-being of displaced populations. Muthengi (2019) examines the influence of socioeconomic and political factors on the local integration of refugees in Nairobi and Kakuma. The study echoes the findings of Betts et al. (2022) that perceptions from the host communities shape the willingness of refugees to integrate. Muthengi (2019) reports a positive relationship between these socioeconomic and political factors and the local integration of refugees in Kenya. However, the study fails to offer the in-depth analysis of the psychological barriers refugees face during integration especially due to their push factors for displacement. Building on this, the current study integrates psychological factors as a coping mechanism and their influence on the access to livelihood assets.

Forsen et al. (2016) focus on vulnerable areas, particularly food insecurity, among refugees in the Kakuma refugee camp. The study notes that food security among refugees is a factor reflecting aid, economic status, and environmental factors. Crisp (2022) stresses the importance of remittances from abroad in addressing short-term and long-term food insecurity crises. Unlike the argument by Forsen et al. (2016) that systematic and structural barriers limit access to livelihood assets, this study notes that targeted financial inclusion strategies are practical solutions to reducing vulnerability among refugees. While the previous studies highlight the importance of food security and the role of humanitarian assistance, there is a need for broader analysis, especially one that focuses on the long-term solutions to food security. The current study takes a broader, holistic approach to assess refugees’ access to assets and how refugees can engage in more sustainable ways to eradicate food insecurity, while taking into consideration the effects of climate change.

2.3. Contribution to the Literature

This study goes beyond the traditional measurements of poverty that are unidimensionally related to either income or expenditure. Zedini and Belhadj (2014) adopt unidimensional poverty analysis, focusing on income and wealth. Aisling and McWilliams (2017) report a positive relationship between displacement and vulnerability to the asset scarcity of refugees in Tanzania. The study adopts an asset-based poverty index designed to alleviate poverty and improve living standards. The MVI bridges this gap by considering multiple forms of population deprivation in measuring vulnerability, including documentation, coping mechanisms, and food resilience. Adopting multiple forms of deprivation provides a deeper understanding of vulnerability, particularly in the displacement context where unidimensional measures might not capture the complexity of deprivation. In addition, unlike the previous indices that focus on economic factors only, this index incorporates institutional and social factors. This not only ensures broad applicability by policymakers, but is also effective in ensuring the population does not fall into higher levels of poverty. The UNDP (2023) developed a multidimensional poverty index (MPI) to explore the multidimensional poverty situation in Sri Lanka. This study capitalizes on the flexibility of multidimensional indexes by measuring vulnerability to lower levels of well-being with dimensions selected from a wider scope. Finally, the MVI developed in this study is a key diagnostic tool for humanitarian agencies, governments, and policymakers that can be adopted to develop targeted and effective strategies to enhance the integration and economic inclusion of refugees. This study, therefore, improves the existing literature by offering an enhanced MVI that is both conceptually and empirically sound, thus offering insights into the integration, self-reliance, and economic inclusion of refugees.

2.4. Vulnerability as a Multidimensional Phenomenon

This study examines the vulnerability of refugees to diminished well-being, with a focus on key dimensions, such as food insecurity, legal frameworks, and adaptive and coping strategies. By analyzing these specific factors, this research aims to provide a comprehensive understanding of how various mechanisms influence the overall vulnerability and resilience of refugees in protracted displacement contexts. Since vulnerability is inherent to the human experience (Fineman, 2005), this study extends the focus on how institutions and structures help mitigate this condition. This study further focuses on resilience by looking at the refugees’ adaptive and coping mechanisms. In this regard, the analytical framework of this study encompasses both susceptibility to poverty and the multifaceted risks associated with the further deterioration of well-being among the refugee population in Kakuma.

Foremost, we must understand the multidimensional nature of vulnerability. Adger (2006) emphasizes the complexity of vulnerability as shaped by the interconnection between social systems, exposure to risk, adaptive capacity, and temporary dynamics. Khalid and Meng (2021) identify the five dimensions of vulnerability, social, economic, physical, institutional, and attitudinal, in their holistic multidimensional vulnerability assessment. By nature of displacement, refugees face a variety of hazards and shocks that negatively impact their well-being. The vulnerabilities experienced by the refugee population vary because of different push factors, their geographic location, their political environment, and the host communities, among other factors. Therefore, it is important to address each population’s unique nature of vulnerability. Going beyond the poverty indicators such as income and assets will help policymakers design policies that reduce the risk of falling to higher vulnerabilities for the refugees and host communities.

