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The Reserve Bank of India (RBI) believes that role of statistics has increased manifold with every passing crisis.
"The role of statistics in terms of data needs, surveys and sophisticated analysis in central bank policy formulation has increased manifold with every passing crisis. Policy issues have become more complex and information and analytical requirements have turned more demanding," said Urjit Patel, deputy governor, RBI in Mumbai.
According to Patel there is a continual need for upgrading researchers knowledge and skills in order to address current issues.
Patel highlight three areas of research that requires attention. First, the role of modeling and forecasting micro-economic variables is very critical for RBI policy formulation. "This has always been difficult in an economy like ours that is passing through rapid transition and we are rarely in a steady state," said Patel.
According to him the challenge is to develop models for forecasting and policy formulation with capture the dynamic behaviour of economic agents.
Second, surveys on macro-economic changes play an important role in forward looking monetary policy making. "While our Department of Statistics and Information Management has been regularly conducting high quality surveys on industrial outlook, inflation expectations, consumer confidence and so on banks has come to explore the scope of integration of results of these surveys in model building in order to enhance the utility for policy. We are happy to say that the surveys are overlooked by our high quality technical advisory committee with distinguished panelists and this has given us in management great confidence about the data that emanates from these surveys in terms of direct policy making," said Patel.
Besides that the last area is the considerable scope to enhance research capabilities to analyse financial market data, said Patel.
"Financial markets linkage with real sectors constitutes an important feedback channel directly and through the confidence. Statistical characteristics of financial market data are somewhat different. These are high frequency granular data which often show high degree of volatility. It has all the elements of big data which are often called fours 'Vs' namely volume, velocity, variety and volatility. But at the same time it is well recognised that it contains important forward looking information. How such data is to be analysed is itself a statistical challenge that should be addressed by our researchers at RBI," said Patel.
