I’m watching the re-re-renewed debate about academic bias against conservatives with a little more skin in the game this time around. Two facts about me: for some strange reason I’m considered conservative by my academic friends, especially by non-economists, and I have decided to take a job outside of academics. So clearly there’s bias in the academy! (Where do I pick up my check.)
Megan McArdle has a great post up where she makes the standard analogy between racial and political bias and she points out that, in true fashion for partisans, the table and arguments used have done a 180. Conservatives are arguing against subtle biases inherent in the the system and liberals are calling the game because there’s no explicit rules against hiring conservatives in the academy or they are otherwise blaming the out-group.
The analogy may be apt but you would be upset with me if I said so and I also said, “who cares”! So, I’ll do just that. The academy and places of employment, say, are free associations of individual people. If these places want to exclude interesting people because of arbitrary differences, then its their loss. In the long-run Beckerian forces prevail and the non-discriminating universities and firms win.
Well, except, I care. The long-run could be a very long time! Life consists of the transitions between steady states. Without a model of how fast those transitions are and, importantly, what shapes they take, analyses of the properties of steady states is next to useless. I want to help progress along a little even to just make it visible within my lifetime. I’m selfish like that.
But there are also standard externality arguments. The academy produces non-rival and non-excludable ideas that are used to produce innovations that drive economic growth. By excluding conservatives, the academy makes the idea generating process less efficient and we all lose out. We need to subsidize Rush!
What’s upsetting about these reasons to care about discrimination is that they don’t apply to racial discrimination or other types of discrimination that I care about much more than bias in the academy. First, I’m not creative enough to make the externality argument for blacks or women. Why does discrimination against them harm me, a white male?
Second: of course the long-run is undetermined with regards to racial discrimination too, but it is not clear that the long-run transition to equality is being driven by the dynamics of discrimination. While there’s significant evidence that anti-discrimination laws had an effect on closing wage gaps, there’s much less certainty about the size of that effect. One estimate has the black-white male wage gap in the South BEFORE the CRA halving every generation or so. The CRA sped up this transition, but only in the South and only for a decade or so. The half-life reduced to about one half a generation in the decade or so after the CRA but there has been no improvement in the black-white southern male wage gap since. This sweeping legislation appears to have had minimal long-run effects, at least with regards to wage gaps. (PS – these stats are from memory, look up the . Donahue and Heckman paper if you don’t believe me)
One option, at this point, is to throw up my arms and to insist discrimination is no big deal. It will fix itself in the long-run and there doesn’t appear to be anything that we can do to speed up the transition to that long-run. But there’s a larger argument about externalities, ones at the foundational level of institutions and the structure of rules.
Tyler Cowen linked to a new paper from Buchanan that points out that the “rules of the game” are endogenous, they are not given, and more importantly non-rival and non-excludable. There is a “market” failure in the production of rules. The rules of the game are inefficiently produced; there is some marginal change to the set of rules that could make everyone better off and there needs to be some meta process that ensures these Pareto improvements can be made (Buchanan cites Coasean political entrepreneurs). The argument against discrimination: if the rules of the game are arbitrarily deficient for some large group of people then its possible they could evolve to be arbitrarily deficient for a group of people that I belong to. I have interest in making sure there exists a process that removes these sorts of deficiencies.
Will Wilkinson has been schooling the internets about
division properly controlling for inflation when figuring real incomes, eliciting bored nods from those that have actually read Broda/Weinstein/Romalis (no links… too boring to write a post about) and confused indignation from those that want to talk about everything except real income inequality. Anyway, this prompted me to take another look at Broda’s (the intellectual ring master of this set of papers) list of working papers.
I found this interesting paper. Broda and Weinstein do the same sort of analysis for Japan that Broda/Romalis did for poor people in the US: he generates price indices (hah!) controlling for substitution and quality issues (but leaving out the fancy math to account for new products). Japan doesn’t make these corrections when calculating its CPI and so the authors just replicate the changes the BLS made in calculating the US’s CPI after the Boskin report but for Japan. They find that deflation was understated:
Ignoring the factoid that “deflation is bad”, this actually means growth in real consumption per person in Japan was higher than previously thought. Instead of growing at a rate 2% slower than the US, using the uncorrected Japanese official statistics, real consumption per capita has been growing at a rate only 0.7% slower than the US.
Here’s the per capita GDP for the G8 countries (relative to the USA):
You can take two lessons from this chart.
1) Japan hasn’t had bad monetary policy relative to, say, the continental European countries
2) Monetary policy just doesn’t matter in the long-run
Also, the more you stare at these real GDP per capita charts, the more you think the 1980s in Japan was an outlier (aka bubble).
Here’s all the Jolts data (minus job openings):
These are not seasonally adjusted so that’s why you get the inverted-U shape every year for the hiring and quits series and the inclined saw shape for firings. Still, you can see something happened the last two or three years. Firings (the pink line) spiked in early 2009 but several months before that quits (blue) and hirings (green) declined by about 20 to 30% each. Here’s a close-up of the most recent period:
A couple things that strike me about these graphs:
1. Firings had a one month spike in January 2009 (a month with a high number of firings to begin with) but the series has stayed about where it usually is (maybe 10% higher if you ignore the recent dip). The story of this recession isn’t of people losing their jobs.
