Microeconomics For Dummies - UK book cover

Microeconomics For Dummies - UK

By: Peter Antonioni and Manzur Rashid Published: 03-21-2016

Your one-stop guide to understanding Microeconomics

Microeconomics For Dummies (with content specific to the UK reader) is designed to help you understand the economics of individuals. Using concise explanations and accessible content that tracks directly to an undergraduate course, this book provides a student-focused course supplement with an in-depth examination of each topic. This invaluable companion provides clear information and real-world examples that bring microeconomics to life and introduces you to all the key concepts. From supply and demand to market competition, you'll understand how the economy works on an individual level, and how it affects you every day. Before long, you'll be conversant in consumers, costs, and competition.

Microeconomics is all about the behaviour of individual people and individual firms. It sounds pretty straightforward, but it gets complicated early on. You may not be an economist, but if you're a business student at university, the odds are you need to come to grips with microeconomics. That's where Microeconomics For Dummies comes in, walking you through the fundamental concepts and giving you the understanding you need to master the material.

  • Understand supply, demand, and equilibrium
  • Examine the consumer decision making process
  • Delve into elasticity and costs of production
  • Learn why competition is healthy and monopolies are not

Even the brightest business students can find economics intimidating, but the material is essential to a solid grasp of how the business world works. The good news is that you've come to the right place.

Articles From Microeconomics For Dummies - UK

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Microeconomics For Dummies Cheat Sheet, UK Edition

Cheat Sheet / Updated 02-28-2022

Microeconomics is that part of economics that looks at the world from the perspective of consumers and firms — asking how they make their decisions and how those decisions come together to make different kinds of markets. You do that by building models of different situations that explore the results of different types of conditions.

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The High Cost and Low Price of Information in Microeconomics

Article / Updated 03-26-2016

Many of the markets that most fascinate microeconomists concern information technology. Information has a strange economic property in that the marginal cost of getting a piece of information to an extra person is now zero. This change is because new forms of dissemination — via the Internet — have taken away the cost of shipping items as books, records, video tapes (remember them!), and boxed floppy discs of software. Therefore, as Hal Varian, Google’s chief economist puts it, information is expensive to create and cheap to reproduce. That reality has transformed many industries and forced people to look at possible solutions to the high cost of information creation. You see, if making the information costs a lot — economists call these first copy costs — it makes recouping your money very difficult when the price is heading toward marginal cost — zero. Creators can rejoice in some good news, though; many possible solutions exist to the problem. Alongside advertising — which was about the first solution entrepreneurs thought up during the early years of television — you can often find a related (or tied) product that consumers are willing to pay for and sell this for a price greater than zero, using the revenues from selling this product to subsidise the one you give away for free. One method that software companies have adapted is to move to subscription models or to sell their consulting services and give the product away for free. One globally popular British heavy metal band is rumoured to use data to find countries that pirate its records heavily and tour there, making money from concerts where it can’t from records. If true, economists would find this approach eminently sensible! In contrast, one solution that economists view with strong scepticism is using technology to restrict the ability to copy your product. When you think that copying may have utility for a consumer, copy-protecting the legal version of the product can very well end up making the illegal copy — relatively — more valuable! Funnily enough, most of the online music and video stores went through an experiment of doing just that. In almost no case has the approach lasted.

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Planning the Future with Microeconomics Scenarios

Article / Updated 03-26-2016

Absolutely no one in the world is an expert on the future, because (in case you hadn’t noticed) it hasn’t happened yet. Enter microeconomics. Not knowing the future is a big problem if, for instance, you need to make an investment that may take 25 years to pay off, such as drilling an oil well or building a train network. The future is so highly uncertain, you have to take some very unusual steps to deal with it! In the field of corporate strategy — which looks at how companies make long-term plans given competition and uncertainty — an unusual tool is available to help. It’s called scenario planning and the insight is that, when things are too complex or uncertain to model, you tell stories about them! The word scenario in this context means a state of the world. In an uncertain future, many such states could apply. If you can assess — qualitatively or quantitatively — what makes them different, you can use a mixture of economic theory — what you know about how markets work — and other sciences and social sciences to give you a flavour of what those worlds are like. When you’ve written those stories, you work back to look for things that may let you know which world you’re heading toward, so that you can adapt your strategy. Scenario planning relies on a full, solid understanding of the working of markets, and so building in game theory, competition, co-operation, and all the lovely supply-and-demand stuff isn’t so out of the way. The main difference is that when you arrive at a model that satisfies your requirements, you keep asking ‘what if?’ to test your intuitions — what if the oil price is high, what if people wear computers on their wrists, and so on. Economists often use scenarios as a complement to their other tools of strategy — they were originally invented to find a language to use to talk about nuclear war, and so they fit very well with game theory, which was developed for the same reason. Scenarios have proved highly effective in the corporate world: the most famous example is Shell’s ability to take advantage of the 1973 oil price shock. The difficulty, though, is that you need a link between drawing up the scenarios and developing and implementing your strategy. One problem is that if communication between planners and the wider company breaks down (as sometimes happens), how good your stories are doesn’t matter, because no one is using your insights.

