The global crisis has helped us refocus our attention on a number of questions that were put on backburner earlier. How much regulation is too much? Are repressive financial policies the solution for fixing financial crises? Over the years, the intellectual support to banking regulation swung between extremely thin or �free� banking to an outright interventionist approach. Interventions, argued advocates of �free� banking, act as a tax on the intermediary system, depress the real interest rate and incentive to save, thus reducing productive investment and ultimately hindering economic growth. The solution prescribed was to liberalise the financial market to allow for the financial deepening that would lead to efficient channelling of resources. On the other hand, the theoretical justification for stringent financial regulation is based on asymmetric information problems. �Free� banking is argued to be at the heart of the financial crises in recent times as liberalisation leads to risky lending behaviour. There is no theoretical consensus on the impact of deregulation on the financial sector and economic growth. Empirical evidence is mixed. Thus, optimal financial policies are purely an empirical matter in a specific institutional and temporal context.

In this short note, we attempt to answer these questions. RBI data from January 1990 to July 2009 is used for the analysis. Lending and deposit rate ceilings and floors are combined in a principal component analysis, to arrive at the index of interest rate regulation. SLR, CRR and priority sector lending constitute the index of prudential regulation whereas the index of bank regulation is an all-encompassing index of interest rate and non-interest rate controls. These indices, shown in panel 1, capture the extent of deregulation till 2005, RBI�s effort to use these measures to manage the credit boom till 2008 and the crisis response from then on.
Panel 1: Time plot of indices of bank regulation, credit to private sector and investment in government securities
Source: RBI, 2009
Autoregressive Distributed Lags (ARDL) regression, which decomposes the short-run and long- run relationship among the variables, shows that banking regulation is a significant determinant of bank credit in the long run. However, the index of industrial production, a measure of economic activity in the economy, does not have much impact on private credit. This is in line with the fact that bank credit to the private sector was mainly driven by consumer credit during most of the sample period. The short-run results exhibit a stronger impact of regulation on credit growth indicating that banks respond quickly to new opportunities. On the contrary, financial deregulation has a dampening effect on bank investment in government securities and helps channel resources to private sector. Overall, the results support the view that deregulation led to efficient resource allocation in the post-reform period in India.
When the analysis is repeated for the sub-sample January 2005 to July 2009, as a robustness check, we find a negative association between regulation and credit growth, albeit insignificant, indicating RBI�s success in dampening the credit boom. In the upswing of the credit cycle in 2005-2008, RBI has managed to force banks to increase their capital cushion and strengthen their liquidity as asset prices, especially housing and real estate, boomed. Decomposing bank credit shows that the credit growth fuelled by deregulation seems to be completely unlinked to production indicating that credit was channelised towards consumption and refinancing rather than production. Thus, there is need for measures to encourage lending to the non-financial business sector.
These results show that the problem with banking regulation is not so much the fact of regulation but the type of regulation. Thus, what is required is a regulatory framework that is adaptable to changes in the macroeconomic environment rather than complete deregulation. Indian experience shows that banking regulation could be effectively used in containing macro-financial risks using macro-prudential tools.