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Fun with Statistics: Reading Edition [Sep. 9th, 2014|01:53 pm]
So, I ran across this on Facebook:

I'm going to focus on one of the key points here: the relationship between poverty and poor literacy. To do that, let's make a table:
In Poverty Not In Poverty Total
Low literacy
High literacy

Now, let's plug in what we know:

(1) About 15% of Americans live in poverty (check official statistics)
(2) 46% of adults (I'll assume American adults...) have "low literacy" (that is, in the bottom 2 levels)
(3) 61% of adults with low literacy live in poverty. (Translation: 46% x 61% = 28% of Americans live in poverty AND have low literacy.)

Filling things in:

In Poverty Not In Poverty Total
Low literacy 28% 18% 46%
High literacy -13% 67% 54%
Total 15% 85% 100%

So, we can conclude:

(1) Assuming you're not in poverty, there's about a 75% chance you have "high" literacy (that is, outside the lower two levels).
(2) If you are in poverty, there's a negative chance (that's LESS than zero) that you have "high" literacy.
(3) At least one of these statistics is screwy, because a negative percentage in this context makes absolutely NO sense.

So, odds are that, somewhere, something got garbled. So, I'm going to share some statistics taht come from the original source:

(2') 21% (or so) of adults have "low literacy" (that is, in the BOTTOM level of literacy)
(3') 41% (or so) of adults with "low literacy" (that is, in the bottom level) live in poverty.

Putting these in, with the new meaning of "low" being "LOWEST"

In Poverty Not In Poverty Total
Low literacy 8% 13% 21%
High literacy 7% 72% 79%
Total 15% 85% 100%

Now, THIS looks more sensible, but it's STILL not accurate.

Why not? Because I'm mixing definitions of poverty from two sources. Official poverty statistics are based on the official poverty line, but the NALS report on literacy has a very different definition of "poor". By official statistics, 15% of Americans are "poor". But, the NALS's data suggests that about 25-30% of Americans are "poor" or "near poor". So, going with 28% poor, and using the bottom two levels for "low" literacy, we'd end up with:

In Poverty Not In Poverty Total
Low literacy 28% 18% 46%
High literacy 0% 54% 54%
Total 28% 72% 100%

So, basically, everyone in poverty has "low" literacy, while only about 25% of those outside poverty have "low" literacy. (This claim is technically contradicted by the report... though not by much.)

Naturally, causation is horrible to untangle in cases like this (do rich people read? or are reading people rich?), but the statistical exercise teaches some important lessons:

(1) Meanings are slippery. Just assuming "poverty" always means the same thing can lead to putting things together in misleading ways.
(2) Some "gatherers" of statistics are terrible presenters... The NALS report is interesting, but doesn't present some other ways of slicing the data that would also be interesting.
(3) Statistical literacy is an important skill. (This is why my "top 2 courses every college student should take" includes "Statistics" - the other is "Logic".)
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Noah Smith on Austrian "brain worms" [Jul. 8th, 2014|01:17 pm]

Last week, Noah Smith (who teaches Finance at Stony Brook University, and runs the blog Noahpinion) has this piece on Austrian economist published on Bloomberg. I've been spending the last 12 hours or so deciding whether or not I needed to respond to it. On the one hand, it is clearly poorly informed about Austrian economics. On the other hand, it's pretty obviously almost 90% an ad hominem and I have other things to do than say "Am not!" to someone calling me names. But, obviously, I finally decided it was worth a response for two reasons: (1) it's bothering me - so I need to respond for my own psychological well-being. (2) This is a case that follows my rules of internet attack - "always aim up".* So, here we go.

Noah's title is a reference to Star Trek II: The Wrath of Khan - arguably the best of the Star Trek movies (I have a particular fondness for Star Trek IV, myself...). In this movie, perennial villain Khan has revealed that he has a "brain worm" that, when it burrows into a person's brain, makes them highly susceptible to suggestion. So, people end up basically mind controlled. The analogy to Austrian economics is fairly obvious - Noah is suggesting that the "Austrian worldview" is basically a brain worm that leads people into absurd beliefs that are out of touch with reality. Its key beliefs seem to be:

Read more...Collapse )

On the whole, I'm convinced that Noah Smith is not interested in engaging with actual Austrian economists (like Pete Boettke, Joe Salerno, Robert Murphy, gosh - even me), but is just arguing against the largely uninformed, libertarian Austrian fanboys that often surround the Mises Institute and On that I agree that the fanboys often do Austrian economics a disservice by being overly vocal on issues they know very little about. But, the fact that a commenter on a blog or Twitter says things that are wrong and identifies themselves (or their ideas) as "Austrian" hardly disproves anything about Austrian economics.

