by
Bill Bonner Recently by Bill Bonner: Measurable Improvements
We also have a way to vastly increase US household income – the feds have only to spend more money! Just add zeros. How about that? The poor family has not a dime more in real, spendable income…but we’ve managed – by clever use of mathematics and economics – to double its income. But that illustrates the nature of modern economics. It is all numbers…and none of them mean anything. And none means less than the zero. I’ve always been especially suspicious of the zero. It is a number. But a number is ‘something.’ The zero, on the other hand, is supposed to represent nothing. Well, which is it? Something or nothing? Nothing, right? But how can something be nothing? You say you have zero tomatoes. And you tell me zero is a number, used for counting. But how can you count tomatoes that aren’t there? You’ve either got tomatoes or you don’t. Zero tomatoes is a contradiction. It’s oxymoronic. And if the zero is actually nothing, how come you can put it after a number…and suddenly you have 10 times as much? Or, put it in front of a number…and you have 1/10 as much. How can nothing do all that? Now if I have 3 tomatoes and I add zero tomatoes, I have done nothing. I still have three tomatoes. But if I multiply my 3 tomatoes by zero, suddenly, I don’t have any tomatoes. If zero is nothing, I want to know what happened to my tomatoes. We didn’t have the zero for thousands of years. As far as I know, we got along fine without it. Numbers are a trap for economists. They make it look like science, but it is not science. Far from it. Initial conditions can never been controlled or fully understood. Instead, they are infinitely complex. Nor can results be reproduced. Nor can hypotheses ever be disproven. That’s why economists can cling to dopey ideas for centuries – they can never be disproven.
Using numbers, economists pretend to tell you something they don’t really tell you, often something they can’t possibly tell you. The unemployment rate, for example. The Bureau of Labor Statistics uses numbers like make-up. Put on enough of them, and you can make things look good…as long as you don’t look too closely. Behind every number is a wrinkle… Small numbers hide small ones. Big numbers hide big ones. A big number, such as the unemployment rate, has a Grand Canyon of wrinkles hidden behind it. There are the statistical adjustments…seasonal adjustments…and enough arbitrary definitions to make a corpse look good. BLS says that 7.8% of the workforce is unemployed. Simple enough. But what does it mean? What’s the ‘workforce’? And what does it mean to be ‘unemployed’? Think of all those people who work for cash…like the Latinos you pick up at gas stations for day work. Are they unemployed? How about the guy who couldn’t find a job, so he went back to school? Is he unemployed? What about the housewife who would like to find a job…sort of…but isn’t actively looking for one? Are these people part of the workforce? It’s obvious that you can change the assumptions a bit and change the reported unemployment rate a lot. When statistician John Williams looks at the US data, for example, he comes up with a real unemployment rate of 23% – almost as high as the jobless rate in Spain. And yet, the BLS tells us that US unemployment is 7.8%. Not ‘around 8%.’ Not ‘less than one in ten.’ But 7.8% exactly. And yet, there are so many greasy assumptions lurking in the cracks of this number that it is not only completely unreliable and practically meaningless, it is the downside of mathematics. It pretends to tell you something…but once you have taken it in you know less than you did before, because what you think you know is largely a fraud. The exact number of people who want a job and can’t get one is unknowable. It is unknowable because the people concerned don’t know it themselves. I saw a bum on the street in Baltimore the other day. He stopped me and asked if I could spare a dollar. I said I couldn’t give him a dollar. “Free money could adversely affect your moral character development,” I explained. Instead, I offered him a job. I had some work to do around the office; I thought I was doing him a favor. What do you think he said?
