The other day I came across a study by some economists (unfortunately I have misplaced the document) arguing that intervention in the exchange market is not only ineffective but sometimes produces changes in prices opposite to what the central bank intends: in other words, for example, the dollar may fall against the rupee on the day the RBI buys dollars in the market. The conclusion was, as usual, supported by statistical correlations. What puzzled me was one question: the analysis should really compare where the level of the exchange rate would have been in the absence of intervention, with where it actually was after the intervention, and not merely the actual price movement. The problem, of course, is that the level of the rate in the absence of intervention, is a "known unknown", but drawing conclusions only on the basis of what is known can lead to illogical conclusions. To elaborate, if the exchange rate started at, say, 40 and ended the day at 39.50 after the RBI had bought a few hundred million dollars, does it prove the counter-productivity of the intervention effort? To my mind, no. The actual comparison should be between the admittedly unknowable level in the absence of intervention, and the actual level. For instance, if there were a way to know that the rate would have gone to 35 in the absence of intervention, then clearly intervention has been successful.
In a broader context, the point is that we often confuse correlations with cause and effect, the messenger with the cause of the message, and then come to often counter-productive administrative actions. To quote two recent instances, consider the ban on export of certain products, cement and rice for example, and the ban on trading in futures contracts on some commodities, both imposed in recent weeks by the authorities in a bid to substantiate their anti-inflation credentials. In fact, as politically sensitive food prices remain high, more than 40 countries have banned the export of various grains and other eatables. To my mind, such actions can be counter-productive in relation to the price level, and also more generally:
Perhaps the most interesting example of confusing correlation for cause and effect is the ban on trading of several commodity derivatives. But more on that next week.
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