Footnote on "always aim up"Collapse )
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Thoughts on "Laborless Production" [Apr. 24th, 2014|04:18 pm]

So, a discussion got started on Twitter - which is not a good platform for long, extended discussions. And my thoughts on this particular topic are long and extended. So, I came here to LJ, where the platform is MUCH more suited to such things.

So, here are some thoughts on "laborless production" - that is, an economic system in which everything is automated and workers are unnecessary.

First thought: such a system shall never exist. There are a number of arguments for why this is probably true.

The why...Collapse )

Second thought: if it happens, the transition to a laborless economy wouldn't be as bad as many people think.

The why...Collapse )

In the end, then, I'm not worried about laborless production. First, it's exceptionally unlikely we will ever get there - so much so that I don't think we ever will. Second, if we do get there, I think the process - while probably not seemless (errors, after all, are common in transition periods) - is likely to be reasonably smooth. We already have the elements in place to handle most of the transition - because people ALREADY transition from "laborer" to "non-laborer" on a regular basis. We just need to be ready to see those systems have a lot more use than they currently do. On a personal level, we need to focus on increasing our wealth-to-income ratios. Put another way: we all need to save. Put away 10% of your income from each paycheck - more if you can manage it. If possible, automate that. You can't cut your spending by 10%? Fine. Then save 100% of your raises. After a few years (probably 5 or so, for most people), you'll be saving 10% of your income. Learn about investing so that you don't take stupid risks - or don't learn about investing, and put money into a deferred fixed annuity that looks good to you, and pay someone else to take the risks.

The best part? This advice is good even if we don't end up with a laborless economy.
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The Marginal Efficiency of Capital [Apr. 10th, 2014|11:00 am]

In a recent article in the QJAE (pdf), Edward W. Fuller explains the differences between the Austrian "Net Present Value" (NPV) approach to ranking investment projects and the Keynesian "Marginal Efficiency of Capital" approach. The difference basically goes like this: The NPV criterion suggests that we should calculate the "present value" of a particular investment by discounting its future cash flows using the going interest rate. The "net present value" takes the present value and subtracts off the current costs of starting the project. Investments are ranked according to their NPV. The MEC criterion suggests that you should use the same information to calculate, effectively, a "rate of return" on the investment, and use that to rank investment projects.

While I found the comparison interesting, I think the article ran into a number of somewhat troubling inconsistencies. Most importantly: the article was inconsistent regarding the Austrian view of imputation.

Here's the Austrian story as I understand it: The present value tells you what the resources needed to start a project are "worth" - so, it's what entrepreneurs should be willing to pay to start the project. As long as the market is at all competitive, the value of the resources will rise to the present value. What does that mean? The NPV of any project can be, at most, zero. If we take PV - cost of starting the project, we'll get exactly zero, since the prices of the resources will be bid up to the PV. So, when we rank investment projects, we're really just comparing zero NPV projects with projects that would use the same resources but have a sub-zero NPV. Since the resource prices are bid up to reflect the most valuable project, this all follows. So, what matters in the Austrian view isn't the NPV - it's the PV itself. It's the PV that determines which project "wins" the resources needed to complete it. Is this a big difference? Maybe not - but it is more than just semantics.

What makes this particularly disturbing is that the article itself criticizes Keynes (I'd say rightly) for acting like the cost of starting the project is fixed, rather than being the result of a competitive bidding process. Then, the article goes on to adopt the same assumption under the "Austrian NPV" view.

One point that the article makes is that the MEC and NPV criteria can lead to different rankings of investment projects. This is true, IF the startup costs are fixed. But, they aren't. Startup costs are the result of a competitive market bidding process. If we suppose that the startup costs rise to reflect the full present value of the most valuable project, then the MEC criterion would give the same result as the NPV criterion, I suspect. Here's my proof: for the most valuable project, the going interest rate will be the MEC (since the interest rate is used to discount the future payoffs, and the NPV is zero. Technically, the MEC is calculated as the interest rate that results in a zero NPV.). For any less valuable project, the NPV is negative. To increase the NPV, the interest rate must be lower. So, the MEC for any unpursued project will be less than for the pursued projects.

