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CONCLUSION

As our objective was to examine direction of cau­sality between credit deposit ratio and credit share ofthe major Indian states for the period 1972-2008, we have observed, by applying standard tools of time series econometrics, that for the entire period of study there is missing of such causality in most of the states.

But for short runs, with pre and post reform phases differently, we get the causality results for half of the states with the direction of causality runs from credit deposit ratio to credit share only. No reverse causation was found. At the same time there were bidirectional causalities in many cases. For the relatively backward states we get the result that rising trends of credit deposit ratio in both the pre and post reform phases have caused the falling trends of credit shares and for the relatively developed states rising trends of credit deposit ratio have caused rising trends in credit shares.

Future direction of research is to find out causal linkage between credit deposit ratio and other economic variables. Spatial analysis can be applied to find out causal direction between credit deposit ratio and credit share. This is our next research agenda.

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ADDITIONAL READING

Bhattacharya, P. C., & Subramonian, M. N. (2005). Trends and Components of Bank Credit in India. Finance India, 19(2), 1971-1999.

Enders, W. (2011). Applied Econometric Time Series. India: Wiley.

Gujarati, D. (2003). Basic Econometrics. USA: McGrawhill.

Kohli, H. S., & Sharma, A. (2010). A Resilient Asia Amidst Global Financial Crisis: From Crisis Management to Global Leadership (ed.), India: Sage Publications Private Limited in collaboration with Asian Development Bank.

Subrahmanyam, S. (1999). Convergence of Incomes across States. Economic and Political Weekly, 34(13), 769-778.

KEY TERMS AND DEFINITIONS

Banking and Finance: The banking and fi­nancial sectosr in India represent the institutions that play intermediatory role in economic func-

tioning. There are scheduled and non scheduled commercial banks operating in India under the Apex body of the Central Bank, The Reserve B ank of India.

The financial sector includes all the sectors in the money market except the banking sector. The reform in these two sectors has been a greater part of the Indian liberalization policy.

Credit Deposit Ratio: It is the proportion of deposit used for lending purpose after keeping aside the amount of statutory reserves in line with the guideline of the central bank. It also shows the efficiency of the banks in using their funds for real sector investments.

Credit Share: It is the part of total credit gener­ated in the total economy. In reference to our study on Indian states credit share of a state means the amount of credit generated by a particular state out of the total credit generated. It also shows the command of a state in the credit market.

Reform: The economic reform in India refers to ongoing economic liberalisation in India that started on 24 July 1991. In 1991, after India faced a balance of payments crisis, it had to pledge 20 tons of gold to Union Bank of Switzerland and 47 ton to Bank of England as part of a bailout deal with the International Monetary Fund (IMF). In addition, the IMF required India to undertake a series of structural economic reforms. As a result of this requirement, the government of P. V. Narasimha Rao and his finance minister Manmohan Singh (currently the Prime Minister of India) started breakthrough reforms, although they did not implement many of the reforms the IMF wanted. The new neo-liberal policies included opening for international trade and investment, deregulation, initiation of privatization, banking and financial sector, tax reforms, and inflation­controlling measures.

2.

3.

Unit Root, Causality and Cointegration: See the methodology section for detail.

ENDNOTES

As is well known, the ECM is a comprehen­sive linear regression equation specification which provides a description of the possible nature of interdependence of the short run movements of a pair of co-integrated vari­ables keeping in view the fact that they bear a long run equilibrium relationship.

Note that here yit = φ0 + φ1x,f + ε1it and xit = φ0 + φ1yit + ε2 it are alternative representations of the (population) long run equilibrium relationship between y and x, where ε's are the stationary error terms. As y and x are cointegrated, by the definition of cointegra­tion for some constants ω + ω. y., + ωx, = εit, where εit is a stationary error term and ω = (ω0, ω1, ω2) is the non- normalized cointegrating vector. Thus, by normalizing ω one may write the long run equilibrium relationship for (y,x) in either form as shown above.

This is for the following reason. If, for ex­ample, ECYt 1>0 for some i,t, it means that the realized value of yi exceeded the corre­sponding long run equilibrium level at t-1, given x Now since yi and χi are cointegrated, once a positive deviation from the long run equilibrium level takes place, the actual value must try to move in the opposite direction in subsequent time points in an attempt to restore the long run equilibrium and hence the negative sign of η and η

This work was previously published in Global Strategies in Banking and Finance, edited by Hasan Dinyer and Umit Hacioglu, pages 121-134, copyright 2014 by Business Science Reference (an imprint of IGI Global).

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Source: Banking, Finance, and Accounting: Concepts, Methodologies, Tools, and Applications. IGI Global,2014. — 1593 p.. 2014
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