Let us interpret data the right way: MInt 5th May 2012

The way we look at data is quite different from what happens globally, which should make us pause and reflect There has been considerable debate on the fallacy of our data systems. While this is important, another issue which is not talked of is how data should be interpreted. Do we look at month-over-month or average annual or cumulative or daily changes in economic variables? This is important because policy decisions are taken based on growth rates where often we may not really have an explanation and fall back on the “base-year effect” —one where present growth rates appear high or low on account of the low or high base on which these rates are reckoned. Also the way we look at data is quite different from what happens globally, which should make us pause and reflect. Let us look at inflation. The Reserve Bank of India (RBI) looks at annual growth rates and hence reckons March 2012 over March 2011 or February 2012 over February 2011 to gauge inflation. Globally, however, inflation indices are tracked across immediate months to conclude whether prices are coming down or going up. From the policy perspective, we ideally should look at average inflation rate as several components, especially food products are susceptible to seasonal fluctuations, which create spikes as removing seasonal effects is not easy to comprehend for the lay man. Households rarely relate with our inflation numbers. Inflation peaked at 10% in September and started coming down, but the index numbers kept increasing right up to March, which means prices were rising and not falling as the inflation numbers implied. The conundrum is stark when there is linkage of policy with this phenomenon. When RBI had its policy last month, it spoke of inflation at 6.9%, which was March 2012 over March 2011. Yet, average inflation was 8.8%. Different prescriptions could have been invoked if the latter was considered. In case of say industrial production, conclusions drawn become bizarre at times, when there are negative or low growth rates in a month followed by opposite extremes in the next. Industrial production typically builds up during the year and there are issues of reporting as well as demand conditions. Orders received could be executed any time, while demand has its own cycles. Consumer goods are in demand during festival time or in the post-harvest season. Capital goods growth is based on existing inventory, demand conditions as well as interest rates and could spread out during the year. This being the case, we should look at a cumulative build-up of production during the year, and an average concept of indices is more realistic. Therefore, while we could be distraught in December and January with low growth rates of 2.5% and 1.1%, respectively, February looked impressive at 4.1%. However, the average for 11 months was 3.5%. Export data, too, is a function of demand conditions from overseas customers and there are time lags between orders being placed and executed. Month-on-month growth rates could be puzzling and we need to cumulate exports during the year to draw comparisons. In the last six months there were extreme variations: Two negative growth rates, two at 4-5%, one above 10% and the last over 20%. Every time the analyst would squeeze in an explanation, only to be contradicted subsequently. Cumulative build-up would be more pragmatic. The same holds for imports. When we look at the capital market, it is even more intriguing. We always tend to look at the Sensex at a point of time and then conclude that market capitalization or the Sensex was up or down. Mutual funds present their net asset values at two points of time, influenced by the points chosen. Ideally, one should be looking at either monthly averages or annual total daily returns. This way the number is unbiased. Using such end points according to convenience may not be right as often there could be high levels of activity at these end points. Interpreting bank activity is also interesting as both credit and deposits jump up in the last week of March as targets are set to be met. Loans are disbursed for short terms—often inter-bank, while deposits move through the certificates of deposits route, only to decline in the first fortnight of April. Here, a better way is to stop at the mid-month level to gauge growth. For the reporting fortnight of 23 March, growth in deposits and credit were 13.4% and 17%, respectively, while after seven days the growth rates shifted to 17.4% and 19.3%, respectively. How does one judge their growth? Exchange rates and interest rates are different kinds of variables. Daily variations are useful when doing statistical analysis. But ideally for policy action, trends need to be studied and if aggregation is required, then monthly averages are more useful. Like the stock market, looking into daily reasons for movements, though enchanting, does not really add value to the policy approach. Clearly, we should interpret data in a more meaningful manner. Just like getting in high frequency data has not quite improved the accuracy levels, more real time interpretation is not only myopic, but could also lead to erroneous conclusions. Periodic reviews over a broader horizon are what may be recommended.