3. Study a durable good monopoly, where the point is that market power is eroded because the monopolist starts to compete with itself.

Size: px
Start display at page:

Download "3. Study a durable good monopoly, where the point is that market power is eroded because the monopolist starts to compete with itself."

Transcription

1 14 Monooly Varian: Read the chater on Monooly. You may also want to go back and review elasticities. U to this oint we have studied rms that take all rices as given. While this may be a reasonable aroximation in highly cometitive markets (which we think of as markets where a large number of rms roduce some homogenous good), rice taking doesn t make much sense in markets where there is some obvious market ower, such as Microsoft, Terasen Gas, Coca Cola, and harmaceutical comanies roducing atented drugs. To analyze monooly ricing we will study a (artial equilibrium) model where a single rm is the only actor in the industry aart from consumers. The consumers will lay a assive role; their behavior is summarized by a demand function (which we think of as generated by otimizing consumers) for the good. We will roceed as follows: 1. Study the standard textbook monooly ricing model.. Make the observation that it is no longer obvious that the ricing scheme should be a single rice er unit sold. Some examles of various forms of rice discrimination will be given 3. Study a durable good monooly, where the oint is that market ower is eroded because the monoolist starts to comete with itself A Pro t Maximizing Monoolist Like a cometitive rm, we assume that the monoolist strives to generate as large ro ts as ossible. That is, it seeks to maximize y C(y): However, unlike a cometitive rm, a rational monoolist understands that it can only sell what the consumers are willing to buy and, since it oerates alone in the market, the rm can set both rice and the level of roduction. We let D () denote the (direct) demand 1

2 for the roduct and note that the monoolist can sell at most D() units at rice. The otimization roblem for the monoolist is thus subj to y D(): max y C(y) ;y Clearly, y = D() in a solution since otherwise the sales could be increased without lowering the rice, so we may rewrite the roblem as max D() C(D()); where we have rice as the choice variable. Alternatively we may invert the demand (view it as in the ictures where we have y as the indeendent variable and as the deendent variable). Then if (y) is the inverse demand we can write the roblem as max (y)y C(y); Inverse and Direct Demand f X x t } f 1 R t y Y Figure 1: The Inverse of a Function Mathematically seaking, if y = D() is the direct demand function, the inverse of D is

3 a function = D 1 (y) such that D 1 ( D() ) = : {z } quantity demanded at rice The concet is illustrated for a general function f in Figure 1. The oint is that if the function f takes x to a value y; then the inverse takes the value y back to the value x we started with. This must be so for each x and each f (x) ; so the inverse reverts the oeration of the original function f: As an examle, say that D() = a b Then, to nd the inverse we only need to solve out as a function of the quantity. That means that y = a b(y), (y) = a b 1 b y = A By where A = a b and B = 1 b 14. The Otimality Condition Both versions of the roblems are equivalent, so in rincile it doesn t matter which one to solve. However, it turns out that it is somewhat more convenient to work with max (y)y y C(y); The rst order condition is 0 (y)y + (y) c 0 (y) = 0, 0 (y)y + (y) = c 0 (y) To interret the condition note that (y)y is the revenue the monoolist gets if selling y units. Hence 3

4 d (y)y = dy 0 (y)y + (y) is the marginal revenue. In words, the additional revenue the monoolist gets for a small extra unit of outut C 0 (y) is just the marginal cost. Thus, the otimality condition is the rather natural condition that the additional revenue from the last small unit outweighs the cost. Observe that the condition = C 0 (y) has the exact same interretation. The di erence is that a cometitive rm treats rice as given, while the monoolist icks rice/quantity combinations on a downward sloing demand curve. Hence the trade-o is di erent for the monoolist. If the monoolist sells few units it can charge a high rice, but the more units it sells the lower rice it must charge. When it lowers the rice to get one additional unit sold it must lower the rice for all units, so the loss in revenue associated with selling one more unit will be higher the more units the monoolist sells. This logic is most easily understood in an examle with constant marginal cost and a linear demand Examle: Linear Demand Let (y) = A By c(y) = cy so the roblem is The rst order condition is max (A By) y y {z } (y) cy By + A By c = 0 4, y = A c B

5 Note that (A By)y is the revenue, so A By is the marginal revenue. The roblem and its solution can thus be deicted in a grah as in a 6 Tc TT cc c T cc sloe TT b c Pro t c cc T TT c sloe b cc T c T MR cc TT Demand c T c - y y Figure : A Pro t Maximizing Monoolist Figure, where the demand curve as well as the marginal revenue is drawn. To some of you it may be geometrically obvious that the solution is to set the quantity halfway in between 0 and the quantity where the demand curve intersects the horizontal line at height c: Solving c = A By we get y = A c; so B y is indeed this middle oint. To understand geometrically that this is the solution to the ro t maximization roblem, observe that the monoolist aims to make the rectangle reresenting ro ts as large as it can. If the quantity sold is small, the ro t is a high thin rectangle and there are few units to loose revenues from if the quantity is increased/rice decreased. If the quantity is close to A By; then ro ts is a low fat rectangle and there are many units to gain revenues from if quantity is decreased/rice increased It may be visually clear that the ro t is the higher with y at the midoint between 0 and A By and one can also show it by ure algebra (no derivatives involved) or elementary (=retty hard) geometric reasoning. Intuitively: 5

6 Additional revenue from extra unit due to increased sales is aroximately (y + 1) = A B(y + 1) A By Loss in revenue in terms of lower rice on all units is ((y + 1) (y)) y = (A B(y + 1) A + By) y = By so the change in revenue is aroximately a By: 14.4 Elasticity The basic trade-o for a monoolist is that: If the rice is high, the ro t er unit is high but it sells only a few units. If the rice is low, the ro t er unit is low, but it sells many units. The outcome of this trade-o is as we saw a comromise between quantity sold and ro t er unit. Clearly, it is imortant for this trade-o how resonsive demand is to changes in the rice. The most obvious measure of resonsiveness to rice is simle D 0 (); the derivative of the demand function. However, for several reasons (that I will not detail) economists usually measure resonsiveness of demand in terms of elasticities. The elasticity of a demand function D() is given by e() = D0 () D() = dy d dy y = y : The reason why this is convenient is that the elasticity is a good aroximation of the ercentage change in quantity demanded over the ercentage change in rice. This can be seen by observing that for a small change in the rice d D( 0 ) D() + D 0 ()( 0 ) 6

7 and utting this into the de nition of the demand elasticity we get e() (D(0 ) D()) D()( 0 ) = y z } { D( 0 ) D() D() {z } ( 0 ) = y y The main usefulness with the elasticity comared to the sloe of the demand function is that it is a unit-free measurement that makes it easy for economists to comare emirical ndings for di erent markets with each other and sometimes even get a sense for whether rms have monooly ower or not The elasticity of a linear demand function. Let D() = a b ) D 0 () = b the elasticity is thus e() = D0 () D() = Now, since elasticities are negative and it is easier to think about ositive numbers we tyically convert elasticities to absolute values. a b b 1. If je()j = 1 ) b a b = 1, b = a b, = a b. je()j > 1 ) b a b > 1, b > a b, > a b 3. je()j < 1 ) b a b < 1, b < a b, < a b b a b! 0 as! 0 b a b! 1 as! a b since b! a and a b! 0 as! a b : DRAW! 7

