Week 10 notes
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This 10 page Class Notes was uploaded by Taryn manciu on Thursday December 3, 2015. The Class Notes belongs to Econ201 at University of Oregon taught by Keaton Miller in Fall 2015. Since its upload, it has received 42 views.
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Date Created: 12/03/15
Week 10 Tuesday Labor Factor 1: Skill-‐biased Technical Change -‐New innovations are complements for skilled labor, but substitute for unskilled labor. Impact on demand? Economics of superstars -‐How Internet (and communication tech) impacts return tp being the best -‐The best singer in the world limited in number of people they can sing to at one time -‐2 best, 3 best, 100 best probably make close to the same amount as the best -‐Now rerecorded music comes out -‐Best singer can now sell to everyone th -‐No one cares about 100 best -‐Winner takes all scenarios -‐Skilled worker at that time: skilled craftsman who has learned a trade after a long apprenticeship -‐Unskilled worker: hands and arms connected to a strong back -‐Technological change at time (Henry Fords assembly line) takes unskilled worker and put him on an assembly line. Up to speed in a few days -‐This is unskilled-‐biased tech. change In this period there was a decline in the skill premium. Factor 2: Expansion of trade and immigration -‐Why should that raise the skill premium in the U.S? -‐Ratio of skilled to unskilled in the U.S is high relative to rest of world -‐With expansion of trade, tend to export goods with high skill content (pacemakers, ipads) and import goods with low skill content (sneakers) -‐Expanding trade reduces demand for unskilled labor in U.S, increases demand for skilled labor Factor 3:Decline of Unions -‐This is not a demand shift but rather a change in market power of the unskilled -‐Unions declined significantly over the past 30yr. Production (“blue collar”) jobs much more likely to be unionized than “white collar” management jobs The 99% and the 1% -‐There is increasing inequality even within the upper range of income distribution -‐“Haves” starting to complain about the “have mores” -‐“Have mores” rising relative to the “haves” How do we explain increase of returns at the very top? -‐Extreme skill-‐biased tech. change -‐Return to a very special talent has gone up -‐Economics of superstars (easier to leverage talent) -‐Return to special talent always there, but past social norms limited pay differences -‐Looting. The 0.01% has figured out a new way to work the system to redistribute the economic social pie to themselves, including busting unions (occupy wall street’s explanation) Example of Theory 1: Return to Talent What about other countries? -‐In terms of other countries, seem to be a difference between “Anglo countries” and others -‐Canada in “U.S. Light” -‐U.K in “U.S Lighter -‐Japan and France completely different -‐If this is all skill-‐biased tech. change, why are Anglo countries different? -‐One possible explanation: France isn’t paying market wages Why do workers in the same country get different wages -‐In competitive markets, people with the same skills receive different wages if working conditions vary -‐Compensating differentials -‐In Competitive markets, people with different skills and ability will get different wages -‐Wage includes a return to human capital -‐If labor markets are NOT competitive, workers of equal ability might receive different pay -‐Union workers get 20% more than non-‐union worker. Discrimination -‐Two types of workers, type and type b, with equal ability -‐Suppose there are two kinds of firms, biased and unbiased -‐Biased firms refuse to hire type b -‐Unbiased firms don’t care; will hire whichever type is cheapest -‐Different demand curve for biased and unbiased^ Analysis of equilibrium: Wb<Wa -‐Biased firms know they can pay less for type b workers, but they refuse to hire them. The wage Wa is where the demand for type A workers by biased firms = all of the supply -‐Since Wb<Wa, unbiased firms wont hire any type A workers since they are too expensive -‐They offer Wb to both kinds of workers, but only type B workers will accept these wages -‐Could we draw things differently and have an equilibrium with Wb>Wa? Long run with biased firms -‐Biased firms pay higher wages for same quality labor so biased firms have higher average cost than unbiased firms -‐Long run, low cost firms tend to drive high cost firms out of the market -‐Conclusion: in discrimination is due to preferences by firms, expect market forces to work toward driving the discrimination out of the market Customers care but firms don’t -‐if discrimination is due to preferences by consumer about the kinds of workers that get hired, we do not expect market forces to work towards driving the discrimination out of the market Asymmetric Information and Moral Hazard -‐How did we get here? -‐Started