In Kenya, 87% of refugees reside in the Daadab and Kakuma camps, which are located among the poorest counties in the country, meaning that the host communities are subject to considerable vulnerabilities. Coupled with the push factors of displacement, such as conflict and war, this creates multiple intersecting vulnerabilities that shape and influence the well-being of the refugee population. By nature, the overlapping of different vulnerabilities is likely to create vicious cycles of poverty from which a population would struggle to break. This, therefore, necessitates a holistic view in understanding and addressing these vulnerabilities.

3. Empirical Approach

3.1. Data

For this study, we use quantitative secondary data collected from a 2019 cross-sectional survey in the Kakuma refugee camp located in Turkana County, Kenya. The data represent 2217 randomly sampled households across the four sub-camps of Kakuma.

Questionnaires were completed by trained interviewers in the selected households using Computer-Assisted Personal Interviewing. The interviewers selected one respondent per household by sampling weights using the number of households in a dwelling and the number of dwellings occupied by a household. The survey collected the data on education, employment, household characteristics, assets, access, vulnerabilities, social cohesion, and coping mechanisms.

The survey provided the data, enabling the extensive analysis of the socioeconomic welfare of the refugees in Kakuma. We adopted variables of coping mechanisms and asset access to formulate the MVI. We then analyzed how education and employment are related to the vulnerability of the refugees in Kakuma. The variables used to develop the MVI were not used in empirical regression to avoid multicollinearity.

3.2. The Multidimensional Vulnerability Index (MVI)

We developed the multidimensional vulnerability index (MVI) based on the Alkire and Foster (2011) method. The United Nations Development Programme (UNDP) adopted this approach in 2023 to develop Sri Lanka’s MVI, which aggregates indicators across three key dimensions to capture the multidimensional and overlapping nature of vulnerability, particularly in climate disasters. The Alkire and Foster method involves identifying relevant dimensions and indicators to measure a population’s vulnerability to lower levels of well-being. This process includes assigning weights to the indicators and calculating the deprivation levels. In developing the MVI, the household is used as the unit of analysis. The index assesses vulnerability through three primary dimensions: documentation, food resilience, and coping mechanisms.

The choice of documentation as a dimension lies in its importance as an enabler in accessing services and providing identity to refugees. The NRC (2017) notes that refugees who lack documentation face challenges in accessing assets and often have a feeling of despair. In this study, we perceive a lack of documentation as a vulnerability since lacking it inhibits access to livelihood assets. Food resilience directly influences the well-being of refugees both in the short run and the long run. The FAO (2020) emphasizes that over-reliance on food aid inhibits refugees’ resilience.

Therefore, improving food security enhances the capacity of refugees to withstand shocks. This approach allows for a comprehensive understanding of the population’s vulnerabilities by considering multiple facets of deprivation and their interactions.

The three dimensions are comprised of 15 indicators, as shown in

Table 1. Dimensions, indicators, and weights for MVI.

Dimension	Indicator	Vulnerability Cut Off	Weight
Documentation (1/3)	Refugee identity card	Vulnerable if the household head does not have a refugee ID	1/15
	Movement pass	Vulnerable if the household head does not have a movement pass	1/15
	Birth certificate	Vulnerable if the household head does not have a birth certificate	1/15
	Passport from country of origin	Vulnerable if the household head does not have a passport from the country of origin	1/15
	Kenyan work permit	Vulnerable if the household head does not have a Kenyan work permit	1/15
	No document	Vulnerable if the household head does not have any documents at all.	1/15
Food resilience (1/3)	Money access to buy food	Vulnerable if the household did not have food/ money to buy food in the past 7 days	1/15
	Reliance on less preferred food	Vulnerable if household relied on less preferred food in the last 7 days	1/15
	Limit meal portion	Vulnerable if household reduced the meal portion among members in the past 7 days	1/15
	Borrow food or money to buy food.	Vulnerable if household borrowed food or money to buy food in the past 7 days	1/15
	Restrict consumption for adults	Vulnerable if household restricted consumption for adults in the past 7 days	1/15
	Reduce the number of meals	Vulnerable if household reduced the number of meals in the past 7 days	1/15
Coping mechanisms (1/3)	Feeling of safety	Vulnerable if the household does not feel safe around Kakuma town	1/15
	Ability to express an opinion	Vulnerable if the household is not able to express an opinion in community leadership	1/15
	Integration in decision-making	Vulnerable if the household does not feel considered in decision-making that affects their well-being	1/15