8 14.6 Elasticities and The Monoolist Problem For this it is convenient to use the version of the monooly roblem with the direct demand, i.e., we solve max D() C(D()) The rst order condition is D() + D 0 () C 0 (D())D 0 () = 0: The interretation of this the same as in the revious version of the rst order condition, but it is a little harder to see: D() + D 0 () is the change in revenue from a slight change in the rice C 0 (D())D 0 () is the change in cost from a slight change in the rice Hence the condition has the same interretation in terms of marginal revenue being equalized to marginal cost (it is the same roblem, so it should). The rst order conditions can be reorganized as Now this tells us that D() + D 0 () = C 0 (D())D 0 (), /divide by D 0 ()/ : D() D 0 () + = C0 (D()), D() D 0 () + 1 = C 0 (D()), 1 e() + 1 = C 0 (D()) 1 e() + 1 > 0 D() D 0 () = 1 e() since otherwise the marginal revenue is negative. Translating the negative elasticity to an absolute value this means that 1 je()j + 1 > 0 8

9 or, je()j > 1: We can then rearrange the rst order condition once more as = je()j je()j 1 C 0 (D()); which is often referred to as a marku ricing formula. The oint with the exression is that we see that rice must exceed the cost. However, since the monoolist icks the elasticity when icking a oint on the demand curve we should kee in mind that the elasticity in general varies (recall the linear examle) The Ine ciency of Monooly Pricing Consumer(s) value the last unit roduced at the monooly rice m : However, the monoolist only gives u the marginal cost C 0 (y m ) if roducing an extra unit, which the consumer would value at m : Due to this wedge between the marginal cost and the willingness to ay for the last unit all agents could be made haier if, in addition to the units traded at monooly rice, the monoolist and the consumer(s) could trade some additional units at a lower rice. You may note that the roblem is the di erence between the marginal cost and the rice the consumers ay, so a tax on a good sold by a cometitive market (which in the constant returns case would imly that the equilibrium rice must be c + t) creates an ine ciency for exactly the same reason Justifying Deadweight Loss Tringles Often times the distortion is quanti ed in a grah using the deadweight loss, which is illustrated for the case of a constant marginal cost in Figure 3. The intuitive idea is that the demand curve gives the willingness to ay for the marginal unit, the that the distance between the demand and the marginal cost curve gives the dollars lost for that unit not being roduced. To really make sense of this we d have to do more careful welfare analysis. However if utility is quasi-linear then it is rather easy to demonstrate that this is a valid way to roceed. Suose U(x; y) = x + v(y) and that the rice of good x is normalized to one. 9

10 a 6 Tc TT cc T c cc sloe b c T Pro t TT T sloe T TT c cc c b cc y MR T T c cc Demand c c - y Figure 3: The Deadweight Loss of a Monooly The roblem for a utility maximizing consumer is then s.t x + y m max x + v(y) Plugging in the constraint and otimizing we get the rst order condition v 0 (y) = This condition de nes the inverse demand function for y (as long as m is large enough so as to guarantee that the solution is interior), that is (y) = v 0 (y) Observe that v(y) v(0) = so since Z y v 0 (y)dy = Z y 0 0 (y)dy = Area under inverse demand; x + v(y) is the utility of consuming (x; y) m + v(0) is the utility of consuming x = m and y = 0 10

11 we have that the consumer is haier if consuming (x; y) than (m; 0) if and only if x + v(y) m + v(0), Area under inverse demand = v(y) v(0) m x Thus, the area under the inverse demand tells you how many units of the other good the consumer would be willing to give u for y units of good y if facing an all-or-nothing choice Price Discrimination The basic reason why a monooly (charging a uniform rice) is ine cient is that even though it would be bene cial for society, the monoolist doesn t want to increase outut since this would reduce the ro ts earned for all the units sold at the monooly rice. However, if: 1. The monoolist can make the rice contingent on quantity, and. Individualize rice/quantity o ers (in case of more than one consumer), then this trade-o disaears. This is illustrated in Figure 4 where the horizontal line indicates the (constant) marginal cost of roduction. If the market would be cometitive, then we know that the equilibrium rice would equal; the marginal cost and that there would be no distortion. The associated demands are given marginal cost ricing are given by y1; y; ::::; yn in the gure. The standard monooly analysis would be to add u all the demand curves and then set a rice so that the ro ts are maximized (given that the rice is the same for all customers and the same no matter how much each customer buys. However, let A i be the area under the demand curve in between 0 and yi for agent i and suose gives the following o er to each agent: Consumer 1 can ay A 1 and get y 1 or ay nothing and get nothing (and this is a non-negotiable o er) 11

12 y1 Consumer 1 y y Consumer y yn Consumer n - y Figure 4: Perfect Price Discrimination Consumer can ay A and get y or ay nothing and get nothing (and this is a non-negotiable o er) and so on for all consumers in the economy. All consumers would be willing to buy (strictly so if the monoolist sweetens the deal with a enny o )! Note, This is fully e cient! It is imossible to increase consumer surlus without reducing the ro t for the monoolist (which resumably has some owner or owners who would have to decrease the consumtion if the ro ts would be reduced). We say that the monoolist fully extracts the surlus from the consumers by using the individualized take it or leave it-o ers. The form of rice discrimination considered in this examle is referred to as erfect rice discrimination Is Perfect Price Discrimination Reasonable? Most economists would robably say that erfect rice-discrimination is unrealistic in most circumstances. There are several reasons for this. For examle: 1. The monoolist is assumed to know the demand function (that is know references) for each and every individual in the economy. While rms robably have a rather good idea about the aggregate demand, this seems rather unreasonable. 1

13 . Even if the monoolist could see who has what demand, the monoolist must somehow revent consumers from trading with each other. However, the imortant insight from the examle with refect rice discrimination is that when we think about a monoolist there is no a riori reason to restrict attention to trading mechanisms where the roducer sets a rice and customers decide how much to buy. Exlicitly introducing the considerations above (the reasons why erfect rice discrimination is not ossible) into the formal model of a ro t maximizing monoolist we can allow more clever ricing schemes than a xed er unit rice equal for all customers. Deending on details of the model we can then make sense of several ricing ractices that we do observe in the real world. For examle: 1. If the monoolist can not see which consumer is high demand and which is a low demand consumer, the monoolist can still cature some extra ro ts comared to a uniform rice by non-linear ricing, which means that the ricing scheme involves quantity discounts.. We can also make sense of student and senior citizen discounts by thinking of being a student/senior citizen as an imerfect measure of willingness to ay. 3. Sometimes the quantity dimension may be relaced by a quality dimension (think of demand for airline tickets) and here the same tye of logic that rationalizes non-linear ricing can be used to rationalize why airlines wants to make economy seats really crummy in order to make business travellers to self-select into exensive but nice seats with caviar and chamagne served Justi cations of the Standard Monooly Model Otional: Which roblem that is the more aroriate descrition of monooly ricing behavior deends on what may aear as tiny details. As just mentioned various forms of rice discrimination can be rationalized as ways to increase the ro ts for the monoolist: there are monooly ricing models that can 13

