The South African government has extended several amnesties to immigrant workers from Zimbabwe. Using employment data from 2014 to 2022, we find that legalizing immigrant workers mostly led to job growth for both locals and immigrants. However, in 2018, some local workers in Cape Town’s CBD lost jobs to immigrants. Overall, though, the ZEP has helped integrate immigrants into the job market. Now the policy focus must be on enhancing employment opportunities.


South Africa has implemented various amnesty schemes, such as the Zimbabwe Exemption Permit (ZEP) of 2017, to integrate undocumented immigrants into the formal labour marketThese permits allow immigrants to work legally in jobs they previously held informally. However, concerns persist that immigrants may displace local workers and thus exacerbate unemployment. This fuels xenophobic sentiments. Despite these concerns, no comprehensive study has examined the impact of the ZEP on local employment, even as South Africa faces severe unemployment, worsening poverty, and inequality.

This study investigates the relationship between local and immigrant employment in Cape Town and eThekwini, two coastal cities with distinct economic structures. It explores spatial mismatches by analysing employment trends in Central Business Districts (CBDs) and transport corridors, where differences in labour demand may lead to varying outcomes for local and immigrant workers.

Background
South Africa hosts Africa’s largest immigrant population, driven by higher wages and economic opportunities. In an effort to regulate undocumented Zimbabwean migrants, the government introduced the following permit schemes:

  1. Dispensation of Zimbabweans Project (DZP) - 2009
  2. Zimbabwe Special Dispensation Permit (ZSP) - 2014
  3. Zimbabwe Exemption Permit (ZEP) - 2017

The ZEP currently provides legal status to approximately 178 000 Zimbabweans, granting them the right to live, work, and study in South Africa. The goal of these permits is to regularize immigrants' status and reduce deportations.

Research on the impact of immigration on employment in developed economies presents mixed results, with outcomes depending on skill levels, language barriers, and work motivations. While some studies suggest that immigration negatively affects local job markets, others highlight how a diverse workforce can enhance productivity.

In South Africa, historical socio-economic disparities caused by apartheid have exacerbated spatial mismatches—where job locations and worker residences are misaligned—affecting local employment. Immigrants, mainly working in the services sector (hospitality, retail, and finance), are concentrated in CBDs, while blue-collar jobs, largely held by locals, are located on the urban periphery.

Methodology
This study employs the Cities Support Program (CSP) panel data from 2014 to 2022, which integrates firm and employee records, as well as nightlight satellite[1] data (to assess productivity variations), and geospatial data (proximity to CBDs and major roads).

Two analytical approaches are applied:

  1. Descriptive Analysis: Examining employment trends using statistics and bivariate maps.
  2. Regression Analysis: Using Ordinary Least Squares (OLS) and event study[2] estimation models to assess the ZEP’s impact on local employment.

Employment change is measured through percentage shifts in local and foreign employment relative to 2016. The study also evaluates whether employment growth was concentrated in high-immigrant areas or spread spatially.

Findings
Employment Trends in Cape Town and eThekwini
Tables 1 and 2 indicate a positive correlation between foreign and local employment over time in Cape Town and eThekwini. Bivariate maps suggest that in Cape Town, local and foreign employment generally grew together. However, in the CBD and transport corridors some local job losses to immigrants occurred, possibly due to employers substituting local workers with lower-wage immigrant labour. For example, restaurant owners in Cape Town often hire immigrants due to their willingness to accept lower wages.

In eThekwini, foreign and local employment also showed complementarity, but significant local job losses occurred in areas with initially high foreign employment shares. This suggests that the ZEP facilitated the formalisation of previously informal immigrant workers, altering employment patterns

Table 1: Descriptive Statistics for Local Employment and Foreign Share in Cape Town

 

2014

2015

2016

2017

2018

2019

2020

2021

2022

Local Employment

3822 (7835)

4014 (8284)

4165 (8623)

4277 (8775)

4347 (8796)

4402 (8862)

4550 (9131)

4394 (8842)

4381 (8869)

Foreign Share (%)

0.037 (0.019)

0.039 (0.019)

0.043 (0.021)

0.044 (0.021)

0.045 (0.020)

0.048 (0.022)

0.050 (0.023)

0.051 (0.024)

0.052 (0.027)

Night Lights

17.98 (17.53)

18.40 (17.59)

18.41 (17.28)

18.30 (16.54)

 

17.02 (15.16)

16.31 (14.06)

15.19 (12.91)

 

Establishments

201 (253)

212 (268)

218 (278)

220 (279)

227 (289)

236 (293)

249 (304)

247 (296)

236 (279)

N

323

323

323

323

323

323

323

323

323

Source: Author’s own calculations from the CSP data

Table 2: Descriptive Statistics for Local Employment and Foreign Share in eThekwini

 

2014

2015

2016

2017

2018

2019

2020

2021

2022

Local Employment

2604 (7537)

2638 (7599)

2632 (7366)

2564 (6424)

2861 (9147)

2834 (8014)

2834 (7714)

2782 (7322)

2806 (7141)

Foreign Share (%)

0.013
(0.005)

0.014
(0.004)

0.014
(0.004)

0.015
(0.004)

0.015
(0.004)

0.016
(0.005)

0.015
(0.005)

0.016
(0.005)

0.015
(0.005)

Night Lights

9.38 (11.62)

9.39 (11.58)

9.38 (11.53)

9.52 (11.31)

 

9.52 (10.59)

9.32 (10.41)

9.06 (9.91)

 

Establishments

131 (210)

135 (216)

141 (223)

140 (222)

143 (225)

148 (231)

155 (243)

157 (247)

146 (220)

N

364

364

364

364

364

364

364

364

364

Source: Author’s own calculations from the CSP data

Tables 1 and suggest that for both Cape Town and eThekwini, there was a positive time-series association between foreign and local employment. We now investigate using bivariate maps whether the increase in foreign employment was associated with higher or lower local employment, comparing different sub-municipal locations at a single point in time.