. We accord equal indicators for the indicators in all the dimensions. Having understood the importance of each of the dimensions chosen in developing the MVI, we seek to address vulnerability holistically by giving the indicators equal weights. Assa and Meddeb (2021) argue that adopting equal weights ensures no single dimension influences the overall index, and thus maintains equal importance for all dimensions. This also aligns with the UNDP (2023) who cautions on the possibility of bias in the index when some dimensions are prioritized over others without enough justification. The choice to use equal weights was made to simplify interpretation (Alkire & Foster, 2011).

The multidimensional vulnerability index (MVI) is derived by aggregating two key components, the headcount ratio (H), which represents the proportion of households identified as vulnerable to lower levels of well-being, and intensity (A), which reflects the average number of types of deprivation experienced by vulnerable households. Alkire and Santos (2013) suggest two approaches for identifying vulnerability, the union method, where a household is considered vulnerable if deprived in at least one indicator, and the intersection method, where vulnerability is identified only if a household is deprived in all indicators. Instead of adopting these extremes, this study employs the identification function proposed by Alkire and Foster (2011), which utilizes a weighting structure to determine a vulnerability cut-off, allowing for a more nuanced assessment of multidimensional vulnerability.

Let the vector of weights for the 15 indicators be as follows:

$$\mathrm{w}=({\mathrm{w}}_1,{\mathrm{w}}_2,\dots ,{\mathrm{w}}_{15})$$

(2)

Since the weights must sum to the number of indicators, we set the following:

$${\sum }_{\mathrm{j}=1}^{15}{\mathrm{w}}_{\mathrm{j}}=1$$

(3)

This implies equal weights for each indicator. Thus,

$$\mathrm{w}=({\displaystyle \frac{1}{15}},{\displaystyle \frac{1}{15}},\dots ,{\displaystyle \frac{1}{15}})$$

(4)

$${\sum }_{\mathrm{j}=1}^{15}{\mathrm{w}}_{\mathrm{j}}=15$$

(5)

The deprivation matrix:

$${\mathrm{g}}^0=\left[{\mathrm{g}}_{\mathrm{i}\mathrm{j}}^0\right]={\mathrm{w}}_{\mathrm{j}}$$

(6)

If individual i is deprived in indicator j, such that x_ij < z_j and ${\mathrm{g}}_{\mathrm{i}\mathrm{j}}^0$ = 0 otherwise. This matrix captures who is deprived in which indicator and the weight of that deprivation. The deprivation count vector c = [c_i], where c_i = ${\sum }_{j=1}^{15}{\mathrm{g}}_{\mathrm{i}\mathrm{j}}^0$ and each element [c_i] represents the weighted number of forms of deprivation for individual i. The vulnerability cut-off for this study was set at 33.334%; that is, a household that is deprived of five or more indicators is categorized as vulnerable, such that k = 5.

The union method, while sensitive, may overestimate vulnerability by including households experiencing relatively minor deprivation. On the other hand, the intersection method, though highly specific, may exclude households facing significant, but not comprehensive deprivation. To balance inclusivity and specificity, this study adopts an identification method with a low vulnerability cut-off (i.e., less than 50%), ensuring that the refugees with varying degrees of vulnerability are captured for analysis without being overly inclusive or exclusive.

Given that vulnerability is a broader concept than poverty, it is crucial to address even those with low levels of vulnerability to prevent their situation from deteriorating into poverty. This approach allows for more nuanced policy implications, targeting the refugees at risk of further socioeconomic decline. We conducted sensitivity analysis to evaluate the robustness of the MVI under different cut-off points. This also was performed to ensure that the index is not over-sensitive to subjective choices like the selection of cut-off point. We analyzed the index under thresholds of 20% (deprived of 3/15 indicators), 33.34% (base cut-off), and 53.33% (deprived of 8/15 indicators). The other key metrics analyzed were the headcount ratio, intensity, and the number of vulnerable households.

3.3. Definition and Measurement

Table 2. Definitions and measurements of variables.

