Course pages 2011–12
Economics and Law
At one level, this course provides a grounding in professional practice and ethics course and prepares you for the courses in business and e-commerce in part 2. But that is not all.
Economic arguments are starting to appear in many areas of computer science. Economics deals with mechanisms whereby global equilibria emerge from the local behaviour of a number of selfish agents. Economic arguments and techniques are starting to be used by computer scientists to tackle problems from network congestion, through resource allocation in distributed operating systems, to security. As systems become ever larger, and involve ever-more diverse stakeholders, these techniques are likely to become more important. (I got roped into teaching this course because of my interest in the interaction between economics and information security.)
Useful though economic arguments and explanations may be, however, there are many reasons why market mechanisms may fail, or yield an equilibrium that is far from the social optimum. Law deals with rules developed to remedy this. As the Internet has changed from a research tool to a public utility over the past fifteen years, legal questions have become increasingly important to computer scientists.
We use game theory as a natural entry point into economics for the computer scientist. Game theory deals with such fundamental issues as whether people cooperate or fight to achieve their goals.
One of the classic puzzles in game theory is the Prisoner's dilemma. Two crooks are arrested and questioned separately about a robbery. The police tell each of them that if he confesses, he will go free while his partner will get 10 years for the robbery. If he keeps quiet and his partner confesses, it will be the other way round. If both confess, they will get five years; while if neither confesses, they will get a year each for possessing a firearm. Here, the optimal strategy from the prisoners' collective viewpoint is for both to keep quiet, but if they cannot both trust the other then the optimal strategy for each individual is to confess.
This is typical of many problems encountered in real life. Resolving them is easier where the games are not isolated, but are part of a series. Then one might, for example, have a strategy of tit for tat – if you cooperate with me this round, I'll return the favour next time; but if you stab me in the back, I'll retaliate. Such are important not just in economics, but also in fields such as evolutionary biology where their evolution is believed to be the foundation for much social behaviour in animals.
At the level of routine economic analysis, game theory provides useful tools for understanding monopoly and oligopoly behaviour. For example, suppose that it costs $250 to fly a passenger from Boston to London and back, and only two airlines comnpete on the route. How will they set prices? Will they collude and charge $500 each, making a healthy profit, or will they compete for market share and charge $300 or even $255? What sort of strategies are available, and what sort of equilibria might emerge? Given the small number of firms in the typical IT market sector, understanding such issues is important for the working computer professional.
There are many books and web pages, such as gametheory.net and the Stanford Encyclopaedia of Philosphy. (Of particular interest to computer scientists is the work of Robert Axelrod, one of the pioneers of the evolution of cooperation, who initiated regular tournaments of interated prisoner's dilemma which contributed to the development of genetic programming ideas. The 20th anniversary competition was won by computer scientists from Southampton.) Finally, we also see game theory in game shows; there's some fun here.
I will then spend about two lectures developing the classical view of economics: that under certain assumptions, markets provide an optimal way of allocating resources. This view had its roots in Adam Smith's Wealth of Nations and was further developed by writers such as Ricardo and Jevons to explain forces driving the industrial revolution. We'll explore concepts such as comparative advantage, marginal utility, opportunity cost and exchange, so that you get at least a rough idea of what's `under the hood'. We will then look briefly at a number of the ways in which classical economic models fail, including the criticisms of Keynes and the fact that efficiency, welfare and justice do not always coincide.
There is a huge literature on basic economics. Cambridge economics students cut their teeth on Varian's textbook, `Intermediate Microeconomics', of which your college library should have many copies. You might look at chapters 1-6 and 14-16 to begin with. For an entirely different perspective, try JK Galbraith's `History of Economics'. A very convenient online reference is the History of Economic Thought website. With the collapse of the Soviet Union and the growth of anti-globalisation protests, trade became a controversial topic: the consensus view of economists can be found in Steven Suranovic's notes. The forced liberalisation of India's trade in 1991 provides some useful data on the value of free trade.
