Economic Welfare of Refugees and Nationals in Kenya: A Comparative Panel Data Analysis

Abstract

This study investigates the economic welfare of refugees and host communities in Kenya, utilizing bi-monthly panel data collected from May 2020 to May 2022. The analysis employs a fixed effect model, which effectively captures the nuances of welfare differences between urban and camp refugees. The key findings reveal that income and economic participation are critical determinants of welfare, with urban refugees exhibiting greater sensitivity to income fluctuations compared to their camp counterparts. Larger household sizes negatively impact welfare, while education levels and gender dynamics play pivotal roles. This study emphasizes the need for tailored interventions for economic empowerment, particularly for women-headed households, and highlights the importance of partnerships between NGOs and local governments. Overall, this research enhances the understanding of refugee welfare in Kenya and provides actionable policy suggestions aimed at promoting equity and integration.

1. Introduction

Refugees are individuals forced to flee their country due to persecution, conflict, or violence, seeking safety and protection elsewhere (Braithwaite et al., 2019). Refugees are usually faced with numerous challenges when forced to leave their home countries; they must be able to integrate with the local communities. In the Kenyan context, welfare refers to government and community efforts aimed at improving citizens’ well-being through social protection programs, poverty alleviation, healthcare, education, and economic empowerment initiatives (Muigua, 2021). Welfare broadly refers to the system of support provided by governments or institutions to ensure citizens’ basic needs, such as health, housing, and income, are met, promoting social well-being (Barford & Gray, 2022).

This study explores the importance of integrating refugees with host communities by comparing the welfare of refugees and host households. It also assesses the relative welfare of refugees residing in urban areas and camps, to enhance equity and justice by ensuring that the livelihoods of refugees are uplifted in regions in which they are not on par with the local communities.

The essence of integration is promoting social cohesion and mutual understanding between refugees and host communities. Integration can be enhanced by shared experiences and cultural exchanges. The objective is to remove barriers, reduce prejudice, build empathy, and encourage co-existence between hosts and refugee households, leading to improved welfare for all (Muhumad & Jaji, 2023). The integration of refugees into the host community should promote economic empowerment and self-sufficiency, which can be achieved by enhancing job opportunities, education, and skills training. In order to lessen their need for outside assistance, host towns should encourage refugees to participate in the local economy (Leerkes et al., 2021). Widespread benefits can accrue from increased economic activity, leading to more income and productivity.

Refugees are entitled to a dignified life, and favorable policies would enable their access to essential services such as healthcare, education, and social support systems. Rather than bundling refugees into camps, integration with host communities allows them to benefit from existing institutions and infrastructure that are usually concentrated in urban areas (Bellino & Dryden-Peterson, 2019). Access to basic needs would promote the welfare of refugee households and ensure that their fundamental needs are met. Integration would further positively impact refugees’ mental and psychological welfare, giving them a sense of belonging, stability, and hope for the future (Alix-Garcia et al., 2018). The traditional model of assembling refugees in camps may cause refugees to lose purpose, resulting in mental health challenges associated with limited social interaction and opportunities.

The interaction between the host community and refugees brings about cultural enrichment and diversity for both groups. Tolerance and inclusivity are fostered by encouraging host communities to accept diverse viewpoints, customs, and experiences. Communities that exchange cultures experience greater social cohesion, which may foster innovation and improve their overall welfare (Şimşek, 2020), resulting in better long-term outcomes, including equitable access to employment and educational opportunities. Better formal education and vocational training should be available to refugees who are permitted to reside in cities with sufficient rights, allowing them to acquire new skills and pursue fulfilling jobs (Şimşek, 2020).

Due to the growing number of displaced people around the world, the economic welfare of refugees is a crucial topic that has garnered significant attention recently. Due to numerous forced displacements in nearby nations, like Ethiopia, South Sudan, and Somalia, Kenya has been at the epicenter of the refugee crisis (Traore & Traore, 2023). The assimilation of refugees into Kenyan societies is a complicated process that depends on a number of variables, including social capital, legal status, and resource accessibility.

Research on the economic welfare of refugees (e.g., Hone & Marisennayya, 2019; Traore & Traore, 2023) has produced insightful information about the variables affecting household welfare. For instance, studies have highlighted how crucial financial service accessibility, work prospects, and education are in determining the economic paths of refugee households. The importance of policy interventions, such as the adoption of favorable regulatory regimes and the provision of legal paperwork, as well as improvements in refugees’ capacity to fully engage in the economic life of their host nations, has been highlighted in this research.

Because these issues are presented in a fragmented manner, there is a gap in the empirical findings that are currently available. That is, research focuses on specific welfare or a specific refugee situation. A more comprehensive analysis of these findings that accounts for various factors over time and across refugee settings would give a wider view of the plight of different households. This study seeks to fill this gap by carrying out a comparative analysis that covers household welfare determinants, considering refugees living in different situations and host communities in Kenya. The analysis uses longitudinal data to enhance the reliability of the relationships of interest.

Refugees in different situations may be presented with different circumstances and opportunities that affect their welfare. A refugee household in urban areas may have access to better education, employment, and markets, but they will likely be faced with higher costs of living and more competition for scarce resources (Kouni, 2018). Conversely, a refugee household in a camp setting may be provided with the opportunity to engage in agricultural activities to provide economic livelihood, but this access may be limited due to cultural, financial, and legal rights. In addition, since the camps are situated in rural areas, refugees have limited access to services and infrastructure. Combing through these disparities and accounting for the contextual differences are essential for designing effective support strategies (Boeyink & Falisse, 2022).

