WEBVTT 00:00:00.000 --> 00:00:01.980 align:middle line:90% [SQUEAKING] 00:00:01.980 --> 00:00:04.455 align:middle line:90% [RUSTLING] 00:00:04.455 --> 00:00:14.380 align:middle line:90% [CLICKING] 00:00:14.380 --> 00:00:16.730 align:middle line:84% ROBERT TOWNSEND: Well, good afternoon, everyone. 00:00:16.730 --> 00:00:18.020 align:middle line:90% Thanks for joining. 00:00:18.020 --> 00:00:23.170 align:middle line:84% So this is 14.04, and the title is Economic Science. 00:00:23.170 --> 00:00:26.090 align:middle line:90% You'll see why momentarily. 00:00:26.090 --> 00:00:29.170 align:middle line:84% So in terms of who we are, I'm Professor Townsend. 00:00:29.170 --> 00:00:31.600 align:middle line:84% I'll be teaching the main lectures. 00:00:31.600 --> 00:00:34.900 align:middle line:90% So what is this course about? 00:00:34.900 --> 00:00:38.870 align:middle line:84% This is about not just theory and certainly not just data. 00:00:38.870 --> 00:00:41.590 align:middle line:84% It's about the combination of theory and data 00:00:41.590 --> 00:00:45.220 align:middle line:84% from the perspective of economics as a science. 00:00:45.220 --> 00:00:47.530 align:middle line:84% So in that respect, it may be a little bit 00:00:47.530 --> 00:00:50.320 align:middle line:84% different from classes that you're used to. 00:00:50.320 --> 00:00:53.410 align:middle line:84% It's not to memorize theoretical material 00:00:53.410 --> 00:00:55.450 align:middle line:84% and know which way to shift a curve. 00:00:55.450 --> 00:00:59.330 align:middle line:84% It's not just reading empirical literature and discussing it. 00:00:59.330 --> 00:01:01.600 align:middle line:84% It's the more challenging and more fun job 00:01:01.600 --> 00:01:04.750 align:middle line:84% of bringing those two things together. 00:01:04.750 --> 00:01:08.470 align:middle line:84% Background quickly, just in case you're worried about it-- 00:01:08.470 --> 00:01:12.670 align:middle line:84% we do assume you've had multivariate calculus as well 00:01:12.670 --> 00:01:16.990 align:middle line:84% as basic economic theory in 14.01. 00:01:16.990 --> 00:01:22.270 align:middle line:84% There will be some use of linear algebra, statistics, 00:01:22.270 --> 00:01:25.630 align:middle line:84% and some language having to do with algorithms and computing. 00:01:25.630 --> 00:01:28.720 align:middle line:84% But you're not to worry about that because if you are not 00:01:28.720 --> 00:01:30.670 align:middle line:84% familiar with the level that we need, 00:01:30.670 --> 00:01:32.950 align:middle line:90% and it's not a very deep level. 00:01:32.950 --> 00:01:37.270 align:middle line:84% In terms of the readings, all the class readings 00:01:37.270 --> 00:01:39.850 align:middle line:84% and the relevant textbook chapters, 00:01:39.850 --> 00:01:42.130 align:middle line:84% there's not one single textbook for the class. 00:01:42.130 --> 00:01:43.510 align:middle line:90% There's four or so. 00:01:43.510 --> 00:01:46.960 align:middle line:84% But we carefully selected the relevant sections 00:01:46.960 --> 00:01:50.010 align:middle line:84% of those textbooks, and you don't need to scramble 00:01:50.010 --> 00:01:53.320 align:middle line:84% to find them because they're on the class website. 00:01:53.320 --> 00:01:58.330 align:middle line:84% So each topic in each lecture has a set of readings. 00:01:58.330 --> 00:02:02.890 align:middle line:84% One, two, or three will be designated as a star. 00:02:02.890 --> 00:02:07.240 align:middle line:84% And that's because they're really the basis of the lecture 00:02:07.240 --> 00:02:10.840 align:middle line:84% or provide key complementary reading material. 00:02:10.840 --> 00:02:15.830 align:middle line:84% You are responsible for those in terms of exams, 00:02:15.830 --> 00:02:18.970 align:middle line:84% and you'll need them for problem sets. 00:02:18.970 --> 00:02:22.270 align:middle line:84% There are other things on the reading list, 00:02:22.270 --> 00:02:26.770 align:middle line:84% recommended readings that I hope you will engage in and enjoy. 00:02:26.770 --> 00:02:29.170 align:middle line:84% And in fact, those could be subjects 00:02:29.170 --> 00:02:30.625 align:middle line:90% for discussion in Piazza. 00:02:30.625 --> 00:02:33.310 align:middle line:90% 00:02:33.310 --> 00:02:37.790 align:middle line:84% We're going to focus on theory and applications. 00:02:37.790 --> 00:02:40.150 align:middle line:84% We're going to be using empirical and theoretical 00:02:40.150 --> 00:02:41.110 align:middle line:90% papers. 00:02:41.110 --> 00:02:43.960 align:middle line:84% And ideally, we are combining them. 00:02:43.960 --> 00:02:46.300 align:middle line:84% As I was already alluding to, this 00:02:46.300 --> 00:02:48.020 align:middle line:90% is not an easy thing to do. 00:02:48.020 --> 00:02:50.350 align:middle line:90% One has to learn how to do this. 00:02:50.350 --> 00:02:53.660 align:middle line:84% And I'm sure you cannot do it on your own, 00:02:53.660 --> 00:02:58.900 align:middle line:84% so I strongly encourage you to participate in the lectures, 00:02:58.900 --> 00:03:02.080 align:middle line:84% and recitations, and interactions. 00:03:02.080 --> 00:03:05.800 align:middle line:84% But anyway, please engage when you're online 00:03:05.800 --> 00:03:09.820 align:middle line:84% and avoid texting, tweeting, emailing, blogging, 00:03:09.820 --> 00:03:14.230 align:middle line:90% et cetera, et cetera, shopping. 00:03:14.230 --> 00:03:17.260 align:middle line:84% You may think that you can multitask, 00:03:17.260 --> 00:03:21.490 align:middle line:84% but typically quality of learning would suffer. 00:03:21.490 --> 00:03:24.530 align:middle line:84% So now we get into the more fun part, 00:03:24.530 --> 00:03:28.610 align:middle line:84% which is what are we going to be studying in this class. 00:03:28.610 --> 00:03:33.730 align:middle line:84% And I'm going to go over the spirit of it, economic science, 00:03:33.730 --> 00:03:35.770 align:middle line:84% and talk about the economies we're 00:03:35.770 --> 00:03:38.500 align:middle line:84% going to be studying, and then go 00:03:38.500 --> 00:03:42.240 align:middle line:84% through the syllabus in a kind of a broad way, 00:03:42.240 --> 00:03:45.530 align:middle line:84% not trying to read everything that's there. 00:03:45.530 --> 00:03:52.090 align:middle line:84% So I'm going to draw on these authors-- 00:03:52.090 --> 00:03:56.310 align:middle line:84% Frisch for thinking about economics as experiments, 00:03:56.310 --> 00:04:01.600 align:middle line:84% Matzkin for a review of some of the fundamentals of vocabulary 00:04:01.600 --> 00:04:06.070 align:middle line:84% of econometrics, Angrist for randomized and natural 00:04:06.070 --> 00:04:13.750 align:middle line:84% experiments, Varian for big data and the need of theory 00:04:13.750 --> 00:04:17.410 align:middle line:84% for causal influence, and Lucas on what 00:04:17.410 --> 00:04:22.089 align:middle line:84% are models, what are artificial economies, and what 00:04:22.089 --> 00:04:24.190 align:middle line:84% is the role of models versus data, 00:04:24.190 --> 00:04:28.500 align:middle line:84% and how does computation help us. 00:04:28.500 --> 00:04:31.100 align:middle line:84% So that's just an outline of what's coming. 00:04:31.100 --> 00:04:38.220 align:middle line:84% Frisch opened his lecture in 1926 00:04:38.220 --> 00:04:42.810 align:middle line:84% with an article entitled "On a Problem in Pure Economics." 00:04:42.810 --> 00:04:45.720 align:middle line:84% And to quote him, he said, "Intermediate between 00:04:45.720 --> 00:04:51.790 align:middle line:84% mathematics, statistics, and economics, Econometrics"-- 00:04:51.790 --> 00:04:55.660 align:middle line:84% he kind of invented the term-- "has as its aim to subject 00:04:55.660 --> 00:04:59.680 align:middle line:84% abstract laws of theoretical political economy or pure 00:04:59.680 --> 00:05:03.520 align:middle line:84% economics to experimental or numerical validation, 00:05:03.520 --> 00:05:07.570 align:middle line:84% and thus to turn pure economics, as far as possible, 00:05:07.570 --> 00:05:10.630 align:middle line:84% into a science in the strictest sense of the word." 00:05:10.630 --> 00:05:13.210 align:middle line:84% Or to put this more in layman's terms, 00:05:13.210 --> 00:05:17.020 align:middle line:84% he's saying economics is not just about theory, 00:05:17.020 --> 00:05:19.970 align:middle line:90% it's about validating theory. 00:05:19.970 --> 00:05:24.010 align:middle line:84% So just like the linear accelerator at Stanford 00:05:24.010 --> 00:05:27.520 align:middle line:84% bombards particles to see whether the outcomes are 00:05:27.520 --> 00:05:30.070 align:middle line:84% consistent with the predictions, that's 00:05:30.070 --> 00:05:33.460 align:middle line:84% our framework for thinking about actual economies, 00:05:33.460 --> 00:05:36.730 align:middle line:84% by running experiments on them to validate them 00:05:36.730 --> 00:05:39.580 align:middle line:90% and to do policy. 00:05:39.580 --> 00:05:43.120 align:middle line:84% This is a graph from Burns and Mitchell, 00:05:43.120 --> 00:05:47.440 align:middle line:90% a book, On Business Cycles. 00:05:47.440 --> 00:05:49.650 align:middle line:84% And if you look closely, you'll see 00:05:49.650 --> 00:05:51.130 align:middle line:90% these dates are pretty early. 00:05:51.130 --> 00:05:54.510 align:middle line:90% They run from 1875 to 1900. 00:05:54.510 --> 00:05:57.720 align:middle line:84% And as a business cycle goes, it's 00:05:57.720 --> 00:06:03.760 align:middle line:84% talking about depressed activity versus upswings and so on. 00:06:03.760 --> 00:06:05.670 align:middle line:84% And you can see the ups and downs. 00:06:05.670 --> 00:06:09.750 align:middle line:84% You might be interested to know that the National 00:06:09.750 --> 00:06:13.500 align:middle line:84% Bureau of Economic Research, which is now housed here 00:06:13.500 --> 00:06:17.670 align:middle line:84% in Cambridge, actually began in Columbia, where 00:06:17.670 --> 00:06:20.820 align:middle line:84% Burns and Mitchell were working on this. 00:06:20.820 --> 00:06:24.790 align:middle line:84% So Koopmans reacted to Burns and Mitchell's book, 00:06:24.790 --> 00:06:26.820 align:middle line:84% which was quite famous and obviously 00:06:26.820 --> 00:06:30.720 align:middle line:84% had an enormous influence, arguing about 00:06:30.720 --> 00:06:32.955 align:middle line:84% whether measurement is enough, which 00:06:32.955 --> 00:06:36.810 align:middle line:90% he says, no, we need theory. 00:06:36.810 --> 00:06:39.750 align:middle line:84% And we need the whole enterprise to be 00:06:39.750 --> 00:06:42.990 align:middle line:84% about understanding and utilizing 00:06:42.990 --> 00:06:45.250 align:middle line:90% the framework for policy. 