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Swiss Journal of Economics and Statistics

Table 2 Main results of the binary response model

From: Firms’ participation in the Swiss COVID-19 loan programme

 

(1) Part.(y/n)

(2) Part.(y/n)

(3) Part.(y/n)

(4) Part.(y/n)

(5) Part.(y/n)

Lockdown index (sectors within cantons)

2.16***

   

1.75***

Virus cases (in canton)

 

0.74***

  

0.73***

Liquidity ratio, mean (sectors within cantons)

  

− 0.13***

 

− 0.11***

Debt ratio, mean (sectors within cantons)

   

− 0.06

− 0.21

Headcount dummies

Yes

Yes

Yes

Yes

Yes

Age dummies

Yes

Yes

Yes

Yes

Yes

Constant

Yes

Yes

Yes

Yes

Yes

Observations

674423

675111

471257

471728

471211

Log-likelihood

− 277189.69

− 281379.54

− 215653.56

− 216776.51

− 212285.10

  1. Logit model. The dependent variable is a firm-level binary variable that indicates firm participation in the loan programme. Standard errors are clustered at the level of the grouped variable of interest; in column (5), clustering is at the sector-canton level of the FSO financial variables. The number of observations varies depending on data availability of the grouped variables. ***, ** and * denote statistical significance (two-tailed) at the 1%, 5% and 10% significance levels, respectively. The coefficients of the headcount and age dummies are displayed in Appendix 6
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