I’ve removed my research page from this site and properly updated my LSE site.
Tag Archive for 'LSE'
This is mostly a note to myself.
Way back in the dawn of the modern-macro era, the fresh-water Chicago kids came up with Real Business Cycle theory where they endogenised the labour supply and claimed that macro variation was explained by productivity shocks.
The salt-water gang then accepted the techniques of RBC but proposed a bunch of demand-side shocks instead.
The big criticism of productivity shocks has always been to ask how you can realistically get negative shocks to productivity. Technological regress just doesn’t seem all that likely.
Now, models of credit cycles like Kiotaki (1998) show how a small and temporary negative shock to productivity can turn into a large and persistent downturn in the economy. In short: Credit constraints mean that some wealth remains in the hands of the unproductive instead of being lent to the productive sectors of the economy. The share of wealth owned by the productive is therefore a factor in aggregate output. A temporary negative shock to productivity keeps more of the wealth with the unproductive for production purposes and it takes time for the productive sector to accumulate it’s wealth back. If some sort of physical capital (e.g. land) is used as collateral, the shock will also lower the price of the capital, thus decreasing the value of the collateral and so imposing tighter restrictions on credit.
But Kiyotaki’s model still requires some productive regress …
Looking at Aiyagari (1994) and Castaneda, Diaz-Gimenez and Rios-Rull (2003) today (lecture 3 by Michaelides in EC442), I realise that small negative productivity shocks are conceptually okay if they’re applied idiosyncratically (i.e. individually) to labour.
Let 
be your efficiency state in period 
. 
is a Markov process with transition matrix 
. 
is the efficiency of somebody in state . Castaneda, Diaz-Gimenez and Rios-Rull use this calibration, taken from the data:
| State | s=1 | s=2 | s=3 | s=4 |
| e(s) | 1.00 | 3.15 | 9.78 | 1,061.00 |
| Share of population | 61.1% | 22.35% | 16.50% | 0.05% |
The transition matrix would be such that the population-shares for each state are stationary.
A household’s labour income is then given by 
.
A movement from s=3 to s=2, say, is therefore a negative labour productivity shock for the household.
The trick is to think of the efficiency states as job positions. Somebody moving from s=3 to s=1 is losing their job as an engineer and getting a job as an office cleaner. They will probably increase 
to partially compensate for the lose in hourly wage (
).
Remember that in the (Neo/New) Classical models, there’s an assumption of zero unemployment. However much you want to work, that’s how much you work. [That might sound silly to a casual reader, but it's okay as a first approximation. There are (i.e. search-and-matching) models out there that look at unemployment and can be fitted into this framework.]
If everybody is equally good at every job position (as we have here) and all the idiosyncratic shocks balance out so the population shares are constant, then – I believe – there shouldn’t be any change in observed aggregate productivity.
However, if you introduced imperfect transfer of ability across positions so that efficiency becomes 
where 
is your private type per job position, then idiosyncratic shocks could therefore show up in aggregate numbers.
This is essentially an idea of mismatching. A senior engineering job is destroyed and a draftsman job is created both in Detroit, while the opposite occurs in Washington state. Since the engineer in Detroit can’t easily move to Washington, he takes the lower-productivity job and a sub-optimal person gets promoted in Washington.
This is mostly for my students in EC102. There’s a concept in economics called sunk costs. A sunk cost is one that is spent and unrecoverable: it’s gone and you can’t get it back. Since you cannot get them back, you should ignore sunk costs when deciding what to do in the future. To illustrate the importance of that dictum, consider the following:
You are a software company. Your business model involves a large, upfront expenditure as you develop and write your program, followed by extremely low variable costs when selling it (the marginal cost of producing another DVD is very low). Since you’ll be the only company selling this particular piece of software, you will have pricing power as a (near) monopolist. Before you start, you can estimate the demand curve you’ll face and from that estimate what your total revenue will be (remember, MR = MC will give you the (Q,P) pair). If your expected revenue is larger than your estimate of the total cost of developing and selling the software, you should go ahead.
For simplicity, we’ll assume that the marginal cost of producing a new DVD is zero. That means that your Variable Cost is zero and Total Cost = Fixed Cost. For any uber-nerds in the audience, we’ll also assume risk-neutrality (so that we only need to look at expected values) and a rate of time preference equal to zero (so that we can compare future money to today’s money without discounting).
