| Literature DB >> 35915708 |
Pham Tien Thanh1, Pham Bao Duong2.
Abstract
The COVID-19 pandemic has caused enormous detrimental impacts on a global scale. Street vendors are one of the most heavily affected groups since they lack the skills and resources to overcome shocks. This study examines the economic burden facing this group during the pandemic and their coping strategies and mitigation mechanisms in response to these adverse effects. We utilized a mixed-methods approach, wherein 91 women vendors completed a survey questionnaire and 15 women vendors were interviewed. These vendors were found to experience a large reduction in business and consumption. The businesses of immigrant vendors suffered more adverse effects than those of local vendors. Also, the vendors selling in wet market areas incurred greater economic burdens than those selling near schools or recreation centers. The vendors lacked coping strategies to sustain their businesses and adopted various mitigation mechanisms to ensure essential consumption. This study highlights the need for urban social policies that can support this vulnerable group amid a pandemic. We also discuss policy implications for cities and economic development with a focus on street vendors.Entities:
Keywords: COVID-19; Economic burden; Mitigation mechanisms; Vulnerability; Women street vendors
Year: 2022 PMID: 35915708 PMCID: PMC9329276 DOI: 10.1016/j.cities.2022.103879
Source DB: PubMed Journal: Cities ISSN: 0264-2751
Fig. 1Street vendors during COVID-19 pandemic: An analytical framework.
Fig. 2Map of Ho Chi Minh City with surveyed districts.
Economic burden during COVID-19 pandemic.
| Variable(s) | Description | Whole sample | Continue vending | Stop vending | |||
|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | ||
| Reduction in business, measured by: | |||||||
| (Mean = 4.97; SD = 1.41) | =1 if unaffected | 4 | 4.4 % | 4 | 11.8 % | 0 | 0.0 % |
| =2 if slightly affected | 1 | 1.1 % | 1 | 2.9 % | 0 | 0.0 % | |
| =3 if moderately affected | 10 | 11.0 % | 7 | 20.6 % | 3 | 5.3 % | |
| =4 if much affected | 15 | 16.5 % | 14 | 41.2 % | 1 | 1.8 % | |
| =5 if seriously affected | 10 | 11.0 % | 7 | 20.6 % | 3 | 5.3 % | |
| =6 if completely affected (almost no sales) | 51 | 56.0 % | 1 | 2.9 % | 50 | 87.7 % | |
| Reduction in daily consumption expenditure, measured by: | |||||||
| (Mean = 3.70; SD = 1.31) | =1 if unaffected | 9 | 9.9 % | 7 | 20.6 % | 2 | 3.5 % |
| =2 if slightly affected | 11 | 12.1 % | 4 | 11.8 % | 7 | 12.3 % | |
| =3 if moderately affected | 8 | 8.8 % | 3 | 8.8 % | 5 | 8.8 % | |
| =4 if much affected | 33 | 36.3 % | 13 | 38.2 % | 20 | 35.1 % | |
| =5 if seriously affected | 30 | 33.0 % | 7 | 20.6 % | 23 | 40.4 % | |
| Observations | 91 | 34 | 57 | ||||
Source: Authors' calculation.
Sample profile.
| Variable(s) | Description | N | % |
|---|---|---|---|
| Marital status | Single, divorced, widowed | 10 | 11.0 % |
| Currently married | 81 | 89.0 % | |
| Education level | Never gone to school | 14 | 15.4 % |
| Elementary school (1st–5th grade) | 34 | 37.4 % | |
| Secondary school (6th–9th grade) | 31 | 34.1 % | |
| High school (10th–12th grade) | 12 | 13.2 % | |
| Age | Young adults (20–35 years old) | 15 | 16.5 % |
| Middle-aged adults (36–55 years old) | 54 | 59.3 % | |
| Older adults (>55 years old) | 22 | 24.2 % | |
| Immigration status | Local resident | 22 | 24.2 % |
| Immigrant | 69 | 75.8 % | |
| Vending experience | ≤2 year | 23 | 25.3 % |
| 2–<5 years | 24 | 26.4 % | |
| ≥5 years | 44 | 48.4 % | |
| Sales area | Schools, recreation centers | 69 | 75.8 % |
| Residential or office areas | 8 | 8.8 % | |
| Wet market areas | 14 | 15.4 % | |
| Commodity | Non-staple food or non-food items | 66 | 72.5 % |
| Staple food | 25 | 27.5 % | |
| Observations | 91 | ||
Source: Authors' calculation.
