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Impacts on the Socio-Economic Development of Nghe An Province When NHTMCP Lends Capital to Enterprises in the Industry and Construction Sector


Research. This shows that the production and business performance of small and medium enterprises in the industrial and construction sectors is relatively good when using bank loans.

Second , the average outstanding loan ratio of each bank to small and medium-sized enterprises in the industrial and construction sectors is relatively large in the total loan fund, however, the ratio tends to decrease gradually during the research period. Part of the reason is that enterprises have gradually become self-sufficient in capital sources for production and business activities, and another part is that the loan fund of joint stock commercial banks also tends to increase in scale.

- Limitations for commercial banks themselves when lending capital to SMEs in the industry and construction sector

Although there are positive achievements for joint stock commercial banks when lending capital to small and medium-sized industrial and construction enterprises in Nghe An province, there are also limitations for banks when the average overdue debt ratio of banks tends to increase, causing difficulties in capital funds as well as risks in capital funds for banks.

3.2.4.2. Impacts on the socio-economic development of Nghe An province when commercial banks lend capital to SMEs in the industry and construction sector

Table 3.21: Some indicators on lending activities of commercial banks for SMEs in industry and construction and socio-economic development of Nghe An province

Criteria

2012

2013

2014

2015

2016

1. Outstanding loans of commercial banks

to 31.12 annually Billion VND


28,284


35,888


44,088


51,383


56,213

2. Gross Regional Domestic Product (GRDP)

Billion Dong.


59,812


51,078


54,566


58,282


58,606.9

3. Industrial and Construction Production Value Billion VND

13,266

11,138

12,551

13,326

14,579

4. Number of Enterprises on

DN province


6.251


6,890


7,250


7,695


8,406

4.1. Number of SMEs in the province

6198

6839

7,199

7,641

8,345

4.2. Number of SMEs in Industry and Construction

2,253

2,292

2,611

2,813

3,195

5. Number of employees working in labor enterprises

162,854

175,072

178,885

190,661

203,500

Tr.at. Number of employees

in SMEs in Industry and Construction


67,590


68,760


78,330


95,642


108,630

6. Average income per capita ( million VND )

21.22

22.96

26

29

28.54

7. Poverty rate (%)

19.35

17.38

14.4

12.3

10.4

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Impacts on the Socio-Economic Development of Nghe An Province When NHTMCP Lends Capital to Enterprises in the Industry and Construction Sector

Source: Nghe An Provincial Statistics Office


Comment:

- Positive impacts of lending by commercial banks to SMEs in industry and construction and the socio-economic development of Nghe An province

Regarding the number of enterprises in general in Nghe An province, there is an increasing trend during the author's research period, in which in 2012 the number of enterprises in the province was 6215 enterprises, in 2016 the number of enterprises in the province was about 8406 enterprises. Along with that trend of the province, there is a relatively strong increase in small and medium enterprises in the industrial and construction sector, in 2012 the number of these enterprises was about 2253 enterprises, increasing to 3195 enterprises in 2016. The number of small and medium enterprises in the industrial and construction sector accounts for a relatively large proportion compared to the total number of enterprises in the province (about 37.76% of the total number of enterprises in 2016). The rapid increase in both quantity and quality of enterprises has a relatively large support from loans from joint stock commercial banks.

Loans from commercial banks have contributed to increasing production value, creating more jobs, increasing workers' income, contributing to the state budget, thereby contributing to solving socio-economic problems of the province.

However, with small loan scale, short loan term, complicated loan conditions, the role of commercial banks in lending to SMEs in the construction industry and trade sector has limited contribution to the socio-economic development of Nghe An province. This is reflected in the low social labor productivity in the province (Construction industry production value/labor is 14,579 billion VND/172,975 workers = 84.28 million VND/year/worker), the average income per capita is not high (28.54 million VND/12 months = 2.378 million VND/person/month).

The weakest link in the lending activities of commercial banks for SMEs in the industry and construction sector is that the lending impact on structural transformation is still at an average and low level. Especially for the structural transformation of the technical level of enterprises, up to now the structure of modern technical level of enterprises is still low, the average technical level is still high.


3.3. Reasons for the limitations in the lending role of commercial banks in the development of SMEs in the industrial and construction sector in Nghe An province at present

3.3.1. Testing the relationship between factors affecting the role of lending activities of commercial banks and changes in the scale, structure and development quality of SMEs in the industrial and construction sector.

To test the relationship between factors affecting the lending role of commercial banks and changes in the scale, structure and quality of enterprise development, the thesis used a multivariate regression model to test the relationship between factors affecting the lending role of commercial banks and changes in the scale, structure and quality of development of SMEs in the field of industry and construction.

Specific results in the following three problems:

Problem 1: Analyze the relationship between factors affecting the role of lending activities of commercial banks and changes in the development scale of SMEs in the field of industry and construction.