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10 Areas for Extending Your Microeconomics Know-How

Article / Updated 03-26-2016

Microeconomics has shot off into all sorts of areas, looking at all kinds of questions — from how people select marriage partners to whether financial markets are inherently unstable. Here are ten areas where you can add to your knowledge of microeconomics and put it into practice, helping you to understand some of the deeper problems of technology, society and organisation. Consider creative destruction and the problems of technology Microeconomists use comparative static models, which means that they’re like looking at two different photographs of the world and comparing the difference: most microeconomists use this as a starting point for how to approach problems. But considering how things change over time is often important too. One problem, however, is that technology, in the sense of inventions, never stands still: it evolves, changing what’s possible in markets, which in turn changes how consumers and producers interact. This reality is extremely important when looking at information technology (IT). The pace of innovation is relentless in this industry, because product lifecycles tend to be short, and because products can build large networks of users in a short period of time. Therefore, some market structures — for instance, perfect competition — tend to get ruled out. Instead, competition is often sequential — a firm gets challenged not by a competitor but by a potential entrant. As a result, economists focus more on a theory like Schumpeter’s creative destruction — that old companies are overturned when people find newer and cheaper ways of doing something. A refinement, the model of disruptive technology, points out that seemingly worse products can win in a marketplace, because they hit new groups of consumers rather than ones that firms in the market already have. IT firms have to cope with a lot of innovation around them and change their best strategies for dealing with it. Microeconomists look at many areas within technology — from exploring the best size of a network to the problem of why some things seem to escape pressure from innovators and become ‘locked in’, such as the QWERTY keyboard users have right now. This area is complicated because information itself is a good with a marginal cost of zero. Therefore, many microeconomists are looking at finding a balance that allows innovators to profit temporarily from their creativity, while preventing them from having permanent monopolies. Question the rationality of politicians: Public choice What happens if you assume that politicians making up a government are rational and play to the incentives set for them? Public choice economics — that is, applying economic principles such as rationality to political questions — looks at this area and makes some startling predictions. For instance, in a voting system such as in the UK or US, the only vote that ever counts is the one that grants victory to a candidate. If 100 people vote and two candidates are involved, the only voter who matters is the one who determines the winning candidate. So if parties know that, say, 40 voters on each side are sure to vote firmly with one party or the other, they put their efforts rationally into winning over the 20 undecided people. That’s why politicians seemingly spend ages courting the ‘floating voters’ who may change their minds. Public choice economists also point out that governments can often be ‘captured’ by special interests. Even when no collective interest exists in pursuing those policies, politicians following their own private interests get persuaded to do so, for example by lobbyists. The problem is that each voter gets only a small fragment of the benefit of her preferred choice, but the costs of ending those policies that lobbyists have successfully persuaded politicians to introduce may be very high to the politician! Economists as politically different as James Buchanan and Elinor Ostrom have used public choice economics as a lens to focus on all kinds of questions — from how best to manage a common resource to the best way to ensure that corruption doesn’t take over a political system. Build a bridge to financial markets: Macroeconomics As a result of the recession of recent years, which began in the financial markets, finance has received a lot of attention lately. Building on economic models, and adding a whole host of computers and data processing, financial economics looks at how financial markets work and how they connect to the wider economy. That means answering questions about the best way to value an uncertain asset or the best way to deal with risk. Given that finance is full of uncertainty — Yogi Berra said it’s not easy to predict anything, especially not the future! — it doesn’t mean that anyone in a market is going to be right. Looking at finance involves a number of special challenges. One of the most important is that it requires a lot of study of probability and statistics, which are needed because financial trades happen very quickly and very often. Another problem is that markets have to price on the basis of predicted values rather than accrued values — because someone will already have booked the profits or losses by the time you trade. One famous result is Eugene Fama’s efficient market hypothesis. People have often questioned since the recession whether financial markets are efficient, but Fama’s hypothesis doesn’t use the concept of efficiency in the same way that ordinary people do. Instead the hypothesis talks about how information gets used in a market: in its weak form, for instance, it says that past performance doesn’t mean future performance, because the present price reflects all past information. It doesn’t say that the price is correct, given