Determinants of the economic burden during COVID-19 pandemic.
| Variable(s) | Reduced business | Reduced consumption | ||
|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | |
| Marital status (Ref = Currently married) | 0.669* | 0.404 | −0.503 | −0.741 |
| (0.086) | (0.315) | (0.375) | (0.165) | |
| Education level (Ref = Never go to school) | ||||
| Elementary school | −0.186 | −0.427 | −0.478 | −0.785 |
| (0.591) | (0.267) | (0.190) | (0.055) | |
| Secondary school | 0.101 | −0.099 | −0.426 | −0.723 |
| (0.798) | (0.809) | (0.288) | (0.070) | |
| High school | 0.735 | 0.138 | −0.089 | −0.695 |
| (0.155) | (0.793) | (0.852) | (0.187) | |
| Age (Ref = Young adults) | ||||
| Middle-aged adults | −0.157 | −0.499 | −0.372 | −0.555 |
| (0.752) | (0.327) | (0.326) | (0.243) | |
| Older adults | 0.153 | −0.337 | −0.470 | −0.899 |
| (0.789) | (0.588) | (0.273) | (0.086) | |
| Immigration status (Ref = Local resident) | 0.597** | 0.776*** | 0.023 | 0.207 |
| (0.026) | (0.008) | (0.934) | (0.505) | |
| Vending experience (Ref = ≤2 years) | ||||
| 2–<5 years | 0.269 | 0.259 | ||
| (0.485) | (0.476) | |||
| ≥5 years | 0.132 | 0.195 | ||
| (0.730) | (0.546) | |||
| Sales area (Ref = Schools, recreation centers) | ||||
| Residential or office areas | −0.030 | 0.222 | ||
| (0.946) | (0.605) | |||
| Wet markets | −0.953** | −1.006** | ||
| (0.016) | (0.018) | |||
| Commodity (Ref = Staple food) | 0.308 | −0.310 | ||
| (0.357) | (0.248) | |||
| Constant cut 1 | −0.746 | −1.430** | −2.444*** | −3.179*** |
| (0.198) | (0.012) | (0.001) | (0.000) | |
| Constant cut 2 | −0.647 | −1.320** | −1.920*** | −2.591*** |
| (0.275) | (0.019) | (0.006) | (0.000) | |
| Constant cut 3 | −0.021 | −0.658 | −1.644** | −2.296*** |
| (0.973) | (0.288) | (0.018) | (0.002) | |
| Constant cut 4 | 0.559 | −0.053 | −0.647 | −1.251* |
| (0.359) | (0.933) | (0.332) | (0.081) | |
| Constant cut 5 | 0.878 | 0.284 | ||
| (0.149) | (0.654) | |||
| Observations | 91 | 91 | 91 | 91 |
Source: Authors' calculation.
Note: robust p-value in parentheses.
** and *** represent statistical significance at the 5 % and 1 % levels, respectively.
Coping strategies to sustain business.
| Strategies | N | % |
|---|---|---|
| Not applicable due to being unaffected | 4 | 4.4 % |
| Change sales area | 1 | 1.1 % |
| Change commodity | 0 | 0.0 % |
| Change sales method | 0 | 0.0 % |
| No solution | 86 | 94.5 % |
| Observations | 91 | |
Source: Authors' calculation.
Mitigation mechanisms in response to reduced consumption expenditure.
| Mechanisms | N | % |
|---|---|---|
| Savings | 25 | 27.5 % |
| Cash or in-kind supports | 29 | 31.9 % |
| From friends or relatives | 10 | 11.0 % |
| From local authorities or government | 14 | 15.4 % |
| From charity programs | 9 | 9.9 % |
| From landlords | 5 | 5.5 % |
| Income from other family members | 22 | 24.2 % |
| Reduced expenditure for non-essential goods and services | 77 | 84.6 % |
| Borrowings | 40 | 44.0 % |
| From friends or relatives | 23 | 25.3 % |
| From moneylenders at high interest | 22 | 24.2 % |
| From financial institutions | 1 | 1.1 % |
| Sales of assets | 18 | 19.8 % |
| Non-productive assets | 17 | 18.7 % |
| Productive assets | 1 | 1.1 % |
| Observations | 91 | |
Source: Authors' calculation.