Nợ xấu của hệ thống ngân hàng thương mại Việt Nam 1683995359

3.2.2. Dynamic panel Generalized Method of Moments

This study applies the two-step dynamic panel data approach suggested by Arellano and Bover (1995) and Blundell and Bond (2000) and also uses dynamic panel GMM technique to address potential endogeneity, heteroskedasticity, and autocorrelation problems in the data. By using GMM estimation, it allows for instrumenting of the endogenous variables and provides consistent estimates. The paper use the lags of right hand side variables in the equations as instruments. In this estimation, the Hansen J-test is used to test the validity of instrument sets and the Arellano-Bond test is applied to check the absence of second-order serial correlation in the first differenced residuals.

3.3. Descriptions of Data

This study analyzes a panel dataset comprising 34 Vietnamese commercial banks over the period 2005–2015. The panel data set is extracted from non-consolidated income statements and balance sheets of these banks. Among 34 commercial banks, there 5 State owned banks and 29 joint stock commercial banks. The sample size of 34 out of 35 joint stock banks is now representative of the JSBs in Vietnam. The macroeconomic data come from IMF – IFS website.

3.4. Summary

This research applies GMM panel model to examine the factors affecting NPLs and the impact of NPLs on the efficiency, capital adequacy and credit growth of the commercial banks in Vietnam. The thesis also measures cost effectiveness by DEA method. With the models and data presented in this section, the next chapter uses the above models to present empirical research.

CHAPTER 4. EMPIRICAL EVIDENCES FROM VIETNAM

4.1. Descriptive statistics

The data used in the GMM model is arranged in panel data. Statistical description is presented in Table 4.1.

Table 4.1. Descriptive statistics of variables

Trung bình	Giá trị nhỏ nhất	Giá trị lớn nhất	Độ lệch chuẩn	Số quan sát
NPL	2.172	0.000	14.856	1.683	357
ROA	1.137	0.000	4.19	0.799	357
CE	0.693	0.228	1	0.233	357
TA	17.343	11.884	20.562	1.648	357
LGR	53.375	-40.811	1131.728	109.780	357
ETA	12.566	0.514	71.206	9.971	357
LDR	66.910	15.333	206.2	27.322	357
LLR	1.150	0.000	3.885	0.715	357
HHI	0.099	0.0715	0.170602	0.0306	357
CR4	0.561	0.456	0.796148	0.105	357
GDP	6.304	5.250	8.440	0.913	357
INF	9.501	0.630	23.120	5.978	357
LNEXI	9.823	9.671	9.984	0.123	357
IR	11.878	7.500	16.95	2.700	357
ESI	9.584	-1.620	20.5	6.519	357

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Source: financial report of Vietnamese commercial banks, own estimations

Table 4.2. Testing the stationary by Fisher với lag=1

Variable

ADF Test		PP Test
	Prb>chi 2		Prb>chi 2
	No trend	Trend	No trend	Trend
NPL	0,000***	0,000***	0,000***	0,002***
GDP	0,026**	1,000	0,000***	0,998
IR	0,888	0,990	0,188	1,000
∆.IR	0,000***	0,000***	0,000***	0,000***
EXI	0,000***	0,241	0,915	1,000
ESI	0,691	0,002***	0,003**	0,575
HHI	0,000***	1,000	0,000***	1,000
INF	0,020**	0,880	0,000***	0,013
ROA	0,000***	0,000***	0,000***	0,000***
CE	0,021**	0,000***	0,000***	0,000***
LDR	0,002***	0,007***	0,000***	0,000***
LGR	0,602	0,000***	0,000***	0,000***
ETA	0,000***	0,000***	0,000***	0,000***
TA	0,000***	0,000***	0,000***	0,000***
LLR	0,831	0,327	0,449	0,418
∆.LLR	0,000***	0,000***	0,000***	0,000***

***, **, * * and ** denote significance at the 10 %, 5 %and 1% levels. Source: own estimations

Results of testing the stationary and cointegration of variables in Table 4.2 and 4.3. In the study model, all independent variables are co-dependent with the dependent variable.