that things will change in the future. Understanding labour markets Is a minimum wage a good thing? How do trade unions affect wages and employment? Labour economics looks at these types of questions. In a labour market, typically the roles of supply and demand are different to ones in other markets: individuals supply their labour and firms demand it. Labour economics looks at these markets — using economic tools, adding in statistical analysis and using specialised models. This field analyses how skills affect the choices of hirers, how people choose to get those skills and how different types of labour market affect outcomes — asking, for example, whether making it difficult to fire people makes it harder to consider hiring them. One consideration, for instance, is that paying higher wages than your competitors may be rational, if workers are motivated by the fact that they won’t get as high a wage at competitors. Thus, you get better productivity — output per unit of work — than rivals, as Henry Ford found when he did just that. Investigating the importance of institutions Institutions, such as government departments, universities or central banks, are important structures in an economy. They have a role in shaping what happens in the economy, for good or ill, in many ways — from how they behave as institutions in their own right to how they affect other people’s decisions. Institutional economics is a diverse approach to looking at the role of these institutions in an economy. This definition seems self-explanatory, but pinning down institutional economics further is almost impossible, because researchers in the field have looked at such diverse problems. One approach grafts on marginalism and becomes the economic analysis of law. Another approach borrows tools from sociology to describe the roles of institutions. After a long period in the shadows, interest in institutional economics has grown recently, because people want to focus on the role that various institutions played in the financial crash and its aftermath. Most recently, Daron Acemoðlu’s work on the role of elites in developing economies has been a big talking point. In his analysis, one reason for the failure of development efforts in some countries is the role of ‘extractive’ elites — who syphon off the gains to development rather than allowing them to spread around the economy for everyone’s good. Studying foxes and bunnies: The complex systems view A famous model in biology examines what happens when foxes and rabbits share a field. How many of each species exist depends on how good they are at reproducing, how good they are at eating — or avoiding being eaten by — each other and the size of field. When you plot the populations of both animals against time, you get two nice smooth curves: For foxes: If they’re too good at eating rabbits, they get too successful. As a result, too few rabbits exist to support that number of foxes, and their population falls and the rabbit population rises. For rabbits: If they’re too good at avoiding being eaten by foxes, they get too successful and foxes find rabbits more plentiful. As a result, they eat more rabbits and the rabbit population falls again. Interestingly, when assuming nothing about the intelligence of the two species, you always get the same type of curve as long as they’re rivals. This simple example illustrates a complex system — complex in this sense means interconnected, not necessarily complicated! Economics is full of interconnected systems like this one, for example between a hardware manufacturer and a software producer. The complex systems approach to economics uses a mix of models — like the foxes and rabbits one — simulations and game theory to answer questions about the development of economic organisation. The tools are quite difficult, but the intuition is simple: economic development has a lot to do with how complex your systems are and how complex the things you make with that system are. Many of these techniques have been imported into economics from biology or physics, and take a slightly different tack on how to look at economic questions. One question that complex systems theory tries to answer is why some places in the world have developed advanced economies and others fail to, no matter how many times people attempt to do just that. One answer suggests that it isn’t related to what people can make on their own, but how they link to one another. For instance, in a peasant economy, what’s the point valuing a cow as an asset you can sell if no market exists where you can sell it. You can also adapt complex systems to look at product complexity. The computers on which most people use in their daily lives are extremely complex products with parts built from thousands of components, involving many different companies all over the world. The complex systems view tries to model how all this comes together to make the final computer — as you can imagine, it’s a tough task. Learning from the past: Economic history One of the interesting things for economists in the UK is that public records go back nearly a thousand years! Economists can pore over all kinds of information to discover all manner of things about the differences in production and consumption between the past and now. Many of the insights are useful: for example, movements in tulip bulb prices during the great tulip boom and bust of the 17th century tells you a lot about how financial systems today behave during a crisis. Economic historians are always analysing available data, or finding or estimating data to give a clearer picture of how the economy came to be. Along the way, they’ve found ways to convert data into prices comparable with today — a surprising number of products have very old roots! — and built data series that can be explored to tell you a fascinating story about the