Skip to main content

Table 2 Estimated regression results of the learning model (Eq. 12)

From: Impact of learning through credit and value creation on the efficiency of Japanese commercial banks

 

(1)

EVA

(2)

FISIM (GO)

(3)

Credit (tloans)

(4)

Secinv

(5)

TI

Panel A: Full Sample

     

\(ln{w}_{p}\)

1.1432**

0.1157**

0.3080***

0.3886***

0.2398***

 

(0.5014)

(0.0485)

(0.0365)

(0.1071)

(0.0585)

\(ln{w}_{d}\)

0.5630***

0.0795

0.1145***

0.1173*

0.1258***

 

(0.1988)

(0.0598)

(0.0389)

(0.0684)

(0.0442)

\(ln{w}_{k}\)

− 0.2209

0.0815

0.0730

0.0597

0.0705

 

(0.3734)

(0.0946)

(0.0929)

(0.1110)

(0.0976)

\(lnNPA\)

− 0.1623

− 0.0095

0.0254

− 0.0164

0.0338

 

(0.1817)

(0.0124)

(0.0333)

(0.0817)

(0.0456)

\({\varnothing }_{it-1}\)

0.1033**

− 0.4050***

− 0.3910***

− 0.6314***

− 0.3841***

 

(0.0491)

(0.0609)

(0.0357)

(0.0357)

(0.0349)

\(\_Con\)

2.2048

6.5630***

1.8128*

5.8399***

1.6899

 

(3.5557)

(0.8573)

(0.9951)

(1.6061)

(1.1574)

\(Obs\)

1687

1687

1687

1687

1687

\(R\_square\)

0.1841

0.5453

0.6336

0.6822

0.6911

\(F\)

16.1579

70.1076

58.9292

121.3465

79.2705

\(p\)

0.0000

0.0000

0.0000

0.0000

0.0000

\(\boldsymbol{r}\boldsymbol{m}\boldsymbol{s}\boldsymbol{e}\)

1.0850

0.1147

0.0954

0.1562

0.0957

Panel B: City Banks

     

\(ln{w}_{p}\)

1.1972*

− 0.1342

0.5235**

0.6591***

0.5378***

 

(0.4494)

(0.1899)

(0.1323)

(0.0975)

(0.0943)

\(ln{w}_{d}\)

0.1521

0.4139**

0.3010***

0.4229***

0.3643***

 

(0.1146)

(0.1094)

(0.0167)

(0.0486)

(0.0186)

\(ln{w}_{k}\)

0.1167

− 0.6238**

− 0.4587**

− 0.5941**

− 0.5551***

 

(1.1646)

(0.1661)

(0.1541)

(0.1434)

(0.1205)

\(lnNPA\)

0.3705

0.1319*

0.0487

− 0.0631

0.0217

 

(0.4150)

(0.0595)

(0.0299)

(0.1094)

(0.0616)

\({\varnothing }_{it-1}\)

0.3070**

− 0.4488*

− 0.0098

− 0.3748***

− 0.0975**

 

(0.0674)

(0.1648)

(0.0328)

(0.0528)

(0.0253)

\(\_Con\)

− 11.0532

5.7353

− 5.5345**

2.7306

− 3.9304*

 

(10.3760)

(3.2280)

(1.7063)

(1.8650)

(1.6947)

\(Obs\)

74

74

74

74

74

\(R\_square\)

0.6145

0.4830

0.8563

0.8272

0.8548

\(F\)

14.9797

23.5488

21.9727

14.9797

127.8709

\(p\)

0.0000

0.0000

0.0000

0.0000

0.0000

\(\boldsymbol{r}\boldsymbol{m}\boldsymbol{s}\boldsymbol{e}\)

0.4101

0.2494

0.0723

0.1536

0.0870

Panel A: Regional Bank I

     

\(ln{w}_{p}\)

0.9437

0.2676***

0.3611***

0.4180***

0.2892***

 

(0.6065)