Category	Variable Name	Definition	Measurement
Household characteristics	Sex	Sex of the household head. The male is the reference group	1 if male, 0 otherwise
	Household size	The number of people residing in a household	Number of people in a household
	Level of education	The level of education that the household head has completed, from primary, secondary, diploma, undergraduate, masters, PhD	Categorical variable
	Age of the household head	Age of the household head	Number of years
	Country of origin	The country from which the respondent originated	Categorical variable
	Source of energy	Type of fuel used to cook: Firewood, electricity, LPG, natural gas, charcoal, kerosene, shrubs, animal waste.	Categorical variable
Food Security	Reliance on less preferred food	A household having opted to less preferred food in the past 7 days due to limited resources	1 if no, 0 if yes
	Money access to buy food	Having food/ money to buy food in the past 7 days	1 if no,0 if yes
	Limit meal portion	A household having to reduce the meal portion among members in the past 7 days	1 if yes, 0 if no
	Borrow food or money to buy food	Households have borrowed food or money to buy food in the last 7 days	1 if yes, 0 if no
	Restrict consumption for adults	Household restricting food for adults for children to eat in the last 7 days	1 if no 0 if yes
	Reduce the number of meals.	Household reducing the number of meals in a day in the past 7 days	1 if no 0 if yes
Vulnerability index	MVI	A measure of vulnerability aggregated from 15 indicators in the three dimensions (consumption expenditure, documentation, and coping mechanisms) of vulnerability among refugees.	Count variable with positive integers ranging from 0 to 1
Documentation	Refugee identity card	A household head having a refugee id	1 if no 0 if yes
	Movement pass	A household head having a movement pass	1 if no 0 if yes
	Birth certificate	A household head having a birth certificate	1 if no 0 if yes
	Passport from country of origin	A household head having a passport from the country of origin	1 if no 0 if yes
	Kenya travel document	A household head having a Kenya travel document	1 if no 0 if yes
	No documents	A household head with no documents at all	1 if no 0 if yes
Livelihood asset	Employment	Labor activities that refugees have engaged in the formal and informal sectors in a week	Number of days
	Access to finance	Access to financing in the form of remittances, account ownership, purchase insurance, having borrowed money and using mobile banking services	1 if yes 0 if no

presents the contextual meaning and measurement of all the variables in this study. The variables are presented in categories, as in the domains presented in the source data. This study defines the demographic factors, the factors used in developing the MVI (food security, documentation, and coping mechanisms), and the livelihood assets factors.

3.4. Materials and Methods

We assess the determinants of vulnerability and the influence of access to finance and employment on vulnerability by regressing these factors against the MVI using a logit-fractional regression model (FRM). Similarly, Ateka et al. (2018) highlight the importance of the FRM in modelling fractional and bounded dependent variables. Since the relationship between the MVI and the independent variables is non-linear, FRM allows for more robust analysis, while avoiding the inconsistencies that may arise in using linear models like the OLS (Ateka et al., 2018).

The model is specified as follows:

MVI = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄ + β₅X₅ + β₆X₆ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄ + β₅X₅ + β₆X₆ + β₇X₇ + β₈X₈ + β₉X₉ + β₁₀X₁₀ + β₁₁X₁₁ + β₁₂X₁₂ + β₁₃X₁₃ + β₁₄X₁₄ + β₁₅X₁₅ + e

(7)

where β₀ is the intercept of the model, while (β₁, β₂, and β₃) represent the coefficients of the independent variables, X₁ is the sex of the household head, X₂ is the household size, X₃ is the level of education, X₄ is the country of origin, X₅ is the age of the household head, X₆ is the source of energy X₇ is bank account ownership, X₈ is remittances from abroad, X₉ is mobile banking account, X₁₀ is borrowed money, X₁₁ is insurance purchase, X₁₂ is holding insurance, X₁₃ is salaried employment, X₁₄ is employer in a non-farm enterprise, and X₁₅ employer in a farm business.

4. Results

4.1. Descriptive Statistics

We first present the analysis and robustness of the MVI.

Table 3. MVI results.

Vulnerability Cut-Off (k)	Measure	Value	Number of Vulnerable Households	Total Households
k = 33.334%	MVI	0.67	1930	2122
	Head Count Ratio (H, %)	97.79
	Intensity (A, %)	68.54

shows the results of the multidimensional vulnerability of the refugee population’s lower levels of well-being in Kakuma, which is based on the Kakuma socioeconomic survey of 2021. The table presents the headcount ratio (H), the proportion of households identified as multidimensional vulnerable to lower levels of well-being, and intensity (A), which shows the average incidences of deprivation experienced by vulnerable households.