This technical problem hints at a larger conceptual problem with the Keynesian system. The Austrian system is built on an economic foundation of scarcity - that's precisely why prices adjust to reflect the present value of a project. The Keynesian system is built on an economic foundation of abundance (or "idle resources"), which is why prices don't adjust - there are just so many of them that there is no "competitive bidding" that goes on. This leaves unanswered the question of where prices come from (Keynes suggests that there's a lot of historical dependence on that account). So, the real, fundamental problem with Keynes remains: his price theory is largely absent. He basically just assumes that prices don't change, gives a few possibilities for why that might be, and then moves on. While it may be true that prices don't change to reflect every little wobble in supply and demand, that doesn't mean we should just assume that they don't move.

Yet, that assumption is in Keynes, and disturbingly, ported into the Austrian NPV criterion as used by Fuller.
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QE and ultra-low interest rates: Distributional effects and risks [Apr. 9th, 2014|11:03 am]

I recently finished reading this paper about quantitative easing's distributional effects. The paper contains a lot of potentially interesting data, but suffers from a handful of weaknesses.

The interesting stuff: The paper pretty clearly demonstrates that the main beneficiaries of ultra-low interest rates are governments, though corporations also gain significantly. Effects on households are mixed - generally, young households with more debt benefit while older households with more savings are hurt. They find that the effects on stock and bond values are more muted than one might think.

The paper suffers really from one big weakness: it focuses only on interest income and, to a lesser extent, financial asset valuation effects from low interest rates. It totally ignores any Cantillon effects that lead to relative price differences, which could be attributed to monetary injections. Just to give an example of where Cantillon effects may have mattered, we can look at a disaggregation of the Consumer Price Index into product categories. This will give us a good idea of which prices are rising quickly, while others are rising slowly.

A quick look suggests that the following broad categories have seen very rapid increases in prices since the beginning of the first round of Quantitative easing (beginning in November 2008) (>30% over that time): Motor fuel, energy commodities, tobacco and smoking products, fuel oil and other fuels, hospital and related services, and educational books and supplies. Meanwhile, a handful of categories have seen decreases in their relative prices of over 10% in that time: information technology, window and floor coverings and other linens, other recreational goods, other household equipment and furnishings.

How much of these relative differences can be chalked up to QE? That's hard to say - but it is clear that not all industries are gaining equally, and ignoring relative price changes means we miss part of the story.
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How Frequent are Small Price Changes? [Mar. 31st, 2014|02:10 pm]

Cut for lengthCollapse )

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Alvarez, Lippi, and Mises [Mar. 29th, 2014|08:26 am]
[Tags|, ]

"Persistent Liquidity Effects and Long-Run Money Demand" was just published in the AEJ: Macroeconomics journal. As I read it, I was struck by something: the article was oddly Misesian in certain respects.

Let's tell the story: the basic idea is that they are trying to come with an explanation for two phenomena: (1) Increases in the money supply tend to decrease interest rates in the short run, (2) but not in the long-run. (Or at least not much in the long run.) Put another (more technical, less clear) way, in the short run, money demand is interest-inelastic, while in the long run, money demand is "interest-elastic". The article centered around trying to explain this seeming contradiction.

To explain it, they adopted a relatively simple (I would suggest realistic) assumption: they divide people into "traders" and "nontraders". The "traders" can participate directly in markets where open market operations happen. The "nontraders" can't. The result is that, when the money supply increases, it only affects prices gradually, so inflation expectations don't rise very quickly. But, as time goes on, the money filters throughout the economy, raising inflation expectations (and therefore interest rates), and also resulting in the "traders" (in effect) moving some of the excess cash from bond markets to consumption, which facilitates the rise in interest rates (by removing the "excess liquidity".

