Let's pick up where we left off the last session. And we were talking there about American Airlines and the incentives companies have to minimize cost. Another example of this is what happens when we move from public ownership to private ownership. Where people have skin in the game. And can more directly benefit from minimizing costs. We see fairly dramatic improvements in productivity. A case in point, where under Margaret Thatcher, and this is portrayed in Table 8.2, the productivity gains that occurred when formerly state owned enterprises were privatized. And these were just four cases. Let's say in the case of British Telecom, the number of employees pre-privatization, the year the organization was privatized, what happened to the employee base after, and the total revenue pre and post. And what you'll see in these different situations, was how much productivity per employee improved. Anywhere on the order of 11% to 180%. In some cases not depicted in Table 8.2 the gains were even more significant. For example, in the coal production, productivity increased by a factor of five. A prominent think tank in England concluded that privatization that you could get the same level of total revenue with half the original amount of employees, the true moving to a privatization approach. What we're seeing nowadays in India and China, provides a wonderful additional set of examples. The gains being made in those countries, Deng Xiaoping, for example, was a prominent driver of reform in China. And two of his most famous sayings is, were, we have to seek truth from facts. And the other he said I don't care if the cat is colored black or white. So long as it can successfully hunt mice. He ultimately promoted the communist system to become more open to markets, and more open to private incentives. One of the most famous economists that pointed out the benefits of private ownership, of skin in the game, was Freidrich Hayek, an Austrian economist. Who predicted in the 30s and 40s that communism would eventually fail. there were two economists before him Lange and Lerner who had set up a model and showed central planning could work. That it could fulfil Karl Marx's dichtome that a system, all it needed to do was be like a highly efficient and intelligent computer, and it could figure out how to take from each according to its ability and give to each according to her needs. Hayek was the first one to point out that in today's dynamic marketplace, that people that are closest to information need to retain incentive, need to have skin in the game to act on that information and to profit from it. And that market economies that leave power in the hands of the general populace do a better job of providing those incentives to minimize cost and ultimately profit. And to show you a couple examples of that phenomena, one of my favorite MBA students of all time went to work for a large dairy products firm and at this firm each year they were frustrated that they weren't getting the sales they hoped for for people that were in transit. namely because at the time, milk cartons were square and cupholders in cars were not. And each year this company would send representatives to Detroit in the United States to convince the big three car manufacturers, at least could you put, at least one of the cupholders, and make it square. So it will accomodate people taking milk cartons on the road. They're unsuccessful each year. Until this person with her creativity and closest to the action decided, well instead of trying to convince one of the big three auto manufacturers, why don't we make the milk container cylindrical. It was the single biggest innovation in the period of five to ten years in the dairy product industry and made her incredibly successful as well as her company. An international example along these lines, in China it has become a big holiday November 11th. And it's called singles day because there are four ones, one, one, one, one. And this year there was a record amount of sales by one provider of online commerce, Alibaba. That sold this year, I believe was $5.3 billion dollars in one day. Surpassing by a factor of 2.5 what the entire US economy did on cyber Monday the year before. The creativity of this company, Alibaba, to notice that people would use this touted holiday as a way to make purchases. and tap and targeting to singles how they could provide the service that singles could commemorate the occasion with, has been an immensely powerful innovation through this privately run company in China. Now, let's turn to how we can use this gold rule of cost minimization. And how we can look at how input prices change and how companies adapt in their cost minimizing behavior. Again the rule we saw last time was as a company you want to equate the marginal productivity per dollar spent on each input across inputs. What happens if input prices change? Let's say we're in the business of producing parking spaces and we use two inputs, concrete and land, and it's depicted in figure 8.5. Initially, we're at point E on the left hand panel of Figure 8.5. We're producing a thousand parking spaces, isoquant a thousand, and through a certain mix of expenditure on land, and concrete, and using a certain amount of total cost, TC1. Now let's say we take this firm and we move it toward a more urban location. So as we move to a more urban location the price of land is going to go up. How will things change? First and foremost, the total cost curve, the isocost line will pivot inward. We can still end up spending the same amount on concrete because the price of concrete hasn't changed, presumably. But, we can't spend, we can't purchase as much land as we did in the former location once we've made the move