The author conducts a test of the suitability of the regression model with the author's data set collected after the investigation process. The regression model the author chooses is a multivariate regression model, the results of the model test are as follows

Model Summary b



Model


R

R

Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Durbin-Watson

R Square

Change

F

Change

df1

df2

Sig. F

Change

1

.782a​

.612

.600

.794

.612

54,787

4

175

.000

1,864

a. Predictors: (Constant), NL_13, TCV_12, PL_5, NL_19

b. Dependent Variable: quan


ANOVA b


Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

172,793

4

34,559

54,787

.000 a


Residual

109,757

175

.631


Total

282,550

179


a. Predictors: (Constant), NL_13, TCV_12, PL_5, NL_19

b. Dependent Variable: quan


The model testing results show that, with Sig coefficient = 0.000, the author's research model is suitable.


The model has coefficient R^2 = 0.612, indicating that the independent variables in the model explain about 61.2% of the meaning of the dependent variable in the model.

Durbin Watson coefficient = 1.864

Then, the author regressed the model of factors affecting the lending role of commercial banks and changes in the development scale of SMEs in the industrial and construction sector, the specific results are as follows:


Coefficients a


Model


Unstandardized Coefficients

Standardized Coefficients


t


Sig.

B

Std. Error

Beta

1

(Constant)

-.977

.348


-2.809

.006


TCV_12

-.197

.127

-.078

-1.554

.122


PL_5

.615

.079

.443

7,820

.000


NL_13

.318

.075

.291

4,261

.000


NL_19

.183

.082

.149

2,220

.028

a. Dependent Variable: quymo

The research results show that: The variables in the research model are all statistically significant.

The thesis draws the following conclusions:

-The tighter the institutional environment, the more difficult it is for SMEs in the industrial and construction sectors to access loans, thus making it more difficult for businesses to change their development scale.

- The better the ability of enterprises to use loans, the better their ability to access loans from joint stock commercial banks, therefore, the better the ability of enterprises to change in scale.

- The better the capital mobilization capacity of joint stock commercial banks, the better the access to loan capital of joint stock commercial banks, the more positive the change in the development scale of enterprises will be.

Problem 2: Analyze the relationship between factors affecting the role of lending activities of commercial banks and changes in the structure of SMEs in the field of industry and construction.


The author conducts a test of the suitability of the regression model with the data set collected by the author after the investigation process. The regression model chosen by the author is a multivariate regression model, the results of the model test are as follows:

Model Summary b


Model


R


R

Square

Adjusted R

Square

Std. Error of the Estimate

Change Statistics


Durbin-Watson

R

Square Change

F

Change


df1


df2

Sig. F Change

dimension0

1

.913a​

.834

.830

.549

.834

175,200

5

174

.000

2.019

a. Predictors: (Constant), NL_13, TCV_12, PL_5, NL_11, PL_4

b. Dependent Variable: cocau


ANOVA b

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

264,427

5

52,885

175,200

.000 a


Residual

52,523

174

.302


Total

316,950

179


a. Predictors: (Constant), NL_13, TCV_12, PL_5, NL_11, PL_4

b. Dependent Variable: cocau


The model testing results show that, with Sig coefficient = 0.000, the author's research model is suitable.

The model has coefficient R^2 = 0.834, indicating that the independent variables in the model explain about 83.4% of the meaning of the dependent variable in the model.

Durbin Watson coefficient = 2.019

Then, the author regressed the model of factors affecting the lending role of commercial banks and the change in the structure of SMEs in the industry and construction sector, the specific results are as follows:

Coefficients a


Model

Unstandardized Coefficients

Standardized

Coefficients


t


Sig.

B

Std. Error

Beta

1

(Constant)

.247

.199


1,242

.216


TCV_12

1,840

.100

-.664

18,465

.000


PL_4

.248

.048

.234

5.123

.000


PL_5

.139

.071

.072

1,974

.050


NL_11

-.056

.047

-.047

-1.192

.235


NL_13

.223

.050

.193

4.465

.000

a. Dependent Variable: cocau

The research results show that: The variables in the research model are all statistically significant.


- The stricter the regulations of the State Bank and the State's macroeconomic policies are, the more difficult it is for SMEs in the industrial and construction sectors to access loans, therefore, it is more difficult to change the development structure of enterprises.

- The better the ability of enterprises to use loans, the better their ability to access loans from joint stock commercial banks, therefore, the better the ability of enterprises to change their development structure.

- The better the capital mobilization capacity of joint stock commercial banks, the better the access to loan capital of joint stock commercial banks, the more positive the change in the structure of enterprises will be.

Problem 3: Analyze the relationship between factors affecting the role of lending activities of commercial banks and changes in the development quality of SMEs in the field of industry and construction.