The headcount ratio is achieved by calculating the number of households that experienced deprivation in at least 33.334% of the weighted indicators and dividing it by the total number of households in the sample. The ratio shows that 97.79% of the refugees’ households in Kakuma are vulnerable to a lower level of well-being, which is a multidimensional vulnerability. The average intensity (A) of vulnerability is 68.54%, which shows that each vulnerable household identified is deprived in more than half of the weighted indicators. The intensity is achieved by dividing the normalized deprivation by the number of vulnerable households. As 67.03% of the households in Kakuma are vulnerable to lower levels of well-being, the 97.79% of the vulnerable refugees identified experience 68.54% of the total deprivation adopted by the MVI.

4.1.1. Sensitivity Analysis of the MVI

Given the MVI is developed using weighted indicators, it is essential to conduct how variations affect the overall index. Figure 2 represents the MVI across different cut-off points. The headcount ratio is greater than 80%, across all thresholds, indicating that the number of households classified as vulnerable remains proportionately high.

As the threshold increases, the number of vulnerable households changes from 2120 at 20% to 1710 at 53.33%. Though this is a significant change, the number of vulnerable households is notably high, with more than half of the households at an even higher cut-off point. Sensitivity exhibits a correlation to the base cut-off of 0.999996453 at 20% and 0.999996423 at 53.33%. Consistency across the headcount ratio, intensity, and the number of households indicate that the MVI is robust as these factors do not drastically change.

4.1.2. Vulnerability Across Different Demographic Factors

Table 4. Vulnerability across different demographic factors.

		Vulnerability (%)
Household Size (%)		Below cut-off (33.334%)	Above Cut-off (33.334%)
0–10	83.10	2.84	48.88
11–20	16.22	1.04	59.29
20–29	0.69	1.14	58.71
Level of Education (%)		Below cut-off (33.334%)	Above Cut-off (33.334%)
Completed Basic Education	63.08	8.76	91.24
Completed High School	25.13	11.21	88.80
Completed Tertiary	11.76	0	100
Sex of the Household Head (%)		Below cut-off (33.334%)	Above Cut-off (33.334%)
Male	40.15	9.5	90.5
Female	59.85	8.79	91.2
Country of Origin (%)		Below cut-off (33.334%)	Above Cut-off (33.334%)
South Sudan	63.08	39.15	48.49
Somalia	25.13	34.39	21.83
Sudan	11.76	10.05	9.89
Congo	8.93	5.29	9.29
Ethiopia	4.05	5.29	3.93
Burundi	5.31	4.76	5.36

shows how different demographic factors interplay in describing the vulnerability context of the refugees in Kakuma. The table indicates that high percentages (59.29% and 58.71%) of the larger households (11–20 and 20–29) are more vulnerable relative to the smaller households. Although 11% of the household heads have completed tertiary education levels, these households still suffer extreme vulnerability, which might be associated with the underlying difficulties in securing jobs, despite their qualifications. The vulnerability distribution across countries of origin shows that South Sudanese households have the highest percentage (48.49%) above the vulnerability cut-off, followed by Somali refugees. This is due to conflict as the main push factor for the refugees from these countries. Female-headed households are predominant in Kakuma (59.85%) and depict more vulnerability (91.2%) as compared to males (90.5%).

4.2. Inferential Statistics

The regression results presented in

Table 5. Vulnerability, employment, access to finance, and MVI.

Variables	Coefficient Estimates
Congo (Reference Category) Somalia	−0.039 **
	(0.016)
South Sudan	−0.014
	(0.014)
Sudan	−0.025
	(0.102)
Completed Standard/Grade 8	0.121
	(0.104)
Completed Form 4/Grade 12	0.101
	(0.102)
Completed Higher National Diploma	0.125
	(0.125)
Completed Undergraduate Year 4	0.182 *
	(0.105)
Completed Undergraduate Year 5	0.100
	(0.114)
Completed Masters Year 2	0.145
	(0.101)
Completed Adult Basic Education	0.133
	(0.102)
Completed Adult Secondary Education	−0.053
	(0.151)
Completed Vocational Training Year 2	0.069
	(0.123)
Completed 40, Madrassa/Duksis	0.143
	(0.112)
Purchased firewood	−0.005
	(0.011)
Biogas	0.147 **
	(0.018)
Kerosene	−2.064 **
	(0.185)
Charcoal	−0.040 **
	(0.013)
Other (Specify)	−2.057 **
	(0.184)
non-farm business	−7.160 ***
	(0.239)
Salaried Employment	−6.390 ***
	(0.351)
Own or family farming activity	−7.569 ***
	(0.227)
Have a Bank Account	−6.444 ***
	(0.453)
Mobile Banking	−7.186 ***
	(0.167)
Insurance Purchase	−7.660 ***
	(0.160)
Constant	−3.568 **
Observations	764

