Tuesday, September 20, 2016

Infrastructure Investment

Politicians want to sell you infrastructure investment. Don’t buy it.

What is infrastructure anyway? It’s basically big capital projects that are kinda’ sorta’ public goods: bridges, roads, airports, and so on.

There’s a notion that in the U.S. our infrastructure is “crumbling”. Maybe. There is no very good way to measure this. One thing we do is talk about how old our infrastructure is. But that misses the “compared to what’ question you should always ask: how do we know a specific age is “old”?

The biggest name in urban economics is Ed Glaeser from Harvard (no one regards Glaeser as a supporter of political conservatives). He’s just published a piece in City Journal entitled “If You Build It …” that’s getting a lot of talk.

Why do politicians always tout infrastructure?

The progressive romance with infrastructure spending is based on three beliefs. First is that it supercharges economic growth. …  [Second], by putting people to work building needed things, infrastructure spending is an ideal government tool for fighting unemployment during recessions. [Third] Infrastructure should also be a national responsibility …

None of this is right. …

First, let’s The thing is, no one spending their own money would do stuff like this.

In 2009, [Glaeser] calculated a rough cost-benefit calculation for a (fictional) high-speed rail link between Houston and Dallas and found that costs outweighed benefits by an order of magnitude.

Note that when a scientist says “an order of magnitude” they mean something is multiplied by the base of log. Typically this is ten for casual use of order of magnitude, but e is probably a reasonable lower bound. Anyway, he’s saying the costs are several times the benefits. That’s not off by a little bit; it’s more like offering to pay $10 or $20 for every gallon of gas. And, if you’re not up on this stuff, Dallas to Houston is one of the corridors across the country that the infrastructure people are always proposing for high speed rail. So it’s not like he picked that example out of a hat.

And who are we trying to help with infrastructure spending anyway?

The relatively simple technology of infrastructure construction of the 1930s meant that the unskilled unemployed could easily be put to work building roads. Among the iconic images of the Great Depression are scores of men wielding shovels and picks. That isn’t how roads and bridges are built anymore, though. Big infrastructure requires fancy equipment and skilled engineers, who aren’t likely to be unemployed. The most at-risk Americans, if they’re working at all, usually toil in fast-food restaurants, where the average worker makes $22,000 a year. They’re typically not trained to labor on complex civil-construction projects. Subsidizing Big Mac consumption would be a more effective way to provide jobs for the temporarily unemployed than subsidizing airport renovation.

 

I love that last sentence. That really gets to the heart of what progressives ought to be telling Americans. But if they did, we’d recognize how silly their ideas actually are.

It turns out that the Council of Economic Advisors has a number they’ve estimated for how much it costs the government to create a “job-year” (that’s one job lasting one year). It’s $92K. What that means is that if you can’t create a job that pays more than that per year, you shouldn’t bother. The thing is, income distribution data shows us that only 15-20% of jobs pay that much. So government is really only capable of economically creating jobs for the rich, but keeps telling us how good it is at creating jobs for the poor. Not so.

On the third point, I love this turn of phrase:

The most pressing problem with federal infrastructure spending is that it is hard to keep it from going to the wrong places. We seem to have spent more in the places that already had short commutes and less in the places with the most need. Federal transportation spending follows highway-apportionment formulas that have long favored places with lots of land but not so many people. …

Low-density areas are remarkably well-endowed with senators per capita, of course, and they unsurprisingly get a disproportionate share of spending from any nationwide program. [emphasis added]

In the end, Glaeser recommends basic economics: use newer technology (like EZ Pass) to get users to pay for the infrastructure they actually use.

Monday, September 19, 2016

The “Pig In the Python”

I’ve been talking in macro classes for several years about how a lot of the weakness in our economy is due to baby boomers starting to retire in large numbers.

Check out this piece from Marketplace. You can either read the transcript or click through and listen to the podcast. The topic is Trump’s claims about what his proposals will do for economic growth. But I’m posting about it here for a small detail. One of the interviewees describes the baby boom as a “pig in the python” that’s been working it’s way through our economic system.

You’ve probably all seen pictures of snakes after a big meal. ‘Nuff said. But the metaphor is that many national labor statistics look the same way.

16-09-19 SUU Macroblog Capture

Tuesday, August 16, 2016

OMG: Thoughtfulness on Significant Digits

The Summer Olympics are running right now.