00:06:45.250 --> 00:06:46.740 align:middle line:84% So there's a bunch of quotes here 00:06:46.740 --> 00:06:50.370 align:middle line:84% from Koopmans in this famous article, Measurement Without 00:06:50.370 --> 00:06:50.950 align:middle line:90% Theory. 00:06:50.950 --> 00:06:53.730 align:middle line:84% He says, "The author's scientific strategy 00:06:53.730 --> 00:06:57.630 align:middle line:84% has measurement and observation preceding, and largely 00:06:57.630 --> 00:07:02.100 align:middle line:84% independent of, any attempts to really explain" the variables. 00:07:02.100 --> 00:07:05.910 align:middle line:84% But he, Koopmans, believes there should or could 00:07:05.910 --> 00:07:07.410 align:middle line:90% be more of a purpose-- 00:07:07.410 --> 00:07:11.490 align:middle line:84% that more is meant, namely, a genuine explanation 00:07:11.490 --> 00:07:14.580 align:middle line:84% of economic fluctuations, with the idea that there 00:07:14.580 --> 00:07:18.780 align:middle line:84% are a few extra economic phenomena that are accepted 00:07:18.780 --> 00:07:20.250 align:middle line:90% as data without inquiry. 00:07:20.250 --> 00:07:24.840 align:middle line:84% But most of it has to do with phenomenon being generated 00:07:24.840 --> 00:07:28.260 align:middle line:84% by assumed behavior of individuals 00:07:28.260 --> 00:07:32.760 align:middle line:84% and the interaction of the behavior in markets. 00:07:32.760 --> 00:07:34.950 align:middle line:90% And then he goes on-- 00:07:34.950 --> 00:07:38.370 align:middle line:84% I don't know if this is tongue in cheek or just soft selling-- 00:07:38.370 --> 00:07:41.370 align:middle line:84% "I am not sure whether a still further objective 00:07:41.370 --> 00:07:45.270 align:middle line:84% is included, which extrapolates the idea of explanation 00:07:45.270 --> 00:07:48.750 align:middle line:84% to prediction, within "the narrowest attainable limits, 00:07:48.750 --> 00:07:52.680 align:middle line:84% the effect of economic policy on the movement 00:07:52.680 --> 00:07:54.750 align:middle line:90% of economic variables. 00:07:54.750 --> 00:07:57.750 align:middle line:84% He actually says, I feel that prediction is actually 00:07:57.750 --> 00:08:01.020 align:middle line:84% the most important objective of the analysis 00:08:01.020 --> 00:08:03.680 align:middle line:90% of economic fluctuations." 00:08:03.680 --> 00:08:06.550 align:middle line:84% So again, it's not just measurement, 00:08:06.550 --> 00:08:09.880 align:middle line:84% it's measurement with theory for understanding, 00:08:09.880 --> 00:08:16.910 align:middle line:84% and with that baseline conducting policy assessments. 00:08:16.910 --> 00:08:20.480 align:middle line:84% Business cycles are still with us, although this discussion 00:08:20.480 --> 00:08:22.620 align:middle line:90% may seem a bit dated. 00:08:22.620 --> 00:08:25.380 align:middle line:84% So I give you a contemporary example, 00:08:25.380 --> 00:08:28.640 align:middle line:84% which is measuring, understanding, 00:08:28.640 --> 00:08:36.450 align:middle line:84% and predicting the economic impact of COVID-19. 00:08:36.450 --> 00:08:40.387 align:middle line:84% And we will return to this theme periodically throughout some 00:08:40.387 --> 00:08:41.054 align:middle line:90% of the lectures. 00:08:41.054 --> 00:08:43.750 align:middle line:90% 00:08:43.750 --> 00:08:49.480 align:middle line:84% Matzkin is about econometrics, and she 00:08:49.480 --> 00:08:52.465 align:middle line:84% delineates the ingredients here quite well. 00:08:52.465 --> 00:08:56.260 align:middle line:84% We have an economic model describing 00:08:56.260 --> 00:08:59.800 align:middle line:84% the agents who are involved, their objective functions, 00:08:59.800 --> 00:09:03.540 align:middle line:84% their information, the way they're interacting. 00:09:03.540 --> 00:09:08.310 align:middle line:84% The econometrician tries to fit the economic model to the data 00:09:08.310 --> 00:09:10.440 align:middle line:84% and has to make the following distinctions-- 00:09:10.440 --> 00:09:13.950 align:middle line:84% first of all, which variables in the model are observable 00:09:13.950 --> 00:09:16.020 align:middle line:90% and which are unobservable? 00:09:16.020 --> 00:09:18.570 align:middle line:84% Also, which variables are determined 00:09:18.570 --> 00:09:21.450 align:middle line:84% outside the model versus those that are determined 00:09:21.450 --> 00:09:22.740 align:middle line:90% inside the model-- 00:09:22.740 --> 00:09:25.050 align:middle line:90% exogenous versus endogenous? 00:09:25.050 --> 00:09:27.300 align:middle line:84% Variables determined within the model 00:09:27.300 --> 00:09:30.450 align:middle line:84% are usually determined by the choices of agents, 00:09:30.450 --> 00:09:33.420 align:middle line:84% by their interaction with each other. 00:09:33.420 --> 00:09:37.680 align:middle line:84% The model also contains a list of functions and distributions. 00:09:37.680 --> 00:09:41.220 align:middle line:84% Some of these functions are primitive, exogenously 00:09:41.220 --> 00:09:41.790 align:middle line:90% determined. 00:09:41.790 --> 00:09:44.250 align:middle line:84% They may be observed or unobserved. 00:09:44.250 --> 00:09:47.460 align:middle line:84% And others are determined within the model itself. 00:09:47.460 --> 00:09:50.280 align:middle line:84% They're not deep concepts, but important to remember-- 00:09:50.280 --> 00:09:54.000 align:middle line:84% observed versus unobserved, exogenous versus endogenous, 00:09:54.000 --> 00:09:57.840 align:middle line:84% parameters versus functions versus distributions. 00:09:57.840 --> 00:10:02.040 align:middle line:84% Josh Angrist on running experiments, as in randomized 00:10:02.040 --> 00:10:05.350 align:middle line:84% controlled trial versus quasi-natural experiments. 00:10:05.350 --> 00:10:08.970 align:middle line:84% So he's referring here to a genuine randomized controlled 00:10:08.970 --> 00:10:11.850 align:middle line:84% trial engaged by Fehr and Goette, 00:10:11.850 --> 00:10:16.140 align:middle line:84% where they selected some bicycle messengers to receive 00:10:16.140 --> 00:10:19.710 align:middle line:84% temporarily higher wages, and had a control group that 00:10:19.710 --> 00:10:21.990 align:middle line:90% did not receive the increase. 00:10:21.990 --> 00:10:25.800 align:middle line:84% And then you compare across the two groups. 00:10:25.800 --> 00:10:28.740 align:middle line:84% The study showed that increase in wages 00:10:28.740 --> 00:10:31.140 align:middle line:90% did make people work harder. 00:10:31.140 --> 00:10:33.690 align:middle line:84% And because it was temporary, it didn't really 00:10:33.690 --> 00:10:35.610 align:middle line:90% change lifetime wealth. 00:10:35.610 --> 00:10:38.760 align:middle line:84% So one is able to out the impact of income changes 00:10:38.760 --> 00:10:43.650 align:middle line:84% as opposed to wealth changes, or in the jargon you'll learn, 00:10:43.650 --> 00:10:46.380 align:middle line:84% we can identify the intertemporal substitution 00:10:46.380 --> 00:10:48.690 align:middle line:90% of elasticity and its magnitude. 00:10:48.690 --> 00:10:52.710 align:middle line:84% But Josh goes on to say experiments are time-consuming. 00:10:52.710 --> 00:10:53.700 align:middle line:90% They're expensive. 00:10:53.700 --> 00:10:55.530 align:middle line:84% They're not always practical but. 00:10:55.530 --> 00:10:58.830 align:middle line:84% This frame that we use of experiments 00:10:58.830 --> 00:11:01.020 align:middle line:84% is still very helpful, especially 00:11:01.020 --> 00:11:04.200 align:middle line:84% because human institutions or the forces of nature 00:11:04.200 --> 00:11:07.830 align:middle line:84% step into the breach and provide natural or quasi-natural 00:11:07.830 --> 00:11:08.770 align:middle line:90% experiments. 00:11:08.770 --> 00:11:12.210 align:middle line:84% So an influential paper by David Card 00:11:12.210 --> 00:11:15.540 align:middle line:90% looked at the Mariel boatlift. 00:11:15.540 --> 00:11:20.640 align:middle line:84% Fidel Castro temporarily allowed free exodus of Cubans 00:11:20.640 --> 00:11:23.070 align:middle line:84% to the US, and they came to Miami. 00:11:23.070 --> 00:11:26.580 align:middle line:84% There was a 7% increase over a period of three months, 00:11:26.580 --> 00:11:30.660 align:middle line:84% and that can be used to study the impact of immigration. 00:11:30.660 --> 00:11:33.540 align:middle line:84% Another example is the destruction 00:11:33.540 --> 00:11:36.780 align:middle line:84% of public housing in Chicago, where they literally 00:11:36.780 --> 00:11:39.870 align:middle line:84% were giving residents alternative places to live, 00:11:39.870 --> 00:11:42.540 align:middle line:84% and then dynamiting the building and blowing it up. 00:11:42.540 --> 00:11:46.260 align:middle line:84% And it's documented that they chose 00:11:46.260 --> 00:11:50.320 align:middle line:84% in effectively a random way which building to blow up. 00:11:50.320 --> 00:11:52.800 align:middle line:84% And so you can compare what's happening 00:11:52.800 --> 00:11:55.020 align:middle line:84% in public housing that remains versus 00:11:55.020 --> 00:11:56.670 align:middle line:84% what's happening to the residents who 00:11:56.670 --> 00:11:58.740 align:middle line:90% have been moved elsewhere. 00:11:58.740 --> 00:12:01.170 align:middle line:84% And to a degree, the financial crisis 00:12:01.170 --> 00:12:04.770 align:middle line:84% also provides something of a series of natural experiments 00:12:04.770 --> 00:12:07.280 align:middle line:90% in banking. 00:12:07.280 --> 00:12:08.780 align:middle line:84% So I'm not sure how many of you have 00:12:08.780 --> 00:12:10.400 align:middle line:90% heard this term, "big data." 00:12:10.400 --> 00:12:15.320 align:middle line:84% It's quite widely used and attracts a lot of attention. 00:12:15.320 --> 00:12:18.050 align:middle line:84% And Varian is talking about that. 00:12:18.050 --> 00:12:20.450 align:middle line:84% Machine learning specialists are primarily 00:12:20.450 --> 00:12:23.210 align:middle line:84% concerned with developing high-performance computer 00:12:23.210 --> 00:12:26.780 align:middle line:84% systems that provide predictions in the presence of challenging 00:12:26.780 --> 00:12:28.820 align:middle line:90% computational constraints. 00:12:28.820 --> 00:12:32.630 align:middle line:84% Data science is a somewhat newer term, concerned with prediction 00:12:32.630 --> 00:12:36.530 align:middle line:84% and summarization, but also manipulation, visualization, 00:12:36.530 --> 00:12:38.280 align:middle line:90% and other tasks. 00:12:38.280 --> 00:12:40.190 align:middle line:90% However, the shoe drops-- 00:12:40.190 --> 00:12:43.610 align:middle line:84% most important area for collaboration 00:12:43.610 --> 00:12:46.130 align:middle line:90% involves casual inference. 