Livelihoods and Income Diversification of Informal Recyclers: A Case Study in the Mekong River Delta, Vietnam

Abstract

This study aims to analyze the livelihood resources and income diversification of informal recyclers in the Mekong River Delta (MRD). The multiple linear regression model was applied to determine income diversification and total household income with the sustainable livelihood analysis framework developed by the United Kingdom Department for International Development (2000), including human resources, physical resources, natural resources, financial resources, and social resources. The results indicated that up to 25% of itinerant waste buyers worked on average more than 7.3 hours/day, which was higher than the urban near-poor level regulated by the Vietnam government. The results of the regression model revealed that total households' income was affected by the factors of health status, gender, urban location type 1, the amount of potential savings, and informal credit participation, while the factors of health status, urban location, the amount of potential savings, and informal credit participation have the effect of diversifying farm household income. Thus, if the informal waste recycling sector is supported and regulated by proper government management, it will not only help poor households diversify their income, but it will also help poor households diversify their income, particularly women's income, which is vulnerable and lower than male income in the MRD.

1. Introduction

For millions of underprivileged people around the world, garbage recycling has become a significant source of income. The collection and selling of recyclable waste are expected to support one percent of the world’s population. Itinerant garbage buyers are people who buy scrap from houses and then sell it to scrap yards in Vietnam. This work can be considered their livelihood, and for some families, it is their primary source of income. A multitude of factors, including natural, human, economical, physical, and social, have an impact on their lives (DFID, 1999). Agricultural intensification, livelihood diversification, and labor migration are three significant livelihood strategies in emerging countries (Ellis, 2000).

In order to precisely and realistically grasp the reasons for nomadic waste purchasers’ professional choices, as well as how they convert their livelihood assets into positive livelihood results, it is vital to approach their lives. As a result, income diversification is achievable through the establishment of jobs in the informal trash recycling sector. Reduce the burden on formal employment creation and social security programs and budgets from there.

According to the General Statistics Office, migrant workers moving from rural to urban regions account for more than two-thirds (69.7%) of all unemployed migrant employees. It’s worth noting that female migrant workers have a greater unemployment rate than male migrant workers. The rate of migration from rural to urban regions is expected to grow as a result of climate change. This has put a lot of pressure on big cities to stabilize their welfare, such as producing jobs and maintaining livelihoods.

In the meantime, the problem of urbanization and pollution in urban areas is becoming more serious. Almost every country on the earth is concerned about pollution. According to figures from the General Department of Environment, the amount of domestic solid trash generated in urban areas is expected to be over 38, 000 tonnes per day, with an annual increase of 12%. Organic waste contributes to 54–77% of urban solid waste, while recyclable waste (plastic and metal components) accounts for 8–18%. Solid waste pollution has become a big issue on par with climate change in terms of environmental contamination. In the Mekong River Delta (MRD), waste collection and recycling are currently primarily reliant on informal itinerant waste purchasers (IWB). This force helps to reduce the quantity of solid waste produced in the environment while also assisting in the creation of jobs for people moving from rural to urban areas.

As a result, the goal of this research is to look into the livelihoods of workers in the informal recycling sector, to propose solutions to diversify job options while also ensuring that environmental protection achieves the goal of sustainable livelihoods without causing damage to natural resources. This study aims to explore and analyze the resources of the Mekong Delta scrap collectors’ livelihood capital (human, natural, physical, financial, and social), analyze the factors affecting the total income of scrap collectors’ households in the Mekong Delta, and propose solutions to diversify the income sources of scrap collectors in the Mekong River Delta.

2. Methodology

Can Tho city (urban-type 1), Soc Trang city, Long Xuyen city, Tan An city, and Ca Mau city (urban-type 2 city) were among the cities in the MRD where 128 scrap collectors were questioned. Thus, the research’s assessed data is highly representative of the population. The networking method and random sampling methods were employed in this study. The research team selects buyers’ scrap and other collectors in their network based on the criteria of the province’s data collection area.