14 exlain student and senior citizen discounts, bundling (of for examle browsers and oerating systems), frequent yer rograms, how a monoolist can sometimes send extra money to make goods less useful, etc. 1 Becasuse of this lethora of models, it is of some interest to ask under what circumstances the standard model described in the beginning of the section makes sense. There are essentially two ways to justify that model: 1. Arbitrage ossibilities: if consumers can trade with each other, this makes it very hard to rice discriminate. As an examle, suose that the er unit rice would be decreasing in the number of units sold. Then, a single consumer has an incentive to buy a large quantity of the good (at a low rice er unit) and resell to consumers that are facing higher rices er unit if buying directly from the monoolist. Note: whether this is ossible or not deends on the good in question. Airline tickets, cable TV services, electricity are examles of non-transferable goods, and for these goods it is either imossible or very hard/costly for the consumers to do arbitrage.. Unit demands and uncertainty about references. One can then show that, if the monoolist cannot observe the references of the consumer, then the otimal ricing mechanism is alying the standard monooly ricing formula, where the demand function is given by D () = 1 F () = 1 Pr [v ] ; that is, F is the cumulative distribution over ossible valuations for the object A Durable Good Monoolist Many goods are durable: cars, refrigerators, light bulbs, art, comuters etc. all last for some time. This durability introduces some quite interesting issues concerning the market ower (or lack thereof) for a monoolist. Intuitively, the main ideas are as follows: Suose that some customers urchase the roduct at date t: The crucial observation is that, the customers that bought the roduct tend to be those with high valuations. 1 An examle of the last ractice was when the 486 chi was introduced. A cheaer, lower quality, variant, 486S, was also avaliable. This was roduced by taking a regular 486 chi and disabling certain functions. 14

15 But then, at date t + 1 the monoolist has an incentive to lower its rice to cature some ro t also from the customers with lower valuations. But then,..., the roblem is that all customers will look forward to the future decrease in rice, which erodes the monooly ower at date t: This is referred to as a time inconsistency roblem, which is similar to Birgittas dilemma in the battle of the sexes game discussed in game theory. If Birgitta could credibly commit to always go to the Oera, then she would get a higher ayo than in the backwards induction solution. Similarly, the durable good monoolist would do better if it could commit never to descrease its rice. The main result in the literature is that, if the monoolist can change its rice often enough, then almost all customers will ay a rice close to the marginal cost. That is, the cometition against future incarnations of itself makes the monooly ower go away almost comletely. This tye of analysis is too advanced for the scoe of this course. Instead, we will show something weaker: that the monooly ro t is always less than commitment to the static monooly rice in both eriods. This we can do in a model with only two eriods by alying the backwards induction rocedure reviously discussed Model 1. There are two eriods, indexed by t = 1;. Both consumers and the monoolist discounts future utility and ro ts resectively at a common discount factor < 1 3. Monoolist sells an indivisible good 4. The (direct) demand is given by D () = 1. For interretation, it is a good idea to think of D () as the robability that the valuation for the good is less than. 5. For simlicity, we let the constant marginal cost be c = 0: 15

16 Static Benchmark (Commitment) First consider the case where the monoolist commits to never changing the rice. Since consumers discount their utilities, nobody will then buy anything at time t = : The best (common) rice the monoolist can charge is then the solution to max (1 ) This roblem has solution = 1 ; and the associated quantity sold is q = D( ) = 1 = 1 ; so the monoolist makes a ro t = q = 1 4 if it somehow can romise never to change the rice in the future (we have not shown it, but this is actually the best the monoolist can do if it is able to commit to rices in both eriods before any sales are made) Selling in Both Periods (Non-Commitment) We will solve the roblem by alying the backwards induction rocedure that we discussed in the section on game theory. To imlement this, we must gure out what haens in the second eriod after any history of lay. A history can be described as either a quantity solved in the rst eriod or a rice. One can roceed either way, but I nd it somewhat easier to work with the quantity; Consider the second eriod, and assume that in the rst eriod the monoolist sold q 1 units. That means that customers with valuations above q 1 have left the market already, so the second eriod inverse demand (as a function of the arbitrary q 1 ) is D (; q 1 ) = 1 q 1 {z } New intercet q Second eriod roblem is thus max q q (1 q 1 q ) ; which has a solution (which deends on q 1 ) given by q (q 1 ) = (1 q 1) (q 1 ) = (1 q 1) : 16

17 The second eriod ro t is thus (q 1 ) = (1 q 1) Now, in the rst eriod a consumer with willingness to ay v will buy the roduct if 4 v 1 0 and v 1 (v ) The rice in the second eriod will be below the rice in the rst eriod, so we can ignore the rst inequality. Now, if q 1 is the quantity sold, it will be bought by the q 1 agents with the highest valuation, so the agents with valuation 1 q 1 v 1 are the ones that buy in the rst eriod, and (1 q 1 ) 1 = ((1 q 1 ) ) ; since the agent with valuation v = 1 q 1 must be indi erent between buying in eriod 1 and buying in eriod. But we know that when the monoolist re-otimizes in the second eriod, then so, the indi erence condition becomes (q 1 ) = (1 q 1) ; (1 q 1 ) 1 = ((1 q 1 ) (q 1 )) = (1 q 1 ) 1 q 1 1 = = (1 q 1) ) 1 (1 q 1 ): The rst eriod ro t maximization roblem for the monoolist is thus max q 1 (1 q 1 ) 1 q 1 + (1 q 1) ; 4 17

18 which gives rst order condition (1 q 1 ) 1 q 1 (1 q 1) = 0, = 1 = 1 q1 (1 ) = 4 3 Now, when we have the solution in terms of the rst eriod quantity we notice: 1. Previously, we exressed the second eriod rice, quantity sold and ro t as q (q 1 ) = 1 q 1 (q 1 ) = 1 q 1 1 q1 (q 1 ) = : By evaluating these exressions at q 1 we get the values that will be chosen after the best rst eriod choice as q = q (q 1) = 1 q 1 = 1 (1 ) 4 3 = (q1) = 1 q 1 = q = (q1) = 1 = 1 4 = (1 ) 4 3 = Next, we observe that the indi erence condition for buying in rst versus second eriod was 1 = so, the rice charged at eriod 1 is 1 = = 1 (1 q 1 ) (1 ) 1 (1 4 3 ) 4 3 (1 ) = ( ) (4 3) :

19 3. Hence, the discounted value of the monoolists ro t is (I write it as a function of as that is a key arameter) 4. Observe that that is: () = 1 + = 1q1 + q ( ) (1 ) = + 1 (4 3) 4 3 {z } {z } {z } q 1 1 = 1 [4 (1 ) + ] (0) = 1 4 = (1) = 1 1 [4 (1 1) + 1] = 1 1 [1] = ; when = 0; nobody cares about the next eriod so the roblem becomes like the static roblem when = 1; the monoolist charges ( 1) (4 3) = 1 (or higher) in the rst eriod, so nobody actually buys anything in the rst eriod. The second eriod is then just like the only eriod in the static model. For intermediate values of we have that 0 < < ; imlying that [4 (1 ) + ] = 4 3 ( ) 4 3 = < = 1 Hence () = 1 4 [4 (1 ) + ] < : That is, the otion to sell to those customers who don t buy at time 1 unambiguously hurts the monoolist. 19

20 Discussion The conclusion that not selling in the second eriod is better for the monoolist is often considered counter intuitive: exibility, which is often times considered valuable, is bad. The oint is that consumers are not going to be fooled. If the monoolist will do what is otimal in the second eriod, otential buyers will understand this, so the monoolist is better o if it can somehow commit not to change the rice in the second eriod even though the second eriod incentive obviously is to change the rice to sell more units. 0

c 2009 Je rey A. Miron 3. Examples: Linear Demand Curves and Monopoly

c 2009 Je rey A. Miron 3. Examples: Linear Demand Curves and Monopoly Lecture 0: Monooly. c 009 Je rey A. Miron Outline. Introduction. Maximizing Pro ts. Examles: Linear Demand Curves and Monooly. The Ine ciency of Monooly. The Deadweight Loss of Monooly. Price Discrimination.