00:12:46.130 --> 00:12:49.190 align:middle line:84% Machine learning has its part to play. 00:12:49.190 --> 00:12:51.410 align:middle line:90% It deals with pure prediction. 00:12:51.410 --> 00:12:54.620 align:middle line:84% But there's a difference between correlation 00:12:54.620 --> 00:12:57.020 align:middle line:90% among variables and causation. 00:12:57.020 --> 00:12:59.240 align:middle line:84% And he gives this example, which nowadays 00:12:59.240 --> 00:13:04.040 align:middle line:84% is a bit more nuanced than it was when he wrote it, 00:13:04.040 --> 00:13:05.550 align:middle line:90% a classic example-- 00:13:05.550 --> 00:13:09.050 align:middle line:84% there are often more police in precincts with high crime, 00:13:09.050 --> 00:13:12.380 align:middle line:84% but that does not mean that increasing number of police 00:13:12.380 --> 00:13:15.555 align:middle line:84% in a precinct would increase the crime. 00:13:15.555 --> 00:13:17.180 align:middle line:84% In other words, what he's trying to say 00:13:17.180 --> 00:13:20.340 align:middle line:84% is which way does the causality go-- 00:13:20.340 --> 00:13:22.950 align:middle line:84% from police to crime or from crime to police? 00:13:22.950 --> 00:13:25.620 align:middle line:84% And just seeing a correlation between police and crime 00:13:25.620 --> 00:13:28.260 align:middle line:84% in the data does not tell you what 00:13:28.260 --> 00:13:30.180 align:middle line:84% the outcome would be of increasing 00:13:30.180 --> 00:13:32.430 align:middle line:90% the number of police. 00:13:32.430 --> 00:13:35.430 align:middle line:90% So Rubin who's an advocate of-- 00:13:35.430 --> 00:13:38.460 align:middle line:84% who's thought of as in the behavioral group-- 00:13:38.460 --> 00:13:40.860 align:middle line:84% is actually in agreement that we need 00:13:40.860 --> 00:13:43.650 align:middle line:84% to think about the causal impact of treatment 00:13:43.650 --> 00:13:45.750 align:middle line:84% to compare outcomes of an intervention 00:13:45.750 --> 00:13:49.730 align:middle line:84% to what would have happened without the intervention. 00:13:49.730 --> 00:13:52.040 align:middle line:90% You can't do it alone with data. 00:13:52.040 --> 00:13:54.635 align:middle line:90% You need some model to do that. 00:13:54.635 --> 00:13:58.390 align:middle line:90% 00:13:58.390 --> 00:14:01.420 align:middle line:90% Lucas on artificial economies-- 00:14:01.420 --> 00:14:04.210 align:middle line:84% one of the functions of theoretical economics 00:14:04.210 --> 00:14:08.920 align:middle line:84% is to provide articulated, artificial economic systems 00:14:08.920 --> 00:14:11.950 align:middle line:84% that serve as laboratories in which policies that 00:14:11.950 --> 00:14:16.270 align:middle line:84% are prohibitively expensive to do in actual economies 00:14:16.270 --> 00:14:20.260 align:middle line:84% can be tested through the model at much lower cost. 00:14:20.260 --> 00:14:23.200 align:middle line:84% But he goes on to say that to do this well, 00:14:23.200 --> 00:14:25.090 align:middle line:84% it's really important to distinguish 00:14:25.090 --> 00:14:29.110 align:middle line:84% the artificial model economy as sharply as possible 00:14:29.110 --> 00:14:31.490 align:middle line:90% from actual economies. 00:14:31.490 --> 00:14:32.680 align:middle line:90% So this is a bit subtle. 00:14:32.680 --> 00:14:36.070 align:middle line:84% Insofar as there is confusion between the statements 00:14:36.070 --> 00:14:38.110 align:middle line:84% of opinion as to the way we believe 00:14:38.110 --> 00:14:41.470 align:middle line:84% actual economies would react to particular policies, 00:14:41.470 --> 00:14:44.770 align:middle line:84% and confused with statements of verifiable fact 00:14:44.770 --> 00:14:47.350 align:middle line:84% as to how the model would react, then 00:14:47.350 --> 00:14:50.360 align:middle line:84% we're not using the theory effectively. 00:14:50.360 --> 00:14:52.720 align:middle line:84% In other words, people will make statements 00:14:52.720 --> 00:14:55.180 align:middle line:84% about what they believe will happen 00:14:55.180 --> 00:14:57.730 align:middle line:84% as a consequence of a policy change. 00:14:57.730 --> 00:15:00.310 align:middle line:84% And the danger is we may not know, 00:15:00.310 --> 00:15:03.820 align:middle line:84% and they may not be clear, if their prediction of what 00:15:03.820 --> 00:15:09.110 align:middle line:84% would happen is based on data or based on the logic of a model. 00:15:09.110 --> 00:15:12.070 align:middle line:84% And then going on, if we have the model, 00:15:12.070 --> 00:15:14.560 align:middle line:84% we can see the predicted outcome based 00:15:14.560 --> 00:15:16.420 align:middle line:90% on the logic of the model. 00:15:16.420 --> 00:15:19.480 align:middle line:84% And then we can go to the data and see which statements 00:15:19.480 --> 00:15:21.590 align:middle line:90% of opinion are accurate or not. 00:15:21.590 --> 00:15:24.760 align:middle line:84% So that's Lucas's view of the science of economics. 00:15:24.760 --> 00:15:27.880 align:middle line:84% And in other words, instead of being pushed toward what would 00:15:27.880 --> 00:15:29.680 align:middle line:90% seem to be an attractive goal-- 00:15:29.680 --> 00:15:32.540 align:middle line:84% to make models more and more complicated 00:15:32.540 --> 00:15:34.150 align:middle line:90% so that they're more realistic-- 00:15:34.150 --> 00:15:37.060 align:middle line:84% Bob Lucas is actually pushing the opposite point 00:15:37.060 --> 00:15:42.310 align:middle line:84% of view, which is to earmark them as artificial, potentially 00:15:42.310 --> 00:15:45.670 align:middle line:84% relatively simple, so that we can understand 00:15:45.670 --> 00:15:49.530 align:middle line:84% the logic of what the models predict. 00:15:49.530 --> 00:15:52.770 align:middle line:84% Well, as I said, keep them relatively simple. 00:15:52.770 --> 00:15:55.950 align:middle line:84% On the other hand, economists are getting better and better 00:15:55.950 --> 00:15:58.140 align:middle line:84% at writing down and analyzing models. 00:15:58.140 --> 00:16:01.170 align:middle line:84% And one of the innovations that has happened over the years 00:16:01.170 --> 00:16:04.320 align:middle line:84% is not just the mathematics, for which Bob Lucas is well 00:16:04.320 --> 00:16:08.250 align:middle line:84% known along with his economics, but also the ability 00:16:08.250 --> 00:16:10.680 align:middle line:84% to compute solutions, which he feels 00:16:10.680 --> 00:16:14.220 align:middle line:84% is neglected in the history of economic science 00:16:14.220 --> 00:16:18.190 align:middle line:84% but which is, in fact, an important consideration. 00:16:18.190 --> 00:16:20.970 align:middle line:84% So you guys are all MIT students. 00:16:20.970 --> 00:16:24.000 align:middle line:84% I probably don't have to say this, but we in this class 00:16:24.000 --> 00:16:28.290 align:middle line:84% are also not going to shy away from computational issues 00:16:28.290 --> 00:16:30.180 align:middle line:90% when they arise. 00:16:30.180 --> 00:16:33.210 align:middle line:84% And I will take you through some of the algorithms 00:16:33.210 --> 00:16:37.030 align:middle line:90% and share those with you. 00:16:37.030 --> 00:16:41.320 align:middle line:84% Now I want to turn to the description of five economies. 00:16:41.320 --> 00:16:44.740 align:middle line:84% And they're also partly representative of the kind 00:16:44.740 --> 00:16:47.350 align:middle line:84% of economies we're going to be studying in the class. 00:16:47.350 --> 00:16:49.660 align:middle line:84% And then I'll get back to economic science, 00:16:49.660 --> 00:16:52.340 align:middle line:84% and we'll talk about how we're going to analyze them. 00:16:52.340 --> 00:16:55.460 align:middle line:84% So let me focus on economies for now. 00:16:55.460 --> 00:16:58.540 align:middle line:84% So the first economy, the medieval village economy, 00:16:58.540 --> 00:17:01.360 align:middle line:84% consists of about 300 households. 00:17:01.360 --> 00:17:05.050 align:middle line:84% They can grow wheat with plows, oxen, and of course, land. 00:17:05.050 --> 00:17:07.000 align:middle line:84% But the land is not consolidated. 00:17:07.000 --> 00:17:10.030 align:middle line:84% The land is spread out over the various fields 00:17:10.030 --> 00:17:14.260 align:middle line:84% into long narrow strips, quite fragmented-- 00:17:14.260 --> 00:17:19.480 align:middle line:84% on average, something like 30 to 60 strips for each household. 00:17:19.480 --> 00:17:23.020 align:middle line:84% Second economy is a Thai village economy. 00:17:23.020 --> 00:17:25.390 align:middle line:84% Households are growing rice and they're 00:17:25.390 --> 00:17:28.390 align:middle line:84% growing it in paddies, not in scattered land. 00:17:28.390 --> 00:17:31.390 align:middle line:84% If the monsoons are overly abundant, 00:17:31.390 --> 00:17:34.630 align:middle line:84% households with low-lying land will experience flooding 00:17:34.630 --> 00:17:40.280 align:middle line:84% and households with land on the rise actually do quite well. 00:17:40.280 --> 00:17:44.020 align:middle line:84% But the opposite is true in a medium to dry year. 00:17:44.020 --> 00:17:47.080 align:middle line:84% The low-lying land does well and the land on the rise 00:17:47.080 --> 00:17:48.370 align:middle line:90% is subject to a drought. 00:17:48.370 --> 00:17:51.980 align:middle line:84% So there's a lot of variation, a lot of risk. 00:17:51.980 --> 00:17:54.670 align:middle line:84% All households in the Thai village 00:17:54.670 --> 00:17:58.120 align:middle line:84% are obliged to transfer a certain amount of their crop 00:17:58.120 --> 00:17:59.620 align:middle line:90% to the local temple. 00:17:59.620 --> 00:18:02.580 align:middle line:90% Buddhist monks run the temple. 00:18:02.580 --> 00:18:05.250 align:middle line:84% Then the households with low crops in a given year 00:18:05.250 --> 00:18:08.460 align:middle line:84% can request an allotment from the temple stocks. 00:18:08.460 --> 00:18:11.940 align:middle line:84% And they don't even necessarily have to repay right away. 00:18:11.940 --> 00:18:14.580 align:middle line:84% That's a function in subsequent years of whether they 00:18:14.580 --> 00:18:16.470 align:middle line:90% get their yields back up. 00:18:16.470 --> 00:18:18.330 align:middle line:84% And otherwise, remarkably, there's 00:18:18.330 --> 00:18:22.890 align:middle line:84% no borrowing and lending in this village, just this institution. 00:18:22.890 --> 00:18:26.730 align:middle line:84% The third economy is drawn on a description of Oaxaca 00:18:26.730 --> 00:18:28.650 align:middle line:90% in Mexico. 00:18:28.650 --> 00:18:31.770 align:middle line:84% It's a set of villages, not just one. 00:18:31.770 --> 00:18:34.050 align:middle line:84% The villages are separated from each other 00:18:34.050 --> 00:18:36.360 align:middle line:90% by nontrivial distances. 