2. Looking at the dramatic decrease in hirings, the story of the recession is that people aren’t finding new jobs.
3. However, because there’s much, much fewer people quitting their jobs the job market isn’t as tight as it could be.
One of the things I do in my dissertation is treat changing jobs as an investment decision. When a worker quits their old job and looks for a new one (maybe not in that order), they are forgoing human capital that made them productive at their old job and they’re investing in new human capital to make them productive in their new job. One possibility — given the JOLTS evidence and thinking of job switching as investment activity — is that like employers who are holding back on new invests (and thus holding back on hiring), workers are holding off on making new investments as well.
I’m not sure about the implications for aggregate demand, but I’m pretty sure this is bad for growth prospects.
I’m jumping ahead of my own narrative, but why does it seem ingrained in people (including economists) that immigrants must be competing with native workers? Why is complementarity so much more unlikely in people’s priors?
We don’t have this bias when it comes to new technologies. In fact, we have the opposite bias. Despite the popularity of the phrase “creative destruction”, quality ladder models are much less common than expanding variety models of growth. Anyone who suggests there may be a negative externality of R&D in competitive industries gets jumped all over.
Can’t immigration be seen as a type of innovation? Immigrants bring more with them than their L.
Or does it?
In the previous post, I mentioned two types of catastrophe: cliff-diving and gradual. Suppose the first is a sudden major decrease in output. How much would returns to capital have to decline to get 1% average yearly returns over a century (given 6% “usual” returns)? This is the solution to this problem:
If I got my sums right, this implies about a 99% reduction in returns to capital in the year of the catastrophe.
Now, suppose the catastrophe plays out over a decade. How negative would growth in capital productivity have to be to get an average 1% returns for a century? Doing a similar calculation, returns to capital would have to be about -35% every year for a decade to get average returns that low over the century.
These examples make the catastrophes of the 20th century pale in comparison. In the US in the 1930s, GDP growth was, on average, positive. Austria was the biggest loser during WWII, in terms of GDP, and it only decreased by about 10% a year from 1938 to 1945.
In Weitzman’s calibration, there’s a 1 in 200 chance of having 1% yearly returns over the next century. These examples make this calibration look rather unrealistic.
Risk aversion usually makes investments look less attractive. In the standard story, then, as risk aversion goes up, we would spend less money today to avert future catastrophes. Martin Weitzman argues, however, this relationship reverses when we’re uncertain about future productivity levels. For if it turns out that productivity is low in the future (e.g. because of a climate catastrophe) then consumption will be low. Low consumption means high marginal utility and so low discount rates.
My purpose here is to focus sharply on clarifying the long-run discounting issue by using a
super-simple super-crisp formulation… There is no good substitute for seeing clearly before ones eyes the basic structure of a model laid bare.
Suppose [there’s uncertainty about discount rates in the future and] that discount rate ri > 0 will occur with probability-like weight wi > 0, where sum wi = 1… The [expected] discount rates … decline over time starting from their average value and going down over time to approach their lowest possible value. Over time, the impact of the higher discount rates … diminishes because the higher rates effectively discount themselves exponentially out of existence, leaving the field to the lower discount rates (and, eventually, to the lowest).
[A]ny given value of [future productivity level] subsequently determines the endogenous future growth rate … and endogenous consumption level … as the solution to a Ramsey optimal growth problem (given that value of [productivity]). The paper shows that when future productivity … is uncertain, then higher values of [risk aversion] are associated with lower future discount rates, thereby reversing the conventional wisdom.
[An example using standard parameter values] indicate[s] that the risk-aversion effects of uncertain future productivity on lowering distant-future discount rates might be quite powerful. The driving force is a ”fear factor” associated with the possibility of low-probability but catastrophically-high permanent damages to future productivity.
I personally would be inclined toward a much lower climate-change discount rate than 6% per annum, but the ultimate goal of this paper … will be to show that under uncertainty, even with expected discount rates as high as 6%, the effective discount rate, which ought to be used, can be much lower than 6%.
The results in the example he gives depend very much on the distribution of future productivity, especially on its variance. Here’s his assumed distribution:
In his model, this distribution should be interpreted as the distribution of the average productivity over a very long time (i.e. the next century or so). To me, his assumed uncertainty about productivity is too high (i.e. the variance of the distribution is too wide). Is it even remotely possible that the capital-output ratio will average 50 or 100 for the next century? Even if there’s a sudden, cliff diving catastrophe, I can’t imagine people won’t invent their way around it thus increasing the productivity of capital in the long run. And if catastrophe happens in slow motion, certainly people will be adjust fast enough to keep returns on capital high on average.
The most striking stylized fact about growth is its constancy. For whatever reason, people route around the particular circumstances of their time and space and invent their way to 2% growth. Why would climate change pose fundamentally different obstacles to innovation than what has been seen over the last 200 years? Do the open systems studied in Diamond’s Collapse tell us anything about the closed global system?
We have an incomprehensible, to most, outside-in view of the world. David Friedman says something correct but incomprehensible:
Climate aside, we do not live in a static world—consider the changes that have occurred over the past century. The shifts we can expect to occur due to technological progress alone, even without allowing for political and demograpic shifts, are much larger than the shifts required to deal with climate change on the scale I am discussing.
A few months back I was debating a petroleum engineer about peak oil. It occurred to me that if petroleum engineers didn’t get excited about hard problems in energy production, maybe those hard problems wouldn’t get solved. This, I think, is the problem with the assumption of exogenous technology and this is the problem with economists giving policy advice.