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Balanced bank credits for balanced economic growth in India

Balanced bank credits for balanced economic growth in India
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The study found that, there is a very close relationship between bank credit to a sector and contribution of that sector to GDP in the entire three sectors. The study also found that, there is an imbalanced growth in Indian economy over the years.

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Balanced bank credits for balanced economic growth in India

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  1. International Journal of Management (IJM)
    Volume 8, Issue 4, July– August 2017, pp.52–59, Article ID: IJM_08_04_007
    Available online at
    http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=8&IType=4
    Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com
    ISSN Print: 0976-6502 and ISSN Online: 0976-6510
    © IAEME Publication

    BALANCED BANK CREDITS FOR BALANCED
    ECONOMIC GROWTH IN INDIA
    Sanjaya Jena
    Research Scholar, Department of Business Administration,
    Sambalpur University, Odisha, India

    ABSTRACT
    Indian economy is based on three pillars such as agriculture sector, manufacturing
    sector and service sector. For the balanced economic growth in India, all the said
    sectors should grow simultaneously. Any imbalance in the Growth among the three
    sectors create problem for the economy in the form of inflation, import etc. Secondly,
    bank credits to business and economic growth rate are positively correlated (Suna
    Korkmaz, 20151; Rashmi Umesh Arora 8). By considering the above two cases the
    present study has given an effort to find out the degree of association that exist between
    bank credits to a particular sector and contribution of that particular sector to GDP.
    So that, by controlling bank credit to a particular sector, policy makers can control the
    whole economy for a balanced economic growth. The study found that, there is a very
    close relationship between bank credit to a sector and contribution of that sector to
    GDP in the entire three sectors. The study also found that, there is an imbalanced
    growth in Indian economy over the years. Service sector is growing faster than
    manufacturing and agriculture sector. Agriculture sector is growing slowly as compare
    to the other two sectors. There is a need and big opportunity in the economy to
    accelerate primary and secondary sectors through bank credit accelerator to bring the
    three sectors in to a common hide which is being neglected over the years in Indian
    economy. The study afraid and guess that, this might be the reason of present agrarian
    distress, inflation etc. in India. So the study has suggested that, bank credit can be used
    as an instrument to manipulate the growth of a particular sector to keep the economic
    imbalances under control.
    Key words: Agricultural Sector, GDP, Manufacturing Sector, Service Sector.
    Cite this Article: Sanjaya Jena, Balanced Bank Credits For Balanced Economic Growth
    in India. International Journal of Management, 8 (4), 2017, pp. 52–59.
    http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=8&IType=4

    http://www.iaeme.com/IJM/index.as 52 editor@iaeme.com

  2. Sanjaya Jena

    1. INTRODUCTION
    To accelerate the pace of economic growth, Indian policy maker took economic reform in the
    year 1991. One of the major components of this reform is financial reform. After financial
    reform Indian financial sector experienced a wide range of changes, specifically Indian banking
    sector. Private Banks were allowed to enter in to the market. Scopes were provided to both
    private and public banks to adopt a liberal credit policy in providing loans and advances. The
    intention behind this might be to fulfil the shortage of funds to finance trade and commerce.
    The objectives of this liberal credit policy was to raise GDP growth rate of India through raising
    production of goods and services in different sector such as primary or agriculture sector,
    secondary or manufacturing sector and territory or service sector which are treated as three
    pillars of Indian economy (Ric Shand and S.Bhide2). The said three sector need to be grown at
    equal rate and their contribution to GDP should also be same. If a particular sector grows with
    a high rate as compare to other sectors then, it creates imbalances in the economy due to
    mismatch between supply and demand. The present study has concentrated on establishing the
    relationship of bank credits to a particular sector with the contribution of that particular sector
    to GDP and how much of funds need to be injected in a particular sector to maintain a balanced
    economic growth.

