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Financial Innovation

Table 5 Panel data regression

From: Research on interaction of innovation spillovers in the AI, Fin-Tech, and IoT industries: considering structural changes accelerated by COVID-19

Depend Variable

Model 1

Model 2

Model 3

Model 4

Model 5

\(({R}_{i,t}-{R}_{f,t})\)

Coefficient

t-statistic

Coefficient

t-statistic

Coefficient

t-statistic

Coefficient

t-statistic

Coefficient

t-statistic

Intercept

 − 0.0199***

 − 2.88789

 − 0.72976***

 − 37.80125

 − 0.02475***

 − 12.04331

 − 0.00250***

 − 3.723995

 − 0.06670***

 − 3.31868

(\({R}_{m}-{R}_{f}\))

1.24E − 05***

11.9587

0.00011***

36.15421

3.52E − 06

1.636524

0.86485***

35.46794

4.70E − 06

0.97005

BMR

 − 0.1124***

 − 18.8808

 − 0.10402***

 − 18.61919

 − 0.00907***

 − 12.34377

 − 7.80E − 05

 − 0.684454

 − 0.02787***

 − 8.59256

Size

1.27E − 07***

7.785249

9.27E − 08***

7.619385

2.98E − 08

0.322771

5.65E − 09

0.466804

0.00340*

1.66917

D

  

 − 0.34246***

 − 20.55658

0.02549***

8.404843

0.00124

1.615604

0.07113**

2.18626

H

  

1.03161***

34.14187

      

\({\sigma }_{i,AI,t-1}^{2}\)

4.86E − 13***

3.431620

1.41E − 12***

3.222290

1.02E − 08**

2.238173

 − 1.14E − 07***

 − 3.209640

2.29E − 07***

5.46373

\({\sigma }_{i,Fin-Tech,t-1}^{2}\)

1.95E − 13***

3.151131

7.78E − 14

0.547852

 − 2.84E − 07**

 − 2.237765

6.74E − 08***

3.933989

 − 6.37E − 06***

 − 5.46381

D*(\({R}_{m}-{R}_{f}\))

    

0.99974***

1321.892

0.01446

0.497166

0.99973***

427.445

D*BMR

    

0.00877***

10.16661

 − 0.00017

 − 1.371775

0.02724***

5.40659

D*Size

    

 − 1.61E − 08

 − 0.171484

8.71E − 09

0.709120

 − 0.00356

 − 1.09197

D*\(({\sigma }_{i,AI,t-1}^{2}\))

    

 − 1.02E − 08**

 − 2.238171

1.14E − 07***

3.209641

1.76E − 06

0.57349

D*(\({\sigma }_{i,Fin-Tech,t-1}^{2}\))

    

2.84E − 07**

2.237767

 − 6.74E − 08***

 − 3.933981

6.95E − 06***

2.84766

N

58,589

 

58,589

 

58,589

 

46,690

 

11,899

 

Adj. R2

0.046807

 

0.095833

 

0.969676

 

0.101251

 

0.96930

 

F − statistic

576.3947***

 

888.1092***

 

170318.1***

 

481.1156***

 

34156.09***

 
  1. Major model \({R}_{i,t}-{R}_{f,t}={{\alpha }_{0s(ns)\_pre-covid}+(\alpha }_{0s(ns)\_covid}-{\alpha }_{0s(ns)\_pre-covid})D+{\beta }_{1s(ns)\_pre-covid}{(R}_{m,t}-{R}_{f,t})+({\beta }_{1s(ns)\_covid}-{\beta }_{1s(ns)\_pre-covid})D{(R}_{m,t}-{R}_{f,t})+{\beta }_{2s(ns)\_pre-covid}ln{\left(SIZE\right)}_{i,t}+({\beta }_{2s(ns)\_covidS}-{\beta }_{2s(ns)\_pre-covid})Dln{\left(SIZE\right)}_{i,t}+{\beta }_{3s(ns)\_pre-covid}{(BMR)}_{i,t}+({\beta }_{3s(ns)\_covid}-{\beta }_{3s(ns)\_pre-covid}){D(BMR)}_{i,t}+{\beta }_{4s(ns)\_pre-covid}{({\sigma }_{i,AI}^{2})}_{t-1}+({\beta }_{4s(ns)\_covid}-{\beta }_{4s(ns)\_pre-covid})D{({\sigma }_{i,AI}^{2})}_{t-1}+{\beta }_{5s(ns)\_pre-covid}{({\sigma }_{i,Fin-Tech}^{2})}_{t-1}+({\beta }_{5s(ns)\_covid}-{\beta }_{5s(ns)\_pre-covid})D{({\sigma }_{i,Fin-Tech}^{2})}_{t-1}+{\varepsilon }_{i,t}\), \({\varepsilon }_{i,t}\)=\({\mu }_{i}+{\lambda }_{i}+{\nu }_{i,t}\); Model 1 examines H1, Model 3 examines the full sample, Model 4 examines H2, and Model 5 examines H3; each model lists the coefficients and t-values of period random effects; *** (P < 0.01) and ** (P < 0.05) are statistically significant; the significance of main variables is shown in bold
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