More information

Economics 431 Fall 2003 2nd midterm Answer Key

Economics 431 Fall 2003 2nd midterm Answer Key Economics 431 Fall 2003 2nd midterm Answer Key 1) (20 oints) Big C cable comany has a local monooly in cable TV (good 1) and fast Internet (good 2). Assume that the marginal cost of roducing either good

More information

Price Elasticity of Demand MATH 104 and MATH 184 Mark Mac Lean (with assistance from Patrick Chan) 2011W

Price Elasticity of Demand MATH 104 and MATH 184 Mark Mac Lean (with assistance from Patrick Chan) 2011W Price Elasticity of Demand MATH 104 and MATH 184 Mark Mac Lean (with assistance from Patrick Chan) 2011W The rice elasticity of demand (which is often shortened to demand elasticity) is defined to be the

More information

A Simple Model of Pricing, Markups and Market. Power Under Demand Fluctuations

A Simple Model of Pricing, Markups and Market. Power Under Demand Fluctuations A Simle Model of Pricing, Markus and Market Power Under Demand Fluctuations Stanley S. Reynolds Deartment of Economics; University of Arizona; Tucson, AZ 85721 Bart J. Wilson Economic Science Laboratory;

More information

1 Gambler s Ruin Problem

1 Gambler s Ruin Problem Coyright c 2009 by Karl Sigman 1 Gambler s Ruin Problem Let N 2 be an integer and let 1 i N 1. Consider a gambler who starts with an initial fortune of $i and then on each successive gamble either wins

More information

Pythagorean Triples and Rational Points on the Unit Circle

Pythagorean Triples and Rational Points on the Unit Circle Pythagorean Triles and Rational Points on the Unit Circle Solutions Below are samle solutions to the roblems osed. You may find that your solutions are different in form and you may have found atterns

More information

Monopoly vs. Compe22on. Theory of the Firm. Causes of Monopoly. Monopoly vs. Compe22on. Monopolis2c Markets P. Natural. Legal.

Monopoly vs. Compe22on. Theory of the Firm. Causes of Monopoly. Monopoly vs. Compe22on. Monopolis2c Markets P. Natural. Legal. Monooly vs. Comeon Monooly Perfect Come,,on Theory of the Firm P Monooly s demand = Market demand (ΔQ P) P Firm s demand = Horizontal line ( Δ P does not change) Monoolisc Markets P d Q Monooly vs. Comeon

More information

c 2008 Je rey A. Miron We have described the constraints that a consumer faces, i.e., discussed the budget constraint.

c 2008 Je rey A. Miron We have described the constraints that a consumer faces, i.e., discussed the budget constraint. Lecture 2b: Utility c 2008 Je rey A. Miron Outline: 1. Introduction 2. Utility: A De nition 3. Monotonic Transformations 4. Cardinal Utility 5. Constructing a Utility Function 6. Examples of Utility Functions

More information

On Software Piracy when Piracy is Costly

On Software Piracy when Piracy is Costly Deartment of Economics Working aer No. 0309 htt://nt.fas.nus.edu.sg/ecs/ub/w/w0309.df n Software iracy when iracy is Costly Sougata oddar August 003 Abstract: The ervasiveness of the illegal coying of

More information

THE WELFARE IMPLICATIONS OF COSTLY MONITORING IN THE CREDIT MARKET: A NOTE

THE WELFARE IMPLICATIONS OF COSTLY MONITORING IN THE CREDIT MARKET: A NOTE The Economic Journal, 110 (Aril ), 576±580.. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, UK and 50 Main Street, Malden, MA 02148, USA. THE WELFARE IMPLICATIONS OF COSTLY MONITORING

More information

UNITED STATES OF AMERICA FEDERAL ENERGY REGULATORY COMMISSION

UNITED STATES OF AMERICA FEDERAL ENERGY REGULATORY COMMISSION UNITED STATES OF AMERICA FEDERAL ENERGY REGULATORY COMMISSION San Diego Gas & Electric Comany, ) EL00-95-075 Comlainant, ) ) v. ) ) ) Sellers of Energy and Ancillary Services ) Docket Nos. Into Markets

More information

Index Numbers OPTIONAL - II Mathematics for Commerce, Economics and Business INDEX NUMBERS

Index Numbers OPTIONAL - II Mathematics for Commerce, Economics and Business INDEX NUMBERS Index Numbers OPTIONAL - II 38 INDEX NUMBERS Of the imortant statistical devices and techniques, Index Numbers have today become one of the most widely used for judging the ulse of economy, although in

More information

How To Determine Rice Discrimination

How To Determine Rice Discrimination Price Discrimination in the Digital Economy Drew Fudenberg (Harvard University) J. Miguel Villas-Boas (University of California, Berkeley) May 2012 ABSTRACT With the develoments in information technology

More information

6.042/18.062J Mathematics for Computer Science December 12, 2006 Tom Leighton and Ronitt Rubinfeld. Random Walks

6.042/18.062J Mathematics for Computer Science December 12, 2006 Tom Leighton and Ronitt Rubinfeld. Random Walks 6.042/8.062J Mathematics for Comuter Science December 2, 2006 Tom Leighton and Ronitt Rubinfeld Lecture Notes Random Walks Gambler s Ruin Today we re going to talk about one-dimensional random walks. In

More information

Effect Sizes Based on Means

Effect Sizes Based on Means CHAPTER 4 Effect Sizes Based on Means Introduction Raw (unstardized) mean difference D Stardized mean difference, d g Resonse ratios INTRODUCTION When the studies reort means stard deviations, the referred

More information

I will make some additional remarks to my lecture on Monday. I think the main

I will make some additional remarks to my lecture on Monday. I think the main Jon Vislie; august 04 Hand out EON 4335 Economics of Banking Sulement to the the lecture on the Diamond Dybvig model I will make some additional remarks to my lecture on onday. I think the main results

More information

Joint Production and Financing Decisions: Modeling and Analysis

Joint Production and Financing Decisions: Modeling and Analysis Joint Production and Financing Decisions: Modeling and Analysis Xiaodong Xu John R. Birge Deartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208,

More information

Elasticity. I. What is Elasticity?