Table 4.3. Westerlund panel cointegration test

Gt	Gα	Pt	Pα
Biến phụ thuộc:NPL
Các biến độc lập
GDP	0,000***	0,000***	0,000***	0,106
IR	0,000***	0,000***	0,000***	0,000***
EXI	0,000***	0,000***	0,000***	0,000***
ESI	0,000***	0,000***	0,000***	0,000***
INF	0,000***	0,000***	0,000***	0,000***
HHI	0,000***	0,000***	0,000***	0,000***
ROA	0,000***	0,000***	0,000***	0,000***
CE	0,000***	0,000***	0,000***	0,000***
LDR	0,000***	0,000***	0,000***	0,000***
LGR	0,000***	0,000***	0,000***	0,122
ETA	0,000***	0,000***	0,000***	0,000***
TA	0,000***	0,000***	0,000***	0,000***
LLR	0,000***	0,000***	0,000***	0,988

***, **, * * and ** denote significance at the 10 %, 5 %and 1% levels. Source: own estimation

4.2. Estimation results for determinants of non-performing loans in Vietnam

The estimation results for the determinant of NPLs of Vietnamese commercial banks are presented in Table 4.4.

Table 4.4. GMM estimation results for the determinant of NPLs of Vietnamese banks

NPL

Model 1

Model 2

Model 3

Model 4

L.NPL

0,3312***

(0,0042)

0,3801***

(0,0045)

0,3033***

(0,0182)

0,4147***

(0,0225)

Bank-specific characteristics

ROA

-0,2335***

(0,0104)

-0,4860***

(0,0121)

-0,2680***

(0,0887)

-0,2665**

(0,0196)

-0,1649**

(0,1778)

-0,1908**

(0,2011)

-0,2510**

(0,1893)

-0,2680*

(0,2582)

ETA

-0,0227***

(0,0060)

-0,0098*

(0,0073)

-0,0270**

(0,0114)

-0,1053***

(0,0214)

LGR

-0,0018***

(0,0003)

-0,0012***

(0,0002)

-0,0005***

(0,0064)

-0,0047***

(0,0014)

0,1405**

(0,065)

0,1146*

(0,1078)

0,0968**

(0,3987)

0,3664***

(0,1802)

LDR

-0,0044***

(0,0016)

-0,0016***

(0,0064)

-0,0018*

(0,0008)

-0,0034*

(0,0031)

LLR

0,0111***

(0,004)

0,0192**

(0,0021)

0,093***

(0,0160)

0,0219***

(0,0117)

Own1

- 0,1158***

(0,4256)

Own2

0,0605***

(0,6212)

Own3

0,0347**

(0,0899)

Industry competition

HHI

-0,553***

(0,2428)

CR4

-0,628*

(0,9957)

-0,273**

(0,0738)

-0,5421***

(0,1367)

Macroeconomic variables

GDP

-0,399***

(0,0708)

-0,3931***

(0,0624)

-0,4589***

(0,0545)

-0,7546***

(0,0462)

INF

0,0188**

(0,0061)

0,0447***

(0,0054)

EXI

0,2059***

(0,4102)

0,3210***

(0,4019)

0,5124***

(0,1103)

0,4397***

(0,1217)

0,1083***

(0,0204)

ESI

0,0683***

(0,0038)

CONS.

-0,6293*** (0,0110)	-1,774*** (0,0257)	-0,5672*** (0,4357)	-1,4959*** (0,3802)
Obs.	323	323	323	323
No. of banks	34	34	34	34
No. of instruments	19	22	23	21
Pro>chi2	0,000	0,000	0,000	0,000
Hansen test	0,488	0,574	0,559	0,625
AR(1)	0,009	0,031	0,015	0,008
AR(2)	0,594	0,775	0,535	0,612

***, **, * * and ** denote significance at the 10 %, 5 %and 1% levels, respectively5% và 10%. Standard errors in parentheses. Source: own estimations

Our findings indicate that factors such as bank efficiency, equity, credit growth and economic growth are the main factors that have a significant and negatively related to NPLs of Vietnamese commercial banks. Meanwhile, lagged NPLs, bank size, loans to deposit, capital and inflation, exchange rates, interest rates and real estate prices have the significant and positive impact on NPLs.

