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Table 3 COVID-19, labor market, and marital status

From: Gender effects of the COVID-19 pandemic in the Swiss labor market

 

Employed

Unemployed

Non-active

Female

−0.00362

−0.00551\(^{***}\)

0.00864\(^{***}\)

 

(0.00325)

(0.00197)

(0.00288)

CovInd

−0.0157\(^{***}\)

0.00737\(^{**}\)

0.0103\(^{***}\)

 

(0.00413)

(0.00313)

(0.00375)

Female \(\times\) CovInd

−0.0115\(^{**}\)

−0.00586

0.0162\(^{***}\)

 

(0.00576)

(0.00437)

(0.00523)

Married

0.0311\(^{***}\)

−0.0134\(^{***}\)

−0.0166\(^{***}\)

 

(0.00323)

(0.00196)

(0.00286)

Married \(\times\) female

−0.0692\(^{***}\)

0.00732\(^{***}\)

0.0603\(^{***}\)

 

(0.00559)

(0.00424)

(0.00508)

Married \(\times\) CovInd

−0.00110

−0.00373

0.00225

 

(0.00559)

(0.00424)

(0.00508)

Married \(\times\) female \(\times\) CovInd

0.0176\(^{**}\)

0.00256

−0.0185\(^{***}\)

 

(0.00776)

(0.00589)

(0.00704)

Constant

0.706\(^{***}\)

0.0329

0.260\(^{***}\)

 

(0.0395)

(0.0234)

(0.0350)

Age FE

YES

YES

YES

Canton FE

YES

YES

YES

Education FE

YES

YES

YES

NOGA FE

YES

YES

YES

ISCO FE

YES

YES

YES

Observations

186881

186881

186881

\(R^2\)

0.419

0.0429

0.460

  1. Estimates from regression (1) of labor market status on a constant, female dummy (1 for women and 0 otherwise), COVID-19 stringency index, marital status dummy (1 for married/in a registered relation and 0 otherwise), and their interactions. Sample includes respondents aged 15 to 64. Regressions estimated with linear probability model, including random effects. Robust standard errors in parentheses
  2. *p < 0.1, **p < 0.05, ***p < 0.01