The factors determining IWB total income, factors representing livelihood outcomes, and the degree of income diversity of IWB households are identified by employed multiple linear regression models as follows:

LnTnhap = α₀+ α1Workingon + α2Goodhealth + α3Moderatehealth + α4Retiremale + α5Nonetiremale + α6Retirefemale + α7Urbantype1 + α8Urbantype2 + α9Potentialsaving + α10Tgtontine + u_i       (1)

ID = β₀ + β1Working_con + β2Goodhealth + β3Moderatehealth + β4Retiremale +  β5Non_retiremale + β6Retirefemale + β7Urbantype1 + β8Urbantype2 + β9Potentialsaving + β10Tgtontine + u₂       (2)

where the dependent variable of LnIncome is measured by the ln of the total income of the IWB household and the dependent variable of SID is the level of income diversity of the IWB household. The degree of income diversification is measured by the formula:

\(\mathrm{SID}=1-\sum_{n=1}^{j} P_{j}^{2};\)       (3)

where P_j is the share of the j^th income in total income.

The theoretical framework of sustainable livelihoods of T = the UK Department for International Development - DFID (1999) is the basis for determining the factors affecting the total income of IWB and the level of income diversification with different livelihood resources. The independent variables in the models include Working_con, Goodhealth, Moderatehealth, Retiremale, Non_retiremale, Retirefemale, Urbantype1, Urbantype2, Potentialsaving, Tgtontine. Livelihood resources include human resources, material resources, natural resources, financial resources, and social resources. Therefore, based on the theoretical framework of sustainable livelihoods of DFID (1999) and previous empirical studies, this study uses variables for analysis as follows.

2.1. Human Resources

Human resources, according to the DFID (1999) (Sustainable Livelihoods Framework), include skills, know- ledge, workability, good health, and creativity. Human resources in the context of IWB include labor capability, education, and health (Adama, 2012; Didero, 2012). As a result, the variables Work-ing con, Goodhealth, Ttkha, Retiremale, Non-retiremale, and Retirefemale are used to measure human resources in this study. The following variables are described in detail as follow:

The variable Working_con is a quantitative variable that is measured by the proportion of labor in the IWB household (%). This variable is calculated by dividing the number of working-age members of the IWB household by the total number of members of the IWB household. Members of working-age contribute to the total income of the household, so households with a higher proportion of workers will have a higher total income. It is expected that this variable has a positive correlation with the total income variable of the household.

The health status of IWB is a factor of human resources. In this study, the health status factor consisted of four attributes, excellent health, good health, average health, and weak health. The health status factor is included in the linear regression model by two variables Goodhealth and Moderatehealth and the base group is the average and weak health group. The variable Goodhealth is a dummy variable that takes two values, Goodhealth = 1 if the IWB is in the healthy group, and Goodhealth = 0, if the IWB is not in the good health group. The variable Moderatehealth is a dummy variable that takes two values, Moderatehealth = 1 if the IWB is in the moderate health group, and Moderatehealth = 0 if the IWB is not in the moderate health group.

Combining the gender and age factors of the IWB can be classified into four groups, male in retirement age, male in working age, female in retirement age, and female in working age. This dual feature is included in the linear regression model using Retiremale, Non_retiremale, and Retirefemale variables. The Retiremale variable is a dummy variable that takes two values, Retiremale = 1 if the IWB is male and of retirement age, and Retiremale = 0, if the IWB does not have this feature. The Non_retiremale variable is a dummy variable that takes two values, Non_retiremale = 1 if the IWB is male and of working age, and Non_retiremale = 0, if the IWB does not have this feature. The variable Retirefemale is a dummy variable that takes two values, Retirefemale = 1 if the IWB has female characteristics and is of retirement age, and Retirefemale = 0, if the IWB does not have this characteristic.