The author conducts a test of the suitability of the regression model with the author's data set collected after the investigation process. The regression model the author chooses is a multivariate regression model, the results of the model test are as follows

Model Summary b


Model


R


R

Square

Adjusted R

Square

Std. Error of the Estimate

Change Statistics


Durbin-Watson

R

Square Change

F

Change


df1


df2

Sig. F Change

dimension0

1

.942a​

.887

.884

.266

.887

272,963

5

174

.000

1,615

a. Predictors: (Constant), NL_19, PL_5, NL_2, NL_16, PL_4

b. Dependent Variable: chatluongphattrien


The model testing results show that, with Sig coefficient = 0.000, the author's research model is suitable.

The model has coefficient R^2 = 0.887, indicating that the independent variables in the model explain about 88.7% of the meaning of the dependent variable in the model.

Durbin Watson coefficient = 1.615

ANOVA b

Model

Sum of Squares

Df

Mean Square

F

Sig.

1

Regression

96,670

5

19,334

272,963

.000 a


Residual

12,324

174

.071


Total

108,994

179


a. Predictors: (Constant), NL_19, PL_5, NL_2, NL_16, PL_4

b. Dependent Variable: chatluongphattrien

Then, the author regressed the model of factors affecting the lending role of commercial banks and changes in the development quality of SMEs in the field of industry and construction, the specific results are as follows:


Coefficients a


Model

Unstandardized Coefficients

Standardized

Coefficients


t


Sig.

B

Std. Error

Beta

1

(Constant)

.664

.110


6,056

.000


PL_4

-.038

.022

-.061

-1.770

.078


PL_5

.292

.056

.258

5,183

.000


NL_2

.385

.031

.553

12,470

.000


NL_16

.191

.038

.209

5,037

.000


NL_19

.086

.026

.113

3.333

.001

a. Dependent Variable: chatluongphattrien


The research results show that: The variables in the research model are all statistically significant.

- The stricter the regulations of the State Bank and the State's macroeconomic policies are, the more difficult it is for SMEs in the industrial and construction sectors to access loans, so it is more difficult to change the quality of business development.

- The better the ability of enterprises to use loans, the better their ability to access loans from joint stock commercial banks, therefore, the better the ability of enterprises to develop.

- The better the capital mobilization capacity of joint stock commercial banks, the better the access to loan capital of joint stock commercial banks, the more positive the change of enterprises will be.

The regression results show that the institutional environment, the enterprise's loan utilization capacity and the lending capacity of commercial banks have a clear impact on the expansion of scale, structural change and improvement of the quality of operations of SMEs in the industry and construction sector.

3.3.2. Specifically, the limitations of factors affecting the role of lending activities of commercial banks in the development of SMEs in the field of industry and construction

3.3.2.1. The institutional environment for lending activities still has many shortcomings, and the level of local socio-economic development is still low.

Laws on lending activities have a great influence on the role of commercial banks' lending activities in the development of enterprises. The restriction or relaxation in State regulations on banking activities, regulations on whether to allow opening branches or not? What types of operations are allowed?... will directly affect


organizational structure, production and business operation plan of the bank, thereby affecting the decisions of commercial banks to lend to SMEs.

Another aspect is the regulations and policies on lending activities of the banking sector for SMEs: they have an impact on expanding lending activities or restricting lending activities to achieve planned goals, ensuring the safety of lending activities of the bank. The right lending policy for each type of customer will attract target customers, ensure the ability to make profits from lending activities on the basis of risk dispersion, compliance with the law, the State's policies and ensuring social justice. In order to increase credit growth for SMEs in the industrial and construction sectors, the bank's policies need to be established to suit the specific needs of this group.

The following table shows the results of the survey subjects' assessment of the impact of the legal, institutional and policy environment on the role of lending activities of commercial banks in the development of SMEs in Nghe An province.

Table 3.22: Actual survey results achieved on institutional environment and socio-economic development level affecting lending of commercial banks for the development of SMEs in industry and construction in Nghe An province


Average score of assessment of current achievements

Total comments

Average score

In there

M1

M2

M3

1. Law on lending activities for SMEs

297

3.29

3.23

3.41

3.23

2. State Bank policies and macroeconomic policies

297

3,187

3.25

3.12

3.19

3. Regulations on lending activities of the banking industry for SMEs

297

3,143

3.2

3.06

3.17

4. Institutions coordinate the management of lending activities for SMEs

297

2.83

2.95

2.65

2.88

5. Economic development

297

3.2

3.37

3.00

3.24

Source: Author's investigation results

The results show that a total of 297 responses collected by the author belong to three groups of subjects: state management officials, business representatives and bank representatives, the assessment score on a 5-point scale, the assessment level of reality achieved from the influence of factors such as laws on lending activities, policies of the state bank, policies

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