wit the first welfare theorem -‐Assumed no externalities, no monopoly, then the free market outcome in efficient -‐Embedded assumption: an assumption market at a low level in your model -‐Generally don’t realize it is an assumption -‐Often comes up in discussions -‐Assumed full information: everyone in the economy knows everything relevant to his or her decisions -‐This doesn’t mean everybody has to know everything! Just relevant things -‐In Reality? Do YOU know everything that’s relevant to your studying decisions? Imperfect information is hard to deal with -‐Economists started thinking about this 40yrs ago -‐Want to understand case when nobody knows anything -‐Need to understand lots of probability theory -‐Still need to make some sort of assumptions about what the possible values of truth are -‐Why is this a problem? -‐Example: CO2 emissions -‐Micro theory says: this is an externality, just apply Pigouvian tax and we’re good to go! -‐Congress turns to environmental scientists and say “how much should we charge” -‐Large-‐scale problem: market may not be efficient, but government may not have an answer either! We will focus on asymmetric information -‐Main idea: the “truth” about some decision-‐relevant information is known to some market participants, but is hidden from others -‐Useful because math becomes much easier to deal with -‐Models many real life situations pretty well -‐Most imperfect information scenarios can be reduced to this scenario 2 Kinds of hidden information -‐Hidden action -‐Someone takes an action that affects you, but you know about it -‐Leads to moral hazard -‐Hidden Characteristics -‐Someone has some ability that you depend on, but don’t know about it -‐Leads to adverse selection Illustrate hidden actions with the insurance industry -‐What is the hidden action? -‐People who are covered by an insurance policy may take actions to reduce (or increase) the probability of an accident happening -‐Ex. Over insurance can lead to hazard for a person’s morals which is where we get the name moral hazard -‐Ex. Employer/Employee relationship – should we pay flat salary or commission? -‐Hidden action: workers performance -‐If paid commission worker bears more risk and has stronger incentives (can cause other problems) -‐The selection of people who purchase the water damage coverage will be adverse from the perspective of the insurance company -‐Main problem with credit cards: people that call up and ask credit cards are adversely selected and a much bigger risk that others (even if they have the exact same credit info!) -‐New law makes it illegal to base insurance rates on pre-‐existing conditions, get adverse selection -‐One side of the market: informed. Other side: Uninformed -‐Screening: when uniformed does something to try to separate out the good -‐Signaling: when informed does something to signal he or she is one of the good ones Moral Hazard and Too Big to Fail (TBTF) -‐Bankruptcy process: GM, Chrysler bankruptcies not disruptive (in relative sense) -‐Many argue banking is different -‐So incentive for government to step in and not let huge banks go into bankruptcy Week 10 Thursday Economics of Matching, employment, marriage, and Tinder. 288 people 400 points available -‐How should Bucky allocate a budget between pizza and beer? -‐How much should a monopolist produce? -‐Should a plant shut down? Many decisions are discrete -‐Choose one cell phone, not 2.7 -‐Spring break in Cancun or South Padre? -‐Matching, where agents from two different groups want to form a pair -‐Even worse: at least every nexus 6P is identical! People are not. More embedded assumptions crept into our markets -‐Thinness: lots of actors on both sides of the market to transact with each other -‐When we moved from stair-‐step marginal cost/benefit graph to a linear one -‐Uncongested: Actors in the market have a lot of time to consider alternative transactions and make the transaction they want -‐Experiment 2 (making burgers and fries): not a lot of time to consider trades or purpose alternatives -‐Safe: Actors can reliably reveal or act upon their information without fear or negative market consequences. -‐President Schill asking students how much college is worth to them. How can we analyze these types of decisions and markets? -‐In Realland, lots of complicated factors, people move around, job requirements and responsibilities change, life events force adaptation. -‐Thickness and congestion of market in endogenous-‐ actors within the market can choose them (to some extent) -‐As always, we have to simplify -‐Plan of attack -‐Start with theory-‐ write down simplest model and see what we can learn -‐Move toward real world -‐Look at examples The two-‐sided matching market -‐We have an equal or two types of people -‐Each person has preference over every person of the other type -‐Heterosexual men and women -‐Employers and employees -‐Graduate school