4.4. Estimation results for impact of non-performing loans on bank behavior

4.4.1. Estimation results for impact of non-performing loans on bank performance efficiency

The results of Table 4.5 show the significant impact of NPLs on bank performance and support the hypothesis developed in Chapter 3: The rising of NPLs reduces cost efficiency as well as profitability of banks.

Table 4.5. GMM estimation results for impact of NPLs on bank performance efficiency

Dependent

Variable

ROA

Model 1

Model 2

Model 3

Model 4

L.ROA

0,2432***

(0,0302)

0,2542***

(0,0347)

L.CE

0,2997***

(0,0968)

0,372***

(0,0251)

Bank-specific characteristics

NPL

-0,1579*** (0,0331)

-0,1904*** (0,0315)

-0,1221* (0,0343)

0,1803*** (0,0427)

ETA

0,0117*** (0,0033)

0,0061** (0,0332)

-0,0118*** (0,0032)

0,0186*** (0,0202)

LGR

0,0019***

(0,0005)

0,0006**

(0,0005)

0,0051**

(0,0002)

0,0053**

(0,0008)

-0,2989**

(0,0606)

-0,3067**

(0,0699)

0,0315***

(0,0366)

0,0781***

(0,2306)

LDR

0,0009***

(0,0020)

0,0008*

(0,0002)

0,0004***

(0,0000)

0,0046***

(0,0027)

Own1

0,1079**

(0,4648)

-0,2425**

(0,1319)

Own2

-0,0896*

(0,1395)

0,1946***

(0,0874)

Own3

-0,0736*

(0,3354)

0,0237**

(0,2619)

HHI

0,2264***

(0,0321)

0,319**

(0,1922)

CR4

0,4198***

(0,3381)

0,1292***

(0,7801)

Macroeconomic variables

GDP

0,0323***

(0,0187)

0,0432***

(0,0279)

0,0441***

(0,0188)

0,0639***

(0,0387)

INF

0,0004***

(0,0022)

0,0005

(0,0030)

0,0229*

(0014)

0,0003***

(0,0045)

LNER

0,1456** (0,0251)

0,2721** (0,3026)

-0,11607*** (0,0329)

0,1473*** (0,2446)

CONS.

-1,248***

(0,096)

-0,5806***

(0,2319)

-0,7255**

(0,5712)

-0,7714

(0,6018)

Obs.

323

No. of

banks

No. of

instruments

Pro>chi2

0,000

Hansen test

0,503

0,304

0,456

0,46

AR(1)

0,007

0,016

0,005

0,002

AR(2)

0,390

0,242

0,742

0,627

***, **, * * and ** denote significance at the 10 %, 5 %and 1% levels, respectively5% và 10%. Standard errors in parentheses. Source: own estimations.

4.4.2. Estimation results for impact of non-performing loans on capital adequacy

Our findings show that there is a negative coefficient of NPLs and ETA and be significant. This result supports the bank lending channel theories. The result is also consistent with Lee and Hsieh (2013), Le (2016) and Alfon (2005).

Table 4.6. GMM estimation results for impact of NPLs on capital edequacy

Dependent variable ETA

Model 1

Model 2

L.ETA

0,3906***

(0,0945)

0,3314***

(0,0863)

Bank-specific characteristics

NPL

-0,1812***

(0,2499)

-0,1750***

(0,2461)

ROA

0,1718***

(0,7270)

0,1061***

(0,7523)

-0,1659***

(0,1013)

-0,1035***

(0,1232)

LGR

0,0174***

(0,0024)

0,0147***

(0,0027)

-0,2680***

(0,5645)

-0,3767***

(0,7296)

LDR

0,0025***

(0,0000)

0,0031***

(0,0000)

OWN1

0,2002**

(0,5815)

OWN2

-0,2564***

(0,7532)

OWN3

-0,1227*

(0,1062)

Industry Competition

HHI

0,4246***

(0,1109)

CR4

0,1235***

(0,4785)

Macroeconomic variables

GDP

0,1574**

(0,2140)

0,1899***

(0,2273)

INF

0,0172***

(0,0227)

0,0042***

(0,0235)

LnER

-0,1162**

(0,2879)

-0,1405**

(0,5816)

CONS

-0,6528***

(0,2772)

-0,6840**

(0,3112)

Obs.

323

No. of banks

No. of instruments