EconS 503 Homework #8. Answer Key

Size: px
Start display at page:

Download "EconS 503 Homework #8. Answer Key"

Transcription

1 EonS 503 Homework #8 Answer Key Exerise #1 Damaged good strategy (Menu riing) 1. It is immediate that otimal rie is = 3 whih yields rofits of ππ = 3/ (the alternative being a rie of = 1, yielding ππ = 1).. The damaged version is sold to the low-valuation onsumers and the normal version to the high-valuation onsumers. Hene, dddddddddddddd = 5/10. To satisfy the inentive onstraint of the high tye, nnnnnnnnnnnn must be hosen suh that 6 10 dddddddddddddd = 1 10 = 3 nnnnnnnnnnnn or, equivalently, nnnnnnnnnnnn = 9/10, whih is less than 3. This results in rofits of (1/)(5/10 1/10) + (1/ )(9/10) = 33/0 > 3/. 3. Hene, the firm makes a higher rofit by introduing the damages version in site of the higher ost of rodution for this version. The high-valuation onsumers are also better off when the damages version is introdued, as they fae a lower rie. Finally, the lowvaluation onsumers obtain zero utility in both ases. The introdution of the damaged version thus results in a Pareto imrovement. Exerise # - Nonlinear riing 1. The monooly hoses to maximize ππ = ( )(1 ). The rofit-maximizing rie is easily found as UU = 1+. The orresonding rofit is ππuu = (1 ). 4. Faing a tariff (mm, ), the artiiation onstraint of a onsumer is CCCC() mm 0, where CCCC() is the onsumer surlus rie. With demand QQ() = 1, we have CCCC() = (1 ). As the monoolist s best interest is to set mm = CCCC(), its roblem is thus to set so as to maximize ππ = CCCC() + ( )(1 ) = 1 (1 )(1 + ). The first-order ondition yields = 0. Hene, the otimal two-art tariff is (mm, ) = (1 ),. The otimal two-art tariff onsists of selling the good at marginal ost, so as to generate the largest onsumer surlus, and in aturing this surlus fully through the fixed fee. The orresonding rofit is ππ TT PP = mm = (1 ). Welfare is maximized under the two-art tariff as it involves marginal ost riing (whereas uniform riing results in a deadweight loss).

2 3. Consumer surlus for agents of tye at any rie is omuted as CCSS () = ( ) 4. We reall from art () of the exerise that CCSS 1 () = (1 ) for any 1. For any rie where the two tyes of onsumer buy (i.e., 1), we hek that CCSS () CCSS 1 (). One otion for the monoolist is to make sure that onsumers of both tyes buy; for this, mm = CCSS 1 () and 1. We then have the same roblem as in art (), with = 1 : (mm, ) = 1, 1 and ππ 8 1 = 1. The alternative otion is to sell only to tye- 8 onsumers with mm = CCSS () and. The monoolist s roblem is then to hoose to maximize ππ = (1/) ( ) + ( 1/)(1 /). 4 The first-order ondition yields = 1/. As = 1/ (i.e., marginal ost riing violates the onstraint), the monoolist hooses a rie of = 1, so that mm = 1/4. The resulting rofit is ππ = 1 1 = 1. Therefore, ππ 4 > ππ 1, imlying that the monoolist refers to sell to tye- onsumers only by setting a rie above marginal ost. Homework #3 Moral Hazard a) The ontrat seifies the ayment ww ss you reeive when you deliver the beer, and the ayment ww FF you reeive when you do not deliver the beer. The two inequalities are the inentive omatibility onstraint and your friend s individual rationality onstraint: 0.9( ee 0.ww SS) + 0.1( ee 0.ww FF) ee 0.(ww FF+5) 0.8(8 ww SS ) + 0.1( ww FF ) 3 (IC) (IR) The solution to these equations (when they hold with equality) is ww SS = 4.81 and ww FF = 1.5. b) The two inequalities are the inentive omatibility onstraint and your own individual rationality onstraint: 0.9( ee 0.ww SS) + 0.1( ee 0.ww FF) ee 0.(ww FF+5) 0.9( ee 0.ww SS) + 0.1( ee 0.ww FF) 1 (IC) (IR) We make these equalities, and solve the two equations. The two imly that ee.(ww FF+5) = 1, and so (taking logs 0. (ww FF + 5) = 0. Hene, ww FF = 5. From (IR), 0.9( ee 0.ww SS) ee 0.( 5) = 1