00:18:36.360 --> 00:18:38.550 align:middle line:84% Sometimes it's flat land on a plain. 00:18:38.550 --> 00:18:40.380 align:middle line:84% Sometimes there were rivers, and valleys, 00:18:40.380 --> 00:18:43.410 align:middle line:84% and other topographical features. 00:18:43.410 --> 00:18:47.520 align:middle line:84% Each village specializes in production of a distinct good-- 00:18:47.520 --> 00:18:52.080 align:middle line:84% could be baskets, or pottery, or textiles, machetes. 00:18:52.080 --> 00:18:54.990 align:middle line:84% They produce a lot of that good and relatively little 00:18:54.990 --> 00:18:57.660 align:middle line:84% of the other ones, but each village 00:18:57.660 --> 00:19:01.800 align:middle line:84% values the commodities which it does not produce. 00:19:01.800 --> 00:19:06.540 align:middle line:84% And then trade occurs in a series of regional markets. 00:19:06.540 --> 00:19:10.020 align:middle line:84% The fourth economy is similar, except that when traders 00:19:10.020 --> 00:19:13.080 align:middle line:84% meet in these geographically separated markets, 00:19:13.080 --> 00:19:15.990 align:middle line:84% they're observe to give up produced goods, not 00:19:15.990 --> 00:19:19.050 align:middle line:84% for other goods but for paper notes, which 00:19:19.050 --> 00:19:23.040 align:middle line:84% are IOUs promising to pay goods in the future 00:19:23.040 --> 00:19:25.000 align:middle line:90% or pay money in the future. 00:19:25.000 --> 00:19:28.620 align:middle line:84% So these notes are observed, and used in exchange, 00:19:28.620 --> 00:19:32.670 align:middle line:84% and circulate around the regional markets. 00:19:32.670 --> 00:19:37.170 align:middle line:84% The fifth economy is from Malinowski's book Argonauts 00:19:37.170 --> 00:19:39.120 align:middle line:90% of the Pacific. 00:19:39.120 --> 00:19:41.280 align:middle line:90% It's another set of islands-- 00:19:41.280 --> 00:19:44.010 align:middle line:84% well, villages, but they're on islands. 00:19:44.010 --> 00:19:46.510 align:middle line:90% And they form a circle. 00:19:46.510 --> 00:19:49.110 align:middle line:84% So typically, residents of each island 00:19:49.110 --> 00:19:52.890 align:middle line:84% embark in canoes on trading expeditions, 00:19:52.890 --> 00:19:57.060 align:middle line:84% traveling either in a clockwise or counterclockwise direction 00:19:57.060 --> 00:19:59.340 align:middle line:90% to the nearest island neighbor. 00:19:59.340 --> 00:20:02.040 align:middle line:84% If they're traveling in a clockwise direction, when they 00:20:02.040 --> 00:20:05.070 align:middle line:84% reach the beach of the island of destination, 00:20:05.070 --> 00:20:09.060 align:middle line:84% they give up their cargo to those neighboring Islanders 00:20:09.060 --> 00:20:11.370 align:middle line:84% in a series of elaborate ceremonies. 00:20:11.370 --> 00:20:15.030 align:middle line:84% The goods go one way and distinctive white-shell 00:20:15.030 --> 00:20:17.190 align:middle line:90% armbands come back. 00:20:17.190 --> 00:20:20.430 align:middle line:84% If they were traveling in the other, opposite direction, 00:20:20.430 --> 00:20:23.550 align:middle line:84% counterclockwise, and they reach the nearest island, 00:20:23.550 --> 00:20:26.280 align:middle line:84% they unload the cargo and receive 00:20:26.280 --> 00:20:28.620 align:middle line:90% distinctive red-shell necklaces. 00:20:28.620 --> 00:20:29.890 align:middle line:90% I'm not making this up. 00:20:29.890 --> 00:20:31.800 align:middle line:90% It's in the book. 00:20:31.800 --> 00:20:34.320 align:middle line:84% These armbands and necklaces are entirely 00:20:34.320 --> 00:20:36.750 align:middle line:84% used for these ceremonies, to prohibited 00:20:36.750 --> 00:20:38.520 align:middle line:90% to be used for other things. 00:20:38.520 --> 00:20:40.560 align:middle line:84% And it's very, very rare for cargo 00:20:40.560 --> 00:20:44.940 align:middle line:84% to arrive without the shells and armbands going 00:20:44.940 --> 00:20:48.120 align:middle line:90% in the other direction. 00:20:48.120 --> 00:20:52.020 align:middle line:84% So at this point, you may be a little worried 00:20:52.020 --> 00:20:56.460 align:middle line:84% that we're about to study villages and anthropological 00:20:56.460 --> 00:21:00.000 align:middle line:84% works, but let me draw an analogy that 00:21:00.000 --> 00:21:01.980 align:middle line:84% is revealing about the way economists 00:21:01.980 --> 00:21:04.710 align:middle line:90% think about modeling economies. 00:21:04.710 --> 00:21:08.100 align:middle line:84% Lucas-- the same Bob Lucas I mentioned before-- 00:21:08.100 --> 00:21:13.470 align:middle line:84% talks about trees bearing fruit, which is an agrarian metaphor, 00:21:13.470 --> 00:21:16.140 align:middle line:84% but he didn't really mean a village. 00:21:16.140 --> 00:21:19.140 align:middle line:84% And Lucas doesn't like villages very much, actually. 00:21:19.140 --> 00:21:21.400 align:middle line:84% He actually meant financial markets. 00:21:21.400 --> 00:21:25.320 align:middle line:84% So a security is an asset like a tree that 00:21:25.320 --> 00:21:27.730 align:middle line:90% bears dividends like fruit. 00:21:27.730 --> 00:21:29.820 align:middle line:84% So this is the language that allows 00:21:29.820 --> 00:21:32.670 align:middle line:84% us to go back and forth from something concrete, 00:21:32.670 --> 00:21:35.430 align:middle line:84% like a tree in a village, to something 00:21:35.430 --> 00:21:38.940 align:middle line:84% a little more abstract, like financial securities. 00:21:38.940 --> 00:21:43.890 align:middle line:84% One of those economies, the fourth one, mentioned IOUs. 00:21:43.890 --> 00:21:46.990 align:middle line:84% They were bills of exchange historically, 00:21:46.990 --> 00:21:50.910 align:middle line:90% and now they're called repos. 00:21:50.910 --> 00:21:54.480 align:middle line:84% So these treasuries used as collateral 00:21:54.480 --> 00:21:57.600 align:middle line:84% to back loan, called the repo contract. 00:21:57.600 --> 00:22:02.850 align:middle line:84% And that repo will circulate where the original borrower 00:22:02.850 --> 00:22:05.340 align:middle line:84% becomes a lender, and the repo contract 00:22:05.340 --> 00:22:08.280 align:middle line:84% goes down the financial chain, and then comes back. 00:22:08.280 --> 00:22:12.300 align:middle line:84% And that strange Malinowski economy I mentioned to you 00:22:12.300 --> 00:22:15.810 align:middle line:84% is actually a close analogy to Bitcoin. 00:22:15.810 --> 00:22:19.740 align:middle line:84% Because Bitcoin tried to keep track of histories of things 00:22:19.740 --> 00:22:21.480 align:middle line:90% to condition outcomes. 00:22:21.480 --> 00:22:25.800 align:middle line:84% And they realized they need to "color" the coins in order 00:22:25.800 --> 00:22:27.240 align:middle line:90% to distinguish more history. 00:22:27.240 --> 00:22:28.770 align:middle line:90% Nowadays they do it differently. 00:22:28.770 --> 00:22:30.780 align:middle line:84% But there was a period where Bitcoin 00:22:30.780 --> 00:22:32.100 align:middle line:90% was featuring colored coins. 00:22:32.100 --> 00:22:34.620 align:middle line:84% And that's very similar-- the economics of that is very 00:22:34.620 --> 00:22:35.640 align:middle line:90% similar-- 00:22:35.640 --> 00:22:39.810 align:middle line:90% to these seashells in Indonesia. 00:22:39.810 --> 00:22:42.720 align:middle line:84% So I've gone all the way from villages, if not 00:22:42.720 --> 00:22:48.090 align:middle line:84% primitive economies, to not only modern-day financial markets 00:22:48.090 --> 00:22:49.680 align:middle line:90% but also to Bitcoin. 00:22:49.680 --> 00:22:53.640 align:middle line:84% And I'm, in the class, going to maintain and come back 00:22:53.640 --> 00:22:57.840 align:middle line:84% periodically to a study of Bitcoin of blockchains 00:22:57.840 --> 00:23:00.210 align:middle line:84% and distributed ledgers, thinking about it 00:23:00.210 --> 00:23:02.950 align:middle line:90% as innovation in the technology. 00:23:02.950 --> 00:23:05.760 align:middle line:90% So what is a distributed ledger? 00:23:05.760 --> 00:23:08.340 align:middle line:84% A distributed ledger technology refers 00:23:08.340 --> 00:23:12.450 align:middle line:84% to the processes and related technologies that enable nodes 00:23:12.450 --> 00:23:16.950 align:middle line:84% in a network or some arrangement to securely propose, validate, 00:23:16.950 --> 00:23:20.580 align:middle line:84% and record state changes to a synchronized ledger that 00:23:20.580 --> 00:23:23.940 align:middle line:84% is distributed across the network nodes-- 00:23:23.940 --> 00:23:26.500 align:middle line:90% a bit long-winded. 00:23:26.500 --> 00:23:28.210 align:middle line:90% We'll come back to it. 00:23:28.210 --> 00:23:29.470 align:middle line:90% Is it important? 00:23:29.470 --> 00:23:30.580 align:middle line:90% Yes. 00:23:30.580 --> 00:23:33.850 align:middle line:84% This from Harvard Business School colleagues, 00:23:33.850 --> 00:23:38.320 align:middle line:84% Iansiti and Lakhani, a quote from them. 00:23:38.320 --> 00:23:41.590 align:middle line:84% "Contracts, transactions, and the records of them 00:23:41.590 --> 00:23:44.020 align:middle line:84% are among the most defining structures 00:23:44.020 --> 00:23:46.570 align:middle line:84% in economic, legal, and political systems. 00:23:46.570 --> 00:23:49.180 align:middle line:84% Yet these critical tools and the bureaucracy 00:23:49.180 --> 00:23:52.480 align:middle line:84% formed to manage them have not kept up with the economy's 00:23:52.480 --> 00:23:54.290 align:middle line:90% digital transformation. 00:23:54.290 --> 00:23:57.310 align:middle line:84% They're like a rush-hour gridlock trapping a Formula 1 00:23:57.310 --> 00:23:58.090 align:middle line:90% race car. 00:23:58.090 --> 00:24:01.690 align:middle line:84% With blockchain, we can imagine a world in which contracts 00:24:01.690 --> 00:24:05.530 align:middle line:84% are embedded in digital code, stored in transparent shared 00:24:05.530 --> 00:24:09.040 align:middle line:84% databases, where they are protected from deletion, 00:24:09.040 --> 00:24:10.990 align:middle line:90% tampering, and revision. 00:24:10.990 --> 00:24:12.760 align:middle line:84% In other words, the entire landscape 00:24:12.760 --> 00:24:16.490 align:middle line:84% can change with these new technologies. 00:24:16.490 --> 00:24:18.980 align:middle line:84% Although the Harvard Business School colleagues 00:24:18.980 --> 00:24:23.390 align:middle line:84% are trying to be neutral, their enthusiasm is evident, 00:24:23.390 --> 00:24:26.480 align:middle line:84% and there's a lot of controversy about Bitcoin 00:24:26.480 --> 00:24:28.260 align:middle line:90% and about blockchain. 