Governor Dr. Subbarao, Prof. R. Radhakrishna, Chairman, National Statistical Commission, Dr. Aurel Schubert, Director General, Statistics Department, European Central Bank (ECB), Deputy Governor Dr. Subir Gokarn; other distinguished speakers Prof. J.R. Varma, IIM Ahmedabad, Prof. Probal Chaudhuri, ISI Kolkata and Prof. Amit Bubna, ISB, Hyderabad; Deputy Governors, colleague Executive Directors, distinguished guests from the financial sector and academia, members of the press, Shri A. B. Chakraborty, Officer-in-Charge, DSIM and friends. I extend a warm welcome to you to this Statistics Day Conference.

29th June is celebrated as Statistics Day to commemorate the sterling contribution of Prof. Prasanta Chandra Mahalanobis to statistics and the Indian statistical system. In addition, the Reserve Bank also holds an annual Statistics Conference, which provides a forum for interface of our statisticians with academia, external experts and with operational departments. These two annual events provide us an opportunity to review the progress of statistical work in the Reserve Bank and guide us in setting the agenda for further work. I am sure, today's conference theme, Data Gaps and Central Banking, will reinforce that process.

In evidence-basedpublic policy and decision-making mechanism, statistics is a critical tool. At the same time, statistics is a public good. Over the years, there have been initiatives by the Government, the Reserve Bank and professional bodies like the Indian Association for Research in National Income and Wealth and the Indian Econometric Society for identifying data gaps in the Indian economy. The Report of the National Statistical Commission (2001) has helped in identifying major gaps in economic database on India.

In 2010, the National Statistical Commission had set up a number of professional committees to look into various issues relating to improvement in official statistics. The Report of the Reserve Bank’s Working Group on Surveys (2009) has also highlighted important data gaps. Improving database is an ongoing process. While several initiatives have been taken at the national level to bridge data gaps, I will focus on the recent initiatives of the Reserve Bank.

The Reserve Bank's policy canvas is large and goes beyond the rubric of a traditional central bank. We have the primary responsibility of compilation of banking and financial statistics as well as balance of payments statistics. We have also been compiling corporate finance statistics. We have been keenly aware of the need to constantly improve the statistics in terms of coverage, quality, frequency and level of dissemination. We participate and generally conform to the various international standards such as the IMF's SDDS and the BIS data bank programme. We have been a part of the G20 data gap initiative that has identified a number of new areas for data collection. Let me now turn to some of the recent initiatives.

First, our banking statistics coverage extends beyond the standard monetary and regulatory attributes to cover socio-economic dimensions. We maintain a database of the vast branch network of commercial banks. We have recently provided on our website a facility of Bank Branch Locator which is a dynamic tool giving information on various characteristics of bank branches such as location and population group.

Second, our recent efforts on data dissemination include: introduction of a user-friendly data warehouse interface with dashboards and time-series formatted reports; bringing out several regular statistical publications directly from the data warehouse, and updating them almost on a real-time basis; dissemination of information through web-publication as the initial point and its synchronisation with the data released on DBIE; and advances in integration of XBRL data collection system directly with data warehouse to eventually replace all existing stand-alone data compilation systems.

Third, a significant recent achievement on external accounts statistics was our contribution to the Co-ordinated Direct Investment Survey (CDIS) of the IMF. This large database provides information on country-wise inward and outward direct investment. On the Balance of Payments (BoP) statistics, we have implemented the Sixth edition of IMF’s Manual, ahead of many advanced economies.

Fourth, the Reserve Bank conducts several quarterly forward-looking sample surveys in the areas of industrial outlook, consumer confidence and inflation expectations to aid monetary policy making. The results of these surveys are now disseminated in public domain simultaneously with our quarterly report on Macroeconomic and Monetary Developments accompanying the monetary policy statement.

Fifth, we have expanded the coverage of our house price index (HPI) based on transaction prices obtained from housing registration authorities to nine cities from seven cities. We expect to add four more cities this year. In parallel, we are developing an Asset Price Monitoring System (APMS) for tracking movements in house prices based on housing finance data available with banks and housing finance companies.

Finally, given the increasing analytical requirements, the Department of Statistics and Information Management (DSIM) was re-organised with added emphasis on research. A structured research agenda was developed to align institutional requirements with individual capabilities. In 2011, 23 research papers were published in various national and international journals with another seven papers published in RBI working paper series.

While these achievements are significant, let me highlight some broad areas where we need to focus to further refine the statistics generation process in the Reserve Bank.

First, it is important to further improve our database of banking infrastructure in the country in order to gauge the extent of financial inclusion and assess the efficacy of various policy actions taken in this regard. Efforts should be made to make available all granular banking data, including those collected through the basic statistical returns (BSRs), on our website through the Database on the Indian Economy (DBIE).

Second, there is need for close co-ordination between statisticians and bank supervisors, both in the commercial and cooperative banking space, to identify and mitigate data gaps in the supervisory review process and also to facilitate appropriate risk assessment for the banking system.

Third, the data reporting system needs to be geared towards automated data capture from the source systems. It is imperative to scrutinise and validate the data used for analysis through application of data filters, so as not to accept data at the face value and also to identify and reduce the noise element inherent in large data sets. This will make macro-financial data more useable. In keeping with the Reserve Bank’s IT Vision, the efforts should be to automate data flow from the reporting entities through adoption of appropriate straight-through-processing systems. The use of data warehouse for processing should be strengthened for improving quality, integrity and delivery of data.

Fourth, “inflation expectation” has come to occupy a central place in our monetary analysis. In this regard, the quarterly forward-looking inflation expectations survey for households (IESH) provides vital inputs in the monetary policy formulation process. But, it is urban-centric as the coverage is limited to 12 cities at present. There is, therefore, a need to further broad-base the coverage for better encapsulation of the heterogeneity of expectations in our system.

Finally, forecasting of key macroeconomic variables has become difficult in the aftermath of the global financial crisis as the feedback loops between the global and the domestic economy, on the one hand, and between the financial and real sectors, on the other, have become more complex. In this context, it has become difficult to make reasonable impact assessment of macro-policies. Moreover, the capability of standard models in the armoury of central banks in predicting growth and inflation is being questioned. Primary assumptions of basic DSGE models have come under attack both from policymakers and academia. There is, therefore, a need to revisit the modelling strategy in the light of the increased uncertainty, leverage and global linkages. It is important to harness appropriate statistical tools to capture the underlying dynamics of economic-financial framework.

Ladies and gentlemen, we are fortunate to have amidst us luminaries who are not only accomplished statisticians but some of them are at the helm of statistical administration. I am confident that the deliberations today will not only guide us in setting our statistical agenda in the Reserve Bank but also will go a long way in strengthening the Indian statistical system, for which Prof. Mahalonobis worked tirelessly.

I once again extend a hearty welcome to all our speakers and all our invitees, and look forward to the intellectual fare ahead.

Thank you.