And in swimming there are a lot of ties.

How is it possible that there are ties when we can measure time accurately to 3 to 6 digits?

Here’s why: because in 0.001 seconds a swimmer travels about 2 millimeters, but the construction tolerance for differences in pool lane lengths is plus or minus 30 millimeters (due to expansion and contraction from heat and cold).

FINA (which governs international swimming) recognized 40 years ago that improvements in timekeeping simply is not differentiating swimmers better. Here’s the link, although it’s not required.

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Why can’t we do this in macroeconomics?

It’s not official, but the popular site usdebtclock.org certainly tries to give people the impression it’s counting off each dollar of national debt. JustFacts.org asserts that on August 4, 2016, our national debt was $19,379,566,441,022. They get this from TreasuryDirect, which sounds like a government site but isn’t.

These numbers are not credible. I would be OK with a figure of $19T, but even that is dicey. We simply do not have the ability to measure things that accurately.

How about GDP? The BEA asserts it was $18,437,600,000,000 in 2016 II. That 600 is 600 million. So they are claiming they have this down — in a country of about 300 million people — to an average of within 2 dollars for each of us? Heck, I don’t know my income in a quarter within 2 dollars. Ever. And I am mostly paid in regular paychecks.

How about economic growth? The most recent figure is 1.2% for that same quarter. Could you feel it if it was 1.3%? Or 1.1%? I have asserted for years in principles that we have trouble feeling GDP growth rate differences of sharper than 1% (and unemployment rate differences of sharper than 0.5%, which is actually consistent with Okun’s Rule).

Why can’t we get bureaucrats be as forthcoming as swimming officials?

 

Regulation, Distrust, and Growth

Countries with high levels of distrust have more regulation.

Note that this is not distrust in markets leads to more regulation of markets. Rather, it is distrust in general leads to more regulation of markets.

But disturbingly, while poor policy choices cause weak growth, it also appears that weak growth may foster additional bad policies — like more regulation of markets.

Here’s something to worry about: distrust leads to more regulation which leads to lower growth which promotes more bad choices and may increase distrust.

The scary thing is this sounds like a lot of countries around the globe. Think South America.

The really scary thing is that measures of trust in the U.S. have been on the decline for over a generation.

Check out this updated post (and at least browse the links) by Alex Tabarrok.

Thursday, August 11, 2016

Stolper on Wages vs. Production

Americans (and others in developed countries) get paid a lot. We also hear a lot of naive people remarking that this makes it difficult for us to compete with workers in other countries who are paid less.

That sort of remark is often nonsense. The reason is that it neglects the “compared to what?” questions we should always ask.

Instead, what’s important is the ratio of wages to production in two places. The lower that is, the more likely a location is to attract productive firms.†

Here’s a quote of what Wolfgang Stolper said in 1960:‡

African labour is the worst paid and most expensive in the world.

It was the worst paid because their wage was so low, but it was expensive because they produced less than what they were paid.

† Of course, smart students will recognize while potential employers will be attracted to places where the wage/production ratio is lower, potential employees will be going in the opposite direction. That’s what economics is all about, because that pair of tendencies is going to tend to make the wage/production ratio the same everywhere. That process of smoothing out differences is called arbitrage, and it’s what makes equilibrium a useful concept.

‡ You also hear many people remark about macroeconomics something like “why didn’t anyone see this before”. One of the things you need to learn about macroeconomics is that most of these things have been seen before, but people prefer to ignore them in favor of magical thinking.

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The source article is really about trade rather than macroeconomics, so I’ve marked off this section because it’s less important for this class.

There is a backstory in the source article. It’s about a textile plant in Nigeria that couldn’t compete without tariff protection.

This is from a longer article in The Economist entitled “An Inconvenient Iota of Truth”. It’s about the Stolper-Samuelsom Theorem (yes, that Samuelson). That theorem explains why, say, oil-rich countries have such lousy economies outside the oil industry. The reason is that when the price of the output in the oil sector goes up, that in turn shifts demand outward for inputs to the oil sector, increasing their price too, but also shifting demand for inputs to other sectors inward, reducing their price. In short, if you live in Saudi Arabia, and don’t work in the oil industry, you’re hurt every time the price of oil goes up. More generally, the input that’s getting scarcer is the one being hurt.