As an Austrian economist of the Mises/Rothbard/Hayek tradition, this felt very familiar. It sounds a lot like the Misesian "Cantillon effects" on interest rates. One way of reading Mises suggests that when money is injected into an economy, it distorts relative prices at the point of entry, so that the price increase is slow and uneven. This is then applied to open market operations and credit expansion - making the point that when new money is created in credit markets, it pushes interest rates down in the short run, but as the money filters throughout the economy, interest rates tend to rise back toward "natural" levels. Which is basically Alvarez & Lippi's point.

One big shortcoming of Alvares & Lippi's version: they rely too heavily on the mathematical model. As a result, they discuss eigenvalues a lot (and, to be honest, I've forgotten a lot of the significance of eigenvalues in economic models...), but say very little about the steps involved in the adjustment process. (They have an "adjustment parameter", but that's about as close as they get.) The result is that their story contains interesting elements, but the story they tell is far more opaque than it could be. It would certainly benefit from a less technical "discussion" section that lays out the process by which equilibrium is approached, rather than just relying on impulse-response functions to get them there.
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GDP Report (again!) [Dec. 5th, 2013|11:44 am]

So, the first revision of the advance estimate for 3rd quarter GDP came out.

I had commented before on the advance estimate.

And, like the BEA, I am updating and revising my entry there.

(1) Real GDP grew at a 3.6% pace, a substantial upward revision from the 2.8% - if I may be allowed to give myself a pat on the back, I had previously said "I don't put much stock in advance estimates". This, my friends, is why. I'm also going to make a prediction for the final revision which will come out in a month: I think it will be below 3.6%, but above 2.8% - it's pretty typical for the final revision to get a result that is between the first two estimates.

(2) I had misinterpreted the data before. The 1.8% increase in prices was an annualized rate - that number's revision kept it the same as before.

Based on this, I would have revise some of my predictions.

At this point, there is no evidence that the excess reserves are actually hitting the economy - as a result, I don't see any reason that a crash would be imminent at this point. The evidence for an artificial boom is not clear at this point, so I don't know that an inevitable crash is coming. However, I still worry about excess reserves, as those have the potential to create a boom-bust cycle if they hit the economy in any significant way.
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GDP Report [Nov. 7th, 2013|03:19 pm]

So, the Bureau of Economic Analysis just put out it's advance estimate of third quarter GDP. Looks like real GDP increased at a 2.8% annual pace, a bit higher than the 2nd quarter's 2.5%.

Since macroeconomists are supposed to have a view of this, I suppose I will.

(1) I don't put much stock in advance estimates. They get revised twice before we have the final number - and revisions can be large (sometimes a full percentage point or more).
(2) The increase in the growth rate was driven by imports slowing, an acceleration in private inventory investment, and an acceleration in state and local government spending.
(3) The price index for gross domestic purchases went up by 1.8% in the third quarter - that's 7.2% at an annualized pace, if I'm reading the data right.
(4) The areas of big growth were primarily in investment - residential and nonresidential structures coming in in first and second place.


I find the combination of data somewhat worrisome. Austrian Business Cycle Theory suggests that periods of artificially low interest rates result in unsustainable booms - typically investment driven - that will inevitably crash when interest rates rise. Why does this make me worried?

(1) Interest rates are obviously very low right now. Whether they are "artificially" low is a fair question. A good way to get at that: is investment outpacing savings? That's not entirely clear - recent data actually suggests that gross saving is actually higher than investment - so rates might be low "for a good reason". At the same time, the massive increase in the monetary base makes it fee unlikely that the low interest rates aren't the result of Federal Reserve policy - that is that rates are "artificially low". The argument goes two ways: one says "The Fed has increased the monetary base - therefore rates are artificially low." The other - which I'm coming more around to - is "The Fed has increased the monetary base - but the money is sitting in banks rather than entering the economy - so the Fed's actions haven't necessarily affected interest rates in any substantial way." We could expect this continue as long as banks don't think there are good opportunities out there. But, here the increase in private inventory investment suggests things may be changing in that regard. One interpretation of inventories says "Oh noes! We're making more stuff than we're selling! We're going to have to cut back production in the future!" It ends up that this interpretation is basically wrong. In reality, most of the variation in inventories isn't from finished goods that just don't have a buyer. It's from partially completed goods that just weren't finished at the time the data was collected. That being the case, an increase in inventories suggests that businesses are optimistic enough about the future that they're starting more production processes. I worry that it's only a matter of time before this increased optimism leads to accelerated lending by banks... and that time might actually have already passed...