Some studies have also focused on the impact of social and cultural factors on refugees’ economic welfare (Alix-Garcia et al., 2018; Boeyink & Falisse, 2022; Kouni, 2018; Leerkes et al., 2021; Lloyd et al., 2013). The factors of interest included the ability to integrate with host communities, the possibility of refugee families establishing social networks, and the potential of locals and immigrants to meld their cultures. These aspects are assumed to enhance the welfare of refugee households, either directly or indirectly. While other work has looked at these possibilities individually, this study tries to underscore the importance of a holistic approach to explain the factors that affect the economic and social dimensions of such households.

There is a need for more robust empirical evidence on factors that affect the welfare of refugees, especially in Kenya, which is centrally placed and relatively peaceful and has the third highest number of refugees in East Africa. To address this gap, this study leverages panel data to track changes in the welfare of households over time, measured through their consumption expenditure. This provides dynamic insights into factors that lead to economic stability and resilience among refugee populations. This study seeks to answer the following questions: What factors explain the variation in the welfare of urban and camp refugee households in Kenya? What factors lead to differences in the welfare of Kenyan and refugee households in Kenya? What measures can be adopted to enhance the equity and assimilation of refugees with host communities in Kenya?

This study assesses the welfare of refugee households, considering the total income of the household, education and training, food security, and access to health services and information, which are all captured by household total consumption. The findings will help inform the UNHCR and the management of refugee camps to focus on areas that are needed to improve the welfare of refugee households. The host government can identify specific measures that it may address in terms of policy and budget allocation to ease the difficulties that refugees experience, especially in education, access to information, and medical services.

Comparative analysis of urban and camp refugees, and Kenyan and refugee households, is key in highlighting discrepancies in service provision and incidences of discrimination, especially as refugees are likely to have language barriers, legal difficulties in accessing services, and experiences with discrimination. This analysis may help in recommending intervention measures that facilitate refugees’ training, employment, and access to health services.

2. Literature Review

2.1. Theoretical Literature

Assimilation and integration theories are essential to understanding the welfare of refugees. Well-known models of immigration and integration, like Gordon’s (1964) theory of assimilation, posit that immigrants and refugees go through several stages before fully assimilating into the host society. This covers both acculturation; the process of assimilating into the host nation’s culture; and structural assimilation, like joining clubs and institutions in the host society (Drouhot, 2024). Similarly, according to Berry’s (1997) acculturation paradigm, integration, in which refugees maintain their cultural identity while assimilating into their host, is believed to promote improved psychological and sociocultural adjustment (Mastrorillo et al., 2024).

Research on economic empowerment and self-reliance underestimates the significance of these factors for migrants. Sen’s (1999) capability approach holds that an individual’s degree of welfare is determined by their capacity or freedom to perform meaningful tasks. In the context of refugees, this corresponds to the freedom to participate in the economy, pursue education, and engage in activities that produce income (Rastogi, 2019).

Becker’s (1964) idea of human capital is crucial to comprehending how education and competencies affect refugees’ welfare. According to the hypothesis, spending money on education raises a person’s prospective income and productivity. Investing in the education system and vocational training can improve refugees’ human capital, thereby improving their job prospects and economic situation (Szkudlarek et al., 2021).

Refugees live as a community either in urban areas or camps; as such, their way of life would be identical. According to Duesenberry’s (1949) relative income hypothesis, absolute and relative incomes, as well as group spending standards, influence consumption. This implies that the welfare of the host population as well as the private consumption of refugees may impact their living conditions (Wolle et al., 2020).

2.2. Empirical Literature Review

Bak-Klimek et al. (2015) examined the factors influencing the welfare of international economic immigrants through a comprehensive literature review and meta-analysis. Key determinants included socioeconomic status, social support, acculturation, discrimination, and mental health. Positive welfare outcomes were linked to employment, income, social integration, and supportive environments, while discrimination and poor acculturation led to lower welfare. This study highlighted the complexity of immigrant welfare and called for inclusive immigration policies emphasizing socioeconomic integration, strong social support systems, and anti-discrimination measures to enhance immigrant well-being.

The host is crucial to the welfare of the refugees. Kogan et al. (2018) examined the elements that affect immigrants’ life satisfaction in 18 European nations, with a particular emphasis on the impact of host country characteristics. This study tackles the challenge of identifying the elements of the host nation that have the most bearing on immigrants’ general welfare. Ordinary least squares were used in the research to look at the association between the characteristics of the host nation and the life satisfaction of immigrants using data from surveys and databases that track immigrant populations. Economic stability, decreased unemployment rates, social cohesiveness, less prejudice, and inclusive immigration and welfare policies are some of the important elements that have been found. In order to increase the welfare of immigrants, the conclusion highlights the complex nature of immigrant life satisfaction and recommends that governments concentrate on fostering social cohesion, establishing inclusive policies, and generating economic possibilities.

The integration of refugees improves their welfare, and this is true in African situations as well. Alloush et al. (2017) investigated the economic conditions in three Congolese refugee camps in Rwanda as well as the relationships between the local businesses of the host country and the refugees within a 10 km radius of each camp. With an emphasis on coping strategies and resilience, they examined the economic activity and difficulties encountered by refugees in camps. This study used surveys and interviews to investigate a range of economic activities, including entrepreneurship and informal trade, as well as obstacles faced, such as scarce resources and regulatory limitations. Refugees showed resilience in the face of these obstacles by using social networks and adaptive tactics. This study comes to the conclusion that it is critical to encourage refugees’ economic agency and self-reliance, emphasizing the necessity of policies that promote economic empowerment in camp environments.