00:24:28.260 --> 00:24:33.350 align:middle line:84% So Satoshi Nakamoto-- we don't know if he's real or not-- 00:24:33.350 --> 00:24:35.810 align:middle line:90% this is a pen name, presumably-- 00:24:35.810 --> 00:24:37.730 align:middle line:90% invented Bitcoin. 00:24:37.730 --> 00:24:40.490 align:middle line:84% And in doing so, he said, "What is needed 00:24:40.490 --> 00:24:45.050 align:middle line:84% is an electronic payment system based on cryptographic proof 00:24:45.050 --> 00:24:48.200 align:middle line:84% instead of trust, allowing two willing parties 00:24:48.200 --> 00:24:50.360 align:middle line:84% to transact directly with each other 00:24:50.360 --> 00:24:53.130 align:middle line:84% without a need for a trusted third party." 00:24:53.130 --> 00:24:56.390 align:middle line:84% Well, this message was not lost on central banks, 00:24:56.390 --> 00:24:58.560 align:middle line:84% because Satoshi is basically saying 00:24:58.560 --> 00:25:01.820 align:middle line:84% we don't need fiat money, we just need Bitcoin, 00:25:01.820 --> 00:25:04.550 align:middle line:84% or Bitcoin can replace Fiat money. 00:25:04.550 --> 00:25:07.370 align:middle line:84% So you'll see the Banker International Settlement 00:25:07.370 --> 00:25:11.090 align:middle line:84% with statements like, "Decentralized technology 00:25:11.090 --> 00:25:13.130 align:middle line:84% associated with cryptocurrencies, however 00:25:13.130 --> 00:25:15.860 align:middle line:84% sophisticated, is a poor substitute 00:25:15.860 --> 00:25:19.220 align:middle line:84% for the solid institutional backing of money." 00:25:19.220 --> 00:25:22.550 align:middle line:84% Or Denison, Lee and Martin, two of whom 00:25:22.550 --> 00:25:24.980 align:middle line:84% are co-authors of mine at the New York Fed, 00:25:24.980 --> 00:25:27.260 align:middle line:90% "People do trust third parties. 00:25:27.260 --> 00:25:31.916 align:middle line:84% They trust central banks to provide currency and reserves. 00:25:31.916 --> 00:25:34.940 align:middle line:84% And they trust derivative payment systems that are run 00:25:34.940 --> 00:25:37.310 align:middle line:84% by named and trusted institutions-- 00:25:37.310 --> 00:25:39.230 align:middle line:84% he has in mind commercial banks-- 00:25:39.230 --> 00:25:42.860 align:middle line:84% that maintain the ledgers and the operating system. 00:25:42.860 --> 00:25:45.710 align:middle line:84% Trustless, expensive, decentralized systems 00:25:45.710 --> 00:25:47.650 align:middle line:90% are not needed." 00:25:47.650 --> 00:25:50.260 align:middle line:84% Many of these distributed ledger platforms 00:25:50.260 --> 00:25:55.660 align:middle line:84% promoted by the industry use the word "disintermediation." 00:25:55.660 --> 00:25:58.180 align:middle line:84% Now, if you view it kindly, what they mean 00:25:58.180 --> 00:26:02.350 align:middle line:84% is third parties are extracting monopoly rents. 00:26:02.350 --> 00:26:03.940 align:middle line:84% But if you're a regulator and you 00:26:03.940 --> 00:26:06.340 align:middle line:84% see someone trying to disintermediate 00:26:06.340 --> 00:26:07.900 align:middle line:84% the financial system, you're going 00:26:07.900 --> 00:26:10.130 align:middle line:84% to be a little bit worried about that. 00:26:10.130 --> 00:26:14.440 align:middle line:84% So it's a very interesting, a very controversial area. 00:26:14.440 --> 00:26:19.600 align:middle line:84% And every, I don't know, five or six lectures 00:26:19.600 --> 00:26:23.200 align:middle line:84% or so, we'll come back to the theory and data 00:26:23.200 --> 00:26:26.380 align:middle line:84% that we've been dealing with, and ask questions 00:26:26.380 --> 00:26:28.720 align:middle line:84% about Bitcoin, and see what we can learn 00:26:28.720 --> 00:26:32.110 align:middle line:90% through the lens of economics. 00:26:32.110 --> 00:26:36.490 align:middle line:84% So I listed previously five economies and the comment 00:26:36.490 --> 00:26:38.500 align:middle line:84% that they're metaphors, including 00:26:38.500 --> 00:26:40.250 align:middle line:84% for the study of modern economies, 00:26:40.250 --> 00:26:41.890 align:middle line:84% including all the way through Bitcoin 00:26:41.890 --> 00:26:44.230 align:middle line:84% and things that are happening today. 00:26:44.230 --> 00:26:45.820 align:middle line:90% Here's a partial list. 00:26:45.820 --> 00:26:48.670 align:middle line:84% We're going to study the medieval village economy. 00:26:48.670 --> 00:26:53.290 align:middle line:84% We're going to study village India, northern Thai villages. 00:26:53.290 --> 00:26:57.190 align:middle line:84% We're going to go from villages to local economies 00:26:57.190 --> 00:26:59.830 align:middle line:84% as in Oaxaca, in this case Thailand, 00:26:59.830 --> 00:27:03.050 align:middle line:84% to regional economies to the whole national economy. 00:27:03.050 --> 00:27:05.890 align:middle line:84% So we're as much talking about nation-states 00:27:05.890 --> 00:27:08.470 align:middle line:84% as we are about individual villages. 00:27:08.470 --> 00:27:10.630 align:middle line:84% In fact, we'll go to the United States 00:27:10.630 --> 00:27:15.010 align:middle line:84% and talk about local, state, and the US national economy. 00:27:15.010 --> 00:27:19.210 align:middle line:84% We will be looking at US financial markets, as well. 00:27:19.210 --> 00:27:22.160 align:middle line:84% Here and there we'll talk about China, 00:27:22.160 --> 00:27:27.910 align:middle line:84% which you might say started as a village or a bunch of villages, 00:27:27.910 --> 00:27:33.960 align:middle line:84% and has become a very important international player. 00:27:33.960 --> 00:27:35.980 align:middle line:90% So that's a list of economies. 00:27:35.980 --> 00:27:38.730 align:middle line:84% Now, what do we mean by an economy? 00:27:38.730 --> 00:27:43.200 align:middle line:84% When we model them, there is a systematic way 00:27:43.200 --> 00:27:46.340 align:middle line:90% to do this that you will learn. 00:27:46.340 --> 00:27:49.430 align:middle line:84% And that is, when we write down an economy, 00:27:49.430 --> 00:27:53.120 align:middle line:84% we mean to specify the commodity space. 00:27:53.120 --> 00:27:54.920 align:middle line:84% And within the commodity space, we'll 00:27:54.920 --> 00:27:59.480 align:middle line:84% talk about the preferences of agents, their endowments, 00:27:59.480 --> 00:28:03.370 align:middle line:84% and the technology available to them. 00:28:03.370 --> 00:28:07.830 align:middle line:84% So one way to remember this is like a PET economy. 00:28:07.830 --> 00:28:11.860 align:middle line:84% It is not the most favorable way of thinking about it. 00:28:11.860 --> 00:28:15.660 align:middle line:84% But PET is in preferences, endowments, and technology. 00:28:15.660 --> 00:28:18.990 align:middle line:84% And it is possible, when you're learning the tools of how 00:28:18.990 --> 00:28:22.350 align:middle line:84% to do the analysis, to get so lost in the notation 00:28:22.350 --> 00:28:25.210 align:middle line:84% that you'll forget about the applications. 00:28:25.210 --> 00:28:27.630 align:middle line:84% So I want to keep coming back, even 00:28:27.630 --> 00:28:30.630 align:middle line:84% on the early building-block lectures, to the idea 00:28:30.630 --> 00:28:35.280 align:middle line:84% that we have a common way of constructing economies that 00:28:35.280 --> 00:28:38.700 align:middle line:84% will allow us to consider dynamics, allow us to consider 00:28:38.700 --> 00:28:43.110 align:middle line:84% geography, and allow us to deal with risk and uncertainty 00:28:43.110 --> 00:28:44.400 align:middle line:90% as in states of the world. 00:28:44.400 --> 00:28:47.310 align:middle line:90% 00:28:47.310 --> 00:28:50.390 align:middle line:84% So now, I want to be more specific about what we're 00:28:50.390 --> 00:28:51.890 align:middle line:90% going to be doing in the class. 00:28:51.890 --> 00:28:54.360 align:middle line:84% And I'm going to do this in two ways. 00:28:54.360 --> 00:28:58.220 align:middle line:84% The first is to go through the main headers 00:28:58.220 --> 00:29:01.850 align:middle line:84% so you'll see the content, and the topics, 00:29:01.850 --> 00:29:04.010 align:middle line:90% and a bit of the methods. 00:29:04.010 --> 00:29:05.780 align:middle line:84% And then I'm going to come back and kind 00:29:05.780 --> 00:29:08.810 align:middle line:84% of selectively look at the smaller print 00:29:08.810 --> 00:29:11.180 align:middle line:90% and make some auxiliary points. 00:29:11.180 --> 00:29:13.070 align:middle line:90% Well, today is Lecture 1. 00:29:13.070 --> 00:29:15.890 align:middle line:84% We're talking about economic science. 00:29:15.890 --> 00:29:18.320 align:middle line:84% Then starting Thursday, we're going 00:29:18.320 --> 00:29:22.490 align:middle line:84% to focus on the building blocks for constructing economies. 00:29:22.490 --> 00:29:26.120 align:middle line:84% As I said, preference, endowments, and technology. 00:29:26.120 --> 00:29:30.060 align:middle line:84% And we're going to try to use that material right away. 00:29:30.060 --> 00:29:32.480 align:middle line:84% So we'll be engaged in conducting 00:29:32.480 --> 00:29:35.870 align:middle line:84% some partial equilibrium applications and experiments. 00:29:35.870 --> 00:29:39.800 align:middle line:84% So the building blocks are consumer choice, consumer 00:29:39.800 --> 00:29:43.680 align:middle line:90% behavior, and production. 00:29:43.680 --> 00:29:46.830 align:middle line:84% This is the traditional way to teach micro, 00:29:46.830 --> 00:29:49.680 align:middle line:84% but it tends to consume much more of the course 00:29:49.680 --> 00:29:50.820 align:middle line:90% than we will. 00:29:50.820 --> 00:29:54.360 align:middle line:84% I want to get the basics down and build on the basics, 00:29:54.360 --> 00:29:55.770 align:middle line:90% as I have been saying. 00:29:55.770 --> 00:29:58.470 align:middle line:84% But here, you may lose track of the fact 00:29:58.470 --> 00:30:01.380 align:middle line:84% that we're doing these building blocks which we're subsequently 00:30:01.380 --> 00:30:05.220 align:middle line:84% going to use when we're constructing economies. 00:30:05.220 --> 00:30:07.620 align:middle line:84% The next section, Lectures 5 and 6, 00:30:07.620 --> 00:30:11.910 align:middle line:84% talk about decision-making under uncertainty, focusing on risk 00:30:11.910 --> 00:30:15.690 align:middle line:84% and on linear programs and dynamic programs. 00:30:15.690 --> 00:30:17.910 align:middle line:84% And I'll come back to that momentarily. 00:30:17.910 --> 00:30:20.370 align:middle line:84% Then lecture 7 through 9, we finally 00:30:20.370 --> 00:30:22.620 align:middle line:90% get to entire economies. 00:30:22.620 --> 00:30:25.050 align:middle line:84% We'll develop a concept of welfare 00:30:25.050 --> 00:30:26.850 align:middle line:90% called Pareto optimality. 