Two things that I’ve found to be a universal truths are that,
- given the chance to blame someone else for a seeming failure, many politicians rarely look at themselves;
- given the chance to take credit for something, politicians rarely give that honour to someone else.
Economic statistics are a great area to see this in action. So, while Jamaica’s economy is doing better in many ways than it has for a long time, there are plenty of signs of some ragged edges. So, what follows is not about one set of numbers but worth thinking about as the gloss goes off the budding economic ‘miracle’ that was taking shape.
One of my good, good Jamaican business friends with a keen eye on what goes on here often suggests to me to write about my time working at the IMF; I keep refusing. I’m not ashamed or hiding any thing really terrible, but I find it more interesting, for the moment to let memories find their way out through some reconnections with current events. Maybe, one day when nothing much is going on in Jamaica, I’ll find the need to fill my days with a set of such reminiscences.
I was sparring this morning on Twitter with attorney-turned-mild-mannered curmudgeon, Gordon Robinson, about some economics data. I don’t need to defend those who compile economic statistics in Jamaica. I think they do they best they can to produce timely and accurate numbers, that meet a number of criteria, including international comparability. Many organizations have their hands in the economics data pie, and many countries are followers not leaders. especially in the area of so-called ‘best practices’.
One thing about a country and its economy is that even when you think that things look much the same as in another country the details can defy all comparison. But, many economics data compilers try to work with a framework to overcome those detailed differences, and produce aggregates that broadly mean the same thing. Just a simple example. Money is something that many people will think they know and understand, but sadly it’s not just a one-size-fits-all concept and can become a different matter when one thinks about how a country actually functions. We can all agree on cash (notes and coins) and often that will be the preferred measure because of its clarity and simplicity. But, once you have any kind of banking system, even one that may be highly dysfunctional, then other things that can act like cash start to matter. The simplest of these would be deposits, which can be used or drawn upon to pay. Already, you get into complications because while cash is cash, all deposits are not alike: some are immediately availabe, some may need notice, some come with chequeing facilities, some may be local currency, some may be in foreign currencies. Some may be in banks, some may be in other financial institutions. But, I wont bore you with the ramifications of those different configurations. I merely wanted to touch on how things can get complicated quickly.
The ‘argument’ centred around inflation statistics. Now, how prices are changing in an economy is hard to measure at the best of times, because they can move in a number of different ways and over different time periods. There are also so many of them that do not behave in linear ways, depending on quantities. Some are explicit, while others are implicit. But, bravely, statistical agencies go through a range of exercises to try to measure price changes. Most often, they design a so-called ‘representative basket’ of goods, and check on their prices in different outlets on a regular basis–daily, weekly, quarterly etc. Economists know this is not perfect not least because the basket, while good in general, can need refining faster than systems allow, so get out-of-date. Goods change in quality, sometimes in ways that are hard to perceive. But, until we arrive at a world where we can monitor all transactions in real-time and get that to feed automatically into some databank, these price ‘surveys’ and their ilk are about the best that can be done.
Of course, with things like prices, each person could tell you how close or far he/she is from the representative basket and also how he/she adjusts, if possible, and if desired to changing prices. (One odd socioeconomic phenomenon is how and why people do not automatically tend towards cheaper goods and services or goods and services whose prices are falling relative to those whose prices are rising. Many factors come into play in purchasing decisions, including ease of access, brand loyalty, access to information, and source of funding. So, one can often find situations where people complain about prices rising yet do little or nothing to mitigate that. Some of the relative inaction relates to budget constraints and how close people are to those limits. We also have situations which run counter to general concerns, such as people complaining about prices falling. Attitudes to price changes depend much on whether you are a supplier or consumer of the good or service.) So, the aggregate always has to contend with the stream of anecdotes that are readily available.
This tells us what?
No one should trust any data set without reservation. Those who produce them should never hesitate to highlight their general shortcomings and any particular problems with the latest set or with any past set, including if they needed to be revised, for whatever reason.
If you feel the data are misrepresenting realities, then you’d better come up with a viable and reliable way of countering those. Sometimes, various pressure groups do their own work to focus on their own group, and that may usually highlight differences of composition of goods, services, timing and other things. But, it’s no easy task to supplant national statistics and to also prove that at the outset and during the time when these alternatives are going to be in play that they have been constructed and collected in what all would agree are unbiased ways.
With a slight knee-bend to other professions, economics rarely has the luxury of anything called ‘incontrovertible evidence’. Even then, so-called open and shut cases sometimes end up inconclusive, at best, or upside down, at worst. That’s not to say that economics data are useless. Far from it.