(0.0400)

(0.0432)

(0.1259)

(0.0616)

\(ln{w}_{d}\)

0.5708***

0.0466

0.1091**

0.1154

0.1243**

 

(0.2008)

(0.0531)

(0.0426)

(0.0710)

(0.0472)

\(ln{w}_{k}\)

− 0.0950

0.0895

0.0804

0.0681

0.0782

 

(0.3064)

(0.0886)

(0.0893)

(0.1049)

(0.0938)

\(lnNPA\)

− 0.0878

− 0.0095

0.0147

− 0.0053

0.0300

 

(0.2304)

(0.0129)

(0.0366)

(0.0911)

(0.0511)

\({\varnothing }_{it-1}\)

0.1171**

− 0.4278***

− 0.4435***

− 0.5837***

− 0.3957***

 

(0.0505)

(0.1825)

(0.0408)

(0.0473)

(0.0400)

\(\_Con\)

2.2965

6.8054***

2.5769**

5.0590***

1.8071

 

(4.2180)

(2.3168)

(1.0362)

(1.8960)

(1.2762)

\(Obs\)

999

999

999

999

999

\(R\_square\)

0.1925

0.5964

0.6557

0.6945

0.7059

\(F\)

11.0512

61.5595

48.3803

109.2990

63.5233

\(p\)

0.0000

0.0000

0.0000

0.0000

0.0000

\(\boldsymbol{r}\boldsymbol{m}\boldsymbol{s}\boldsymbol{e}\)

1.1277

0.1027

0.0981

0.1481

0.0971

Panel A: Regional Bank II

     

\(ln{w}_{p}\)

1.3381**

0.2253***

0.1478***

0.2893*

0.0644

 

(0.6588)

(0.0395)

(0.0344)

(0.1664)

(0.0627)

\(ln{w}_{d}\)

0.7009**

0.0388

0.0998**

0.0993

0.1053**

 

(0.2908)

(0.0441)

(0.0431)

(0.0706)

(0.0485)

\(ln{w}_{k}\)

− 0.7036

0.0858

0.0636

0.0550

0.0632

 

(0.7483)

(0.0958)

(0.0992)

(0.1188)

(0.1026)

\(lnNPA\)

− 0.3441**

− 0.0174

0.0325

− 0.0223

0.0392

 

(0.1411)

(0.0153)

(0.0274)

(0.0749)

(0.0386)

\({\varnothing }_{it-1}\)

0.0798

− 0.2411***

− 0.4115***

− 0.7257***

− 0.4315***

 

(0.0717)

(0.0426)

(0.0506)

(0.0279)

(0.0511)

\(\_Con\)

− 0.0217

3.6700***

− 0.0308

4.7133***

− 1.9340**

 

(2.6294)

(0.6625)

(0.9250)

(1.3106)

(0.9227)

\(Obs\)

614

614

614

614

614

\(R\_square\)

0.2163

0.6437

0.6663

0.7215

0.7241

\(F\)

16.4636

49.2820

57.9316

57.8995

63.2943

\(p\)

0.0000

0.0000

0.0000

0.0000

0.0000

\(\boldsymbol{r}\boldsymbol{m}\boldsymbol{s}\boldsymbol{e}\)

1.0539

0.0989

0.0827

0.1538

0.0843

  1. Driscoll–Kraay standard errors in parenthesis.
  2. *** p < 0.01, ** p < 0.05, * p < 0.1
  3. \(\text{EVA} \,\sim \,\text{economic value added,}\)
  4. FISIM(GO)\(\sim \,\text{Financia Intermediation Services Indirectly Measured (Gross Output)}\)
  5. \(\text{secinv}\,\sim\, \text{tota security investment},\)
  6. \(\text{tloans}\,\sim\, \text{total loans},\)
  7. \(\text{TI} \,\sim \,\text{Total Investment}\)
  8. \({\varnothing }_{it-1}\sim \,\text{learning elasticity}\)