differences between today and the past. (The Bank of England, for example, has an amazing set of data on all kinds of things.) How much you can learn from the past fascinates economists. In theory, the past should be a sunk cost, and people should learn from their mistakes. In practice, patterns re-emerge throughout history — you can see some of the same runaway behaviour in the Japanese property crash of the 1990s as in the South Seas bubble that gripped London in 1720 or the tulip mania of the 1630s! In each case investors piled into the market in expectation of rising returns, making lots of money until some event made the expectation of profit unlikely and the market crashed. (If you’re interested, the ‘Tulip Mania’ case informed a famous book by Charles Mackay called Extraordinary Popular Delusions and the Madness of Crowds.) Reflecting behaviour in the real world: Bounded rationality The rational consumer model has many advantages. But it also has some problems if you want to use it for prediction — not every decision can be explained when you assume rational consumers. Perhaps people have limited foresight, limited time or limited ability to understand what offers are put to them; or they just believe that the optimum is unavailable. These limitations change the way people make their decisions and mean that some of the equilibrium results may not be as robust in reality as they are in the model. In contrast, bounded rationality models often emphasise that because the world is complex, and people limited, the best outcome is often ‘good enough’ given all the constraints on a person. As a result, people’s methods for making choices matter — bounded rationality calls these heuristics. For instance, supermarkets stock many types of tomato ketchup, but buyers don’t go through them all to choose which one they want. Instead they probably form a preference and then follow a heuristic that says ‘look for that tomato ketchup and if it’s there, buy it’. This behaviour doesn’t mean that people are stupid, not at all! It means that instead of going for what the rational choice model thinks is optimal, people go for what they can get given the overall difficulty of constantly making choices in the world. Bounded rationality adds to the analysis an understanding that sometimes acting in a way that microeconomics considers irrational is actually rational. Going to the gym every week just because you paid a subscription may not be rational, but your friend who does exactly that is likely to get fitter than you (feel the burn!). You can to some extent say that bounded rationality models and traditional economic rationality can be the same thing under certain circumstances. Imagine you want to optimise not only the utility you receive from buying something, but also the time and calculation effort that went into choosing what to buy. Under those circumstances, you can also say that bounded rationality and traditional rationality may get the same result when you include the time, effort and emotion that goes into choosing as a cost to the consumer. Exploring statistical relationships: Econometrics Econometrics is the branch of economics that looks at what happens in the real world by building models and testing them using statistical techniques to see whether they work. Economics as a whole uses a lot of data these days, partly because so much gets collected. Having the data available means that you can perform better quality tests in all kinds of areas. Econometrics does two things: Develops sophisticated statistical techniques for looking at economic data: Such data often has issues — it’s never perfect and doesn’t always follow the same distributions that you expect statistical data to follow. Econometricians come up with techniques for dealing with these problems — most of which are now quite simple to implement on a computer. Tests models using various techniques that have different advantages and disadvantages: Applied economists test in several different ways to ensure that they have the best chance of weeding out false correlations — where data seem to be connected — while unearthing real ones. Finding lags and leads: Time series analysis Most data in economics concerns changes over time — for instance, growth is a measure of how much gross domestic product changes over a year. A particular problem exists, however, because the past is often completely different from today — what determined growth in 1950 may not be same as today. Time series analysis tries to develop models that are robust to those changes where possible, in order to get a view of how things change over time and what relationships — for example, between earnings and dividends that companies pay shareholders — stay reasonably consistent. Many issues exist with time series — not just the problem of the past being unlike the present. Nobel laureate Clive Granger picked up a particular one — spurious regression. If you have two series that are both increasing, and you run a time series model to find out how they’re correlated, the measure of correlation goes up as the number of points in each series does — so that the longer the run of the model, the more likely you’ll find a relationship. That’s why statisticians found that when the Danish stork population increased, so did the birth rate. Economists are often interested in finding lagging and leading relationships, because some time is usually required for economic adjustments to happen. If you change tax rates this year, you may not see an effect on consumer spending until next year — in other words, the tax change leads the change in consumer spending. Leading indicators are important because they give you an estimate of what will happen in the future, and forewarned is often forearmed. For this reason, financial markets in particular pay lots of attention to them!