00:30:26.850 --> 00:30:32.130 align:middle line:84% And we'll right away move toward applications, risk sharing 00:30:32.130 --> 00:30:34.930 align:middle line:84% and dynamics in village economies, 00:30:34.930 --> 00:30:39.360 align:middle line:84% including social networks, supply chains, impact 00:30:39.360 --> 00:30:40.470 align:middle line:90% of health shocks. 00:30:40.470 --> 00:30:45.600 align:middle line:84% And here right away we'll get into the impact of COVID 00:30:45.600 --> 00:30:47.190 align:middle line:84% as a function of whether or not there 00:30:47.190 --> 00:30:49.110 align:middle line:90% are these insurance networks. 00:30:49.110 --> 00:30:53.460 align:middle line:84% And we'll merge this with supply chains and production 00:30:53.460 --> 00:30:56.110 align:middle line:90% as in lecture 9. 00:30:56.110 --> 00:31:00.800 align:middle line:84% Lecture 10 is about financial accounts and management. 00:31:00.800 --> 00:31:05.350 align:middle line:84% So it will talk about income statements and balance 00:31:05.350 --> 00:31:07.720 align:middle line:84% sheets, and household financial statements 00:31:07.720 --> 00:31:11.980 align:middle line:84% generally, and then also talk about cash management, which 00:31:11.980 --> 00:31:13.570 align:middle line:90% brings us to Bitcoin. 00:31:13.570 --> 00:31:16.360 align:middle line:84% I promise Bitcoin in distributed ledgers. 00:31:16.360 --> 00:31:19.660 align:middle line:84% "Ledgers" means "accounts," so this is the natural way 00:31:19.660 --> 00:31:24.670 align:middle line:84% to start talking about Bitcoin, and ledgers, and management. 00:31:24.670 --> 00:31:28.840 align:middle line:84% Lectures 11 through 12 start to bring in obstacles to trade, 00:31:28.840 --> 00:31:31.360 align:middle line:84% in particular private information, where 00:31:31.360 --> 00:31:35.420 align:middle line:84% we need to think about contracts and mechanism design. 00:31:35.420 --> 00:31:38.080 align:middle line:84% So we'll do this in theory and we'll 00:31:38.080 --> 00:31:39.820 align:middle line:90% add an application right away. 00:31:39.820 --> 00:31:43.480 align:middle line:84% And we'll actually do several applications. 00:31:43.480 --> 00:31:45.227 align:middle line:90% Lectures 13 through 15-- 00:31:45.227 --> 00:31:46.810 align:middle line:84% these three lectures are going to deal 00:31:46.810 --> 00:31:50.050 align:middle line:84% with the definition of a competitive equilibrium, 00:31:50.050 --> 00:31:54.550 align:middle line:84% or Walrasian equilibrium, in the general equilibrium setting. 00:31:54.550 --> 00:31:57.550 align:middle line:84% And we're going to use it for prediction, namely 00:31:57.550 --> 00:32:01.870 align:middle line:84% what is the impact of trade or tariffs? 00:32:01.870 --> 00:32:04.840 align:middle line:84% What is the impact of not only real, but also 00:32:04.840 --> 00:32:08.090 align:middle line:84% financial liberalization and repression? 00:32:08.090 --> 00:32:10.960 align:middle line:84% We'll do that in Thailand and we'll do it in the US. 00:32:10.960 --> 00:32:13.590 align:middle line:90% 00:32:13.590 --> 00:32:17.880 align:middle line:84% Then lectures 16 and 17 deal with whether or not 00:32:17.880 --> 00:32:21.270 align:middle line:84% competitive equilibria are Pareto optimal, 00:32:21.270 --> 00:32:26.340 align:middle line:84% and with issues of existence of competitive equilibria and Nash 00:32:26.340 --> 00:32:27.960 align:middle line:90% equilibrium. 00:32:27.960 --> 00:32:32.160 align:middle line:84% These two lectures, 18 and 19, are a juxtaposition 00:32:32.160 --> 00:32:34.830 align:middle line:84% of the micro and the macro, the macro 00:32:34.830 --> 00:32:38.820 align:middle line:84% being dealing with aggregates from the top imposing 00:32:38.820 --> 00:32:41.670 align:middle line:84% the structure, basically from above, 00:32:41.670 --> 00:32:45.720 align:middle line:84% versus juxtaposed with the micro and the data, 00:32:45.720 --> 00:32:49.230 align:middle line:84% where we can talk about whether anything can be really 00:32:49.230 --> 00:32:53.460 align:middle line:84% identified, talk about identifying, identification, 00:32:53.460 --> 00:32:55.590 align:middle line:90% and falsification. 00:32:55.590 --> 00:32:58.620 align:middle line:84% And the last two lectures focus on the failure 00:32:58.620 --> 00:33:00.690 align:middle line:84% of the two welfare theorems, which 00:33:00.690 --> 00:33:03.210 align:middle line:84% have to do with whether competitive equilibria are 00:33:03.210 --> 00:33:06.600 align:middle line:84% optimal and whether optimal allocations can be supported 00:33:06.600 --> 00:33:08.010 align:middle line:90% as competitive equilibria. 00:33:08.010 --> 00:33:10.800 align:middle line:84% Those two theorems can fail, but there 00:33:10.800 --> 00:33:13.260 align:middle line:84% are interesting consequences of that. 00:33:13.260 --> 00:33:17.640 align:middle line:84% Namely in those economies, we have value intrinsically 00:33:17.640 --> 00:33:19.650 align:middle line:90% worthless but valued money. 00:33:19.650 --> 00:33:22.800 align:middle line:84% We can talk about the value of Bitcoin, for example, 00:33:22.800 --> 00:33:24.780 align:middle line:90% and other cryptocurrencies. 00:33:24.780 --> 00:33:28.050 align:middle line:84% And we can talk about monetary policy. 00:33:28.050 --> 00:33:30.360 align:middle line:84% And indeed, we can focus on bubbles, 00:33:30.360 --> 00:33:34.560 align:middle line:84% and not whether bubbles are bad necessarily, but ironically, 00:33:34.560 --> 00:33:35.980 align:middle line:90% whether they're big enough. 00:33:35.980 --> 00:33:38.520 align:middle line:84% So those are the broad headers I'm 00:33:38.520 --> 00:33:41.730 align:middle line:84% quite excited about the class, and teaching the class, 00:33:41.730 --> 00:33:43.860 align:middle line:90% and interacting with you. 00:33:43.860 --> 00:33:45.990 align:middle line:84% Hopefully, going through that, you 00:33:45.990 --> 00:33:49.110 align:middle line:84% can see how much material we will cover 00:33:49.110 --> 00:33:52.500 align:middle line:84% and the importance of the material. 00:33:52.500 --> 00:33:54.710 align:middle line:84% But let me come back a minute, without going 00:33:54.710 --> 00:33:56.720 align:middle line:84% into the details of everything here, 00:33:56.720 --> 00:33:59.160 align:middle line:84% to let you in on a secret of the strategy. 00:33:59.160 --> 00:34:03.380 align:middle line:84% So when we get, for example, right away on Thursday 00:34:03.380 --> 00:34:07.070 align:middle line:84% to consumer choice, we'll be talking about consumption sets, 00:34:07.070 --> 00:34:09.679 align:middle line:84% and rational preferences, and utility functions, 00:34:09.679 --> 00:34:11.600 align:middle line:84% and properties of various things, 00:34:11.600 --> 00:34:13.460 align:middle line:90% which is extremely important. 00:34:13.460 --> 00:34:16.639 align:middle line:84% But we jump into an application even 00:34:16.639 --> 00:34:19.520 align:middle line:84% in that lecture, which is utility maximization 00:34:19.520 --> 00:34:21.290 align:middle line:90% subject to budget constraints. 00:34:21.290 --> 00:34:24.960 align:middle line:84% And in order to do those things, we need our first major method. 00:34:24.960 --> 00:34:27.920 align:middle line:84% So we're going to talk about constrained optimization 00:34:27.920 --> 00:34:30.380 align:middle line:84% and the use of Lagrangian programs. 00:34:30.380 --> 00:34:33.080 align:middle line:84% So the not-so-secret secret is going 00:34:33.080 --> 00:34:35.570 align:middle line:84% to be that we're training, hopefully, 00:34:35.570 --> 00:34:37.969 align:middle line:84% learning the methods of analysis, 00:34:37.969 --> 00:34:41.540 align:middle line:84% as these theories and topics come up. 00:34:41.540 --> 00:34:45.440 align:middle line:84% Usually in every lecture or almost every lecture, 00:34:45.440 --> 00:34:47.360 align:middle line:84% there's something about a method that 00:34:47.360 --> 00:34:50.179 align:middle line:84% will be very powerful that I'll want you to learn. 00:34:50.179 --> 00:34:53.409 align:middle line:84% And we will take the time to go over it. 00:34:53.409 --> 00:34:56.290 align:middle line:84% Consumer behavior, which is Lecture 3, 00:34:56.290 --> 00:34:59.710 align:middle line:84% is an elaboration on the application, which 00:34:59.710 --> 00:35:02.050 align:middle line:84% is what happens and how do consumers 00:35:02.050 --> 00:35:06.010 align:middle line:84% behave when prices are moving and their incomes are moving 00:35:06.010 --> 00:35:06.850 align:middle line:90% about. 00:35:06.850 --> 00:35:09.070 align:middle line:84% So there's some abstract stuff you 00:35:09.070 --> 00:35:13.210 align:middle line:84% may have seen before about normal goods and Giffin Goods. 00:35:13.210 --> 00:35:16.310 align:middle line:84% Instead of just memorizing that stuff, 00:35:16.310 --> 00:35:18.700 align:middle line:84% we're going to go to an actual economy, which 00:35:18.700 --> 00:35:22.900 align:middle line:84% is China, where the authors actually did 00:35:22.900 --> 00:35:25.750 align:middle line:84% one of our randomized controlled trial experiments, 00:35:25.750 --> 00:35:30.280 align:middle line:84% and varied prices, and looked at whether or not demand actually 00:35:30.280 --> 00:35:34.360 align:middle line:84% went the wrong way-- demand went up when prices go up. 00:35:34.360 --> 00:35:36.010 align:middle line:84% And then we'll learn some more tools. 00:35:36.010 --> 00:35:37.660 align:middle line:84% We'll make this distinction between 00:35:37.660 --> 00:35:42.880 align:middle line:84% compensated and uncompensated demands, duality, Slutsky-- 00:35:42.880 --> 00:35:46.060 align:middle line:84% doesn't mean anything now, probably. 00:35:46.060 --> 00:35:48.940 align:middle line:84% But again, we're building towards statements 00:35:48.940 --> 00:35:52.930 align:middle line:84% of if you had data, could you use data to accept or reject 00:35:52.930 --> 00:35:54.490 align:middle line:90% a model. 00:35:54.490 --> 00:35:56.850 align:middle line:84% So the mapping from the theory to the data, 00:35:56.850 --> 00:36:00.420 align:middle line:84% as Lucas would have put it, is happening with the ingredients 00:36:00.420 --> 00:36:02.160 align:middle line:90% at the end of Lecture 3. 00:36:02.160 --> 00:36:04.410 align:middle line:90% Lecture 4 is on production. 00:36:04.410 --> 00:36:06.300 align:middle line:84% That's the second building block. 00:36:06.300 --> 00:36:10.260 align:middle line:84% And there we do production functions, inputs and outputs, 00:36:10.260 --> 00:36:11.640 align:middle line:90% return to scale. 