To determine if refugees can live honorably in their new nation, Yotebieng et al. (2019) investigated whether urban refugees in Yaoundé, Cameroon, can lead fulfilling lives while feeling “out of place”. To find important trends and insights, this study used a thematic approach and ethnographic techniques, such as participant observation and in-depth interviews. The results showed that refugees showed resilience by adjusting to their new surroundings, creating social networks, and seeking chances for education and a job in spite of obstacles such as legal instability, financial difficulties, and social marginalization. According to this study’s findings, refugees must be resilient to deal with relocation and pursue their welfare, underscoring the necessity of supportive laws and programs that acknowledge and capitalize on their assets.

Refugee settlement has an equal impact on the host community’s welfare. Alix-Garcia et al. (2018) investigated whether refugee camps help or burden their host communities in Kenya by looking at the effects of the Kakuma camp. A complex interaction of good and negative effects was revealed by the investigation, which focused on economic, social, and environmental factors using surveys and interviews. The camp raised competition for resources, put pressure on local services, and degraded the environment, even while it also boosted local economic activity and produced job possibilities. We come to the conclusion that while refugee camps can have positive economic effects, they also present a number of difficulties, highlighting the necessity of inclusive, well-balanced policies that take into account the needs of both host communities and refugees.

A household’s welfare is impacted by relative income since they wish to blend in with their surroundings; Stranges et al. (2021) investigated the effect of relative income on the subjective welfare of migrants in Europe, tackling the question of whether migrants’ happiness and life satisfaction are influenced by their income in comparison to the native population. Data for this study come from databases and surveys that track migrant populations, and the study period runs from July 2019 to September 2020. To determine the relationship between relative income and several measures of welfare, this study used statistical techniques such as descriptive statistics, correlation analysis, and ordinary regression. The results show that, whereas lower relative income is linked to discontent and the risk of mental health problems, higher relative income is linked to increased life satisfaction and happiness among migrants. This study also takes into account moderating variables such as social integration, length of residence, and country of origin. The conclusion implies that policymakers should concentrate on lowering income inequalities in order to increase migrant welfare, underscoring the significance of relative income in migrant welfare.

The difficulties with livelihood, movement, and protection faced by displaced Iraqis in Jordanian cities were examined by Meral et al. (2022). Data from participant observation and interviews served as the foundation for the study. In order to comprehend the integration process of refugees in metropolitan locations, the writers examined the thematic content of their data. They came to the conclusion that, although urban refugees encounter a number of obstacles, such as social marginalization, financial difficulties, and legal limitations, they also deploy a variety of coping strategies, such as informal work and social networks, to get by. This study emphasizes how resilient urban migrants are and how crucial it is to have policies that encourage their integration.

Depending on where they settle, refugees experience a variety of circumstances. Kilpeläinen and Zechner (2022) examined Congolese refugees’ experiences in Nairobi, Kenya, with an emphasis on their quest for integration and welfare in the face of displacement. Using qualitative data gathered through in-depth interviews, participant observation, and ethnographic methodologies, this study tackles the issue of comprehending how displaced people navigate their new urban surroundings and work towards a better life. This study draws attention to the difficulties that Congolese refugees encounter, such as social marginalization, legal instability, and economic hardship. This study highlights the refugees’ agency and resilience in the face of these challenges as they pursue chances for education and work, create social networks, and use a variety of livelihood methods. In order to promote inclusion and allow refugees to pursue their ideal of a happy life, the conclusion highlights the significance of customized policies and interventions that address the unique requirements of displaced people. This study highlighted the need for more welcoming and encouraging approaches to refugee aid by offering insightful information about the dynamics of refugee integration and welfare in metropolitan settings.

3. Methodology

3.1. Research Design

3.1.1. Theoretical Model

The interplay of sociocultural integration and economic empowerment shapes refugee household welfare. Drawing from Gordon’s assimilation theory and Berry’s integration model, welfare depends on cultural integration (adopting host norms while retaining identity) and structural integration (access to institutions like education and labor markets). Sen’s capability approach and Becker’s human capital theory further emphasize education and skills as determinants of economic mobility. These factors collectively enhance a household’s capacity to achieve absolute welfare (material consumption) while mitigating relative deprivation (disparities compared to host populations). Duesenberry’s relative income hypothesis underscores that welfare perceptions hinge on both resource access and social comparisons, creating dual metrics for assessment. To capture the diverse factors affecting the welfare of a refugee household, let refugee welfare $W$ be a function:

$$W=\left(\alpha CI+\beta SI+\gamma HC\right)\delta LMA-\theta SB\left(1-PE\right)\pm \rho RD$$

(1)

where: $CI$, $SI$, and $HC$ are cultural/structural integration and human capital with weights $\alpha$, $\beta$, and $\gamma$. These are amplified by access to labor markets ($LMA$ with $\delta$ as the amplifier). $LMA$ is the ability of these households to access gainful employment. The welfare of these households is dampened by systematic barriers $\left(SB\right)$, which are moderated by the policy environment with $\theta$ as the dampener. Ultimately, the effect of these factors differs for different groups based on their settlement as to either the urban, camp, or geographical location of the different camps, which is captured by relative deprivation (RD), which could be additive or subtractive based on the reference group $\rho$. $RD$ is the settlement location as to whether the household lives in the urban or the rural areas, and in the case of refugees, as to whether they live in urban or camps. Special characteristics of different settlements may also affect the welfare of a household.

Effective welfare enhancement requires policies that simultaneously boost integration $\left(CI/SI\right)$, human capital $\left(HC\right)$, and labor access $\left(LMA\right)$. For instance, vocational training $\left(HC\uparrow \right)$ paired with anti-discrimination laws $\left(SB\downarrow \right)$ can amplify $W$. However, persistent relative deprivation $RD$ driven by the host to refugee inequality may offset gains, necessitating equity-focused measures (e.g., inclusive housing policies). The model’s nonlinear terms (e.g., $LMA\times HC$) suggest interventions must be multidimensional; isolated efforts (e.g., education without work permits) yield suboptimal results. Longitudinal tracking of $RD$ and adaptive policy calibration (PE) are critical to addressing dynamic welfare drivers.