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A Quick Study in Behavioural Economics

Article / Updated 03-26-2016

The financial crisis caused many economists to re-examine a lot of old questions in microeconomics. One is the extent to which people are rational in the economic sense ‒ choosing the best they can do for the budget they have. If they aren’t, a number of results, like the predictions of what kind of equilibria will exist in a market, can’t work ‒ and you have to throw out over 100 years of research into microeconomics. Fortunately, the news so far isn’t catastrophic! Instead, it points to people being boundedly rational: that is, they more or less try to do the best they can, but their decision-making isn’t perfect and they’re prone to a number of systematic biases. Economists have been drawing on results from psychologists to refine their models. The area of — largely — microeconomics that studies this problem is called behavioural economics. It uses lab experiments and other data to get a handle on how to adapt the utility-maximising model to try and make it more realistic and predictively better. Some interesting examples have already come out of how people’s biases affect their decisions. For a start, take the way a problem is framed. If your doctor told you that you could take medicine to clear up a cold in seven days, but if you left it to itself it could take a week, would you take the medicine? The first part is framed more positively, and so behavioural economics predicts that you’d choose the former! Picking up some behavioural economics is a good idea, whether you want to model those choices or just arm yourself with some self-defence against certain selling tactics. When, for example, restaurant sommeliers describe a more expensive bottle of wine to you, they’re framing your choice in some way. If you know a wine is expensive, you’re more likely to rate it as higher quality, even though you’d be unable to distinguish it from cheap plonk in a blind test. Finding people’s biases and exploring them leads to interesting outcomes. One is that choice isn’t necessarily a good thing in all circumstances. In one experiment, people were more likely to buy from a stall containing a small number of products than one with a larger number. Why? Well, although more people stopped at the larger display, they were overwhelmed by the amount of choice available and didn’t buy anything! When risk or uncertainty is involved, the biases are sometimes stunning! Ask yourself whether you’d prefer to be given £100 or enter a lottery where you have a 1 in 10 chance of winning £1,000. You may not realise but, rationally, you’ve been offered the same thing in both cases: you get expected outcome by multiplying outcome by probability and so both offers amount to £100! But would you prefer the risk of not receiving the money — 9 times out of 10 you’d get nothing with the second offer! If people aren’t rational in the way the utility model says, does it matter? Well, the answer depends on what you want to model and why you want to do so. If you want to see how markets work on average and don’t mind having to qualify your answer with a ‘more or less’, it probably doesn’t particularly matter. Even if you do use behavioural data to inform you, it may not predict what a given individual does in that situation. But when you need explanations for why the predicted equilibrium may not be holding, adapting models in the light of behavioural conditions may be just what you need.

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Balancing Shareholders and Management in Microeconomics

Article / Updated 03-26-2016

In reality, companies are often very complex entities. In microeconomics, the main difference is that large companies tend to be owned by one set of people — shareholders — and managed by another — the professional managers they hire. Deciding how vital shareholders are to a company is an important question, and the answer isn’t as obvious as it may seem. The American Academy of Management, for instance, completely changed its view on the matter between the 1970s and 1980s (and has changed back again since). In 1973, it announced that the company was at the centre of a set of relationships, between workers, owners, customers, and wider society. In 1980, though, following management fashion at the time, it said that only shareholders were important to the company, and only their interests should really matter! Shareholders in a company typically have a stake in the ownership of the firm that entitles them to a share of its profits. The problem is that offering the share is management’s decision. That means that managers have to impress shareholders with their pitch for how much of the company’s profits — earnings in financial terms — they return to shareholders and in what form they do so. Clearly, many trade-offs are required here. For instance, if a company retains too little of its profits for investment, shareholders may be called upon to stump up more cash in the future for investment purposes. They may not like that. Retain too much of its profits, however, and shareholders wonder why you’re making unproductive investments. Make too much cash without a corresponding investment and investors — who want to make as much return on their capital as they can — can start demanding that you return some cash to them, either as dividends or by buying back some of their shares. Therefore, although the economic model of a profit-maximising firm is a good modelling tool for general purposes, when you look specifically at how a company keeps all these people happy, you soon see that the problem becomes far more complex than you expected!