00:36:11.640 --> 00:36:15.210 align:middle line:84% But again, we jump to an application, 00:36:15.210 --> 00:36:18.960 align:middle line:84% which is profit maximization, which is the analog-- 00:36:18.960 --> 00:36:21.540 align:middle line:84% firms maximize profits given prices, 00:36:21.540 --> 00:36:26.310 align:middle line:84% consumers maximize utility subject to prices and income. 00:36:26.310 --> 00:36:29.030 align:middle line:84% So we'll go through that and derive some properties. 00:36:29.030 --> 00:36:31.430 align:middle line:84% And then up pops another method, namely, we 00:36:31.430 --> 00:36:33.800 align:middle line:84% need something called the Envelope Theorem. 00:36:33.800 --> 00:36:37.200 align:middle line:84% So when we get there, we can go over what that means. 00:36:37.200 --> 00:36:40.160 align:middle line:84% And then we jump back, at the end of this lecture, 00:36:40.160 --> 00:36:42.020 align:middle line:90% to some fake economies. 00:36:42.020 --> 00:36:46.100 align:middle line:84% Robinson Crusoe economy is one of the economists' 00:36:46.100 --> 00:36:49.970 align:middle line:84% all-time favorite-- an island populated by one person, 00:36:49.970 --> 00:36:50.790 align:middle line:90% essentially. 00:36:50.790 --> 00:36:53.870 align:middle line:84% But that immediately leads to international trade, 00:36:53.870 --> 00:36:55.490 align:middle line:90% two-country examples. 00:36:55.490 --> 00:36:57.650 align:middle line:84% And I'll show you some work that Leontief 00:36:57.650 --> 00:37:00.620 align:middle line:84% did on Input/Output matrices that is actually 00:37:00.620 --> 00:37:04.910 align:middle line:84% relevant for understanding Google search algorithms 00:37:04.910 --> 00:37:09.230 align:middle line:84% and for studying the great East Japan earthquake. 00:37:09.230 --> 00:37:11.240 align:middle line:84% And on this topic of decision-making 00:37:11.240 --> 00:37:16.340 align:middle line:84% under uncertainty, we will talk about risk and measures 00:37:16.340 --> 00:37:19.640 align:middle line:84% of willingness to get out of risk if you had the option 00:37:19.640 --> 00:37:20.900 align:middle line:90% to buy insurance. 00:37:20.900 --> 00:37:23.360 align:middle line:84% So we will go through some important concepts. 00:37:23.360 --> 00:37:25.580 align:middle line:84% But then we will immediately apply it 00:37:25.580 --> 00:37:29.780 align:middle line:84% to the medieval village economy that I've already referred you 00:37:29.780 --> 00:37:32.300 align:middle line:84% to, and including land fragmentation. 00:37:32.300 --> 00:37:36.500 align:middle line:84% And then for methods we'll be focusing on linear programs. 00:37:36.500 --> 00:37:39.930 align:middle line:84% And that carries over, not just to this topic. 00:37:39.930 --> 00:37:42.770 align:middle line:84% But we will use linear programs frequently 00:37:42.770 --> 00:37:45.770 align:middle line:84% from this point on through many of the other subsequent 00:37:45.770 --> 00:37:46.550 align:middle line:90% lectures. 00:37:46.550 --> 00:37:51.080 align:middle line:84% And coupled with linear programs are dynamic programs, where 00:37:51.080 --> 00:37:52.850 align:middle line:90% things are happening over time. 00:37:52.850 --> 00:37:56.030 align:middle line:84% And the application there is going to be, 00:37:56.030 --> 00:37:59.240 align:middle line:84% why were these medieval villages starving to death every 12 00:37:59.240 --> 00:38:03.140 align:middle line:84% years, even though in principle, they could be storing grain? 00:38:03.140 --> 00:38:04.440 align:middle line:90% They didn't do it much. 00:38:04.440 --> 00:38:08.120 align:middle line:84% And the method is going to be dynamic programming and value 00:38:08.120 --> 00:38:09.410 align:middle line:90% functions. 00:38:09.410 --> 00:38:12.360 align:middle line:84% When we get to Pareto optimality, of course, 00:38:12.360 --> 00:38:13.860 align:middle line:90% we'll define what it means. 00:38:13.860 --> 00:38:15.800 align:middle line:84% We'll talk about the Pareto frontier. 00:38:15.800 --> 00:38:20.990 align:middle line:84% We'll have our first genuinely spelled-out economy, 00:38:20.990 --> 00:38:23.870 align:middle line:84% an Edgeworth Box Economy in the abstract. 00:38:23.870 --> 00:38:27.080 align:middle line:84% I'll show you a way to determine the set 00:38:27.080 --> 00:38:29.510 align:middle line:84% of efficient Pareto-optimal allocations 00:38:29.510 --> 00:38:31.700 align:middle line:90% for any given economy. 00:38:31.700 --> 00:38:36.440 align:middle line:84% And then we have another tool, separating hyperplanes. 00:38:36.440 --> 00:38:38.840 align:middle line:84% And I'll define it and show you some pictures. 00:38:38.840 --> 00:38:41.840 align:middle line:84% And then we go right away to an example, which 00:38:41.840 --> 00:38:43.400 align:middle line:84% has to do with how would you know 00:38:43.400 --> 00:38:46.700 align:middle line:84% whether an economy is really efficiently allocating risk 00:38:46.700 --> 00:38:47.720 align:middle line:90% or not? 00:38:47.720 --> 00:38:49.610 align:middle line:84% In fact, the next two lectures do 00:38:49.610 --> 00:38:53.060 align:middle line:84% that in much greater detail, going to Village India, 00:38:53.060 --> 00:38:55.520 align:middle line:84% which I mentioned was one of the economies we were going 00:38:55.520 --> 00:38:58.250 align:middle line:84% to study, looking at relationship 00:38:58.250 --> 00:39:01.910 align:middle line:84% between consumption and income, and then go back 00:39:01.910 --> 00:39:05.570 align:middle line:84% to the medieval village economy, and try to understand 00:39:05.570 --> 00:39:08.270 align:middle line:84% whether the way they were dividing up land 00:39:08.270 --> 00:39:11.030 align:middle line:84% into those narrow strips would or would not 00:39:11.030 --> 00:39:14.500 align:middle line:84% be consistent with an optimal allocation of risk bearing, 00:39:14.500 --> 00:39:17.250 align:middle line:90% and under what circumstances. 00:39:17.250 --> 00:39:20.190 align:middle line:84% And then we throw production in there, as well. 00:39:20.190 --> 00:39:22.770 align:middle line:84% So now we have risk, consumers, and production. 00:39:22.770 --> 00:39:26.570 align:middle line:84% And we'll talk about risk and return, and risk premia, 00:39:26.570 --> 00:39:30.500 align:middle line:84% whether they share idiosyncratic household-specific shocks, what 00:39:30.500 --> 00:39:33.530 align:middle line:84% to do about common, macro-aggregate shocks. 00:39:33.530 --> 00:39:37.760 align:middle line:84% And this part of the lecture ends with the role of gifts, 00:39:37.760 --> 00:39:41.870 align:middle line:84% the role of social networks, and the transmission 00:39:41.870 --> 00:39:43.130 align:middle line:90% of shocks in villages. 00:39:43.130 --> 00:39:46.340 align:middle line:84% The transmission of shocks is actually a health shock. 00:39:46.340 --> 00:39:48.470 align:middle line:90% It wasn't a COVID shock. 00:39:48.470 --> 00:39:51.830 align:middle line:84% But it does give us a way of thinking 00:39:51.830 --> 00:39:56.570 align:middle line:84% about the impact of COVID in terms of impacting a household, 00:39:56.570 --> 00:40:01.880 align:middle line:84% and whether or not they have formal or informal coverage 00:40:01.880 --> 00:40:05.810 align:middle line:84% to cover that bad shock, and if they don't, how the impact can 00:40:05.810 --> 00:40:07.940 align:middle line:84% spread around to other people that they've 00:40:07.940 --> 00:40:09.470 align:middle line:90% been interacting with. 00:40:09.470 --> 00:40:12.620 align:middle line:84% And I don't mean the spread of the virus. 00:40:12.620 --> 00:40:15.890 align:middle line:84% I mean the economic adverse outcomes 00:40:15.890 --> 00:40:18.020 align:middle line:84% that propagate, not the way the virus 00:40:18.020 --> 00:40:21.070 align:middle line:84% propagates, but through economic mechanisms. 00:40:21.070 --> 00:40:23.750 align:middle line:84% When we get to household financial accounts-- 00:40:23.750 --> 00:40:26.300 align:middle line:84% I mentioned this already about five minutes ago-- 00:40:26.300 --> 00:40:28.820 align:middle line:84% we'll talk about ledgers and management. 00:40:28.820 --> 00:40:30.710 align:middle line:84% We'll talk about household financial accounts 00:40:30.710 --> 00:40:33.050 align:middle line:84% because we need them to understand ledgers. 00:40:33.050 --> 00:40:34.800 align:middle line:84% With the income and the balance sheet, 00:40:34.800 --> 00:40:37.130 align:middle line:84% we can talk about life cycle management. 00:40:37.130 --> 00:40:40.670 align:middle line:84% And I'll show you a wealth planner, a life-cycle wealth 00:40:40.670 --> 00:40:43.610 align:middle line:84% planner that we implemented in Thai villages, 00:40:43.610 --> 00:40:47.150 align:middle line:84% and show you an analog wealth planner for the US. 00:40:47.150 --> 00:40:49.220 align:middle line:84% Then we merge to Bitcoin, for which 00:40:49.220 --> 00:40:51.920 align:middle line:84% you need to understand the statement of cash flow 00:40:51.920 --> 00:40:55.700 align:middle line:84% and the relationship between the flow and the stocks, 00:40:55.700 --> 00:40:59.150 align:middle line:84% as in the balance sheet and the cash flow, which will take us 00:40:59.150 --> 00:41:02.430 align:middle line:84% to thinking about alternative economies, 00:41:02.430 --> 00:41:06.110 align:middle line:84% for example Thailand, again, which 00:41:06.110 --> 00:41:09.120 align:middle line:84% is still using paper currency all over the place-- 00:41:09.120 --> 00:41:12.290 align:middle line:84% and we'll talk about whether that's efficient or not-- 00:41:12.290 --> 00:41:15.740 align:middle line:84% to Sweden, which has virtually no currency left. 00:41:15.740 --> 00:41:18.170 align:middle line:84% It's a virtually cashless economy now. 00:41:18.170 --> 00:41:20.120 align:middle line:90% They're worried about that. 00:41:20.120 --> 00:41:21.830 align:middle line:84% Instead of fighting Bitcoin, they're 00:41:21.830 --> 00:41:24.800 align:middle line:84% thinking about introducing a central bank digital currency. 00:41:24.800 --> 00:41:26.330 align:middle line:90% And we'll talk about that. 00:41:26.330 --> 00:41:31.040 align:middle line:84% And Kenya is a poor developing country in between, 00:41:31.040 --> 00:41:34.280 align:middle line:84% where they have both Kenyan shillings, which 00:41:34.280 --> 00:41:39.290 align:middle line:84% is fiat money, as well as an electronic money, M-Pesa, 00:41:39.290 --> 00:41:45.130 align:middle line:84% which are claims on your cellphone-- basically cellphone 00:41:45.130 --> 00:41:46.507 align:middle line:90% accounts, cellphone credits. 00:41:46.507 --> 00:41:48.340 align:middle line:84% And we'll talk about some of the issues that 00:41:48.340 --> 00:41:53.320 align:middle line:84% come up with distributed ledgers in all those three contexts-- 00:41:53.320 --> 00:41:56.410 align:middle line:90% Thailand, Sweden, and Kenya. 