However the topic that excites most people, given the severe economic downturn over the last three year, is the business cycle. Progress over the last three centuries has involved a pattern of several years' growth followed by a year or more of recession. In order to understand this, and assess its effects on our industry, we have to study some macroeconomics. This year for the first time I'll have about half a lecture on macro. The best survey of the effects of credit crunches historically has been written by Reinhart and Rogoff; a classic text from 1936 is Keynes' General Theory of Employment, Interest and Money. The one economist to have correctly predicted the credit crunch is Nouriel Roubini; his macro lecture notes are here.
Of enduring interest to computer scientists are some more modern criticisms of the classical approach that fall within the realm of microeconomics rather than macroeconomics.
Information goods and services markets tend to be characterised by high fixed costs, low marginal costs and increasing returns to scale, together with lock-in effects, all of which tend to lead to monopoly or oligopoly. In many markets, there are also network effects: the more people use a given service, the more value it is to each user. So products may take a long time to reach critical mass, then take off very rapidly (as happened with faxes in 1985-88 and email ten years later). Network effects can reinforce a tendency to monopoly.
We will look at a number of other ways in which information goods and services markets can deviate from the classical ideal. These include asymmetric information, where one party to a contract knows more than the other. For example, people applying for health insurance typically know more about their health than the insurance company does, and this leads to adverse selection effects whereby sick people buy more cover. (Attitudes to risk in general are well known to be perverse; see John Adams on Cars, Cholera and Cows.)
The strategies used by monopolies to maximise their revenue are important, both as a practical foundation for later work on e-commerce and as a theoretical underpinning for understanding regulation (and the antitrust cases that successful tech companies often end up fighting). Monopoly strategies include market segmentation, price differentiation and bundling. Why, for example, does Microsoft prefer to sell Office as a single product rather than as separate word processor, spreadsheet and other programs? There's a good paper on Strategies for Two-Sided Markets by Eisenmann, Parker and van Alstyne which analyses who ends up subsiding whom, and why, in two-sided markets.
By far the best book overall is Shapiro and Varian's `Information Rules'. Varian's textbook also has some useful material, especially in chapters 32-36. As for online resources, there are many: the Information Economy page at Berkeley is a reasonable place to start.
A lot of current work in auction theory spills over between economics and computer science. Auctions have been around since at least the times of ancient Greece; they have long been the traditional way of selling art, livestock and much else. A lot of money was invested during the dotcom boom on the premise that technology would so lower the transaction costs associated with auctions that they would become the dominant means of doing business in many sectors. Ebay grew from nothing to blue-chip status in a few years; and the UK government made billions from auctioning off spectrum for third-generation mobile phones.
A surprising number of things can go wrong with auctions. The British government's success was not replicated everywhere else; in a number of countries, phone companies managed to rig the auctions and get bandwidth cheaply. Often this didn't require any overt criminal behaviour; the rules of the auctions were such that players could signal to each other, during the bidding process, which blocks they were interested in. The resulting tacit collusion meant that the taxpayers in many places got much less than expected. (The UK government's adviser, Paul Klemperer, has some interesting papers on what people did wrong – see especially `What Really Matters in Auction Design' for the practicalities. For a proof of the Revenue Equivalence Theorem, see his Guide to the Literature, and for its applications see Why Every Economist Should Learn Some Auction Theory.)
Over the last decade, there has been a huge surge of interest among computer science researchers in the design of combinatorial auctions. A combinatorial auction is one in which you can bid for combinations of objects: `I'll give you $100 for lots 1 and 4 and 7, or I'll give you $80 for lots 3 and 4 and 7'. Finding an optimal allocation in such an auction is not merely an NP-complete problem, but is close to many engineering problems of practical interest – such as finding a low-cost route across a network. (For more detail and links, see the notes of a course at Berkeley by Christos Papadimitriou.)
Classical economics assumes rational actors, and yet we often see people acting irrationally. The public misperception of risk is a particular problem: people worry too much about terrorism, for example, and about child safety, while less personal hazards from cyber-crime to global warming get discounted. There is now a thriving field of "behavioral economics" at the boundary between economics and psychology that seeks to explain systematically irrational behaviour in terms of the perceptions and biases that we acquired in the course of our evolutionary history.
