Hi, in this next set of lectures we're gonna look at a series of models that help us try and understand an empirical phenomenon. That empirical phenomenon is this: so if you look out there in the world you'll see that groups of people who hang out together tend to look alike, think alike, act alike So, [inaudible] is trying to make sense of why that's the case. First, lemme sort of explain what I mean a little bit. If you look at a city like Detroit, this is a census map of the city of Detroit, what you see is each blue dot represents a city block that's majority African American. The majority people living in that block, census block, are African American. The red dots are blocks that are majority Caucasian. So what you see in the city of Detroit, you see incredible segregation. It shows that people literally choose to live with people who look a lot like they do. But it's not just this sort of sorting effect. Another reason that people who sort of are hanging out together look and act similarly, is that, well, we change our behavior, we moderate our behavior to match that of people around us. So take, for example, smoking It could be that you don't smoke and you start hanging out with a bunch of people who do, so you may have an occasional cigarette. Or alternatively, you may have spent your whole life smoking but now you hangout with a group of people who don't smoke and so you say, "You know what? That's it, I'm gonna, I'm gonna stop smoking." So, if these two forces, one of them which is sorting, or what sociologists call homophily. You know that we sort of choose to hang out with people who are like us. And there's this other effect which is we choose to start acting like, believing like, people we're hanging out with. And so both of these things are gonna create groups of people who look similar to one another. Okay, so what we wanna do is we wanna try and get some understanding of how those processes work. Through some simple models. Now, these may seem like, sort of, fairly obvious things to look at but what we're going to find is when we construct models we get some pretty interesting unexpected results. Okay, so let's get started. What's it gonna look like? What are the lectures going to look like in this unit in this module. We're going to start out with a famous model constructor, a guy named Thomas Schelling. And this is a model of racial segregation and it's sometimes called Schelling's tipping model. And that model we're going to see how it's a little more subtle than we might think about what causes those segregation models like we see in Detroit. After that, we're gonna look at a model by a guy named Mark Granovetter who looked at sort of people's willingness to participate in some sort of collective behavior. This could be a riot, this could be a political uprising, it could be a social movement. Very, very simple model. After that, we're going to extend this Granovetter's model is something I call the standing ovation model. This a model that my friend John Miller and I developed kind of for fun but it gets at a really serious point. It is a model of peer effects where you change your behavior to match that of others around you. And what's interesting about it is the standing ovation gives us a really nice framework within which to think about this question. And again there we are going to get some surprising results. Oh right. Then last after we have sort of done all of this, we are going to talk about something called the identification problem. And that is, suppose it's the case that I look at a group of people and they all seem similar. Well, the question is did they sort? I mean, did they choose to hang out with one another because they were similar? Or was there some sort of peer effect? Were they hanging out and they ... Do they all sort of look, and talk and act the same? So that is an interesting question to try and figure out. And these models will give us some understanding how we can tell these two things apart. Okay. So Let's get started. Now before we do though one quick comment about the type of model we are going to be using here. Now, a lot of times when people think about models they think about equation based models. So when I teach this course, let's [inaudible] I teach this course to my undergraduates one of the things that some of them care about, not all, but a lot care about is their grade. And so I can say to them well you know here is an equation based model for your grade. It looks something like this. Your score on the final exam is going to be 50 plus five times the number of hours you worked. Study, right? So, if you don't study at all, you put in no hours of study, you will probably get a fifty on the exam and fail the course. If you put in ten hours on the exam then you'll probably, you know studying for the exam, then you will probably ace the test and get an A of the course. So this would be a linear model. Sort of explains how the world works with an equation. Now the models we are going to do in this unit aren't linear models. They are what is called agent based models. So what's an agent based model? An agent based model works as follows. You have a bunch of agents. These can be people, these can be firms, they can be countries, they could be organizations. But they're agents, objects of the model. Now these agents have behaviors. Things that they do, rules they follow. Now in some cases these rules might be optimal rules. They may be optimized. In that case it becomes what we call a game theory model or rational choice model where individuals are doing the optimal thing in the context of the model. In a [inaudible] shoot we study here, they're not going to be optimizing. They're going to following Pretty simple rules. And then the third part of the [inaudible] models, once you've got all these agents following all these rules, that creates something at the macro level. It creates some sort of outcome. And so what we can do is then ask sort of what kind of outcome do we get. What we will find in these models is that the outcomes are sort of surprising and that's, again, why models are so useful. Because we may logically think that if we assume agents that follow this behavior we are going to get outcome A. But when we work through the model and actually, you know, work through all the logic we'll find, in fact, that maybe the opposite is true or that something, or you know, sort of surprising is true. Okay. So that is it. That is the plan. We are going to look at some models of sorting and we are going to look at some models of peer effects and we'll learn how the two differ and how the two are also a little bit the same. All right. Thank you.