    2. SIGNIFICANCE OF THE STUDY
    Assessment of the effectiveness of bank credit for the development of particular economic
    activities is necessary to prepare further strategic plans. The present study has tried to establish
    the relationship or association between loans and advances to different sector and the
    contribution of that sector to GDP. The study may be an information source for banks working
    in India and also for the policy makers to prepare strategic plans for sustainable and balanced
    economic growth.

    3. OBJECTIVES OF THE STUDY
    • To know the degree of association between bank credits to a particular sector and contribution
    of that particular sector to GDP.
    • To analyze the changes of bank credits in different sectors over the years.
    • To predict the amount of funds need to be offer to the economy to have a balanced economic
    growth.

    4. REVIEW OF LITERATURE
    Suna Korkmaz (2015)1 has undertaken a study named “Impact of bank credits on economic
    growth and inflation” to test the relationship between domestic credits & inflation and GDP in
    European Countries and found that, domestic credits has no impact on inflation but effect
    economic growth. Z. Yakubu and A. Y. Affoi (2014)3 in their study named “An analysis of
    commercial Banks’ credits on economic growth in Nigeria” reached in a conclusion that, bank
    credits has a significant impact on economic growth. The study has taken GDP as dependent
    variable and bank credit as independent variable. This result is further supported by a study
    conducted by Dr. B.C.Emecheta and R.C. Ibe (2014)4 named “Impact of bank credit on
    economic growth in Nigeria: Application of reduced vector Auto regressive (VAR)”. On a
    working paper, Neelam Timsina (2014)5 has examined the correlation between bank credits by
    banks in Nepal with the economic growth of Nepal and stated the existence of a strong
    relationship between the two variables. Fadi Hassan et.al.(2017)6 in a working paper found that,
    among the European countries, in Italy, the productive use of bank credits is less as compare to
    other countries such as France and Germany. Ujjal Bhuyan (2017)7 has conducted a study
    named “A study on the gross deployment of bank credits to various sector in the economy” and

    http://www.iaeme.com/IJM/index.as 53 editor@iaeme.com

  3. Balanced Bank Credits For Balanced Economic Growth In India

    concluded that GDP, interest rate, commodity price and propensity to consume influence bank
    credits in India. Rashmi Umesh Arora (2009)8 in a study named “Bank credits and economic
    development: An empirical analysis of Indian states” proved that bank effort to use resources
    somewhere neglect the development need in the different states in India. Ric Shand and S.Bhide
    (2000)2 has given concluding remark on a study name “Sources of growth in the Indian
    economy before and with reform” that high GDP growth rate has achieved through the high
    growth rate in agriculture, industry and service sector. The study found very rare work on
    establishment of relationship between credit deployment to different sector and their effect on
    contribution to GDP which has provided scope to undertake the study.

    5. RESEARCH METHODOLOGY
    The data involved under the study are secondary in nature. Data has been collected from official
    web site of RBI, IBA and NABARD. Data of 8 years from 2009-2016 has been used under the
    study. Linear Regression Model and Karl Pearson’s coefficient of correlation is used under the
    study. Bank credit is taken as independent variable and GDP is taken as dependent variable.
    GDP is taken at current price. The model used is:
    GDP = β1 + β2 Bank credit +u
    Where β1 = Intercept (GDP with no bank credit)
    β2 =slope coefficient (change in GDP with a unit change in Bank credit)
    u =Error term. (Effect of other factor on GDP)
    Including this, Line Graphs, Bar Diagrams are used to present the data diagrammatically.

    6. DATA ANALYSIS AND FINDINGS
    Fig.1 shows the relationship between bank credit to agriculture & allied activities and the
    contribution of agriculture and allied activities to GDP of India. The movement of the two lines
    are in the same direction. The absolute value of bank credit has increased by 2.12 times from
    Rs. 4157.41 billion in the year 2009-10 to Rs.8829.42 billion in the year 2015-16. The
    contribution of this sector to GDP has also increased by 1.93 times from Rs.10835.14 billion to
    Rs.20930.81 billion for the same time periods. However the Average increase in bank credit to
    agriculture sector is 13 % and the average increase in contribution to GDP is 12 %. The degree
    of association between the two lines is 0.96 which clearly shows a positive correlation between
    the two variables.