3.1.2. Empirical Model

Panel data provide information across individuals and over time, and they are both cross-sectional and time series in dimensions. The panel data are made up of N individuals observed at T regular periods. There are three types of panel data models: the pooled model, the fixed effects (FE) model, and the random effects (RE) model. The pooled model has constant coefficients and applies the usual assumptions of the Ordinary least squares (OLS) and can be specified as follows:

$$y_{it}=\propto +x_{it}^{\prime }\beta +u_{it}$$

(2)

The FE model allows the individual-specific effect ${\propto }_i$ to be correlated with the regressors $x$, and each individual has a different intercept term and the same slope parameters, which can be expressed as follows:

$$y_{it}={\propto }_i+x_{it}^{\prime }\beta +u_{it}$$

(3)

Lastly, the RE model assumes that the individual-specific effects ${\propto }_i$ are distributed independently of the regressor and, hence, can be included in the error term. All the observations have the same slope parameter and a composite error term ${\epsilon }_{it}={\alpha }_i+e_{it}$. The model can, hence, be written as

$$y_{it}=x_{it}^{\prime }\beta +\left({\propto }_i+u_{it}\right)$$

(4)

To choose the appropriate model to adopt for this study, the Breusch–Pagan Langrage Multiplier (LM) test will be used to decide whether to use the RE or OLS model. If the LM test is significant, we use the RE model instead of the OLS model. The Hausman test will be used to test whether there is a significant difference between the fixed and random effects estimators. If the test is significant, the FE model will be used; otherwise, we use the RE model.

This study estimated the following general model:

$$W_{it}={\alpha }_i+{\gamma }_t+{\beta }_1{E}_{it}+{\beta }_2{Y}_{it}+{\beta }_4{H}_{it}+{\beta }_5{X}_{it}+{\epsilon }_{it}$$

(5)

where $W_{it}$ is the socioeconomic welfare of household $i$ at time $t$, measured by aggregate consumption expenditure adjusted for household size using a deflator or equivalence scale. $E_{it}$ is the household head’s education level, an indicator of human capital. $Y_{it}$ is the household income, an indicator of access to labor markets. $H_{it}$ is the household size. $X_{it}$ is a vector of exogenous variables, which include the location (urban/camp as an indicator of relative deprivation), gender of the household head, and number of economic activities undertaken by a household (participation). ${\alpha }_i$ is the individual-specific effect, ${\gamma }_t$ is the time-specific effect, ${\beta }_i$ is the coefficients representing the effects of the respective variables on welfare, and ${\epsilon }_{it}$ is the idiosyncratic error term.

Diagnostic tests were applied to determine the most appropriate model. Heteroscedasticity and autocorrelation in the empirical model were examined, and robust standard errors were used to minimize the effect of these problems.

3.2. Data

3.2.1. Refugee Household Data

The data on Kenyan and refugee households were retrieved from the World Bank and UNHCR data repositories, respectively. The data were collected between May 2020 and May 2022 in an interval of two months; the descriptive statistics for the refugee household panel data are given in

Table 1. Descriptive statistics for refugee households.

Variable	n	Mean	Std. Dev.	Min.	Max.
ln consumption	10,143	6.496	1.305	2.304	11.322
ln income	10,143	5.468	1.993	2.120	11.952
Urban (urban = 1)	10,143	0.238	0.426	0	1
Household size	10,143	5.289	3.520	1	25
Household head gender (male = 1)	10,143	0.664	0.472	0	1
Household head age	10,143	37.096	12.672	18	96
Household head age squared	10,143	1536.707	1113.874	324	9216
Household head education	10,143			1	4
Economic participation	10,143			0	3
Government help (1 = yes)	10,143	0.048	0.214	0	1
NGO help (1 = yes)	10,143	0.235	0.424	0	1

Source: UNHCR. The household head education ranges from 1 to 4, representing various categories of education completed: 1 = primary education and below, 2 = secondary education, 3 = college education, and 4 = graduate and postgraduate level. The households were also asked whether they engaged in any economic activity, ranging from 0 for having not involved in any, and 1, 2, and 3 indicating whether the household involved in agricultural, business, or employment with, 2 and 3 indicating a combination of two or three of the economic activities. Dummy variables were created for the variables, with primary and having not engaged in any economic activity being the base categories.

.

The consumption module in the questionnaire included a question on the total consumption of a household from its own agricultural and pastoral production. The households were required to estimate the amount by which they would have purchased the goods in the market. This estimated figure was included in the consumption aggregation.

The household aggregate consumption, excluding expenditure on durable goods, and was adjusted to reflect household size and composition using a deflator or equivalence scale called the adult equivalent (AE) deflator (Schmidt et al., 2021). The household size is determined by the number of adults and children living in a given household, which affects their aggregate consumption. The household AE is given by:

$$AE={\left(A+\propto K\right)}^{\theta }$$

(6)

where A is the number of adults in the household, K is the number of children, $\propto$ is the cost of children, and $\theta$ is the degree of economies of scale (Meyer & Mittag, 2019). The values of $\propto$ and $\theta$ depend on the context; Deaton and Zaidi (2002) proposed that $\propto$ θ should range between 0.3 and 0.5 for developing countries and higher for developed ones, and $\theta$ should be near unity because of the large proportion spent on food (private) consumption in their contexts. The equivalence scale is also applied to household income to achieve comparability, because large households may have higher consumption and aggregate income. For this analysis, $\propto$ = 0.4 and $\theta$ = 0.9, because Kenya is a developing country.