(2) Now, we come to the problem with the "money is just sitting in banks" argument - the price index for gross domestic purchases went up very fast in the 3rd quarter - this suggests that the money the Fed created IS entering the economy and being spent - driving prices up - which there's reasonable evidence for. (Though I have to note that the inflation rate as measured by more conventional measures - like CPI - remains pretty tame.) This will create pressure on the Fed to increase interest rates...

(3) Which would lead to the crash. (Actually, it would lead to a kind of crash even if the interest rate wasn't artificially low to start with.)

(4) How bad would the crash be? Well, that depends on a few things. Consider two different crashes. The first was the "tech bubble" which crashed in 2000-2001. In this case, the tech bubble was funded largely by equity, and the real investments were largely in things that had good alternative uses (computers, knowledge, etc.). The crash happened, and we recovered fairly quickly. The second was the "housing bubble" which crashed in 2007-2009. This was funded largely by debt, and the real investments were largely in things that didn't have good alternative uses (houses). So, the transition has been difficult. So, what's happening now? The current investments are in things that probably don't have good alternative uses (structures), but they seem to be funded largely through equity - at least, borrowing has been small (home mortgages are declining on net, though there has been a somewhat troubling increase in the amount of corporate debt being issued).

So, in my view, odds are good there's a crash of some kind coming - but I'm thinking it probably won't be as bad as the housing crash proved to be, but would be worse than the tech bubble popping was.

But, all of this is just based on advance estimates.
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Fed Chairs and Recessions... [Nov. 6th, 2013|02:56 pm]

So, it was observed - partially in jest, I think - that Janet Yellen should steer clear of the Fed chair job because it's a trap. But, it raised a real question: is there a connection between changing of the Fed chair and recessions setting in?  Here's what I found...

At this point, we have had 14 different Fed chairs since 1914. Of those, 4 did not experience a business cycle "peak" (that is, a turning point from the economy booming to falling into a recession/depression). 10 of them DID experience some kind of peak. What was the timing? (One of them took over in the same month as the economy peaked in 1923 - ouch. For him, I'll just use the NEXT peak which didn't happen for about 3 years after that.)

For those that experienced a business cycle peak, there was an average of 26 months between when they assumed the Fed chair and when the peak happened - so just over 2 years between taking over and the economy taking a turn for the worse, on average.

But, we can't read too much into this. "On average" is an important phrase - and the economy is often not "average". (For example, while the average is 26 months between taking the Fed chairmanship and the next peak, NO Fed chair saw that exact number of months pass.)

So, doing some absolutely atrocious statistics (because it's likely to be pretty inaccurate, not because it's difficult...), and assuming a normal distribution (probably shouldn't, but oh well!)...

Given that Janet Yellen is going to take over in February 2014, and assuming that she won't be one of the lucky chairs that doesn't experience a recession at all, there's a roughly 68% chance we'll have a business cycle peak sometime between March 2015 and May 2017, and a roughly 95% chance we'll have a business cycle peak between February 2014 and June 2018. Which... isn't very informative since the bands are so wide.

To get at the significance of the new chair, though - let's suppose that business cycle peaks are purely random. If so, then there being 33 months where business cycle peaks happen in about 1872 months (since June 1857) suggests there's a 1.75% chance that any particular month will be the peak of a business cycle - and a 98.25% chance it won't. Assuming independence (a HORRIBLE assumption here in all likelihood), the odds of there being at least one business cycle peak in a 26 month period is about 37% - so the new chair does increase the odds somewhat in the March 2015 to May 2017 period (from 37% to 68%). The odds of there being at least one business cycle peak in a 52 month period is about 61.5% - a new chair drives that up to 95%.

Now, we want to be careful about cause and effect. It's perfectly possible there's no causal connection - there's a dreaded "3rd thing" that leads to new Fed chairs AND business cycle peaks having this relationship. But, there are two possible direct causal connections I can think of: Either the new Fed chair causes the ensuing recession - or foreseeing the coming recession leads the previous chair to leave. Interestingly, most estimates suggest that monetary policy takes about 2 years to "work" - so it could easily be either...

This, friends, is the joy of uncertainty.
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