    Agriculture sector
    25000

    20000

    15000
    GDP
    10000
    Bank Credit
    5000

    0
    2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16

    Figure 1 Association between Bank Credits and contribution of Agriculture Sector to GDP.
    Source: Author, Amount in Billion Rupees

    http://www.iaeme.com/IJM/index.as 54 editor@iaeme.com

  4. Sanjaya Jena

    Manufacturing Sector
    30000
    25000
    20000
    15000 GDP

    10000 Bank Credit

    5000
    0
    2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16

    Figure 2 Association between Bank Credits and Contribution of Manufacturing Sector to GDP.
    Source: Author, Amount in Billion Rupees.
    Fig. 2 clearly indicates a strong and close relationship between the credits to industrial
    sector and the contribution of industrial sector to GDP. Here the absolute values of bank credit
    have increased from Rs.13114.51 billion in 2009-10 to Rs.27306.77 billion in 2015-16 which
    is 2.08 times more. Contribution of this particular sector to GDP has also increased 2.2 times
    more from 2009-10 to 2015-16. The direction of the change is almost equal. The mean value of
    increase in bank credit to manufacturing sector is 13 % and of GDP contribution is 14 %. Here
    the correlation coefficient is 0.99 which indicate the presence of high degree of association
    between the two variables.

    Service Sector
    80000
    60000
    40000 GDP

    20000 Bank Credit

    0
    2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16

    Figure 3 Association between Bank Credit and contribution of Service Sector to GDP, Source:
    Author, Amount in Billion Rupees.
    Fig.3 shows the data on service sector. In service sector, the growth in bank credit and
    contribution of service sector to GDP have increased by 2.12 and 1.97 times respectively from
    2009-10 to 2015-16. The average increase in loan and advances to service sector is same 13 %
    and 11 % for contribution to GDP. Here also the movement of the two graphs are in same path
    and coefficient of correlation is 0.99 which explains a strong positive correlation between bank
    credit and contribution to GDP.

    http://www.iaeme.com/IJM/index.as 55 editor@iaeme.com

  5. Balanced Bank Credits For Balanced Economic Growth In India

    Table 1. Bank Credit to different Sectors
    Year Agriculture Manufacturing Services
    2009-10 4157.41 13114.51 7267.9
    2010-11 4806.34 16045.76 8942.01
    2011-12 5466.26 19373.25 10229.60
    2012-13 5899.14 22301.79 11518.86
    2013-14 6659.79 25164.83 13374.51
    2014-15 7658.80 26576.27 14130.97
    2015-16 8829.42 27306.77 15410.67
    Source: RBI Database, Amount in Billion Rupees.

    30000

    25000

    20000

    15000 Agriculture and Allied Activities
    Industries
    10000
    Services
    5000

    0

    Figure 4 Bank Credit to different Sectors, Source: Author, Amount in Billions Rupees.
    The above bar diagram shows the deployment of bank credit to different sectors. Over the
    years the credit to industry sector is comparatively more than agriculture and service sector.
    Credit to industry sector is 3.15 times more than the agriculture sector and 1.80 times more than
    service sector. The credit to service sector is 1.75 times more than agriculture sector. However
    the increase of credit to different sectors from 2009-10 to 2015-16 are almost same at a rate
    more than two times.

