ALCOHOLICS and economists have something in common. Both have problems of addictions. Alcoholics have a soft spot for alcohol while economists have a fetish for hard statistics. A fetish is something that is abnormally stimulating and if left unchecked can push the fetishist to the dark side.
A fetish for statistics is not as bad as some other fetishes but it gives you a good idea of the relationship between economists and numbers.
Numbers count. Serious economists need statistics if they are to be counted and taken seriously. An economic viewpoint or paper which is not graced by statistics will not be taken too seriously, and the author will be in a state of disgrace.
Economists have ignored the admonition of “Statistics, statistics and damn lies” because it does not count.
Economists and analysts pine and whine over the availability of statistics. They wait with bated breath for the release of statistics throughout the year which is akin to waiting for the release of detainees from detention camps.
Official statistics somehow have more cachet over other types of statistics, but this should not be the case; these statistics have the aura that they are definitive and are truths.
Economists and analysts want more accessibility to the statistical but it is not an exaggeration to say that the official view is always to provide the minimum and to leave them panting. This policy leads to the Oliver Twist statistical situation of asking for more and is the reason for the pining and whining.
There are only a handful of statistics that have been popularised and that have become the lingua franca of the proverbial man in the street.
By now everyone has some working knowledge or has heard of the statistics, or knows someone who has heard of the Gross Domestic Product (GDP), Gross National Product (GNP), consumer price index (CPI), sales, exports, imports, foreign reserves, employment and unemployment, household income, wages, per capita income, poverty and inequality.
They have become like items on the national economic menu or name droppings.
Statistics usually are collected by the Statistics Department through a census, e.g. population census, which is very expensive or a survey. A census is a complete count while a survey usually is a sample survey and the better ones are representative of the universe of statistics.
A fundamental assumption of statistics is that when people are asked through a census or survey, they tell the whole truth and nothing but the truth. Of course, only fairies tell the truth; a Spanish Inquisition approach of using the rack could improve the response rate and accuracy of statistics.
It is a well-known statistic and fact that people who have been repeatedly surveyed are fatigued and fed-up of being asked for 50 years or more the same questions over and over again and from one generation to the next.
Refusing to respond, giving misleading statistics or lying as protests can be enticing. Indeed, the under-reporting of income is a very universal response whenever people are surveyed and asked for their income.
The richer they are the more they under-declare their income for tax reasons and because, despite the assurance of confidentiality, they are worried that the size of their wealth will be divulged to criminals.
Economists tend to use the averages or means of statistics. A lot are hidden from an average. No one, for example, really believes that the prices, as measured by the CPI, is reliable and represent the truth. People believe their own statistics on the prices that they see and pay at the corner mini-market or shop.
They find it hard to believe when the corner grocery shop prices have increased by 30%, while the CPI says that prices increase by only 3%, which is the average for about 60,000 retail outlets throughout the country.
Some statistics are volatile, while others are docile. Statistics on the stock market, quarterly GDP, and trade tend to be volatile and add excitement to the lives of those whose fortunes depend on them. The Gini coefficient, a statistic that measures the distribution of income, changes sedately even over long periods. Even so, it is doubtful that violent demonstrators check out first the state of statistics, e.g. what has been the level of the CPI or the Gini coefficient, before going down to the streets.
Meanwhile, one marvels at the unchangeability and stability of scientific statistics such as the value of pi (3.14159), which is the ratio of the circumference of a circle to its diameter, for even the most violent of protests will have no effect on their values.
What have been the most seminal and outstanding statistics that have appeared so far? Over the past 38 years, I think that the statistics on the incidence of absolute poverty, the inter-ethnic income disparity, overall income inequality and the ownership of share capital of bumiputras have been the most outstanding statistics because of their wide repercussions. And controversial too.
Before these statistics were released no one knew what the situation really was and so I remember the state of shock that greeted these statistics.
I remember in 1969, when I had been posted to the Economic Planning Unit after returning from England, and after the May 13 racial riots, the shocks that were palpable when the first statistical tables trickled in on income from the Post Enumeration Survey (PES) of the Population Census of 1970, ownership statistics from the Ownership Survey with reference year 1969 and later the estimates of absolute poverty.
A catatonic ambience was in the air and it was like receiving news of the deaths of people close to you. How could the statistics be so bad ? These statistics helped to launch the New Economic Policy.
I would hazard a guess that we need breakthroughs in generating new statistics. We need to better measure race relations, integration, segregation and fragmentation in the community. Reliable statistics can take the sting and deflate the extreme emotions.
Datuk Zainal Aznam Yusof is a member of the Economic Council and a distinguished fellow of ISIS Malaysia