This can also be extended to skilled and unskilled labor in developed countries like the U.S. Unskilled labor is scarce in the U.S. And th story of the last century or so is that worldwide economic growth increases the price of the outputs of our skilled labor. Following the Stolper-Samuelson result, this means that unsklled workers are hurt because people around the world want the exports of our skilled workers. This gives some motivation for the politics of protecting unskilled workers from trade with other countries.

Coming full circle, protecting unskilled workers in developed countries is the flip-side of protecting skilled workers in developing countries. That was Stolper’s point about Nigeria. They couldn’t develop skilled labor for the future without protecting inefficient industries (where they might work) in the present.

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Via Greg Mankiw’s Blog.

Tuesday, August 9, 2016

Productivity Down for Third Straight Quarter

I don’t worry too much about occasional downs in macroeconomic statistics, as long as they are mostly ups. Three in a row gets my attention though.

Productivity probably should be the key macroeconomic statistic. After all, the increased productivity of individual workers is the only reason that anyone can afford to pay them more in real terms.

The thing is, productivity isn’t the key statistic because we can’t measure it directly. Instead we measure it as a residual. We track output growth first, then we subtract out how much of that has to do with growth in employment and hours. From that we subtract out how much has to do with growth in amount and utilization of capital. What’s left is improvements in productivity (usually attributed to improved technology). So, productivity is a little dicey.

Nonetheless, government statisticians are careful about their data and methods, so while we may treat a productivity growth number as imprecise, we think that evens out over several consecutive measurements.

So, why on earth would productivity be slowing down? Determining causality here is problematic. What we do in practice is run through some plausible explanations.

First, could technology be going backwards? This seems unlikely. Just look around. Some would argue that the technological improvements we are making are just not that important (it’s summer of 2016, so the big new thing is Pok√©mon Go), and maybe that’s true. Personally, I’m always leery of just-so stories about how the present is horrible and the past was so much better. Nonetheless, there is a serious macroeconomic research looking into this possibility (like this).

Second, are our machines not working properly? The statistic to look at here is capacity utilization. This shows roughly what percentage of available hours the available machinery is working, so higher is better. This has been on a downward trend for decades, and we’re not sure that’s a bad thing. It does mean that we should probably focus on the last decade or so though. Now, the way this relates to productivity is that if capacity utilization is higher, productivity might be lower because we’re pushing the more marginal machines into production. This does not seem to be the case: capacity utilization has been falling for about a year. Maybe we pushed our machines too hard a year or two ago, and we’re seeing the consequences now … but that’s stretching a bit, don’t you think?

Third, are our people not working properly? Maybe productivity, averaged across all of us, is faltering because some of us just stink at working.

Macroeconomics is a craft that one practices. No one ever really knows anything for certain. But the idea with a craft is that you practice to get better at noticing the details and taking care of them. And for my money, that last one is the explanation that’s holding water for me.

Our labor force is near, or at, full employment, with our unemployment rate hovering below 5%. Firms say that have lots of jobs (you have to dig into the JOLTS data a bit to find this) but have trouble finding people with the skills needed to fill them (job openings are going up faster than job hires). Taken together, these tend to suggest that firms are scraping the bottom of the barrel with their new hires. A third factor to add is that, demographically, the baby boomers are starting to retire in large numbers. They take their experience with them, and this is hurting some firms.

The question that needs to be addressed then, is whether what we’re experiencing is 1) merely the tempoarily heavy replacement of experienced workers with inexperienced ones (if a demographic change that’s going to take a couple of decades to play itself out is best described as temporary), or 2) solid evidence that a larger than normal chunk of the population simply isn’t worth employing. Productivity data is pretty volatile, but a quick graph I produced on the BLS website shows that productivity has been in negative territory quite a bit during the Obama expansion. For as long as I can remember, society has been complaining about an underclass of people who don’t fit into the working world. I used to regard that as just grousing, but now I wonder if that group is finally large enough to make an observable difference.

Wednesday, July 13, 2016

IT Companies Are Hiring Lots of Economists

This is according to Bloomberg BusinessWeek, in a June 13-26 article entitled “Algorithms Aren’t Just for Coders”.

I found it online here at PressReader. I think the long-term viability of that link is sketchy. I got to it by entering the following into Google

“algorithms aren’t just for coders” bloomberg businessweek

If you still can’t find it, let me know; I downloaded a copy.