2.2. Natural Resources and Material Resources

The sustainable livelihoods framework considers natural capital to be natural resources and their services. In the research of workers in the informal recycling sector, the main natural resource is the amount of waste generated (Nzeadibe & Anyadike, 2012; Nzeadibe & Mbah, 2015; Rouse & Ali 2001) because the generated waste contains a large amount of waste (Thanh et al., 2010). Based on these statements, the study has selected the urban-type factor to represent the natural resources of the IWB. In Vietnam, depending on the speed of urbanization, each city, either directly under the province or directly under the central government, will be classified as a grade 1 city, grade 2, or grade 3 city.

The amount of solid waste generated depends on the speed of urbanization (Ministry of Natural Resources and Environment of Vietnam, 2016, 2017, 2020). Therefore, it is possible to use the urban-type factor representing the amount of waste generated. In addition, the urban-type factor is also used to represent the infrastructure factor, which is an element of physical resources (Adama, 2012; Didero, 2012). The urban-type factor is included in the model by two variables Urbantype1 and Urbantype2. The variable Urbantype1 is a dummy variable that takes two values, Urbantype1 = 1 if the IWB is in type 1 urban city, and Urbantype1 = 0, if the IWB is not in type 1 urban city. The variable Urbantype2 is a dummy variable that takes two values, Urbantype2 = 1 if the IWB is in type 2 urban city, and Urbantype2 = 0, if the IWB is not in type 2 urban city.

2.3. Financial Resources

Financial resources, according to the Department for International Development (DFID), include available reserves, savings, cash, bank deposits or liquid assets, and regular cash flows, as well as government subsidies. Adama (2012) and Didero (2012) reveal that the financial resource of workers in the informal trash recycling sector is income in the case of Adama (2012) and Didero (2012). Scrap revenue is derived from the collection and sale of scrap Because scrap income can supplement a household’s total income to pay living expenses, leaving the remainder of the revenue available for savings. As a result, the prospective savings factor is used in the study to reflect IWB’s financial resources. The potential saving variable is used to incorporate the savings element into the model. Potential saving is a dummy variable with two values: 1 if the IWB’s household net income is more than 0 and 0 if the IWB’s household net income is equal to 0.

2.4. Social Resources

Individuals rely on social resources such as networks of connections, membership relationships, and trust relationships to make the greatest use of their resources and pursue their livelihoods (Coleman, 1990). design that is environmentally friendly (Ellis, 1999). Due to challenging agricultural production conditions and the impact of saltwater intrusion, workers in the informal waste recycling sector are largely rural-urban migrants (Ministry of Natural Resources and Environment of Vietnam 2019). As a result, social contacts and informal networks are frequently used by workers in the informal garbage recycling business (Adama, 2012; Didero, 2012).

Workers can financially support each other through “hui” - informal tontine – as a result of these informal social interactions. As a result, this participation factor is employed to indicate IWB’s social resources. Simultaneously, because it is a basic type of credit, the IWB can take advantage of other people’s funds to fulfill a household or IWB-related practical purpose. As a result, the participation factor is regarded as a representative element for the IWB’s financial resources. Tgtontine is a variable in the model that represents the participation factor tontine. Tgtontine is a dummy variable with two possible values. If the IWB participates in a tontine, Tgtontine is 1, and if the IWB does not engage in a tontine, Tgtontine is 0.

3. Results and Discussion

3.1. Demographic Characteristics of IWBs

Workers in the informal waste recycling sector in general, and IWB in particular, believe their jobs are challenging since they are performed without the use of sophisticated machinery and must be done outside, according to the findings of the survey. As a result, it appears that this employment is only suitable for workers who are physically fit and can handle adverse weather. However, one interesting finding from our MRD survey is that their ages range from 16 to 78, with an average age of 51.78. This is far older than the average IWB age in Hanoi in 2006, which was roughly 38 years old (Mitchell, 2008) (Mitchell, 2008). However, the age of IWB in the MRD is quite similar to the age of scrap pickers in Cape Town and Durban, South Africa, from 30 to 80 years old, respectively (Benson & Vanqa-Mgijima, 2010) and 23 to 72 years old (McLean, 2000). Another interesting thing is that the number of female workers doing scrap collection in the MRD is higher than the number of male workers.