applicants and admissions committees -‐Organ donors and organ recipients Key theoretical question -‐Can we find a matching that is both complete and stable? -‐Matching: a list of pairs of people in the market (A, 3)(B, 1)(C, 2) -‐Complete: Every person in the market is matched with someone else -‐you get a match, and you get a match and you get a match! -‐Stable: There are no two people in the matching such that each of them prefers the other over their match -‐Donald is married to Jane, Edward is married to Laura, but Donald would prefer to be with Laura and Laura would prefer to be with Donald. Answer… YES! -‐Very famous result from Gale and Sharply in 1962 -‐If there are an equal number of participants on both sides, and each participant has a completely stick preference ordering over the opposite side, then a stable matching exists -‐Compete: I have preferences over all of the people in the other side of the market -‐Strict: There are no ties/indifferences in my preferences -‐ I can “strictly” prefer one alternative to another -‐How do you prove this? Find the stable matching Gale-‐Shapley algorithm: Deferred Acceptance Proposals 1. Each man m proposes to his first choice 2. Each woman looks at the proposals she has received, “holds” the best one, and rejects the others 3. Each man who was rejected makes a new proposal to the next highest choice who hasn’t yet rejected him. 4. Each woman holds her most preferred acceptable offer to date and rejects the rest 5. Repeat 3 and 4 until no more proposals are made This is generalizable -‐Following this algorithm generate a proposer-‐optimal matching -‐It is impossible to find a matching that is complete and stable that each proposer would like at least as much as the one generated by the algorithm -‐That matching might be significantly different from the acceptor-‐optimal matching -‐Intuition: when you are the proposer, you can go straight to your first choice and see if it works out. If it doesn’t you’d never be able to get it anyway -‐Can acceptors do anything to improve their outcome? -‐LIE! -‐Acceptor 1 could reject prosper A over proposer B (even though 1 may prefer B to A) -‐Proposer A then goes to acceptor 2, who currently is “holding” C -‐C proposes to 1, who prefers C to both A and B -‐In fact: no matching mechanism exists for which truth telling is a dominant strategy for every agent -‐There is an incentive for someone in the market to lie -‐In other words, a matching market is not safe because people who tell the truth may be worse off than people who lie -‐Of course, you can only lie if you know enough information to make it effective Match clearinghouses exist in some markets -‐New doctors, applying for their residency -‐Hospitals are the proposers, doctors are the acceptors -‐Grad students in NYC and Boston -‐Schools are prospers, doctors are the acceptors -‐Kidney exchange -‐I can donate a kidney to A, A can donate to B, B to C, and so on until my friend gets a kidney What about one-‐sided matching? -‐Roommates, bridge-‐partners, non-‐heterosexual partners? -‐Also happens when one side in a market isn’t an active participant -‐Assigning people to rooms in a dormitory A stable matching might not exist -‐A, B, and C are the most preferred person for someone -‐In any solution, one of A, B, or C must be paired with D and the other two with each other -‐Whoever is partnered with D will have someone else who rated him or her highest -‐The person who is partnered with D prefers anyone to D We use a search model to understand real-‐world behavior -‐Can think of potential applications as coming from a pool, with a distribution of quality -‐The higher their quality, the higher their marginal product -‐Costly search-‐ firms can spend some effort to take a draw from the distribution and learn about their quality (interview process) -‐When should the firm make an offer? Solve search model with a cutoff strategy -‐Set a cutoff level of quality in your distribution that depends on the marginal product, the probability of getting someone above the cutoff, and the cost of searching -‐Keep taking draws from the distribution until you find someone above the cutoff In the real world, use multiple stages -‐Costs can be incredibly high, particularly if you hire (or marry!) the wrong person. So implement a staged cutoff system -‐Application stage -‐Interview stage -‐Probationary period -‐Promote from within -‐At each level, gain more information about quality of person (screening) and choose whether to progress -‐People also use other signals to determine quality – doesn’t always work -‐If you have a nice car, you probably make a decent amount of money (but might be a jerk) -‐If you volunteer to support the homeless, you’re probably a nice person (but might just be doing it to look like a nice person) -‐Too much moral philosophy for my blood!
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