00:41:56.410 --> 00:41:59.770 align:middle line:84% We'll get to contracts next, which has 00:41:59.770 --> 00:42:01.690 align:middle line:90% to do with private information. 00:42:01.690 --> 00:42:03.970 align:middle line:84% In terms of methods, I'll share with you 00:42:03.970 --> 00:42:06.610 align:middle line:84% something called the Revelation Principle, which 00:42:06.610 --> 00:42:10.720 align:middle line:84% allows us to append some extra constraints onto things that we 00:42:10.720 --> 00:42:13.810 align:middle line:84% did previously and continue to use the same methods. 00:42:13.810 --> 00:42:18.040 align:middle line:84% Here, we'll need some lotteries to get the commodity 00:42:18.040 --> 00:42:19.930 align:middle line:90% space to be tractable. 00:42:19.930 --> 00:42:23.800 align:middle line:84% And in this lecture, we'll go to those Harvard Business School 00:42:23.800 --> 00:42:26.770 align:middle line:84% professors and talk about smart contracts-- 00:42:26.770 --> 00:42:30.670 align:middle line:84% what it means, how to implement solutions to mechanism 00:42:30.670 --> 00:42:31.930 align:middle line:90% design problems. 00:42:31.930 --> 00:42:34.660 align:middle line:84% This part, again, is now, when you understand 00:42:34.660 --> 00:42:39.040 align:middle line:84% contracts, the language of smart contracts will make more sense. 00:42:39.040 --> 00:42:40.660 align:middle line:84% We'll do both together, and then we'll 00:42:40.660 --> 00:42:43.270 align:middle line:84% have applications studying contracts 00:42:43.270 --> 00:42:48.340 align:middle line:84% in practice for small and medium enterprise in Thailand. 00:42:48.340 --> 00:42:50.890 align:middle line:84% In this case, again, one of these 00:42:50.890 --> 00:42:54.460 align:middle line:84% lectures where we combine the theory and the data 00:42:54.460 --> 00:42:57.040 align:middle line:84% together to make inferences about what 00:42:57.040 --> 00:42:59.770 align:middle line:90% the obstacles to trade are. 00:42:59.770 --> 00:43:03.340 align:middle line:84% So then we get to the Walrasian Equilibrium, 00:43:03.340 --> 00:43:04.900 align:middle line:90% competitive equilibrium. 00:43:04.900 --> 00:43:07.480 align:middle line:84% We'll define it, and we'll immediately 00:43:07.480 --> 00:43:11.780 align:middle line:84% apply it to the concept of trade across countries, 00:43:11.780 --> 00:43:13.840 align:middle line:90% the gains from trade-- 00:43:13.840 --> 00:43:16.600 align:middle line:84% or actually, who loses, not just who 00:43:16.600 --> 00:43:19.810 align:middle line:84% wins from trade-- and some well-known theorems about that, 00:43:19.810 --> 00:43:23.860 align:middle line:84% about the effect of trade on wages and input prices. 00:43:23.860 --> 00:43:27.970 align:middle line:84% With that theory in hand, we'll go to two different economies. 00:43:27.970 --> 00:43:31.090 align:middle line:84% We'll go to Thailand and talk about villages 00:43:31.090 --> 00:43:33.400 align:middle line:84% as small open economies, what's been 00:43:33.400 --> 00:43:37.990 align:middle line:84% the impact on them of increasing trade within the economy, 00:43:37.990 --> 00:43:40.450 align:middle line:84% the impact on them in terms of the opening 00:43:40.450 --> 00:43:42.700 align:middle line:84% up of the financial system so that money 00:43:42.700 --> 00:43:46.150 align:middle line:84% is flowing more easily, which is the flip side of tariffs. 00:43:46.150 --> 00:43:48.340 align:middle line:84% And there are losers to liberalization, 00:43:48.340 --> 00:43:50.020 align:middle line:84% just like there are losers to trade. 00:43:50.020 --> 00:43:52.150 align:middle line:84% So the thrust of all of this is try 00:43:52.150 --> 00:43:55.270 align:middle line:84% to use the model with the data to identify who wins 00:43:55.270 --> 00:43:56.920 align:middle line:90% and who loses from trade. 00:43:56.920 --> 00:44:01.510 align:middle line:84% And then, obviously, we'll be set up to talk about the US 00:44:01.510 --> 00:44:04.450 align:middle line:84% in terms of the thing now called the China Shock, which 00:44:04.450 --> 00:44:09.220 align:middle line:84% is the rise of China, the rise of China exports, 00:44:09.220 --> 00:44:12.550 align:middle line:84% into Europe and into the US, and the impact that 00:44:12.550 --> 00:44:16.540 align:middle line:84% has had on various states that used to produce goods, which 00:44:16.540 --> 00:44:20.590 align:middle line:84% are now not so competitive with Chinese imports. 00:44:20.590 --> 00:44:25.870 align:middle line:84% Regardless of your view, you can see the importance here. 00:44:25.870 --> 00:44:29.080 align:middle line:84% Because what's going on in the US and these policy 00:44:29.080 --> 00:44:31.510 align:middle line:84% measures that are adopted having to do with trade, 00:44:31.510 --> 00:44:35.000 align:middle line:84% and which used to be NAFTA and so on, 00:44:35.000 --> 00:44:38.050 align:middle line:84% and now it's pulling out of the Asia-Pacific Agreement 00:44:38.050 --> 00:44:40.130 align:middle line:84% and having this contest with China. 00:44:40.130 --> 00:44:42.040 align:middle line:84% So we want to look at those issues, 00:44:42.040 --> 00:44:44.410 align:middle line:84% not from a political standpoint but 00:44:44.410 --> 00:44:46.630 align:middle line:84% from an economic standpoint, to understand 00:44:46.630 --> 00:44:51.320 align:middle line:84% what we know about the beneficiaries and the losers, 00:44:51.320 --> 00:44:53.500 align:middle line:84% and ideally try to quantify that. 00:44:53.500 --> 00:44:55.930 align:middle line:84% This section is also about the data 00:44:55.930 --> 00:44:58.600 align:middle line:90% available to do the analysis. 00:44:58.600 --> 00:45:01.900 align:middle line:84% Sometimes we have far less data than we wish that we did. 00:45:01.900 --> 00:45:04.355 align:middle line:84% And in particular, I have a section 00:45:04.355 --> 00:45:06.820 align:middle line:84% which I have to update periodically 00:45:06.820 --> 00:45:11.020 align:middle line:84% on what is the impact of COVID-19 on the US economy. 00:45:11.020 --> 00:45:14.020 align:middle line:84% And again, we'll go back to what's 00:45:14.020 --> 00:45:17.860 align:middle line:84% the impact on income, looking at income levels, 00:45:17.860 --> 00:45:20.650 align:middle line:84% and ethnicity, and so on, but also what's 00:45:20.650 --> 00:45:23.800 align:middle line:84% the impact on the balance sheet and on debt. 00:45:23.800 --> 00:45:26.440 align:middle line:84% And we know some things, but you will 00:45:26.440 --> 00:45:29.440 align:middle line:84% discover that the integrated data is not 00:45:29.440 --> 00:45:30.820 align:middle line:90% available in the US. 00:45:30.820 --> 00:45:34.060 align:middle line:84% So there are actually surprising things we don't know. 00:45:34.060 --> 00:45:37.930 align:middle line:84% Likewise, all this discussion about inequality, how much 00:45:37.930 --> 00:45:39.940 align:middle line:90% wealth the top 1% own-- 00:45:39.940 --> 00:45:42.430 align:middle line:84% that's much less securely measured 00:45:42.430 --> 00:45:43.700 align:middle line:90% than you might imagine. 00:45:43.700 --> 00:45:46.660 align:middle line:84% And we'll go into the reasons why. 00:45:46.660 --> 00:45:49.330 align:middle line:84% And we have optimality of competitive equilibria 00:45:49.330 --> 00:45:50.380 align:middle line:90% in existence. 00:45:50.380 --> 00:45:53.740 align:middle line:84% We have theorems-- existence of competitive equilibria, 00:45:53.740 --> 00:45:55.810 align:middle line:90% existence of Nash equilibria. 00:45:55.810 --> 00:45:57.490 align:middle line:84% For the Nash equilibrium, we'll go 00:45:57.490 --> 00:46:00.250 align:middle line:84% to a model of US financial markets 00:46:00.250 --> 00:46:03.520 align:middle line:84% and try to analyze why we see trade fails, 00:46:03.520 --> 00:46:07.480 align:middle line:84% where those repo contracts fail, and whether penalties 00:46:07.480 --> 00:46:09.280 align:middle line:84% could or should have been in place 00:46:09.280 --> 00:46:11.390 align:middle line:90% to prevent those failures. 00:46:11.390 --> 00:46:15.190 align:middle line:84% I think I said enough about aggregation and identification 00:46:15.190 --> 00:46:17.930 align:middle line:84% already when I went through this the first time. 00:46:17.930 --> 00:46:21.700 align:middle line:84% And we end with when the welfare theorems fail, 00:46:21.700 --> 00:46:23.590 align:middle line:90% but not stopping there. 00:46:23.590 --> 00:46:26.770 align:middle line:84% The analogy with pollution is to fix it 00:46:26.770 --> 00:46:29.710 align:middle line:90% by selling rights to pollute. 00:46:29.710 --> 00:46:32.440 align:middle line:84% We'll talk about how to handle externalities 00:46:32.440 --> 00:46:34.480 align:middle line:90% much more generally. 00:46:34.480 --> 00:46:37.120 align:middle line:84% We'll talk about failures of the First Welfare theorem 00:46:37.120 --> 00:46:40.550 align:middle line:84% when there's dynamics and an infinite amount of wealth. 00:46:40.550 --> 00:46:43.250 align:middle line:84% And likewise, when it fails, we'll 00:46:43.250 --> 00:46:45.320 align:middle line:90% see the emergence of money-- 00:46:45.320 --> 00:46:48.500 align:middle line:90% both fiat money and Bitcoin. 00:46:48.500 --> 00:46:49.790 align:middle line:90% One word about Bitcoin-- 00:46:49.790 --> 00:46:52.850 align:middle line:84% when the former head of the New York Fed 00:46:52.850 --> 00:46:57.380 align:middle line:84% referred to Bitcoin as the adversary, 00:46:57.380 --> 00:46:59.510 align:middle line:84% he was saying something about there's 00:46:59.510 --> 00:47:02.750 align:middle line:84% nothing fundamental pinning down the value of Bitcoin. 00:47:02.750 --> 00:47:04.880 align:middle line:84% Well, if you're a central banker, 00:47:04.880 --> 00:47:08.000 align:middle line:84% don't throw stones when you live in glass houses, 00:47:08.000 --> 00:47:10.250 align:middle line:84% because there's absolutely nothing fundamental pinning 00:47:10.250 --> 00:47:12.530 align:middle line:84% down the value of the US dollar, either. 00:47:12.530 --> 00:47:16.400 align:middle line:84% And the same model will make clear that statement, 00:47:16.400 --> 00:47:21.140 align:middle line:84% and hence, why it's possible Bitcoin is volatile and danger, 00:47:21.140 --> 00:47:25.240 align:middle line:84% again, for fiat money, and remedies having 00:47:25.240 --> 00:47:29.380 align:middle line:90% to do with monetary policy. 00:47:29.380 --> 00:47:34.650 align:middle line:84% And again, the course moves systematically, 00:47:34.650 --> 00:47:36.150 align:middle line:90% so try to keep up. 00:47:36.150 --> 00:47:37.970 align:middle line:90% Thank you. 00:47:37.970 --> 00:47:46.000 align:middle line:90%