*** p < 0.01, ** p < 0.05, * p < 0.1. Non-constant variance chi²(1) 2.00 prob > chi² = 0.16.

can be used to analyze our two objectives in depth; the determinants of the multidimensional vulnerability index (MVI), with a specific focus on the effects of country of origin, educational attainment, and the primary source of energy for cooking. These factors are crucial as they provide a nuanced understanding of the socioeconomic disparities that contribute to vulnerability at both the household and community levels. This table also presents the effect of the relationship between access to finance and employment on the MVI.

We test for heteroskedasticity using the fitted values of the MVI as the independent variable, which indicates a p-value of 0.16 > 0.05. Thus, we fail to reject the null hypothesis (H0). There is no heteroscedasticity in the residuals of the regression model (i.e., the variance of the residuals is constant). This suggests that there is insufficient evidence to conclude that there is heteroscedasticity in the residuals of the regression model. Therefore, based on this test, the assumption of constant variance of the residuals (homoscedasticity) holds for the model.

To assess the presence of multicollinearity among the independent variables, this study computes a Variance Inflation Factor for the predictor variables. The demographic factors, age, sex, education, and the source of energy, have a mean VIF of 6.44. The variables for access to finance, bank account, mobile banking, and insurance purchase, have an average VIF of 1, while the variables for employment have an average VIF of 6.62. The mean VIF of 4.69 suggest moderate collinearity, thus insufficient to invalidate the regression models.

4.2.1. Determinants of Vulnerability

The estimated coefficient for the Somali refugee households suggests that on average, their multidimensional vulnerability index (MVI) score is 0.039 units lower than that of the Congolese households (p < 0.05). This indicates a statistically significant difference in the vulnerability levels between the two groups. The units of the MVI reflect overall vulnerability on a continuous scale, where lower scores correspond to less vulnerability. The significant difference may be driven by distinct push factors influencing each refugee population. For instance, while Somalia and Congo have been affected by conflict, the nature of these conflicts, the coping mechanisms of the displaced populations, and their access to support may vary. Somali refugees may have stronger social networks or access to resources compared to their Congolese counterparts, which could explain their lack of vulnerability in the host environment. This emphasizes the role of social networks in influencing the resilience of refugees.

The results indicate that educational attainment generally has a positive effect on reducing vulnerability, though the strength and significance of this relationship vary across different education levels. For instance, the completion of adult education is associated with a reduction in vulnerability by 0.005 units (p < 0.05). The other educational levels, such as Standard/Grade 8 (0.121) and Grade 12 (0.101), show positive, but not statistically significant effects, indicating a trend where higher education is associated with less vulnerability, though the evidence is not uniformly strong. This is explained by the disadvantaged state of refugees to higher-level education. Martin and Stulgaitis (2022) note that only 3% of the refugees enrolled on higher education institutions compared to 38% of gross enrollment.

Regarding the type of energy used for cooking, this study show significant associations with vulnerability. The households using biogas show a positive association, with a vulnerability increase of 0.147 units (p < 0.01), which suggests that while biogas may generally be considered a clean and efficient energy source, its higher cost may limit its use to households with higher incomes, reflecting broader socioeconomic patterns. In contrast, reliance on kerosene is associated with a significant decrease in vulnerability by 2.064 units (p < 0.01), and charcoal use is linked to a reduction in vulnerability by 0.040 units (p < 0.01). The “Other (Specify)” category also shows a significant reduction in vulnerability by 2.057 units (p < 0.01). The results align with the findings of Elrha (2020), who highlight that the use of clean energies like LPG can significantly enhance food security, and reduce pollution among refugees and host communities.

