Is mass immigration really good for the economy, or is it a politically correct position backed by phony statistics?
Is unemployment really down, or is the government manipulating the data to make it look that way, conveniently ignoring those who are underemployed or have given up looking for work?
Is the reliance on statistics, in general, an elitist tool for imposing a particular agenda on people, or is it a legitimate way of obtaining information in order to formulate policy based on fact rather than intuition, prejudice or self-interest?
The question of the role of statistics in society has become an increasingly vexing one, with broad ramifications. Those rows of numbers, the tables and graphs, the dry data of experts, has become a nexus of seething emotions. For some, the data is the basis of fact, the anchor of truth and the answer to urgent social questions. For others, it is academically rigged, cooked-up lies and misinformation, smoke and mirrors to get you to go along with ideas and policies that serve others but not you.
For decades, governments, businesses and scientists have used statistics for everything from drawing up voting districts and tracking the spread of bird flu to profiling the insurgency in Iraq and predicting what kind of touch screen you’ll buy.
But in recent years, resistance to the influence of statistics has grown. Just as bacteria develop resistance to antibiotics over time, distrust has led many people to develop immunity to statistics. They have been made to consume them day in and day out for many years — and now the effect is wearing off. The numbers do not seem to make their lives any better; they suspect, in fact, that they are used to make them worse while making things better for others, namely, for the propagators of those statistics.
Easiest to understand is the growing disbelief in election polls. That’s a predictable result of too many instances where expert predictions have been outvoted on Election Day.
More problematic is the public suspicion about official data concerning such issues as immigration and unemployment, where the facts are not subject to the irrefutable test of election returns.
For example, in Britain, a research project conducted recently by Cambridge University and YouGov found that 55 percent of the population believes the government “is hiding the truth about the number of immigrants living here.” For those people, no amount of statistically based argumentation will persuade them that immigrants are good for the economy. They choose to believe instead the evidence of their own eyes, which see foreign workers willing to work for less pay taking over jobs.
It’s the same in the U.S. For years, liberal policy-makers have been saying that the country has historically been built on immigrant labor and talent, and that it’s a democratic tradition from which everyone benefits. There’s a great deal of truth in that. But it doesn’t help the guy who lives in the Rust Belt who has to compete with illegal immigrants who work for next to nothing.
The Brexit decision pitted the elites against the ordinary Briton. The politicians, economists, bankers and their European colleagues formed a solid consensus of expert opinion that leaving the European Union would be disastrous for the British economy. The ordinary citizen didn’t believe them and completely rejected their facts and analysis. The Brexit vote was a declaration of independence not only from the European Union but from the insufferable know-it-all-ism of the experts in Britain as well.
But if scientific research and statistical analysis cannot be relied upon, what then? How does a country the size of the United States or the United Kingdom formulate policy on the great issues? How do policy-makers ascertain how large socio-economic groups are faring without collecting information about them? How to allocate government funds to communities without knowing how many people live there and what their needs are? How to find out what people want without asking them?
Statistical methods, as much as they are suspected and resented, will not go away. This is not due to malevolence or mere habit. Rather, because the value of having data has been proven over and over again, the people who wield them will continue to do so.
However, some predict, with a difference. In the future, statistics will, to a large extent, go underground. They will be used just as much by politicians and marketing strategists (not necessarily the same thing) — but secretly. The experts and their customers will learn — as they already are learning — to crunch their numbers with their mouths closed, so the public doesn’t hear and get annoyed.
Of course, government will continue to grind out official numbers for public consumption: unemployment up, unemployment down. But politicians will likely make less use of them, relying more on the old-fashioned stuff such as anecdotal evidence, appeals to sentiment and populist rhetoric.
Maybe that’s the best idea. Instead of totally rejecting statistics, policy-makers should evaluate them with care and not treat them as the sole deciding factor when formulating a course of action. The number-crunchers will still be there in the background, but we will hear less about them.