Figures 1 and show percentage changes in local and foreign employment in Cape Town and eThekwini, respectively. 

The pattern of locals losing jobs to immigrants in the CBD was investigated further using the Ordinary Least Squares (OLS) statistical method by specifically analysing the relationship between local job growth and foreign job growth, with adjustments made for the distance to the CBD and the nearest main road. We do so to capture whether access to main roads could lead to better or worse employment outcomes for locals and immigrants. Results showed that in Cape Town’s CBD, immigrants replaced locals only in 2018. In all other years the association was insignificant.

Figure 1: Percentage Changes in Local and Foreigner Employment in Cape Town 2017 – 2022

Figure 1

Source: Author’s own calculations from the CSP data

Figure 1 shows local employment growth versus foreign employment growth in Cape Town from 2017 to 2022. The light red colour shows locations that experienced negative local and foreign employment, whereas the dark red colour shows locations that experienced a trade-off between local and foreign employment jobs with locals losing jobs to foreigners. The light green colour illustrates locations where foreigners lost jobs to locals, whereas the dark green shade shows areas where there was complementarity of local and foreign employment.

Figure 2: Percentage Changes in Local and Foreigner Employment in eThekwini 2017 – 2022

Figure 2

Source: Author’s own calculations from the CSP data

Figure 2 shows local employment growth versus foreign employment growth in eThek wini from 2017 to 2022. The light red colour illustrates locations that experienced negative local and foreign employment, whereas the dark red colour shows locations that saw locals losing jobs to immigrants. The light green shade shows locations where immigrants lost jobs locals whereas the dark green shade shows areas where local and foreign employment grew together.

The loss of local jobs as shown in bivariate maps (red spots) in Figure 1 was significant only in 2018, while the loss of local jobs was mainly limited to the CBD. On the other hand, in eThekwini, there was complementarity between locals and immigrants in the CBD in 2018 and 2020 only. The positive effects were mainly limited to the CBD.

We then compared local employment outcomes at locations with many locals potentially affected by the ZEP with locations with fewer locals potentially affected.  We show that foreign employment declined in parts of both cities where the shares  were initially high. The dominant pattern is that foreign employment grew in new places. These new patterns suggest that ZEP was associated with formalization of work for ZEP holders who were initially in the informal labour market – and not counted in the initial foreign share - switching into the formal labour market.

We also asked whether the growth and loss we saw in Figures 1 and happened where the initial foreign employment share was high or low, or whether a new pattern of changes in local employment was emerging in parts of the cities where foreigners were initially not in the formal labour market. We answered this using another set of bivariate maps that mapped initial foreign employment share against local employment growth. Results showed new patterns in Cape Town and eThekwini, suggesting that the ZEP was associated with formalization of work for ZEP holders who were initially in the informal labour market.

Conclusion and policy recommendations
What was the impact of the ZEP on local employment outcomes in Cape Town and eThekwini, two cities with distinct industrial profiles? Our analysis shows that the ZEP facilitated the formalisation of labour markets and created significant complementarities between local and foreign labour in both cities. However, in Cape Town, the evidence indicates that local workers in the CBD experienced job displacement by immigrants in 2018.

The findings suggest that special permits for undocumented immigrants, such as the ZEP, facilitate formal labour market integration and create complementarities between local and immigrant workers. However, localized job displacement—particularly in Cape Town’s CBD in 2018—highlights the need for targeted interventions to mitigate short-term disruptions and enhance long-term employment opportunities for locals.

To address these challenges, the following policies should be considered:

  1. Skills Development & Vocational Training: Implement targeted upskilling programs in high-immigrant employment sectors (such as hospitality and retail). These programs should focus on equipping locals with industry-relevant skills to improve their competitiveness.
  2. Employer Incentives for Inclusive Hiring: to balance employment opportunities and reduce wage undercutting, introduce subsidies or tax incentives for businesses that actively hire and train both local and immigrant workers.
  3. Geographic-Specific Employment Support: Develop employment assistance programs such as job placement services, and entrepreneurship support in high-immigrant concentration areas, particularly in CBDs, to support local workers affected by job displacement.
  4. Monitoring & Policy Adaptation: To allow for timely policy adjustments, establish a labour market monitoring system to track employment trends in immigrant-dense areas.

By implementing these measures, policymakers can maximize the benefits of immigrant labour market integration while ensuring that locals are not disproportionately disadvantaged.


[1]  Nightlights satellite data refers to images and measurements of artificial light emitted at night, captured by satellites orbiting the Earth. The sensors onboard these satellites measure light intensity, by providing clear images of human-made lighting. The processed data are then used to create global and regional maps that show the brightness of different areas at night.

In this study, nightlights data were extracted from the Colorado School of Mines website. Specifically, the logarithm of the mean aggregate local nightlights for the year 2016 was used.

[2] Event study regression refers to a statistical method used to measure the impact of a specific event or policy (which in our case, is the implementation of the Zimbabwe Exemption Policy, ZEP) on a dependent variable, (in our case, the changes in local and foreign employment relative to 2016, the base year period). The model estimates changes by comparing actual outcomes with what would have happened in the absence of the ZEP policy.

A forum for economic policy debate

Econ3x3 promotes analysis and debate on unemployment and employment, income distribution and inclusive growth in South Africa. It publishes accessible research- and expertise-based articles and provides a forum for engagement between research and policy making. We invite contributions from economists and other social science researchers, policy advisors and independent experts.

About Us

Authors

Valentine Madzudzo

Valentine Madzudzo

Download this Article