conditions can change quickly over a very short period of time, as evidenced by the ongoing global financial crisis. we, therefore, need a renewed focus on assessing cyclical conditions through leading indicators, including supportive research on macroeconomic linkages, time series and seasonal adjustment, business cycle analysis, short - term business indicators, sensitivity analysis, and detailed analysis of quarterly results of the financial and non - financial companies to assess the impact on the real sector. the slew of surveys initiated by the reserve bank over the past few years have been very helpful and these would have to be further expanded / strengthened as warranted. ( iv ) financial soundness indicators the global financial crisis has brought into focus the importance of targeting financial stability as an explicit variable. even as policy makers and regulators are still grappling with the precise definition and quantitative indicators of financial stability, there is a reasonable clarity on the symptoms of financial instability. the responsibility for ensuring financial stability implicitly rests with the central bank. one of the several tools required for monitoring financial stability is stress testing – a term that has now become widely used – but variedly understood. the united states has recently published the results of its stress tests with very positive outcomes in terms of shaping expectations and shoring up market confidence. europe too is undertaking stress tests. as part of the self assessment done by our committee on financial sector assessment ( cfsa ), we too performed stress tests for the banking sector which showed that our banks are safe, healthy and operating prudently. the stress tests done by the cfsa are a good beginning, but admittedly rudimentary. we need to refine both our database and our analytical capabilities for stress tests. this is another challenge for the reserve bank on the data and analysis side. ( v ) data on employment finally, i come to a major gripe. globally, trends in employment are one of the most important inputs in setting monetary policy response. unfortunately, we do not have any reliable nation - wide statistics on employment. data on factory - sector employment are available from annual survey of industry, but with a large lag that makes it virtually useless for monetary policy purposes. farm sector employment data are also available at poor frequency and with long lags. non - farm pay rolls capture employment trends in some economies. but, in india, data on organised sector employment, as obtained from employment exchanges, cover a very small part of the workforce. against this backdrop, timely and accurate information on employment conditions will enhance our

importantly, we have with us dr. wilbert van der klaauw, assistant vice president of the federal reserve bank, new york. dr. klaauw is heading the fed ’ s project team on inflation expectations, an area of keen interest, and may i add, perplexing challenge, to central banks around the world. once again, a very warm welcome to all of you to this annual conference. three challenges statistics and statistical analysis are central to a lot of what we do in the reserve bank. many of the decisions that we have to make and judgments that we have to form are based on analysis and interpretation of data. quite evidently, we are often plagued by incomplete, inconsistent or non - timely data. all of inductive learning is a progression along the intellectual hierarchy – from data to information to knowledge to wisdom. the relevance and effectiveness of our policy judgments, therefore, depend crucially on the quality of data and the efficacy of analysis and interpretation. it is important, therefore, for public policy institutions like the reserve bank of india, to focus on statistics and statistical analysis. to give this task a specific focus, i would like to highlight three challenges in the area of statistical analysis and interpretation that this conference can address. first, what are the gaps in the official data and data analysis and how do we bridge them? the quality of data that various official agencies, both in india and abroad, collect depends critically upon the completeness and accuracy of the responses. significant non - responses and time - varying pattern of responses can provide misleading information and result in suboptimal policy responses. but, how do we get credible and complete data, and that too in good time? in a liberalised economic environment, it is no longer possible to mandate submission of data or responses to surveys by official fiat or regulatory prescription. also, with globalisation, it is becoming increasingly difficult to get credible and timely information on cross - border flow of goods, services and capital. the first challenge, therefore, is what steps do the official data agencies need to take to ensure that data are comprehensive, consistent and timely? second, our official statistical agencies have made several efforts to improve the collection and dissemination of statistics. yet, there is scope for significant improvement in, for example, the construction of wpi or iip, where the coverage baskets have to be more representative of target populations. given the fast pace of changes in the structure of the economy in the face of dereg