The insights from Elrha (2020) emphasize the importance of energy choices that are socially and economically viable, while maximizing the health, social, and environmental benefits. The findings of this study stress practical feasibility and adoption barriers, while providing alternative sources of energy. While cleaner sources of energy like biogas are recommended, their impact on reducing vulnerability is dependent on the implementation feasibility in the marginalized counties where the refugees reside. It is likely that underlying socioeconomic factors, such as income and access to affordable energy sources, influence the choice of cooking fuel and the level of vulnerability. Further research is needed to explore whether interventions that promote cleaner fuels directly reduce vulnerability or whether the use of such fuels is simply a reflection of broader socioeconomic improvements.

4.2.2. Employment and Vulnerability

The refugees who participated in non-farm business activities in the previous seven days exhibit a 7.16% lower multidimensional vulnerability index (MVI) compared to those who did not engage in these activities (p < 0.01). This finding indicates that engagement in non-farm business activities is associated with less vulnerability, suggesting that such activities may help refugees improve their economic stability and resilience. In addition, involvement in entrepreneurial endeavors outside of agriculture provides a crucial avenue for economic stability and resilience among refugees.

Furthermore, people who engage in their own or family farming activities show a 7.569% lower MVI (p < 0.01). This highlights the pivotal role of agricultural livelihoods in providing food security and stability to displaced populations, particularly when coupled with access to land and resources. Muhangi et al. (2022) confirm that involving refugees in crop production builds their resilience and enhances food security among refugees in Uganda.

Similarly, receiving any form of wage, salary, commission, or payment in kind emerge as a significant mitigating factor against vulnerability. The refugees who received regular payments show a 6.39% lower MVI (p < 0.01). This aligns with the broader economic theories that underscore the importance of a consistent stream of income in bolstering financial security and reducing susceptibility to economic shocks. However, findings by Malaeb and Wahba (2018) show that labor market competition may limit the opportunities among refugees.

4.2.3. Access to Finance and Vulnerability

The household heads with access to a bank account or mobile banking services display a 6.444% and 7.186% lower MVI (p < 0.01), indicating the importance of financial inclusion in enhancing resilience and mitigating economic hardships. This aligns with Heywood and Vaughn (2024) who emphasize the role of financial inclusion in strengthening resilience and reducing reliance on aid. The study stresses the need to address structural and legal issues to achieve meaningful results from financial inclusion.

Additionally, having insurance like the National Hospital Insurance Fund emerges as a critical factor in reducing vulnerability among the refugees. The households with insurance exhibited a 7.66% lower MVI (p < 0.01). The UNHCR (2018) notes the importance of context-based analysis to ensure that insurance schemes available for refugees are sustainable and meet their financial capacity.

In totality, regression analysis underscores the intricate interplay between access to finance, employment, and refugee vulnerability. Economic engagement, financial inclusion, and risk management mechanisms emerge as crucial pillars in mitigating vulnerability and fostering resilience among displaced populations. These findings call for targeted interventions and policies aimed at promoting economic opportunities and expanding access to financial services. Further, policies should strengthen social protection mechanisms to enhance the well-being of refugees worldwide.

5. Discussion

Camp-based refugees face higher levels of vulnerability compared to urban refugees (Chapman, 2021). Addressing the multidimensional nature of these vulnerabilities is important in understanding and addressing them. From this analysis, 97.79% of the refugees’ households in the Kakuma are vulnerable to lower levels of well-being. These vulnerable households have an average deprivation of 68.54% of the total indicators due to issues related to lack of documentation, food insecurity, and inadequate coping mechanisms.

The findings reveal that although the women-headed households are more prevalent compared to the male-headed households, the male-headed households are, on average, more multidimensional and vulnerable. The findings align with the NRC (2017) that the traditional norms favor men, while women continue to face barriers in accessing livelihood assets. The demographics of the household heads show an intersectionality of gendered patterns. In addition, the households headed by older individuals tend to be less vulnerable compared to young individuals. This finding contradicts Strong et al. (2015) who found that older refugees are three times more vulnerable especially due to disability as compared to younger refugees.

Age, level of education, and country of origin significantly influence the level of vulnerability of the refugee households. In particular, school advancement is associated with decreased vulnerability as only 8.76% of the refugees who completed basic education are below the vulnerability cut-off as compared to 11.21% who completed high school. This pronounced drop is particularly alarming given the rising cost of living in Kenya, which renders education-related expenses increasingly unaffordable for the most vulnerable segments of the refugee population. The finding aligns with Klugman et al. (2022) that education is the key in reducing vulnerability, leading to better economic opportunities and health outcomes.