to the urban location. At the extreme, we can reach point N prime versus point N before. The isocost line is pivoted in. And earlier, we saw analogs and consumer theory how budget constraints pivot in when a particular price of a final good increases. Now we ask the question at this higher price of land, if we still want to produce the same thousand parking spaces, how much will we have to spend and what will be the mix of labor and concrete? To answer that question we have to think at the new slope of the isocost line MN prime. How much do we parallel shift it outward to be able to reach the same isoquant and produce that isoquant at now the lowest possible cost? With the higher price of land, the least costly input combination now occurs at E prime, and with us spending TC2 on total, on inputs across the two inputs. Note two things about this end result. We're using more concrete and less land. We've substituted away from land toward concrete as the price of land has increased. And at each output level, in pan, in the right hand panel, if we want to produce a thousand units of output, the marginal cost and the average cost have increased because one of the inputs is now grown more expensive. This figure, these figures have import for what happens in the real world. Think about what parking structures look like when we move from suburban to urban settings. In places like Tokyo where the land is very expensive, we'll end up with 40 story parking structures, maybe accommodating four cars at each level, and elevators take the cars up and down. Will use very little land, but a lot of concrete, to react to this higher price a land in the urban setting. And think through more in slow motion if we're trying to equate marginal product of concrete per price of concrete, to the ratio of marginal product of land to price a land. If first there's an increase in the price of land, then the ratio of marginal product of land to the price of land will go down. The rate of return now on land is less than the rate of return on concrete. And so what will firms do? The rate of return on concrete on that bank is higher so we've got to shift more money, more of our total expenditure into concrete away from land. And we'll keep shifting until those ratios are out of whack, until they are brought into equality. What helps bring 'em into equality, the law of diminishing returns. As we spend more on concrete, the marginal product goes down. And as we spend less on land, the marginal product of land goes up. So that reallocation of the law of diminishing returns will serve to bring the equalities into line. A few other examples of the law of, of the golden rule of cost minimization at work. let's say we look at how buildings used to be raised, destroyed, in Hong Kong three, four decades ago. Typically nowadays, in the United States we'll use dynamite or some explosive, and we'll rig the building so it collapses on itself. A few decades ago in Hong Kong they would employ a lotta labor. Literally a group of workers would show up with pickaxes, and start at the topmost floor. And end up picking at the top floor until it was removed and carrying off the building on their backs. And literally they would work their way down the different levels of the skyscaper. Why? It's the golden rule of cost minimization at work. Labor at that time in Hong Kong was cheaper relative to the United States. The dynamite cost about the same. And so as you moved from destroying buildings from the United States to Hong Kong, the rate of return on a dollar spent on labor was higher than the rate of return on dynamite. It pro, and it induced that shift away from dynamite, toward labor. Sometimes it's not the input prices that vary. Sometimes it's the marginal productivities of inputs. Think about baseball or hockey. Not all stadiums are the same size and so, stadiums that are larger, the marginal productivity of faster players, of players that can hit singles is greater than in, in smaller stadiums. In smaller stadiums the marginal productivity of people that can hit, of hitters that can hit the ball out of the park, home runs, is higher relative to larger stadiums. And so what we see in smaller stadiums is teams adjust. They tend to hire players that are better at hitting home runs. And shift away from players that are speedier on the base pass that are good singles hitters. Same in college hockey. I used to teach undergraduates at Harvard when I was a graduate student at MIT. And I got hooked on following college hockey through a number of my students. One time had a student a guy by the name of Mark Benning, who showed up in my class and was watching the news later that evening. And, and they were recounting the hockey score, and they said Harvard beats Yale, and Benning scores two goals. I was having a hard time. I had seen this name before, and finally realized it was a student in my class. But he, he wasn't that tall, and he wasn't that brawny. And yet he was very quick. Harvard's hockey rink is pretty large, and they even super cool the rink so that it makes the ice that much more quick. What the size of the rink at Harvard has led to is that university tending to recruit players that are quick on their feet and less brawny. Yale by contrast, built a smaller rink at the time and they tended to recruit more NHL national hockey league type, very brawny, hunt down the opposition and kill them. because a smaller rink place to the advantage of skaters that aren't that quick but are muscular in being able to check people into the boards and keep them, keep them at bay. So sometimes it's the marginal productivities that differ across locations. But it's the same underlying golden rule of cost minimization that's at work.