Elasticity. I. What is Elasticity? Elasticity I. What is Elasticity? The purpose of this section is to develop some general rules about elasticity, which may them be applied to the four different specific types of elasticity discussed in

More information

Re-Dispatch Approach for Congestion Relief in Deregulated Power Systems

Re-Dispatch Approach for Congestion Relief in Deregulated Power Systems Re-Disatch Aroach for Congestion Relief in Deregulated ower Systems Ch. Naga Raja Kumari #1, M. Anitha 2 #1, 2 Assistant rofessor, Det. of Electrical Engineering RVR & JC College of Engineering, Guntur-522019,

More information

Chapter 27: Taxation. 27.1: Introduction. 27.2: The Two Prices with a Tax. 27.2: The Pre-Tax Position

Chapter 27: Taxation. 27.1: Introduction. 27.2: The Two Prices with a Tax. 27.2: The Pre-Tax Position Chapter 27: Taxation 27.1: Introduction We consider the effect of taxation on some good on the market for that good. We ask the questions: who pays the tax? what effect does it have on the equilibrium

More information

Asymmetric Information, Transaction Cost, and. Externalities in Competitive Insurance Markets *

Asymmetric Information, Transaction Cost, and. Externalities in Competitive Insurance Markets * Asymmetric Information, Transaction Cost, and Externalities in Cometitive Insurance Markets * Jerry W. iu Deartment of Finance, University of Notre Dame, Notre Dame, IN 46556-5646 wliu@nd.edu Mark J. Browne

More information

Memory management. Chapter 4: Memory Management. Memory hierarchy. In an ideal world. Basic memory management. Fixed partitions: multiple programs

Memory management. Chapter 4: Memory Management. Memory hierarchy. In an ideal world. Basic memory management. Fixed partitions: multiple programs Memory management Chater : Memory Management Part : Mechanisms for Managing Memory asic management Swaing Virtual Page relacement algorithms Modeling age relacement algorithms Design issues for aging systems

More information

Working paper No: 23/2011 May 2011 LSE Health. Sotiris Vandoros, Katherine Grace Carman. Demand and Pricing of Preventative Health Care

Working paper No: 23/2011 May 2011 LSE Health. Sotiris Vandoros, Katherine Grace Carman. Demand and Pricing of Preventative Health Care Working aer o: 3/0 May 0 LSE Health Sotiris Vandoros, Katherine Grace Carman Demand and Pricing of Preventative Health Care Demand and Pricing of Preventative Healthcare Sotiris Vandoros, Katherine Grace

More information

Dynamics of Open Source Movements

Dynamics of Open Source Movements Dynamics of Oen Source Movements Susan Athey y and Glenn Ellison z January 2006 Abstract This aer considers a dynamic model of the evolution of oen source software rojects, focusing on the evolution of

More information

C-Bus Voltage Calculation

C-Bus Voltage Calculation D E S I G N E R N O T E S C-Bus Voltage Calculation Designer note number: 3-12-1256 Designer: Darren Snodgrass Contact Person: Darren Snodgrass Aroved: Date: Synosis: The guidelines used by installers

More information

price elasticity of demand; cross-price elasticity of demand; income elasticity of demand; price elasticity of supply.

price elasticity of demand; cross-price elasticity of demand; income elasticity of demand; price elasticity of supply. Unit 3: Elasticity In accorance with the APT rogramme the objective of the lecture is to hel You to comrehen an aly the concets of elasticity, incluing calculating: rice elasticity of eman; cross-rice

More information

Large firms and heterogeneity: the structure of trade and industry under oligopoly

Large firms and heterogeneity: the structure of trade and industry under oligopoly Large firms and heterogeneity: the structure of trade and industry under oligooly Eddy Bekkers University of Linz Joseh Francois University of Linz & CEPR (London) ABSTRACT: We develo a model of trade

More information

What is Adverse Selection. Economics of Information and Contracts Adverse Selection. Lemons Problem. Lemons Problem

What is Adverse Selection. Economics of Information and Contracts Adverse Selection. Lemons Problem. Lemons Problem What is Adverse Selection Economics of Information and Contracts Adverse Selection Levent Koçkesen Koç University In markets with erfect information all rofitable trades (those in which the value to the

More information

DEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES

DEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES ISSN 1471-0498 DEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES MARGINAL COST PRICING VERSUS INSURANCE Simon Cowan Number 102 May 2002 Manor Road Building, Oxford OX1 3UQ Marginal cost ricing versus insurance

More information

Pinhole Optics. OBJECTIVES To study the formation of an image without use of a lens.

Pinhole Optics. OBJECTIVES To study the formation of an image without use of a lens. Pinhole Otics Science, at bottom, is really anti-intellectual. It always distrusts ure reason and demands the roduction of the objective fact. H. L. Mencken (1880-1956) OBJECTIVES To study the formation

More information

Unit 3. Elasticity Learning objectives Questions for revision: 3.1. Price elasticity of demand

Unit 3. Elasticity Learning objectives Questions for revision: 3.1. Price elasticity of demand Unit 3. Elasticity Learning objectives To comrehen an aly the concets of elasticity, incluing calculating: rice elasticity of eman; cross-rice elasticity of eman; income elasticity of eman; rice elasticity

More information

An Introduction to Risk Parity Hossein Kazemi

An Introduction to Risk Parity Hossein Kazemi An Introduction to Risk Parity Hossein Kazemi In the aftermath of the financial crisis, investors and asset allocators have started the usual ritual of rethinking the way they aroached asset allocation

More information

Common sense, and the model that we have used, suggest that an increase in p means a decrease in demand, but this is not the only possibility.

Common sense, and the model that we have used, suggest that an increase in p means a decrease in demand, but this is not the only possibility. Lecture 6: Income and Substitution E ects c 2009 Je rey A. Miron Outline 1. Introduction 2. The Substitution E ect 3. The Income E ect 4. The Sign of the Substitution E ect 5. The Total Change in Demand

More information

Piracy and Network Externality An Analysis for the Monopolized Software Industry

Piracy and Network Externality An Analysis for the Monopolized Software Industry Piracy and Network Externality An Analysis for the Monoolized Software Industry Ming Chung Chang Deartment of Economics and Graduate Institute of Industrial Economics mcchang@mgt.ncu.edu.tw Chiu Fen Lin

More information

F inding the optimal, or value-maximizing, capital

F inding the optimal, or value-maximizing, capital Estimating Risk-Adjusted Costs of Financial Distress by Heitor Almeida, University of Illinois at Urbana-Chamaign, and Thomas Philion, New York University 1 F inding the otimal, or value-maximizing, caital

More information

Computational Finance The Martingale Measure and Pricing of Derivatives

Computational Finance The Martingale Measure and Pricing of Derivatives 1 The Martingale Measure 1 Comutational Finance The Martingale Measure and Pricing of Derivatives 1 The Martingale Measure The Martingale measure or the Risk Neutral robabilities are a fundamental concet

More information

IEEM 101: Inventory control

IEEM 101: Inventory control IEEM 101: Inventory control Outline of this series of lectures: 1. Definition of inventory. Examles of where inventory can imrove things in a system 3. Deterministic Inventory Models 3.1. Continuous review:

More information

Risk and Return. Sample chapter. e r t u i o p a s d f CHAPTER CONTENTS LEARNING OBJECTIVES. Chapter 7

Risk and Return. Sample chapter. e r t u i o p a s d f CHAPTER CONTENTS LEARNING OBJECTIVES. Chapter 7 Chater 7 Risk and Return LEARNING OBJECTIVES After studying this chater you should be able to: e r t u i o a s d f understand how return and risk are defined and measured understand the concet of risk

More information

Monopoly WHY MONOPOLIES ARISE

Monopoly WHY MONOPOLIES ARISE In this chapter, look for the answers to these questions: Why do monopolies arise? Why is MR < P for a monopolist? How do monopolies choose their P and Q? How do monopolies affect society s well-being?

