How to read an economic survey well

A survey's design determines its findings; understanding the logic behind measurement is key to interpretation, says TN Ninan.

Neilsen has put out its latest quarterly survey on the consumer mood in 60 countries.

For the last few quarters, and earlier too, Indians have turned out to be the most optimistic — sometimes by substantial margins over the next country in the list.

This is the case even when half the respondents believe that the economy is in a recession. Which makes you wonder — are we surveying those who might do relatively well through the business cycle, so long as the economy is growing?

The surveys are done online, and Nielsen recognises that internet penetration in India is no more than 11 per cent. How representative is that?

That question can be asked of other international surveys and rankings, some of which have gained currency in recent times.

There is, for instance, the Global Competitiveness Index, constructed for more than three decades by the World Economic Forum.

It has always been a mystery why the fastest growing economies are never seen as the most competitive.

In Asia, for instance, Singapore and Japan are seen as the most competitive, well ahead of China.

The trick is in the definition of competitiveness, as factors that define the productivity of a country. In turn, productivity is seen as setting a country’s level of prosperity.

Fair enough, so why not call it a productivity index? Other factors that allow a country to grow rapidly, and for companies in that country to grow rapidly, don’t seem to influence the list — like high investment rates and competitive currency rates.

It’s no different with the Corruption Perceptions Index, put out by the Berlin-based Transparency International.

The index assesses public sector corruption, and is based on third-party surveys, but this is a tricky thing.

Some might contend that a candidate for being termed the most corrupt (or corrupting) country in the world is Switzerland.

For decades it has prospered by welcoming and hosting stolen or tax-dodged money on the strength of guaranteed banking secrecy.

Swiss banks have also pocketed pre-War German Jewish wealth, and treat whistle-blowers as thieves who have stolen bank secrets — secrets that may be about stolen money.

If you have seen The Wolf of Wall Street, you will get the picture.

Is this public sector corruption? In a manner of speaking, yes, because it is the state that has passed enabling laws.

But that is not in the index, and so Switzerland does well on corruption perception.

It took the Americans to read the riot act to the Swiss, and they are now cleaning up their act, at least partly.

The point is that words have different meanings in different countries, and they can be used in subtle ways to influence debate.

For instance, two leading American universities (Yale and Columbia) have been putting out country listings on an Environment Performance Index that they have constructed. Which countries have the best scores on the index?

You guessed it: Switzerland, Luxembourg, Australia, etc. And which countries have the worst record? Poor Somalia, Mali and Haiti. In a way, this makes sense.

If you look at the quality of air or water, the rich countries do well and the poor ones don’t. If you look at vulnerability to environmental degradation, the poor ones are more at risk.

But how about the role of greenhouse gas emissions? Australia in particular has among the highest emissions per capita.

The index factors this in, but the importance it gets would seem to be marginal, or the country would not be a star performer on the index.

Measurement is an old tool for controlling thought processes — what you measure, how you measure it, who does the measurement, and how you use the findings are all important.

So the next time you cite such survey findings at a conference or in something you write, take a little care to understand what they mean, and don’t mean.