Women account for 60.16 percent of the total number of legal tenderers interviewed in the MRD who participate in scrap collection activities. This rate is similar to DiGregorio (1994). In 2006, this percentage increased sharply to 94 percent (Mitchell, 2008). However, this differs from the number of women engaging in informal garbage recycling in Mongolia, where 17 percent of 220 respondents (Uddin & Gutberlet, 2017), and Lagos, Nigeria, where 13.4% of 112 respondents (Uddin & Gutberlet, 2017; Afon, 2012). Thus, if the recycling sector is promoted and handled effectively, it will not only assist poor households to diversify their revenues but will also help poor women improve their wages. External factors make women more vulnerable, and they earn less than males, especially in the MRD.

Moreover, although scrap trading is a challenging job, the majority of legal tenders in the MRD are passionate about it; their average number of years working in scrap trading is 16, with the maximum instance being 47. The independence that this job affords IWB is one of the main reasons that they continue to work in the area. The independence here is the initiative in planning their time for scrap collecting and family care.

Workers in developing nations select informal garbage recycling occupations for a variety of reasons, including a lack of basic prerequisites to work in the formal sector, such as a lack of a vocational diploma, not attending school, or not completing higher education. This characteristic is quite comparable to the features of legal malpractices in the MRD, where up to 17.97 percent of legal malpractices are unable to attend school, 52.34 percent attend primary school, and just 3.91 percent have vocational training certificates.

Furthermore, workers in the informal waste recycling sector in India, where 80 percent of people are illiterate and only 20% have a primary school education (Agarwal et al., 2005), and in Lagos, Nigeria, where 18.8% of respondents did not attend school and 51.8 percent attended primary school, share this trait (Afon, 2012).

3.2. Work Characteristics of IWBs

Working time in the informal recycling business is totally up to the individual; nevertheless, because working time is a crucial component of earning income, employees in better health will want to work harder to earn money. Employees at IWB work 7.3 hours per day, 6.8 days per week, and 28 days per month on average. This data reveals that IWBs work longer hours than workers in the official sector, who work 8 hours per day and 5 days per week. IWBs in the MRD, on the other hand, work an average of 8 hours per day and 5 days per week, which is comparable to the 9 hours per day worked by IWBs in Freetown, Sierra Leone. They assume that the longer they work, the more money they will be able to make.

Aside from the topic of working time, obtaining and maintaining clients is also a factor in IWB’s revenue generation. As a result, 81.25 percent of IWB in the MRD own at least one mobile phone that they can use to communicate with customers. The majority of IWB’s customers are families with a lot of scrap to sell. These consumers are self searched by IWB, and they are rarely referred by others.

Although many different types of scrap can be recycled, most MRD IWBs only buy a few of the most common ones, such as iron, copper, aluminum, plastic, paper, and glass. Scraps are scraps collected by the scrap yard. IWB collected an average of 72.42 kg each day, with 41.5 percent of that being paper waste, 32.98 percent being recyclable metal, 24.77 percent being recycled plastic, and 0.73 percent being glass (Table 1).

Table 1: Classification and Quantity of Purchased Scraps

3.3. Income Structure, Level of Income Diversification, and Impact of Livelihood Resources on the Total Income of the IWB’s Household

The income from IWB’s scrap collection in the MRD is equal to the amount of scrap collected multiplied by the difference between the customer’s scrap buying price and the scrap selling price. Another intriguing discovery is that this activity generates an average of US\($\)4.26 per person per day, equating to US\($\)124.06 per person per month for the IWB. This income level is higher than the urban near-poor income level of US\($\)55.67/month set forth in the Decision on the Promulgation of the Multidimensional Poverty Line for the period 2016–2020 (Vietnam Government, 2015), but lower than the Region II minimum wage of US\($\)167.88/month set forth in the decree on regional minimum wages for employees working under labor contracts (Vietnam Government, 2018). This highlights how earnings from informal garbage recycling help workers pay their expenses and stay out of trouble with the law. This is echoed in a study by Uddin and Gutberlet (2018), who indicated that informal garbage recycling is the principal source of revenue for 78 percent of scrap pickers in Mongolia. Scrap collection has also helped 22.3 percent of MRD residents aged 60 to 78 years old generate income and eliminate the need for child subsidies.