Here’s the situation we start with:
| Month | Fixed Cost (actual) | Fixed Cost (future, estimated) | Fixed Cost (total, estimated) | Total Revenue (estimated) |
| January | 0 | 100 | 100 | 120 |
In January, since you expect your revenue to exceed your costs, you decide to go ahead. But in February, after spending 50, you realise that it’s going to take more work than you first thought to write the software. In fact, you still need to spend another 80 to get it ready for sale. You’re now facing this situation:
| Month | Fixed Cost (actual) | Fixed Cost (future, estimated) | Fixed Cost (total, estimated) | Total Revenue (future, estimated) |
| January | 0 | 100 | 100 | 120 |
| February | 50 | 80 | 130 | 120 |
Should you still keep going?
The answer is yes! The reason is that, in February, the 50 you spent in January is a sunk cost. You cannot get it back and so should ignore it in your calculations. In February you compare a future cost of 80 and a future revenue of 120 and decide to go ahead. The 40 you will make will offset your sunk costs for a total profit of -10. If you stopped, your total profit would have been -50.
This sort of situation is depressingly common in the IT industry. You can even get awful situations like this:
| Month | Fixed Cost (actual) | Fixed Cost (future, estimated) | Fixed Cost (total, estimated) | Total Revenue (future, estimated) |
| January | 0 | 100 | 100 | 120 |
| February | 50 | 80 | 130 | 120 |
| … | … | … | … | … |
| October | 140 | 10 | 150 | 80 |
By October, you’ve already spent 140 – more than you ever thought you might make as revenue – and you still aren’t finished. Thankfully, you think you’ve only got to spend 10 more to finish it, but you’ve also now realised that the demand isn’t so good after all (maybe you’ve had to cut back on the features of your product so not as many people will want it), so your estimated future revenue is only 80.
Even then you’re better off ploughing ahead, since you’re choosing between a loss of 140 and a loss 70.
For extra credit: Imagine that you’re the bank lending money to this software company. In January you lent them 100, in February an extra 30. In October, knowing that the company is going to go bankrupt, would you lend them the last 10 as well? (Yes, I realise that I’m ignoring the cost to the IT company of interest repayments.)
Once again, I’m teaching EC102, a mathematics-oriented introduction to economics for first-year undergraduate students at the London School of Economics. The following is a question from one of the students’ weekly quizzes:
A population consists of two types, “friendlies” (Fs) and “aggressives” (As). Each individual interacts with a randomly chosen member of the population. When two Fs interact, they each earn 3 units. When two As interact, they each earn 0. When an F and an A interact the former gets 1 unit and the latter 5 units. The growth rate of each type is proportional to their average payoff. What will be the equilibrium population share of Fs?
There are some hints over the fold …
Continue reading ‘Could you do first-year economics?’
Today I sat down with my supervisor, Professor Andrea Prat, to talk some more about my research ideas. I would have liked to speak with him more frequently over this year, but it turns out that teaching is taking more time than I anticipated, just as everyone warned me it would.
My ideas are a lot more fleshed-out than the vague arm-waving on my research page and Prof. Prat seemed excited at where they are going. That’s big in itself – when one of my friends here at LSE heard that he was going to be my supervisor he replied with: “Wow. He must have an IQ of, like, a million.” Not having great, gaping holes shot in my thoughts is a minor victory in itself. 
I wasn’t planning on developing it fully for my research paper this year, but even on the area that I was thinking of doing, his unnerving comment was that it is probably still a bit too big an idea for this year.
Bugger.
Apologies for the hiatus. I’ve been moving house, dealing with a broken computer, finishing up a job and stuff like that.
It turns out that I will be a class teacher (a “T.A.” for any Americans in the audience, a “tutor” for any Australians) this year for EC102. It is the largest course offered by LSE, with something like 700 students. It’s meant to be a year-long introduction to economics for the more mathematically-inclined students that intend to continue studying the topic in the rest of their degree. I’ll be looking after five classes, with 15 or so eager young minds in each. Joy.
Brad DeLong has mused on the purpose of a course in political economy:
This is where we cash in our winning intellectual bets, tie all the threads together, and come up with running code for a rough-and-ready framework for thinking about everything that happens at the crossroads where history and politics meet economies and sociologies in a world where village elders along the Zambezi lecture the principal deputy managing director of the International Monetary Fund on the implications of the Republican convention.
I sat in on a few lectures for LSE’s graduate-level course in this stuff over the last year (I may yet take it formally as my second optional) and I have to say that I find Brad’s vision a lot more interesting. Perhaps I should be doing my PhD at Berkeley?
Recent Comments