More information

An important observation in supply chain management, known as the bullwhip effect,

An important observation in supply chain management, known as the bullwhip effect, Quantifying the Bullwhi Effect in a Simle Suly Chain: The Imact of Forecasting, Lead Times, and Information Frank Chen Zvi Drezner Jennifer K. Ryan David Simchi-Levi Decision Sciences Deartment, National

More information

The Online Freeze-tag Problem

The Online Freeze-tag Problem The Online Freeze-tag Problem Mikael Hammar, Bengt J. Nilsson, and Mia Persson Atus Technologies AB, IDEON, SE-3 70 Lund, Sweden mikael.hammar@atus.com School of Technology and Society, Malmö University,

More information

Complex Conjugation and Polynomial Factorization

Complex Conjugation and Polynomial Factorization Comlex Conjugation and Polynomial Factorization Dave L. Renfro Summer 2004 Central Michigan University I. The Remainder Theorem Let P (x) be a olynomial with comlex coe cients 1 and r be a comlex number.

More information

Synopsys RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Development FRANCE

Synopsys RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Development FRANCE RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Develoment FRANCE Synosys There is no doubt left about the benefit of electrication and subsequently

More information

Penalty Interest Rates, Universal Default, and the Common Pool Problem of Credit Card Debt

Penalty Interest Rates, Universal Default, and the Common Pool Problem of Credit Card Debt Penalty Interest Rates, Universal Default, and the Common Pool Problem of Credit Card Debt Lawrence M. Ausubel and Amanda E. Dawsey * February 2009 Preliminary and Incomlete Introduction It is now reasonably

More information

A joint initiative of Ludwig-Maximilians University s Center for Economic Studies and the Ifo Institute for Economic Research

A joint initiative of Ludwig-Maximilians University s Center for Economic Studies and the Ifo Institute for Economic Research A joint initiative of Ludwig-Maximilians University s Center for Economic Studies and the Ifo Institute for Economic Research Area Conference on Alied Microeconomics - 2 March 20 CESifo Conference Centre,

More information

The risk of using the Q heterogeneity estimator for software engineering experiments

The risk of using the Q heterogeneity estimator for software engineering experiments Dieste, O., Fernández, E., García-Martínez, R., Juristo, N. 11. The risk of using the Q heterogeneity estimator for software engineering exeriments. The risk of using the Q heterogeneity estimator for

More information

We are going to delve into some economics today. Specifically we are going to talk about production and returns to scale.

We are going to delve into some economics today. Specifically we are going to talk about production and returns to scale. Firms and Production We are going to delve into some economics today. Secifically we are going to talk aout roduction and returns to scale. firm - an organization that converts inuts such as laor, materials,

More information

A graphical introduction to the budget constraint and utility maximization

A graphical introduction to the budget constraint and utility maximization EC 35: ntermediate Microeconomics, Lecture 4 Economics 35: ntermediate Microeconomics Notes and Assignment Chater 4: tilit Maimization and Choice This chater discusses how consumers make consumtion decisions

More information

Point Location. Preprocess a planar, polygonal subdivision for point location queries. p = (18, 11)

Point Location. Preprocess a planar, polygonal subdivision for point location queries. p = (18, 11) Point Location Prerocess a lanar, olygonal subdivision for oint location ueries. = (18, 11) Inut is a subdivision S of comlexity n, say, number of edges. uild a data structure on S so that for a uery oint

More information

1 Present and Future Value

1 Present and Future Value Lecture 8: Asset Markets c 2009 Je rey A. Miron Outline:. Present and Future Value 2. Bonds 3. Taxes 4. Applications Present and Future Value In the discussion of the two-period model with borrowing and

More information

Compensating Fund Managers for Risk-Adjusted Performance

Compensating Fund Managers for Risk-Adjusted Performance Comensating Fund Managers for Risk-Adjusted Performance Thomas S. Coleman Æquilibrium Investments, Ltd. Laurence B. Siegel The Ford Foundation Journal of Alternative Investments Winter 1999 In contrast

More information

Large-Scale IP Traceback in High-Speed Internet: Practical Techniques and Theoretical Foundation

Large-Scale IP Traceback in High-Speed Internet: Practical Techniques and Theoretical Foundation Large-Scale IP Traceback in High-Seed Internet: Practical Techniques and Theoretical Foundation Jun Li Minho Sung Jun (Jim) Xu College of Comuting Georgia Institute of Technology {junli,mhsung,jx}@cc.gatech.edu

More information

CFRI 3,4. Zhengwei Wang PBC School of Finance, Tsinghua University, Beijing, China and SEBA, Beijing Normal University, Beijing, China

CFRI 3,4. Zhengwei Wang PBC School of Finance, Tsinghua University, Beijing, China and SEBA, Beijing Normal University, Beijing, China The current issue and full text archive of this journal is available at www.emeraldinsight.com/2044-1398.htm CFRI 3,4 322 constraints and cororate caital structure: a model Wuxiang Zhu School of Economics

More information

Chapter 15: Monopoly WHY MONOPOLIES ARISE HOW MONOPOLIES MAKE PRODUCTION AND PRICING DECISIONS

Chapter 15: Monopoly WHY MONOPOLIES ARISE HOW MONOPOLIES MAKE PRODUCTION AND PRICING DECISIONS Chapter 15: While a competitive firm is a taker, a monopoly firm is a maker. A firm is considered a monopoly if... it is the sole seller of its product. its product does not have close substitutes. The

More information

1 Monopoly Why Monopolies Arise? Monopoly is a rm that is the sole seller of a product without close substitutes. The fundamental cause of monopoly is barriers to entry: A monopoly remains the only seller

More information

Price C hange: Change: Income and Substitution Effects

Price C hange: Change: Income and Substitution Effects Price Change: Income and Substitution Effects THE IMPACT OF A PRICE CHANGE Economists often searate the imact of a rice change into two comonents: the substitution i effect; and the income effect. THE

More information

Managing specific risk in property portfolios

Managing specific risk in property portfolios Managing secific risk in roerty ortfolios Andrew Baum, PhD University of Reading, UK Peter Struemell OPC, London, UK Contact author: Andrew Baum Deartment of Real Estate and Planning University of Reading

More information

Measuring relative phase between two waveforms using an oscilloscope

Measuring relative phase between two waveforms using an oscilloscope Measuring relative hase between two waveforms using an oscilloscoe Overview There are a number of ways to measure the hase difference between two voltage waveforms using an oscilloscoe. This document covers

More information

Two-resource stochastic capacity planning employing a Bayesian methodology

Two-resource stochastic capacity planning employing a Bayesian methodology Journal of the Oerational Research Society (23) 54, 1198 128 r 23 Oerational Research Society Ltd. All rights reserved. 16-5682/3 $25. www.algrave-journals.com/jors Two-resource stochastic caacity lanning

More information

The fundamental question in economics is 2. Consumer Preferences

The fundamental question in economics is 2. Consumer Preferences A Theory of Consumer Behavior Preliminaries 1. Introduction The fundamental question in economics is 2. Consumer Preferences Given limited resources, how are goods and service allocated? 1 3. Indifference