Furthermore, according to the survey data, the average total income of the NMPL household is about US\($\)276.38/month, while the total spending for 3.8 people/household is about 4, 286, 992 VND/month, a savings of US\($\)92.78/ month may be achieved. IWB households earn money from agricultural activities, official non-agricultural activities, and informal non-agricultural activities in addition to scrap collection. Although IWB’s family earns money from a variety of sources, scrap collection remains the family’s primary source of income. IWB households earn money from scrap gathering, which accounts for 70.59 percent of total household income. This income is higher in IWB households than in other households, possibly because many family members work in the scrap industry (27.34 percent of IWB households have two or more members), and 64.06 percent of IWB households believe scrap collection income is enough to cover all of the family’s expenses (Figure 1).

Figure 1: Classification of IWBs’ Household Income Sources Note: US\($\)1 was equal to 23, 350 Vietnamese Dongs (VND) on January 01, 2021.

Table 2 shows the results of the OLS regression of the factors determining the amount of income divergence and total income of the IWB household.

Table 2: Factors Affecting Income Diversity and Total Household Income of IWBs

Source: Survey data, 2019.

Note: *, ** and *** are statistically significant at 10%, 5%, and 1%, respectively, and ns are not statistically significant, and “-” is the non-incidental expense.

The White test was used in this study to examine the phenomena of homoscedastic, correlation coefficient, and multicollinearity. According to the test results, both linear regression findings do not violate the premise of perfect multicollinearity. While the results of the linear regression analysis of factors impacting income diversity do not violate the assumption of variable variance, the results of the linear regression study of factors affecting the total income of IWB households do. To address this problem, the researchers utilized a strong subcommand.

According to regression results, income diversity and total income are higher in IWB households with better health and IWB families with female representatives under 55 years old. This indicates how IWB households effectively use human resources to create revenue and diversify their income sources. IWB households in cities with a higher level of urbanization, on the other hand, have a higher level of income diversity and total income. As a result, IWB households have increased their income and dispersed their economic risks by utilizing physical and natural resources. In addition, IWB households with better savings capacity and participation in “tontine” will have more income and income diversity. As a result, social resources play an important role in both the IWB households’ livelihood strategy and their livelihood outcomes.

4. Conclusion

The purpose of this research is to learn more about the sources of income and the factors that influence income and income diversification for IWBs in the MRD. The level of urbanization is used to stratify analytical data gathered from direct interviews with respondents across the MRD region. Scrap collecting income accounts for more than 70% of overall household income, according to our data. Additionally, the scrap-collecting household obtains money from various sources such as agricultural, non-agricultural, and non-farm activities.

As a result, despite the fact that IWB’s family earns money from a number of sources, scrap collection is still the family’s principal source of income. According to the regression study, income diversity and total income are also higher among households in cities with increased urbanization. This shows how IWB households have efficiently used human resources to seek income and diversify their incomes, as well as material and natural resources to improve quality of life, income, and household income risk distribution.

Furthermore, IWB households with higher income and income variety will have stronger savings capacity and “ton-tine” involvement. As a result, social resources play an important role in both the IWB households’ livelihood strategy and their livelihood outcomes. The government, according to the findings of this study, needs to develop very specific policies and issue-specific laws to support these people, ensuring their role as official recyclers, contributing to their conservation, and thus protecting the environment and stabilizing the lives of low-income immigrants.

*Acknowledgements:

This study is funded in part by the Can Tho University Improvement Project VN14-P6, supported by a Japanese ODA loan.