3 ee 0.ww SS = 1 0.1ee = ww SS = log(0.809) = 0.1 ww SS = 1.06 In the first-best ontrat, it is observable whether the beer is drunken or onfisated, and so that agreement an require that the beer is delivered. The ayment is onstant beause the risk-neutral arty should bear all the risk. The ayment is the solution to your individual rationality onstraint: ee 0.(ww) = 1. Hene, w = 0. Your utility is -1 in both the first-best and seond-best ontrats, beause it is assumed here that your friend gets all the gains from trade. Your friend s utility is higher for the first-best than for the seond-best agreements: Case Utility 1st-best 0.9 (8) +0.1 (0) = (8-1.06) (0 - ( -5)) = nd-best 6.75

4 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD 44 Maximizing with reset to R(x) for every ositive x leads to the following rst order 1 = (x) u 0 (W 0 + R (x) x) = (a) for 8x > (0) = 0, 1 u 0 (W 0 + R (0)) = 1 0 (a) 1 (a) where we assumed that (a) never equals to 0 or 1. In other words, we assume that it is extremely ostly for the agent to ensure there will be no loss whatsoever, but extremely hea to make sure that the loss does not our with robability 1. Given the ositive Lagrange multiliers and 0 (a) < 0, we nd for 8x > 0 1 u 0 (W 0 + R (0)) > 1 > 1 u 0 (W 0 + R (x) x), R (0) > R (x) x: So the otimal ontrat is suh that the insuree is unished when a loss ours, but the unishment is not related to the size of the loss x sine the robability of a larger loss is indeendent of the agent s e ort. Therefore, the seond-best ontrat will indue variation in the insuree s ayo only between 0 and x > 0. The exat shae of the ontrat will be fully determined by the rst order ondition with reset to e ort and the zero-ro t ondition. 4.3 Question 1 Consider a rinial-agent roblem with three exogenous states of nature, 1 ; ; and 3 ; two e ort levels, a L and a H ; and two outut levels, distributed as follows as a funtion of the state of nature and the e ort level: State of nature 1 3 Probability 0:5 0:5 0:5 Outut under a H Outut under a L The rinial is risk neutral while the agent has utility funtion w when reeiving monetary omensation w, minus the ost of e ort, whih is normalized to 0 for a L and to 0.1 for a H. The agent s reservation exeted utility is Derive the rst-best ontrat.. Derive the seond-best ontrat when only outut levels are observable. 3. Assume the rinial an buy for a rie of 0.1 an information system that allows the arties to verify whether state of nature 3 haened or not. Will the rinial buy this information system? Disuss.

5 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD First-Best Contrat The robabilities are as follows: Pr (q = 18ja H ) = 0:75 Pr (q = 18ja L ) = 0:5: Thus, when the rinial an ontrat on the level of e ort, he will solve max 0:5q(a i; 1 ) + 0:5q(a i ; ) + 0:5q(a i ; 3 ) a i;w w subjet to w (ai ) 0:1 Under ation hoie a H, w H 0:1 = 0:1 ) w H = 0:04: Therefore, E P (a H ) = 18 (0:75) + 1 (0:5) 0:04 = 13:71: Under ation hoie a L, w L = 0:1 ) wl = 0:01: Therefore, E P (a L ) = 18 (0:5) + 1 (0:75) 0:01 = 5:4: Thus, the otimal ontrat sei es a = a H and w = 0: Seond-Best Contrat When only outut levels are observable, the otimal ontrat to indue the e ort level a H solves a minimization of the wage bill, subjet to min w 18;w 1 0:75w :5w 1 0:75 w :5 w 1 0:1 0:1 (IR) 0:75 w :5 w 1 0:1 0:5 w :75 w 1. (IC) We an rove that in the two outomes/two ations ase both (IR) and (IC) must be binding at the otimum. If (IR) is not binding, the exeted wage bill an be dereased by lowering w 1 whereas the (IC) will even be relaxed. If (IC) is not binding, but the (IR) is, then we an derease w 18 and inrease w 1 suh that the (IR) is still binding. In artiular, given w1 dw 1 = 3, dw 18 w18

