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Journal for Labour Market Research

Table 5 Model estimates of lockdown effects on informal sector employment probabilities.

From: Lockdown stringency and employment formality: evidence from the COVID-19 pandemic in South Africa

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

POLS

POLS

POLS

FE

DiD (POLS)

DiD (POLS)

DiD (FE)

Treatment

0.076***

0.075***

0.067***

 

0.095***

0.089***

 
 

(0.006)

(0.006)

(0.006)

 

(0.008)

(0.007)

 

Post

 

 − 0.061***

 − 0.081***

 − 0.059***

 − 0.047***

 − 0.066***

 − 0.045***

  

(0.003)

(0.003)

(0.004)

(0.004)

(0.004)

(0.005)

Treatment × post

    

 − 0.033***

 − 0.036***

 − 0.035***

     

(0.007)

(0.007)

(0.007)

Time-varying controls

N

N

Y

Y

N

Y

Y

Time-invariant controls

N

N

Y

N

N

Y

N

Individual FE

N

N

N

Y

N

N

Y

Constant

0.137***

0.173***

0.249***

0.068

0.165***

0.239***

0.034

 

(0.004)

(0.004)

(0.037)

(0.482)

(0.005)

(0.037)

(0.482)

Observations

26,286

26,286

26,069

26,069

26,286

26,069

26,069

R2

0.010

0.016

0.188

0.793

0.017

0.189

0.794

  1. This table presents estimates of specification (1) with a binary informal sector employment variable serving as the dependent variable. Sample restricted to the working-age population (15–64 years) as of 2020Q1. POLS = pooled ordinary least squares, FE = fixed effects, DiD = Difference-in-Differences. Standard errors presented in parentheses and are clustered at the panel level. All estimates weighted using sampling weights. Time-varying controls include age, highest education level, and employment type. Time-invariant controls include sex, racial population group, province of residence, a binary urban residence indicator, an ‘industry or occupation job-mover’ indicator, and a ‘formality job mover’ indicator as described in Sect. 3.3
  2. ***p < 0.01, **p < 0.05, *p < 0.10
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