It begins with an “F”. Now, should that man be counted as unemployed? He certainly didn’t have a job. But if you offer a job to most people…what will they say? They’ll reply – maybe. Because it depends on a lot of things that even they don’t have the answers to. How much will they be paid? How many holidays will they have? How far will they have to commute? Will they get health benefits? And those are just the obvious questions. If you’re considering taking a job you also have to think… ‘What are my other options?’ ‘Could I make more without working?’ ‘Maybe I should start my own business instead.’ Or, ‘Let me see if I can get on disability, first…’ That’s why the old economists thought it was absurd to try to calculate an unemployment rate. It was just an empty number. And it was even more absurd to try to ‘increase’ employment. As long as buyers and sellers of labor were both free to make a deal, there would never be any ‘unemployment.’ There would merely be people who, given the current bid, decided to withhold their labor from the market. The old economists knew their limits…all they could do was describe the conditions under which people had jobs…and come up with some general rules and principles that explained why some people had jobs and others didn’t. But you could not say with any precision how many people were unemployed. But today, economists tell us not only how many people are looking for work…but what to do so that more of them find jobs. How? The easy slight-of-hand would be to redefine what the workforce means…reduce the workforce and you automatically increase the employment rate. That’s what economists and their numbers can do for you. During the Obama administration a record number of people left the workforce, substantially lowering the unemployment rate. But now if you want to get your face on the cover of TIME magazine as a hero of some sort, you’ve got to come up with some other, craftier subterfuge. How about this… Raise the taxes on overtime pay! This is exactly what Francois Hollande has done in France. He says it will increase employment. And he’s probably right. Because now it is more expensive to pay someone to work overtime than it is to hire someone new. So, with a little luck, the unemployment numbers may look better in France. Is that good? Are people better off? Who knows? The numbers certainly don’t tell you. In America, they’ve kept the jobless numbers down by lending people money to go to school. So, instead of people officially counted as unemployed….people are counted as students. They load them up with debt – student debt is now over $1 trillion. Now, when the young person finally gets out of school, his job prospects may still be uncertain, but his debt is undeniable. Is he better off? Is anyone better off? Has any improvement been wrought? The numbers are not silent on the matter. They lie at the top of their voices. Probably no numerical grease is thicker and less transparent than the GDP. There, the numbers dissemble and mislead, just like economists’ other numbers.
Here’s a story from The New York Post:
Trashy? Tasteless? In 2012, the biggest house in America sat unfinished. It may never be finished. But hey, it added to the GDP! GDP numbers are a complete scam. They don’t tell you if you’re coming or going. They don’t tell you if you’re getting richer or poorer. This is another way that numbers fail. They can only measure quantity. Or speed. Here’s an example. An article ran in the Wall Street Journal last month. It explained how Italy’s economic growth was retarded by strong family attachments. Half the young children in Italy are raised by their grandparents – their ‘nonni’ – while their parents work. Instead of going to day care centers, the kids go to their grandparents.
How does this affect an economy? There is no exchange of money when the grandparents do the day care. So, it doesn’t register in the GDP. No exchange of money, no ‘growth.’ The article also went on to say that people were reluctant to leave their hometowns to seek work elsewhere because they relied on the family for childcare. Theoretically, a mobile population increases GDP too…GDP increases when people take new jobs, move, buy houses and furniture, sign up for health clubs, day care and so forth. All these things add to GDP growth, even though they do nothing to really increase quality of life. They are a kind of phony growth. GDP looks only at the quantity and velocity of money transactions, not the quality of them…nor the quality of life they produce…nor the real wealth of the people in an economy. I cut your lawn. You mow my lawn. We pay each other. The GDP goes up. The more transactions per person per year – the greater the GDP of a country. Is anybody better off? What really have the numbers told us? Has one single extra lawn been mowed? One single extra blade of grass cut down? No, right? So, if a number…the GDP growth number…tells you that you’re growing…and you’re not really growing…what good is the number? It’s a flimflam. An empty number. There’s no good information in it. It’s like the unemployment number. Empty. Hollow. A zero. And so are almost all the compound, formula-driven numbers used by economists. They are dishonest. Their only role is to tart up economists’ confections and make it appear that they can do things they can’t really do. They are designed to make economics look like engineers, working on the economy as though they were real technicians preparing a moon launch. But if these guys were building a bridge, none of us would want to drive over it. If they were building cars, we wouldn’t buy them. And if they were running the phone company, and we needed a telephone number, we could call “Directory Information;” they’d estimate it for us. October 13, 2012 Bill Bonner is the author, with Addison Wiggin, of Financial Reckoning Day: Surviving the Soft Depression of The 21st Century and The New Empire of Debt: The Rise Of An Epic Financial Crisis and the co-author with Lila Rajiva of Mobs, Messiahs and Markets (Wiley, 2007). His latest book is Dice Have No Memory. Since 1999, Bill has been a daily contributor and the driving force behind The Daily Reckoning. Copyright © 2012 Daily Reckoning
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