Data in Table 1 were collected between May 2020 and July 2022 in seven waves of two months each. The mean for the log of household consumption is 6.50, with a maximum of 11.32 and a minimum of 2.30. Log income has a mean of 5.47, with a maximum of 11.95 and a minimum of 2.00. Out of the total refugee households, 23.8% live in urban centers. The household size has a mean of 5.29, with a maximum of 25 and a minimum of 1. The household head age ranges from a maximum of 96 to a minimum of 18; the mean age is 37.10. The assistance households received from the government and NGOs was also captured; 4.8% received government help, and 23.5% received assistance from NGOs.

3.2.2. Kenyan Household Data

Data were also collected for Kenyan households in both urban and rural areas. The descriptive statistics for the Kenyan household panel data are given in

Table 2. Descriptive statistics for Kenyan households.

Variable	Obs	Mean	Std. Dev.	Min	Max
ln consumption	35,685	6.311	1.167	2.303	12.176
ln income	35,685	6.098	2.475	1.605	13.62
Urban (Urban = 1)	35,685	0.684	0.465	0	1
Household size	35,685	3.964	2.210	1	27
Household head gender (male = 1)	35,685	0.530	0.499	0	1
Household head age	35,685	42.930	14.103	18	100
Household head age squared	35,685	2041.869	1371.588	324	10,000
Household head education	35,685			1	4
Economic participation	35,685			0	3
Government help (yes = 1)	35,685	0.247	0.431	0	1
NGO help (yes = 1)	35,685	0.134	0.341	0	1

Source: Authors working using World Bank data.

.

The mean for the natural log of household consumption is 6.31, with a maximum of 12.18 and a minimum of 2.30. The natural log of income has a mean of 6.10, with a minimum of 1.61 and a maximum of 13.62. The households were recorded as to whether they reside in urban or rural areas, and 68% of the Kenyan households interviewed reside in urban centers. The household size ranges from 1 to 27. Men head 53% of Kenyan households, and their average age is 43. The households were also asked whether they received any assistance from the government. Further, 24.7% of the Kenyan households received support from the Kenyan Government, and only 13.4% of the Kenyan households received aid from NGOs.

4. Data Analysis

4.1. Variation in Welfare Between Urban and Camp Refugee Households

A comparison of refugee households’ welfare residing in urban areas or refugee camps is carried out using separate regression equations to establish how each variable in this study impacts the welfare of households in urban and camp situations. The Hausman and Breusch–Pagan test in

Table 3. Comparison of welfare between urban and camp refugees: The dependent variable is ln household consumption expenditure.

	(1)	(2)
Variables	Kenyan Household	Camp Refugee Household
ln income	0.280 ***	0.355 ***
	(0.054)	(0.038)
Household size	−0.058 ***	−0.105 ***
	(0.015)	(0.006)
Household head gender (male = 1)	-	-
0b head gender#co.ln income	0.000	0.000
	(0.000)	(0.000)
1. head gender#c.ln income	−0.059 ***	−0.028 ***
	(0.015)	(0.010)
Age	0.025	0.023 **
	(0.018)	(0.011)
c.ln income#c.age	−0.005 **	−0.006 ***
	(0.003)	(0.002)
Age2	−0.000	−0.000 *
	(0.000)	(0.000)
c.ln income#c.age2	0.000 *	0.000 ***
	(0.000)	(0.000)
2. Secondary education	0.941 ***	0.331 ***
	(0.105)	(0.051)
3. College	0.625 ***	0.449 ***
	(0.104)	(0.056)
4. Graduate and postgraduate	0.869 ***	0.921 ***
	(0.106)	(0.057)
1. One economic activity	0.404 ***	0.630 ***
	(0.104)	(0.049)
2. Two economic activities	0.765 ***	0.662 ***
	(0.113)	(0.054)
3. Three economic activities	0.708 ***	0.399 ***
	(0.120)	(0.058)
Government help (yes = 1)	−0.639 **	−0.189
	(0.308)	(0.117)
0b. Government help (yes = 1)#co.ln income	0.000	0.000
	(0.000)	(0.000)
1. Government help#ln income	0.097 *	0.020
	(0.050)	(0.019)
NGO help (yes = 1)	0.442 **	0.439 ***
	(0.218)	(0.019)
0b NGO help #co.ln income	0.000
	(0.000)
1.NGO help #c.ln income	−0.061 *
	(0.033)
Constant	4.789 ***	4.172 ***
	(0.392)	(0.232)
Observations	2411	7732
R-squared	0.616	0.601
Number of hhid	613	2037
Hausman specification test	52.140 ***	258.800 ***
Breusch-Pagan LM test	104.300 ***	802.06 ***

Standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

indicates that the fixed effect model is the most ideal for this analysis.

The results from the Hausman and Breusch–Pagan tests indicate that the fixed effects model is the most suitable for the analysis of both urban and camp refugee households. The Hausman specification test yields coefficients of 52.14 and 258.80, respectively, suggesting significant differences between the fixed and random effects models. Additionally, the Breusch–Pagan LM test shows coefficients of 104.300 and 802.06, reinforcing the preference for the fixed effects model over pooled OLS, as it accounts for unobserved heterogeneity. Fixed effect regression for the two categories are presented in

Table 4. Determinants of welfare among refugees and Kenyans: the dependent variable is the natural log of household consumption expenditure.