Here are the slides for the economics lectures.
Introduction to law
There will be two talks on legal topics. The first, by Nicholas Bohm of the Law Society's Electronic Law Committee, will cover the basics. (His notes are here.) As the syllabus puts it, these are: contract and tort; copyright and patent; liabilities and remedies; competition law; choice of law and jurisdiction. The gloss on that is: what do you have do do online in order to incur liability, or to impose it on someone else; and where can you be pursued, or pursue them, through the courts once you have done so? A standard introductory text is "Learning the Law" by Glanville Williams and ATH Smith.
The second talk, by Richard Clayton of FIPR, looks at more technology-specific aspects of law and regulation. (His notes are here.) There are a number of EU directives which affect how you can do business on the net, covering subjects that range from distance selling, electronic commerce, data protection and electronic signatures to copyright; and there are a number of particular issues relating to their UK implementation. There are also some specific UK laws, such as the Regulation of Investigatory Powers Act and the Data Protection Act, that you might have to watch out for. One of the best-regarded cyber-law courses is that taught at Berkeley by Pam Samuelson (who deals mostly with US law issues); her course notes are here.
The course title `economics and law' also refers to the academic discipline whose subject matter centres on copyright, patent, and related topics such as database rights. This will be covered in the final lecture.
Intellectual property is sometimes seen as the foundation of prosperity in the information age, but is perpetually controversial. Powerful lobby groups, such as Hollywood and the music industry, have pushed for increased legal protection in ways that have brought them into conflict with the computer industry and with digital-rights groups. A popular writer on the effects of IP law on innovation is Larry Lessig; for further analysis of the economic effects, see papers by Scotchmer, especially ``The Law and Economics of Reverse Engineering''. A paper that has caused much controversy is The Effect of File Sharing on Record Sales: An Empirical Analysis by Felix Oberholzer and Koleman Strumpf. This shows that file-sharing has little effect on CD sales and may even help promote sales of the most popular CDs. You might also be interested in a talk given at the Computer Lab in 2002 by Richard Stallman. And some of the lab's most successful startups, from RealVNC to Xensource, have made versions of their products available as free software.
But despite the complex and sometimes tenuous connection between IP and business success, venture capitalists tend to look more favourably on startups who can claim some IP as a foundation for sustainable business advantage in the future. So if you're starting a business you may want to think carefully about what sort of IP strategy you'll follow. (And even within Cambridge University, there was a row when a previous Vice-Chancellor tried to assume ownership of almost all IP rights generated by faculty and research students. After academics put up a fight we were left with our copyrights and 85% of patent royalties.)
Finally I'll discuss ethics. Technology is moving so quickly in our field that the law usually lumbers along ten years behind. Lawmakers are not always the most geeky members of society, and so the laws they make often don't fit that well with reality. So laws alone cannot provide a comprehensive guide for action, except possibly for the rapacious. Ethics and social norms take up some of the slack. Quite a lot has been written on ethics in the last few thousand years; some of it may be useful, and interesting new debates are opening up in topics from neuroethics to policy. Some of these debates have live connections to economic arguments, and some of them will no doubt crystallise into laws in due course.
Supervisions, books and past exam questions
This course was created in 2002-3 by amalgamating and extending some of the basic material in the part 2 E-commerce and Business studies courses. Exam questions since 2003 are here, while some previous relevant Tripos questions are here, here, and here. In addition to this, see the revision questions in Varian's textbook, chapters 1-6, 14-17, 24-25, 27-28 and 32-36, and the problems in its companion volume `Workouts in Intermediate Microeconomics'. This course also subsumed the Professonal Practice and Ethics course that used to be taught separately in part 1a until 2009-10.
One word of warning: many part 1b students may never have studied a humanties subject since GCSE. It is a different task from learning a programming language; it is not sufficient to acquire proficiency at a small core of manipulative techniques, and figure out the rest when needed. Breadth matters. You should spend at least half of the study time you allocate to this subject on general reading. There are many introductory texts on economics and on law; your college library is probably a good place to start.