    Table 2 Contribution of different Sector to GDP
    Year Agriculture Manufacturing Services
    2009-10 10835.14 11953.38 38300.51
    2010-11 13196.86 13969.15 45322.59
    2011-12 14990.98 15945.68 52980.25
    2012-13 16807.97 20749.50 54542.76
    2013-14 19024.52 22665.20 62118.42
    2014-15 19952.51 24387.76 70383.83
    2015-16 20930.81 26331.88 75531.40

    http://www.iaeme.com/IJM/index.as 56 editor@iaeme.com

  6. Sanjaya Jena

    80000

    70000

    60000

    50000
    Agriculture and Allied Activities
    40000
    Industries
    30000 Services

    20000

    10000

    0
    2009-102010-112011-122012-132013-142014-152015-16

    Source: RBI Database, Amount in Billion Rupees.

    Figure 5 Contribution of different sector to GDP, Source: Author, Amount in Billion Rupees.
    The contribution of service sector in absolute amount is far ahead in comparison to industry
    and agriculture sector. It is 3.53 times and 3.20 times more than agriculture and industry sector
    respectively in the year 2009-10. Where as in the year 2015-16 it is 3.61 times and 2.87 times
    more. The contribution of agriculture sector is lowest. Manufacturing sector is next to
    agriculture sector. The diagram clearly shows the imbalances between the contributions of
    different sectors to GDP.

    Table 3 Corelation Coefficient between Bank Credits to different Sectors and their Contribution to
    GDP.
    Contribution to GDP
    Agriculture Manufacturing Service
    Agriculture 0.959 – –
    Bank Credit Manufacturing – 0.998 –
    Service – – 0.988

    Table 4 Regression Analysis of Bank Credits to different Sectors and their Contribution to GDP.
    Scale Agriculture Industry Service
    Correlation 0.959 0.988 0.988
    Goodness of Fit (R Square) 0.921 0.977 0.978
    Adjusted R Square 0.906 0.971 0.973
    Slope co efficient 2.19 1.00 4.47

    http://www.iaeme.com/IJM/index.as 57 editor@iaeme.com

  7. Balanced Bank Credits For Balanced Economic Growth In India

    Table 5. Other Statistics
    Scale Agriculture Industry Service
    Mean(Bank Credit) 6211.023 21411.88 11553.5
    Mean % increase 13 13 13
    Standard Deviation(Bank Credit) 1511.662 5044.018 2719.699
    Mean(Contribution to GDP) 16534.11 19428.94 57025.68
    Mean % increase 12 14 11
    Standard Deviation(Contribution
    to GDP) 3449.437 5102.998 12287.99
    Contribution/Credit Ratio 2.66 0.91 4.94
    Allotment of credit Lowest Highest Average
    Contribution to GDP Lowest Average Highest
    Amount in Billion Rupees

    Table 6 Amount of Credits that had to be injected in to the Economy to have Parity in all Sectors.
    Bank Credit to Agriculture Sector Bank credit to Manufacturing Sector
    Year
    Actual For Parity Difference Actual For Parity Difference
    2009-10 4157.41 16150.59 11993.18 13114.51 40277.89 27163.38
    2010-11 4806.34 19357.30 14550.96 16045.76 47299.97 31254.21
    2011-12 5466.26 22853.67 17387.41 19373.25 54957.63 35584.38
    2012-13 5899.14 23567.15 17668.01 22301.79 56520.19 34218.4
    2013-14 6659.79 27026.36 20366.57 25164.83 64095.80 38930.97
    2014-15 7658.80 30800.52 23141.72 26576.27 72361.21 45784.94
    2015-16 8829.42 33151.00 24321.58 27306.77 77508.78 50202.01
    Amount of Credits that need to be injected in to the Economy to have Parity in all Sectors.
    (Expected)
    2017-18 9977.24 41156.00 31178.76 30856.65 95039.61 64182.96
    2018-19 11274.28 45830.31 34556.03 34868.01 105276.46 70408.45
    2019-20 12739.93 51018.84 38278.91 39400.85 116639.36 77238.51
    Amount in Billion Rupees