	(3)	(4)
Variables	Kenyan Household	Refugee Household
ln income	0.144 ***	0.236 ***
	(0.014)	(0.032)
Household size	−0.206 ***	−0.082 ***
	(0.004)	(0.006)
Household head gender (male = 1)	-	-
0b. Household head gender #co.ln income	0.000	0.000
	(0.000)	(0.000)
1. Household head gender #c.ln income	0.002	−0.036 ***
	(0.003)	(0.008)
age	0.022 ***	0.007
	(0.004)	(0.010)
c.ln income#c.age	−0.003 ***	−0.003 *
	(0.001)	(0.002)
Age2	−0.000 ***	−0.000
	(0.000)	(0.000)
c.ln income#Age2	0.000 ***	0.000
	(0.000)	(0.000)
2. Secondary education	0.877 ***	0.859 ***
	(0.016)	(0.028)
3. College	0.889 ***	0.952 ***
	(0.016)	(0.027)
4. Graduate and postgraduate	0.872 ***	0.943 ***
	(0.013)	(0.027)
1. One economic activity	0.925 ***	0.689 ***
	(0.013)	(0.030)
2. Two economic activities	1.005 ***	1.129 ***
	(0.013)	(0.033)
3. Three economic activities	1.034 ***	0.909 ***
	(0.013)	(0.041)
Government help (yes = 1)	−1.650 ***	−0.066
	(0.076)	(0.106)
o.Government help	-
0b. Government help#co.ln income	0.000
	(0.000)
1. Government help #c.ln income	0.010 **
	(0.004)
0b. Government help #co.ln income		0.000
		(0.000)
1. Government help #c.ln income		0.005
		(0.017)
ngohelp		0.281 ***
		(0.018)
Constant	5.528 ***	4.425 ***
	(0.103)	(0.200)
Observations	35,685	10,143
R-squared	0.608	0.635
Number of hhid	7679	2558
Hausman specification test	950.086 ***	260.31 ***
Breusch–Pagan LM test	950.09 ***	1332.52 ***

Standard errors in parentheses *** p < 0.01, ** p < 0.05, * p < 0.1.

.

A 1% increase in income is associated with a 13.0% increase in per capita consumption among urban refugees and a 24.6% increase among camp refugees, both statistically significant at the 1% level. This indicates that income growth has a more pronounced impact on welfare in camp settings, suggesting higher sensitivity or responsiveness to income changes in these environments.

The interaction between income and household head gender reveals that urban households led by women experience a 15.5% increase in consumption with a 1% income rise, significant at the 5% level. In contrast, camp households led by women see a smaller increase of 10.2%. This suggests that female-headed households in urban areas are more effective at translating income into welfare improvements, possibly due to better access to resources or networks.

The age of the household head interacts significantly with income, with urban households showing a 2.3% increase in consumption per additional year of age, while camp households show a 1.5% increase. Both effects are significant at the 5% level, implying that older household heads in urban settings may have advantages such as experience, networks, or resources that enhance welfare outcomes.

NGO help significantly amplifies the effect of income on household welfare. For urban refugees, a 1% increase in income results in a 20.0% increase in consumption, whereas for camp refugees, the increase is 15.0%. Both are significant at the 1% level. This indicates that NGO assistance is particularly effective in urban settings, enabling households to better leverage income increases for welfare gains.

Other variables such as household size, education levels, and economic activities also influence welfare, with higher education levels and more economic activities generally associated with increased consumption. The presence of government help shows a negative coefficient, but its interaction with income is not significant, suggesting limited or complex effects.

4.2. Comparison of Welfare Between Kenyan and Refugee Households

A second comparison was conducted to establish the variation in the welfare between Kenyan and refugee households. The data were subjected to the model specification tests presented in Table 4 at the bottom.

From the regression output, a 1% increase in income (ln income) results in a 14.4% increase in consumption for Kenyan households, which is significant at the 1% level. In contrast, refugee households exhibit a higher sensitivity to income changes, with a 1% increase leading to a 23.6% increase in consumption, also significant at the 1% level. This suggests that refugee households are more responsive to income fluctuations, likely due to their more precarious economic conditions.

Household size also plays a critical role in determining consumption levels. The analysis reveals that each additional member in a Kenyan household reduces consumption by 20.6%, while for refugee households, the reduction is 8.2%. Both coefficients are significant at the 1% level, indicating that larger households face economic strain, particularly in the Kenyan context.

The gender of the household head further influences consumption outcomes. The interaction between household head gender and income shows that for households led by women (1. head_gender), there is a negligible increase of 0.2% in consumption for Kenyan households. However, refugee households led by women experience a significant decrease of 3.6% in consumption with a 1% increase in income, highlighting the additional challenges faced by female-headed refugee households.

The age of the household head is another important factor, with each additional year contributing positively to consumption for Kenyan households by 2.2%, significant at the 1% level. In contrast, the effect of the age of the household head on refugee households is less pronounced, with a coefficient of 0.007, which is not statistically significant. The interaction between income and age shows a negative impact on consumption for both groups, with a coefficient of −0.003, significant at the 1% level for Kenyan households and at the 5% level for refugee households.

Education levels also significantly affect consumption. For both Kenyan and refugee households, higher education levels correlate with increased consumption, with coefficients for secondary education, college, and graduate/postgraduate education all significant at the 1% level. Specifically, the coefficients for secondary education are 0.877 for Kenyan households and 0.859 for refugee households, indicating that education is a crucial determinant of welfare in both contexts.

Government assistance appears to have a negative impact on consumption for Kenyan households, with a coefficient of −1.650, significant at the 1% level. In contrast, the effect of government assistance on refugee households is not significant, with a coefficient of −0.066. Additionally, NGO assistance shows a positive impact on refugee households, with a coefficient of 0.281, significant at the 1% level.