More information

An optimal batch size for a JIT manufacturing system

An optimal batch size for a JIT manufacturing system Comuters & Industrial Engineering 4 (00) 17±136 www.elsevier.com/locate/dsw n otimal batch size for a JIT manufacturing system Lutfar R. Khan a, *, Ruhul. Sarker b a School of Communications and Informatics,

More information

An inventory control system for spare parts at a refinery: An empirical comparison of different reorder point methods

An inventory control system for spare parts at a refinery: An empirical comparison of different reorder point methods An inventory control system for sare arts at a refinery: An emirical comarison of different reorder oint methods Eric Porras a*, Rommert Dekker b a Instituto Tecnológico y de Estudios Sueriores de Monterrey,

More information

Pricing the Internet. Outline. The Size of the Internet (Cont.) The Size of the Internet

Pricing the Internet. Outline. The Size of the Internet (Cont.) The Size of the Internet Pricing the Internet Costas Courcoubetis thens University of Economics and Business and ICS-FORTH Outline The growth of the internet The role of ricing Some ricing roosals Pricing in a cometitive framework

More information

Machine Learning with Operational Costs

Machine Learning with Operational Costs Journal of Machine Learning Research 14 (2013) 1989-2028 Submitted 12/11; Revised 8/12; Published 7/13 Machine Learning with Oerational Costs Theja Tulabandhula Deartment of Electrical Engineering and

More information

EECS 122: Introduction to Communication Networks Homework 3 Solutions

EECS 122: Introduction to Communication Networks Homework 3 Solutions EECS 22: Introduction to Communication Networks Homework 3 Solutions Solution. a) We find out that one-layer subnetting does not work: indeed, 3 deartments need 5000 host addresses, so we need 3 bits (2

More information

Time-Cost Trade-Offs in Resource-Constraint Project Scheduling Problems with Overlapping Modes

Time-Cost Trade-Offs in Resource-Constraint Project Scheduling Problems with Overlapping Modes Time-Cost Trade-Offs in Resource-Constraint Proect Scheduling Problems with Overlaing Modes François Berthaut Robert Pellerin Nathalie Perrier Adnène Hai February 2011 CIRRELT-2011-10 Bureaux de Montréal

More information

Chapter 4 Online Appendix: The Mathematics of Utility Functions

Chapter 4 Online Appendix: The Mathematics of Utility Functions Chapter 4 Online Appendix: The Mathematics of Utility Functions We saw in the text that utility functions and indifference curves are different ways to represent a consumer s preferences. Calculus can

More information

http://www.ualberta.ca/~mlipsett/engm541/engm541.htm

http://www.ualberta.ca/~mlipsett/engm541/engm541.htm ENGM 670 & MECE 758 Modeling and Simulation of Engineering Systems (Advanced Toics) Winter 011 Lecture 9: Extra Material M.G. Lisett University of Alberta htt://www.ualberta.ca/~mlisett/engm541/engm541.htm

More information

On the predictive content of the PPI on CPI inflation: the case of Mexico

On the predictive content of the PPI on CPI inflation: the case of Mexico On the redictive content of the PPI on inflation: the case of Mexico José Sidaoui, Carlos Caistrán, Daniel Chiquiar and Manuel Ramos-Francia 1 1. Introduction It would be natural to exect that shocks to

More information

Risk Aversion. Expected value as a criterion for making decisions makes sense provided that C H A P T E R 2. 2.1 Risk Attitude

Risk Aversion. Expected value as a criterion for making decisions makes sense provided that C H A P T E R 2. 2.1 Risk Attitude C H A P T E R 2 Risk Aversion Expected value as a criterion for making decisions makes sense provided that the stakes at risk in the decision are small enough to \play the long run averages." The range

More information

POISSON PROCESSES. Chapter 2. 2.1 Introduction. 2.1.1 Arrival processes

POISSON PROCESSES. Chapter 2. 2.1 Introduction. 2.1.1 Arrival processes Chater 2 POISSON PROCESSES 2.1 Introduction A Poisson rocess is a simle and widely used stochastic rocess for modeling the times at which arrivals enter a system. It is in many ways the continuous-time

More information

Reference Pricing with Endogenous Generic Entry

Reference Pricing with Endogenous Generic Entry Reference Pricing with Endogenous Generic Entry Kurt R. Brekke, Chiara Canta, Odd Rune Straume Aril 18, 2016 Abstract Reference ricing intends to reduce harmaceutical exenditures by increasing demand elasticity

More information

Econ 101: Principles of Microeconomics

Econ 101: Principles of Microeconomics Econ 101: Principles of Microeconomics Chapter 14 - Monopoly Fall 2010 Herriges (ISU) Ch. 14 Monopoly Fall 2010 1 / 35 Outline 1 Monopolies What Monopolies Do 2 Profit Maximization for the Monopolist 3

More information

ECON 600 Lecture 5: Market Structure - Monopoly. Monopoly: a firm that is the only seller of a good or service with no close substitutes.

ECON 600 Lecture 5: Market Structure - Monopoly. Monopoly: a firm that is the only seller of a good or service with no close substitutes. I. The Definition of Monopoly ECON 600 Lecture 5: Market Structure - Monopoly Monopoly: a firm that is the only seller of a good or service with no close substitutes. This definition is abstract, just

More information

The Behavioral Economics of Insurance

The Behavioral Economics of Insurance DEPARTMENT OF ECONOMICS The Behavioral Economics of Insurance Ali al-nowaihi, University of Leicester, UK Sanjit Dhami, University of Leicester, UK Working Paer No. 0/2 Udated Aril 200 The Behavioral Economics

More information

DAY-AHEAD ELECTRICITY PRICE FORECASTING BASED ON TIME SERIES MODELS: A COMPARISON

DAY-AHEAD ELECTRICITY PRICE FORECASTING BASED ON TIME SERIES MODELS: A COMPARISON DAY-AHEAD ELECTRICITY PRICE FORECASTING BASED ON TIME SERIES MODELS: A COMPARISON Rosario Esínola, Javier Contreras, Francisco J. Nogales and Antonio J. Conejo E.T.S. de Ingenieros Industriales, Universidad

More information

ECON 103, 2008-2 ANSWERS TO HOME WORK ASSIGNMENTS

ECON 103, 2008-2 ANSWERS TO HOME WORK ASSIGNMENTS ECON 103, 2008-2 ANSWERS TO HOME WORK ASSIGNMENTS Due the Week of June 23 Chapter 8 WRITE [4] Use the demand schedule that follows to calculate total revenue and marginal revenue at each quantity. Plot

More information

Multiperiod Portfolio Optimization with General Transaction Costs

Multiperiod Portfolio Optimization with General Transaction Costs Multieriod Portfolio Otimization with General Transaction Costs Victor DeMiguel Deartment of Management Science and Oerations, London Business School, London NW1 4SA, UK, avmiguel@london.edu Xiaoling Mei

More information

Comparing Dissimilarity Measures for Symbolic Data Analysis

Comparing Dissimilarity Measures for Symbolic Data Analysis Comaring Dissimilarity Measures for Symbolic Data Analysis Donato MALERBA, Floriana ESPOSITO, Vincenzo GIOVIALE and Valentina TAMMA Diartimento di Informatica, University of Bari Via Orabona 4 76 Bari,

More information

The Cubic Formula. The quadratic formula tells us the roots of a quadratic polynomial, a polynomial of the form ax 2 + bx + c. The roots (if b 2 b+

The Cubic Formula. The quadratic formula tells us the roots of a quadratic polynomial, a polynomial of the form ax 2 + bx + c. The roots (if b 2 b+ The Cubic Formula The quadratic formula tells us the roots of a quadratic olynomial, a olynomial of the form ax + bx + c. The roots (if b b+ 4ac 0) are b 4ac a and b b 4ac a. The cubic formula tells us

More information

Principles of Hydrology. Hydrograph components include rising limb, recession limb, peak, direct runoff, and baseflow.

