Today, we started out by talking about an article in this week’s New Yorker which reviews two books:
- “Predictably Irrational: The Hidden Forces That Shape Our Decisions” (Harper; $25.95), Dan Ariely
- “Nudge: Improving Decisions About Health, Wealth, and Happiness” (Yale; $25), Richard H. Thaler and Cass R. Sunstein
We talked briefly about how, when visibly faced with a higher number, you will assign a higher price to an object and vice versa, without consciously being aware that they are doing so. Ariely’s experiment on students assigning prices after being told to write the last two digits of their SSN confirmed this. Students with the highest SSNs had three times as high prices than those with the lowest SSNs. This is disturbing to economists because in all of our models, prices are determined by supply and demand, and not by the presence or absence of large numbers in view.
We then went over the results of Tuesday’s class survey and, as you all overwhelmingly pointed out – I am going too fast. In response to that, I will do my best to go slower and implement as many of your various suggestions as I can.
As I said in class, your feedback is much appreciated.
On to Regular Business
We started out by reviewing the assumptions of the flexible-price model. The time horizon of the model is such that it allows all prices and wages to adjust, so that all markets are in equilibrium. We talked about the example of umbrella-sellers in Times Square in Manhattan. When it rains, the prices increase, and when it stops they go down again. This is a case of perfectly flexible prices – they adjust to increases in demand instantaneously. This flexibility is the fundamental basis of this model: Everything is always in equilibrium. Later, we will look at when everything is not always in equilibrium.
We reviewed the concept of potential output and distinguished it from actual output (current real GDP). In our model however, because we have everything always in equilibrium, there is no unemployment (everyone who wants to work is always working) and so our actual output is always equal to potential output.
We calculate potential output by using a close cousin of our old friend Cobb-Douglas, but this time, labor (L) is held constant, along with efficiency (E) and the diminishing-returns-parameter (). The new function (and its graph) looks like this:
Now that we know how potential output is determined, we are concerned with how the labor market comes into equilibrium.
The Labor Market
The labor market depends on the businesses in the economy. Since we are in equilibrium, it so happens that the businesses hire all available workers. Each individual business however, will hire workers to maximize its own profits. And the rule it uses to maximize profits, is marginal revenues = marginal costs. That is, the revenue gained from producing one extra unit of output, should equal the costs of hiring one extra worker. Since we are looking at the labor market, we hold the amount of capital constant, and to simplify things we let the total amount of capital (K) = 1.
Each business has its own Cobb-Douglas III production function, and while we assume K = 1, and E are determined from firm to firm and L is determined by the profit-maximizing rule. At this point, we introduce a new concept – that of the marginal productivity of labor (or MPL). It is the additional output produced by adding one extra unit of labor (or one worker) to the firm. This has to do with profit-maximization, and the MPL x Price of product (or P) = marginal revenue. The marginal costs are the costs of hiring one additional laborer, which is the wage rate (W). The free markets decide W and P. So, the profit-maximizing rule in our case becomes: MPL x P = W.
We went over an example to calculate MPL – this is in my slides (and in your text, with less detail), and I will not repeat that here – do take a look at the slides for that example. We ran out of time finishing up the example, but a take-home exercise for you to do was to calculate the MPL and the revenues when the firm in our example goes from hiring 400 laborers, to 401.
We’ll go over this again in the next class.