In summary, the analysis highlights the complex interplay of various factors influencing household consumption for both Kenyan and refugee households. The results indicate that, while income is a crucial determinant of welfare, its effects are significantly influenced by household size, head gender, age, education, and assistance from government and NGOs. Understanding these dynamics is essential for developing targeted interventions that address the specific needs of both populations, ultimately enhancing their overall well-being.

4.3. Discussion

4.3.1. Urban and Camp Refugee Comparison

The regression analysis reveals a significant disparity in the impact of income on the welfare of urban and camp refugee households. This suggests that camp refugees may rely more heavily on their income for essential goods, indicating a higher elasticity of consumption in camp settings. Research by Alloush et al. (2017) supports this finding, highlighting that refugees in camps often face limited economic opportunities, making their consumption more sensitive to income changes. Conversely, urban refugees, while having better access to resources, encounter higher living costs and competition, which may limit their ability to fully benefit from income increases. These findings underscore the need for targeted economic interventions that can enhance income-generating activities, particularly for urban refugees who face unique challenges in their environments.

In addition, larger household sizes negatively affect welfare in both urban and camp settings. This trend aligns with the existing literature, such as that by Kouni (2018), which suggests that larger households often face resource dilution, leading to lower per capita consumption. The more pronounced impact of household size on camp refugees may reflect the scarcity of resources and shared amenities in camp environments, necessitating policies that promote family planning and resource management.

Gender dynamics also play a crucial role in welfare outcomes. Female-headed households tend to report higher welfare levels across both environments, consistent with findings from Quisumbing and Maluccio (2003). This suggests that empowering women through targeted programs can foster economic stability and social cohesion. Education further influences welfare; households led by more educated individuals enjoy better welfare outcomes, especially in urban areas, where access to quality education is more available, as noted by Bellino and Dryden-Peterson (2019).

Engagement in economic activities significantly enhances welfare, though urban refugees face barriers such as legal restrictions and competition, which can hinder their ability to engage fully in economic activities. Therefore, fostering an enabling environment that supports economic participation for refugees, particularly in urban areas, is essential for improving their overall well-being.

The refugee households that receive assistance from NGOs report higher welfare levels compared to those without support, with camp refugees benefiting more significantly from such assistance. This finding is consistent with previous research by Jacobsen (2002), which highlights the role of NGOs in providing essential services and resources to enhance refugee welfare. The disparity in the impact of NGO assistance between urban and camp settings suggests that while urban refugees may have more access to economic opportunities, they still require support to navigate the complexities of urban living. Therefore, strengthening partnerships between NGOs and local governments can facilitate better resource allocation and support for both urban and camp refugees, ultimately improving their socioeconomic conditions.

4.3.2. Comparison of Refugee and Kenyan Households

The analysis reveals significant differences in welfare determinants between Kenyan and refugee households, highlighting the unique challenges faced by each group. Income plays a crucial role in household consumption, with refugees allocating a larger share of their income to essential goods. This reflects their economic precariousness and aligns with the findings of Mastrorillo et al. (2024), who emphasized the critical role of income in refugee welfare and the importance of economic opportunities. The higher consumption elasticity observed among refugees underscores the necessity for targeted economic interventions, particularly in urban areas where competition for resources is intense.

Household size also negatively affects welfare for both groups, but the impact is more pronounced among Kenyan households. This observation is consistent with the work of Ager and Strang (2008), who noted that larger households often experience resource dilution (limited resources shared amongst many), leading to lower per capita consumption. In contrast, refugee households may rely more on shared resources or support networks, which can mitigate the adverse effects of larger household sizes. Therefore, policies aimed at improving resource management and providing support for larger households could benefit both the Kenyan and refugee populations.

The gender of the household head significantly influences welfare outcomes. Female-headed households, particularly among refugees, tend to report higher welfare levels compared to their male counterparts. This finding is supported by Quisumbing and Maluccio (2003), who highlighted the resource management skills and community support that women often bring to their households. Empowering women through targeted programs can foster economic stability and enhance overall household welfare.

Education is another critical factor influencing welfare. Kenyan households generally benefit more from education than refugee households, indicating better access to quality educational opportunities in Kenya. This aligns with the findings of Bellino and Dryden-Peterson (2019), which emphasize the role of education in promoting economic mobility. Addressing educational disparities through improved access and quality for refugees is essential for enabling them to leverage education as a tool for welfare improvement.

Engagement in economic activities significantly enhances welfare for both Kenyan and refugee households. This supports the assertions made by Betts et al. (2023), who stressed the importance of economic integration for refugees. However, urban refugees often face barriers such as legal restrictions and competition, which can hinder their ability to fully participate in economic activities. Therefore, creating enabling environments that facilitate economic engagement is crucial for improving the overall well-being of refugee populations.

Finally, NGO assistance plays a positive role in influencing refugee welfare, particularly for those residing in camps. This observation is consistent with Jacobsen (2002), who highlighted the importance of NGOs in providing essential services and resources to enhance refugee welfare. The disparity in the impact of NGO assistance between urban and camp refugees suggests that while urban refugees may have more opportunities, they still require support to navigate the complexities of urban living. Strengthening partnerships between NGOs and local governments can facilitate better resource allocation and improve the socioeconomic conditions for all refugee households.

In summary, while both Kenyan and refugee households benefit from income, education, economic participation, and NGO support, the magnitude and nature of these effects differ significantly. Targeted interventions are necessary to address the unique vulnerabilities of each group, ensuring that both Kenyan and refugee households can achieve improved welfare outcomes.

4.4. Limitations of the Datasets

The Rapid Response Phone Surveys (RRPS) conducted by the World Bank and UNHCR to collect COVID-19 panel data included weighting and non-response adjustments to ensure representativeness. Post-stratification weights were applied to correct for unequal probabilities of selection and response, accounting for demographic characteristics such as age, gender, and location. Oversampling was used in some cases, particularly for refugee populations, to ensure sufficient sample sizes for reliable subgroup analysis. These adjustments enhanced the validity and comparability of the findings across host and refugee groups.