    7. CONCLUSION AND SUGGESTION
    In one side Agriculture sector provide livelihood to more than 60 % of people in India, Farmers
    are under stress and committing suicide, Price of agricultural product is increasing day by day
    and Bank credit to agriculture sector is lowest as compare to other sectors. In other side the
    degree of association between bank credit to agriculture and its contribution to GDP is
    significant and Productivity of bank credit (GDP contribution/Bank Credit) is good enough.
    Somewhere, the above sentences of the two sides are not matching with each other. So the
    present study strongly concludes and suggests that there is a immediate need to make necessary
    arrangement to provide sufficient funds to agriculture sector to accelerate GDP growth. The
    contribution of service sector to GDP is highest as per the findings of the study and there is also
    a strong relationship between the bank credit to service sector and its contribution to GDP.
    Though the degree of association between bank credits and GDP contribution is very high but,
    the productive use of bank credit in manufacturing sector is lowest. Necessary arrangement
    need to be undertaken by giving more importance to this sector. Perhaps this findings match
    perfectly with the concept of Make in India and more amount of bank credits to different sector,
    specifically agriculture and manufacturing sector, may increase GDP of India very sharply.

    http://www.iaeme.com/IJM/index.as 58 editor@iaeme.com

  8. Sanjaya Jena

    From 2009 to 2016 the bank credit has on an average increased to double which is quite
    encouraging. Effort should be given to continue the pace or to increase it. Agriculture and
    service sector are most consistence in receiving bank credit as compare to manufacturing sector
    where as agriculture and manufacturing sector are more consistence in contributing to GDP as
    compare to service sector.

    REFERENCES
    [1] Suna Korkmaz (2015); Impact of Bank Credits on Economic Growth and Inflation. Journal
    of Applied Finance and Banking. Vol.5, No.1, pp 57-69, ISSN-1792-6580, 1792-
    6599(online), Science press ltd.
    [2] Ric Shand and S.Bhide (2000); Sources of Growth in the Indian Economy before and with
    Reform. Journal of South Asian Studies, 23:S1, 221-237, DOI:
    10.1080/00856400008723410.
    [3] Z. Yakubu and A. Y. Affoi (2014); An analysis of commercial Banks’ credit on economic
    growth in Nigeria. Current Research Journal of Economic Theory. 6 (2), pp11-15,
    ISSN2042-4841, e-ISSN 2042-485X, Max well scientific Organisation.
    [4] Dr. B.C.Emecheta and R.C. Ibe (2014); Impact of Bank Credit on Economic Growth in
    Nigeria: Application of Reduced Vector Auto Regressive (VAR). European Journal of
    Accounting, Auditing and Finance Research, vol.2, No.9, pp11-21, Nov.2014.
    [5] Neelam Timsina (2014); Impact of Bank Credit on Economic Growth in Nepal. Nepal
    Rastra Bank, Working Papaer No.22, June 2014.
    [6] Fadi Hassan et.al. (2017); Bank Credit and Productivity Growth. Working Paper Series,
    No.008/Feb 2017, European Central Bank.
    [7] Ujjal Bhuyan (2017); A Study on the Gross Deployment of Bank Credit to Various Sector
    in the Economy. International Journal of Applied Research, (4), pp 308-312, ISSN 2394-
    7500.
    [8] Rashmi Umesh Arora (2009); Bank Credit and Economic Development: An Empirical
    Analysis of Indian State. Journal of Asian Public Policy, 2:1, 85-104, DOI:
    10.1080/17516230902734502.
    [9] Wendrila Biswas, Public Private Partnership and Economic Growth with special reference
    to India – An overview. International Journal of Management, 7(3), 2016, pp. 18-26.
    [10] Settapong Malisuwan, Noppadol Tiamnara and Dithdanai Milindavanij. The Impact of
    Spectrum Assignment on Economic Growth and Competitiveness in Thailand. International
    Journal of Management, 6(12), 2015, pp. 11-21.

    http://www.iaeme.com/IJM/index.as 59 editor@iaeme.com

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