Principles of Hydrology. Hydrograph components include rising limb, recession limb, peak, direct runoff, and baseflow. Princiles of Hydrology Unit Hydrograh Runoff hydrograh usually consists of a fairly regular lower ortion that changes slowly throughout the year and a raidly fluctuating comonent that reresents the immediate

More information

The Magnus-Derek Game

The Magnus-Derek Game The Magnus-Derek Game Z. Nedev S. Muthukrishnan Abstract We introduce a new combinatorial game between two layers: Magnus and Derek. Initially, a token is laced at osition 0 on a round table with n ositions.

More information

Examples on Monopoly and Third Degree Price Discrimination

Examples on Monopoly and Third Degree Price Discrimination 1 Examples on Monopoly and Third Degree Price Discrimination This hand out contains two different parts. In the first, there are examples concerning the profit maximizing strategy for a firm with market

More information

Cash-in-the-Market Pricing and Optimal Bank Bailout Policy 1

Cash-in-the-Market Pricing and Optimal Bank Bailout Policy 1 Cash-in-the-Maret Pricing and Otimal Ban Bailout Policy 1 Viral V. Acharya 2 London Business School and CEPR Tanju Yorulmazer 3 Ban of England J.E.L. Classification: G21, G28, G38, E58, D62. Keywords:

More information

Assignment 9; Due Friday, March 17

Assignment 9; Due Friday, March 17 Assignment 9; Due Friday, March 17 24.4b: A icture of this set is shown below. Note that the set only contains oints on the lines; internal oints are missing. Below are choices for U and V. Notice that

More information

Pricing I: Linear Demand

Pricing I: Linear Demand Pricing I: Linear Demand This module covers the relationships between price and quantity, maximum willing to buy, maximum reservation price, profit maximizing price, and price elasticity, assuming a linear

More information

Double Integrals in Polar Coordinates

Double Integrals in Polar Coordinates Double Integrals in Polar Coorinates Part : The Area Di erential in Polar Coorinates We can also aly the change of variable formula to the olar coorinate transformation x = r cos () ; y = r sin () However,

More information

Monitoring Frequency of Change By Li Qin

Monitoring Frequency of Change By Li Qin Monitoring Frequency of Change By Li Qin Abstract Control charts are widely used in rocess monitoring roblems. This aer gives a brief review of control charts for monitoring a roortion and some initial

More information

X How to Schedule a Cascade in an Arbitrary Graph

X How to Schedule a Cascade in an Arbitrary Graph X How to Schedule a Cascade in an Arbitrary Grah Flavio Chierichetti, Cornell University Jon Kleinberg, Cornell University Alessandro Panconesi, Saienza University When individuals in a social network

More information

Normally Distributed Data. A mean with a normal value Test of Hypothesis Sign Test Paired observations within a single patient group

Normally Distributed Data. A mean with a normal value Test of Hypothesis Sign Test Paired observations within a single patient group ANALYSIS OF CONTINUOUS VARIABLES / 31 CHAPTER SIX ANALYSIS OF CONTINUOUS VARIABLES: COMPARING MEANS In the last chater, we addressed the analysis of discrete variables. Much of the statistical analysis

More information

Interbank Market and Central Bank Policy

Interbank Market and Central Bank Policy Federal Reserve Bank of New York Staff Reorts Interbank Market and Central Bank Policy Jung-Hyun Ahn Vincent Bignon Régis Breton Antoine Martin Staff Reort No. 763 January 206 This aer resents reliminary

More information

Storage Basics Architecting the Storage Supplemental Handout

Storage Basics Architecting the Storage Supplemental Handout Storage Basics Architecting the Storage Sulemental Handout INTRODUCTION With digital data growing at an exonential rate it has become a requirement for the modern business to store data and analyze it

More information

1 Maximizing pro ts when marginal costs are increasing

1 Maximizing pro ts when marginal costs are increasing BEE12 Basic Mathematical Economics Week 1, Lecture Tuesda 12.1. Pro t maimization 1 Maimizing pro ts when marginal costs are increasing We consider in this section a rm in a perfectl competitive market

More information

The Competitiveness Impacts of Climate Change Mitigation Policies

The Competitiveness Impacts of Climate Change Mitigation Policies The Cometitiveness Imacts of Climate Change Mitigation Policies Joseh E. Aldy William A. Pizer 2011 RPP-2011-08 Regulatory Policy Program Mossavar-Rahmani Center for Business and Government Harvard Kennedy

More information

Chapter 14 Monopoly. 14.1 Monopoly and How It Arises

Chapter 14 Monopoly. 14.1 Monopoly and How It Arises Chapter 14 Monopoly 14.1 Monopoly and How It Arises 1) One of the requirements for a monopoly is that A) products are high priced. B) there are several close substitutes for the product. C) there is a

More information

Chapter 3. The Concept of Elasticity and Consumer and Producer Surplus. Chapter Objectives. Chapter Outline

Chapter 3. The Concept of Elasticity and Consumer and Producer Surplus. Chapter Objectives. Chapter Outline Chapter 3 The Concept of Elasticity and Consumer and roducer Surplus Chapter Objectives After reading this chapter you should be able to Understand that elasticity, the responsiveness of quantity to changes

More information

INDIVIDUAL WELFARE MAXIMIZATION IN ELECTRICITY MARKETS INCLUDING CONSUMER AND FULL TRANSMISSION SYSTEM MODELING JAMES DANIEL WEBER

INDIVIDUAL WELFARE MAXIMIZATION IN ELECTRICITY MARKETS INCLUDING CONSUMER AND FULL TRANSMISSION SYSTEM MODELING JAMES DANIEL WEBER INDIVIDUAL WELFARE MAXIMIZATION IN ELECTRICITY MARKETS INCLUDING CONSUMER AND FULL TRANSMISSION SYSTEM MODELING BY JAMES DANIEL WEBER BS, University of Wisconsin - Platteville, 1995 MS, University of Illinois

More information

Branch-and-Price for Service Network Design with Asset Management Constraints

Branch-and-Price for Service Network Design with Asset Management Constraints Branch-and-Price for Servicee Network Design with Asset Management Constraints Jardar Andersen Roar Grønhaug Mariellee Christiansen Teodor Gabriel Crainic December 2007 CIRRELT-2007-55 Branch-and-Price

More information

More Properties of Limits: Order of Operations

More Properties of Limits: Order of Operations math 30 day 5: calculating its 6 More Proerties of Limits: Order of Oerations THEOREM 45 (Order of Oerations, Continued) Assume that!a f () L and that m and n are ositive integers Then 5 (Power)!a [ f

More information