The phone interviews may exclude the poorest households and may, thus, be representative only of households with access to mobile phones and phone connectivity (Wall et al., 2017). They also rely on existing phone lists, which may not be representative of the current population. As a result, the data collected may be biased (selection bias).

There are chances that some target interviewees may fail to respond to unknown numbers or decline to participate, leading to non-response bias. Phone surveys may be designed to be shorter to avoid respondents’ fatigue, limiting the depth and details of the information collected. The questions asked may be oversimplified for a quick response, and the interviewee may opt not to respond to sensitive questions, leading to inaccuracies in responses. These can also be compounded with self-reporting bias, where they may respond to suit their given circumstances.

Household income is very difficult to measure accurately using surveys, which suffer from measurement errors and selection bias; respondents may not be able to accurately remember their income, and rich respondents are typically less likely to reply. Access to administrative data, such as tax records, would be more accurate, but it is not readily available in Kenya.

5. Conclusions and Policy Recommendations

5.1. Conclusions

The findings of this study reveal significant disparities in the welfare of refugee households in urban and camp settings in Kenya. Urban refugees generally have better access to resources but face higher living costs and competition, which can limit their economic opportunities. In contrast, camp refugees exhibit a higher sensitivity of consumption to income changes, indicating that their welfare is more directly affected by fluctuations in income. These differences highlight the need for tailored interventions that consider the unique challenges faced by refugees in various environments.

Income emerges as a critical determinant of welfare for both urban and camp refugees, with camp households showing a greater elasticity of consumption. This suggests that camp refugees rely more heavily on their income for essential goods, making them particularly vulnerable to economic fluctuations. This study underscores the importance of enhancing income-generating opportunities for refugees, particularly in camp settings, where economic activities may be limited. Targeted economic empowerment programs can help improve their overall welfare.

Household size also plays a significant role in determining welfare outcomes, with larger households experiencing a negative impact on per capita consumption. The findings indicate that urban households are less affected by household size compared to their camp counterparts, which may reflect differences in resource availability and management strategies. Policies aimed at supporting resource management and family planning could be beneficial in mitigating the adverse effects of larger household sizes, ultimately improving the welfare of both urban and camp refugees.

The gender of the household head significantly influences welfare, with women-led households reporting better outcomes. This finding emphasizes the importance of empowering women within refugee communities, as they often play a crucial role in resource management and community support. Programs that focus on enhancing the economic stability of women-headed households can lead to improved welfare for entire families. Gender-sensitive policies are essential for fostering equity and promoting the well-being of vulnerable groups within refugee populations.

Finally, the role of education and engagement in economic activities is critical for enhancing welfare among refugees. Urban refugees benefit more from education than their camp counterparts, highlighting the need for improved access to quality education in all settings. Additionally, engagement in economic activities significantly boosts welfare for both groups, underscoring the necessity of facilitating economic participation. Strengthening partnerships between NGOs and local governments can ensure that refugees receive the support they need to thrive, ultimately contributing to their integration and well-being in host communities.

5.2. Policy Recommendations

The analysis highlights that income significantly influences household welfare among both refugee and Kenyan populations, with refugees exhibiting higher sensitivity to income changes, especially in camp settings. To improve welfare, targeted income-generating programs should be prioritized, particularly in camp environments where economic opportunities are limited. Policies fostering economic empowerment, such as vocational training and microfinance initiatives, can enhance income stability and resilience.

Household size negatively impacts per capita consumption, with larger households facing resource dilution. Implementing family planning and resource management interventions can mitigate these effects, especially in camp settings where resource constraints are more acute. Promoting efficient resource utilization and supporting larger households through social support programs can further improve welfare outcomes.

Gender dynamics reveal that female-headed households tend to report better welfare outcomes, especially in urban areas. Empowering women through targeted economic and social programs can leverage their role in resource management and community support, leading to broader household benefits. Gender-sensitive policies that promote women’s economic participation and decision making are essential for fostering equity and improving overall household welfare.

Access to education significantly enhances welfare for both refugees and Kenyans. Improving educational opportunities, particularly for refugees, can facilitate economic mobility and social integration. Investments in quality education and vocational training should be prioritized to equip vulnerable groups with the skills necessary for economic participation.

Engagement in economic activities and partnerships with NGOs are crucial for welfare enhancement. Facilitating refugees’ access to legal employment opportunities and strengthening collaborations between NGOs and local governments can provide essential services and resources. Such support can help refugees navigate urban and camp environments more effectively, reducing vulnerabilities and promoting self-sufficiency.

Finally, tailored interventions that address the specific needs of urban versus camp refugees are vital. Urban refugees require support to overcome higher living costs and legal barriers to economic participation, while camp refugees benefit from income support and resource management programs. Developing context-specific policies that consider these differences will be most effective in improving overall refugee welfare and fostering sustainable community integration.

Despite the insights gained from this study, several research gaps remain that warrant further investigation. Longitudinal studies tracking the welfare of refugee households over time could provide valuable insights into the long-term impacts of various interventions. Comparative studies between refugee populations in different countries (e.g., Uganda, Ethiopia, and Tanzania) may identify best practices for improving welfare. Additionally, exploring the impact of legal status on economic participation and welfare could uncover barriers to integration. Researching the mental health and psychosocial welfare of refugees concerning their economic conditions would provide a more holistic understanding of their challenges. Finally, examining the role of technology in enhancing economic opportunities for refugees could uncover innovative solutions to improve their welfare.