This study confirms that access to finance and employment significantly reduces the level of vulnerability. The results of the study are consistent with the existing literature. For example, Forsen et al. (2016) show a positive relationship between household size and vulnerability. This is mainly because the humanitarian aid is shared among the number of people in a household. However, the current study contradicts the role of aid in reducing vulnerability, noting that aid does not significantly reduce the level of vulnerability, thus there is a need for more sustainable ways towards achieving food security and self-reliance. This study highlights the need for targeted interventions for refugees in Kakuma and the host community in streamlining resource allocation, programmatic support, and policies in the utmost vulnerable areas.

This study finds that the country of origin shapes the intensity of vulnerability. Women originating from Somali are reported to be less vulnerable compared to Congolese women. This is majorly because of the push factors and the cultural norms. However, Flamand et al. (2023) note that the country of origin solely cannot influence the vulnerability of a refugee, but the intersectionality of personal, institutional, and situational factors.

While the traditional sources of energy cause economic degradation and health hazards, this study links the use of biogas with higher vulnerability and kerosene with decreased vulnerability. The findings of Tran et al. (2021) contradict this, noting that traditional biomass fuel exposes women and girls to gender-based violence.

Despite this study providing important highlights on the vulnerability of refugees, it has some limitations. This study focuses on camp-based refugees, and thus the findings might limit the applicability to urban refugees and those in informal settings. The well-being of camp-based refugees is shaped by geographic location, access to livelihood assets, and social networks. However, this study employs comprehensive data, ensuring a representative sample of refugees of different countries of origin, ages, and levels of education. In addition, we conducted this study using broad literature on forced displacement to establish whether the insights from this study align with the general literature.

6. Conclusions and Policy Implications

Analyzing context-based vulnerability is crucial in providing targeted and practical policies. This study seeks to analyze access to livelihood assets and vulnerability to lower levels of well-being in Kakuma. This is achieved by examining the determinants of vulnerability and assessing how access to livelihood assets (employment and finance) influences the vulnerability of this population. This study adopts the Alkire and Santos (2013) methodology to develop the MVI by aggregating the indicators across food resilience, coping mechanisms, and documentation to explain the vulnerability context of this population. The results suggest that the level of education, age, and the country of origin are the key determinants of vulnerability. Further, having a salaried wage, a farm business, and a bank account reduces the vulnerability to lower levels of well-being for refugees.

This study recommends active engagement and awareness for refugees and labor market players on recognizing prior skills for refugees. Many refugees are skilled and competent in different fields; however, they frequently lack the requisite documentation to substantiate these qualifications. Skill acquisition occurs in multiple contexts, with some refugees developing competencies within the confines of the camps, while others obtain these skills in their countries of origin before displacement.

Recent initiatives spearheaded by the International Labor Organization (ILO), in collaboration with the Kenya National Qualifications Authority, aim to address this gap through the implementation of “Recognition of Prior Learning” (RPL). This program seeks to formally recognize and validate refugees’ prior experiences and skills, thereby facilitating their integration into the labor market. A concerted effort from various actors within the Kenyan labor market is essential to ensure that the RPL process is successfully implemented, particularly for those residing in refugee camps.

In developing the MVI, food security indicators were aggregated among those of coping mechanisms and documentation. These results reveal widespread food insecurity in the camp. In 2021, the reduction in food rations for the refugees in Kakuma, as well as in Dadaab and Kalobeyei, is a result of severe funding shortfalls faced by the United Nations World Food Programme (WFP).

As of recent measures, the refugees in these camps are now receiving only 40% of the recommended minimum calorie intake, but in some contexts, this has been specified as a reduction from 60% to 52% of a full ration. This adjustment allows for the WFP to stretch the remaining resources until the end of the year, but it is still far below the minimum daily requirements (Lisanza et al., 2023). With the influx of refugees into the camp, the population is likely to face more severe food insecurity. There have been efforts to educate and empower refugees to garden to improve their diets. The government should integrate refugees into plans to enhance food security and cope with climate change. Providing training on drought-resistant farming would be beneficial to refugees since the camps are based in arid and semi-arid areas. In line with this, the government should empower refugees by providing them with seeds and sustainable water sources. This would increase sustainability, food security, and the overall welfare of the refugees and the host communities.