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D. Murali

INVESTORS pay great attention to numbers, so do regulators to back their decisions, both micro and macro. Normally we don't pause to ask if the cup of economic and financial statistics is `half full or half empty'. But that's what William White, Economic Adviser, Bank for International Settlements, sought to answer early this month in his keynote presentation at an Irving Fisher Committee conference in Basel.

"Statistics had their beginning with a wish to measure the state of the here and now, albeit with the usual reporting lags," he observes. However, over time, "interest began to shift to more forward-looking statistics which might indicate how the world could evolve over time." Something important for marketers and money-makers, yet there is considerable uncertainty as to "the relevance and the reliability of the numbers" collected or calculated, he points out.

To explain, White discusses four questions: Are we measuring accurately what we want to measure and do we have a clear sense of what the data are for? Is the quality of data okay? How far is inter-temporal and international consistency present? And, are we doing enough even to know where we are, much less where we are going?

First question is about methodology. Statistical experts and new models abound "to measure and price financial risks of various sorts" even as there is a growing importance of financial markets in the modern world, "with their promise of greater efficiency but also greater instability". But White cautions: "Our theoretical frameworks "often have serious shortcomings." For example: "Does rapid growth in GDP really measure an increase in human welfare if associated with unmeasured increases in hours worked (with mobiles and laptops we are all on call all the time), or if earned through great environmental degradation (as increasingly evident in a number of emerging market economies)?"

A measurement problem that White mentions in the context of private wealth is: "As house prices increase, the measured wealth of the housing sector increases even though the future liabilities of households (higher implicit rents on the same properties) have gone up. There is something odd here. And it becomes all the odder, and more worrisome, when we realise that in many countries the household sector has reduced its saving rate dramatically in response to these measured wealth increases."

On the second issue of data quality, the speech notes how data for emerging markets tends to be of lower quality, though these countries are of global importance. India and China account for 30 per cent of the world's growth in real GDP, but there are "no reliable numbers" of commodity "stock-building in China". Again, though house prices play a large role in economic cycles, many countries don't have reliable statistics on this.

On the third issue, comparability, less said the better, because of huge gaps. Inter-temporal comparison of a company can pose challenge for analysts. Across firms and boundaries, source data tends to be "idiosyncratic", with varying accounting practices; deviations are not well described, "perhaps because it would simply be embarrassing to do so"; and there is "too much national discretion as to how things should be done".

Finally, though there is "more bang for the statistical buck" statistical resources are not in sync with shifts in the real economy such as newer products in the financial sector, and services overtaking manufacturing. As a result, "we continue to know too little about developments that are becoming increasingly relevant to our future".

If we don't pay attention to timeliness and reliability of statistics, that old joke about lies and damn lies would only be vindicated.

dmurali@thehindu.co.in

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