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5 Reasons Why Markets Fail

Article / Updated 03-26-2016

Understanding why markets fail is a key element in understanding microeconomics. Markets can fail for a number of different reasons, but the two most common are when a market provides something society doesn’t want, or doesn’t provide something society does want. Other reasons include the following: Information: If consumers and producers do not have complete information then the problem is called asymmetric information. A lemon market — a market where there are lots of low quality products and you can’t tell before buying what the product quality is — is one example. Too Few Property Rights: If no property rights are assigned then the good is called a common good and individuals will have an incentive to over-use it — as no one is paying for using it! The Tragedy of the Commons is an extreme example of this situation. Too Many Property Rights: If a product depends on other things — for example earlier research — and there are property rights assigned to each of those things, then a market can fail because paying for the use of those properties is too high a fraction of total cost. This is called the Anti-Commons effect. Public Goods: Public goods are not excludable, which means you can’t exclude anyone who hasn’t paid for the good — an example is street lighting. Markets find it hard to price these goods, so they tend to be produced collectively or through philanthropy Externality: An externality is a cost or benefit that falls on a third party; for instance, if you buy land and build a factory but someone nearby is affected by your emissions.

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Classifying Types of Markets in Microeconomics

Article / Updated 03-26-2016

Microeconomists compare different types of market depending on the number of firms in the market, the ease of entering the market and the degree to which products sold are similar. There are four main types are: Perfect Competition: A very large number of firms sell to a very large number of consumers. Firms make an identical product, and consumers are perfectly informed about prices and quantities. An example might be a fruit and veg market. Pure Monopoly: A pure monopoly is the only firm selling in a market, and there may be high entry or exit costs. Monopolies will produce less for a higher cost. Consumers will get worse welfare under monopoly, and society as a whole will take some part of the loss - a deadweight loss. Oligopoly: Oligopolies are markets where there are only a few competitors, and probably high entry costs. Oligopolies will tend to produce more than monopolies but less than forms in perfect competition - the result depends on how firms compete with each other. Monopolistic Competition: In a monopolistically competitive market firms make different products from each other. As a result they behave like monopolies in the short run and competitive firms in the long run. Firms in monopolistic competition have to consistently invest in their product to keep themselves making higher profits.

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Understanding the Key Definitions in Microeconomics

Article / Updated 03-26-2016

Microeconomics comes complete with its own set of vocabulary, which can sometimes be confusing. To get a true feel for microeconomics, three key terms must be defined and understood. Those terms are: Utility: Utility is the value people get from making a choice. You can find out how much utility a consumer gains by working it out from the choice they make. Consumers optimise — get the best level of utility they can, given that they have to do so within a budget constraint. Profits: Profits are what’s left over from a firm’s revenue once all relevant costs have been accounted for. Firms try to make as much profit as they can, and they do this by producing until marginal revenue — the revenue gained from adding an extra unit — equals marginal cost - the cost of producing that extra unit. Markets: Markets are places where consumers and firms trade. In a model of a market, consumers optimise their utility and firms try to maximise their profits. The price and quantity in the market will be the affected by lots of things — from the number of firms in the market to the income, or valuations of consumers.

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Understanding the Prisoner’s Dilemma in Microeconomics

Article / Updated 03-26-2016

The prisoner’s dilemma can help you better understand microeconomics. In the prisoner’s dilemma, two people are arrested for a crime and put in separate rooms so that they can’t communicate. The authorities make the same offer to both, one that means that their best option if they could communicate is unattainable. Because neither party can fully trust the other they will default to a Nash Equilibrium that is not as good as the collective best outcome. In strategy, a Nash Equilibrium is the condition where each player is doing the best they can, given that all other agents are also doing the best they can. A Nash Equilibrium is the best any individual player can do, but it’s possible that a better collective outcome could exist if players were better at co-operating with each other. So, what’s the Nash Equilibrium used for in cases like the prisoner’s dilemma? Cartels: If cartels could make legally binding contracts then it is possible that they could co-operate and act as a single monopoly. But since cartels are illegal, no one can make that contract, therefore the members can never fully trust each other. Organised crime: Organised crime is an attempt to beat the prisoner’s dilemma. The syndicate uses its power to ensure that none of its members have an incentive to cheat.

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