6 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD 46 this would hange the exeted wage bill by w1 0:75dw :5( 3 )dw 18 : w18 By (IC), we have w 1 < w 18. Therefore, a derease in w 18 leads to a negative hange in the wage bill, 0:75(1 r w1 w 18 )dw 18 < 0 With the binding restritions (IR) and (IC), it is easy to nd the otimal wage shedule w 1 = 0:005 w 18 = 0:065: Note that the limited liability onstraint imlied by the utility funtion w is not binding here. The exeted utility of the rinial is E P (a H ) = 13:75 0:065 0:75 0:005 0:5 = 13:705: So the exeted ro t of induing a H is greater than the exeted ro t of induing a L, regardless of whether the e ort level is observable or not Information System For this sei rie the answer is trivially no. The rinial is not willing to buy the information system, beause even with erfet information the highest ro t he an attain is 13:71. Therefore, the maximal gain of using the information system will always be smaller than the ost of imlementing the system, 13:71 13:705 = 0:0075 < 0:1: We now nd the ro ts the rinial an make when state 3 an be observed. Then we an nd for whih rie the rinial would be willing to ay for the information system. Let us denote by y the signal that takes the value 1 when 3 is realized and the value 0 otherwise. If y = 1, the rinial an still not identify the e ort level being exerted. However, when y = 0, only the low e ort level an lead to an outut level of 1. So by enalizing the agent in nitely when q = 1 and y = 0, the rst-best an be attained. Indeed, the agent will hoose the high e ort level to be sure to avoid the unishment. Given that no variation in reeived inome is needed, the high e ort an be imlemented at the lowest ost. However, given the liability onstraint imlied by the utility funtion, the rinial is restrited to ositive levels of omensation. Hene, the rinial will ay w 1 = 0 when the outut is 1 and the signal is 0: In addition, w 18 and w 3, the wages aid when q = 18 and y = 1; q = 1 resetively, are set to solve min w 18;w 3 0:75w :5w 3

7 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD 47 subjet to 0:75 w :5 w 3 0:1 0:1 (IR) 0:75 w :5 w 3 0:1 0:5 w :75 3 w w3. (IC) 3 The inentive omatibility onstraint is binding and simli es to Hene, and 0:75 w 18 0:1 = 0:5 w 18 : w 18 = 0:04: 0: 0:75 0: w 3 = = 0:04: 0:5 So the rst-best an be ahieved by the ontrat w 18 = w 3 = 0:04 and w 1 = 0. Finally, from the alulation above, the rinial will imlement the information system if the ost falls below 0: Question 13 Consider the modi ed linear managerial-inentive-sheme roblem, where the manager s e ort, a a ets urrent ro ts, q 1 = a + " q1, and future ro ts, q = a+" q, where " qt are i.i.d. with normal distribution N(0; q). The manager retires at the end of the rst eriod, and the manager s omensation annot be based on q. However, her omensation an deend on the stok rie P = a + " P, where " P N(0; P ). Derive the otimal omensation ontrat t = w + fq 1 + sp. Disuss how it deends on P and on its relation with q. Comare your solution with that in the Chater CEO Comensation Note that this question uses notation that is not onsistent with the exosition in setion The rogram for this roblem is the following, max a;w;f;s E (q 1 + q t) subjet to E e [t (a)] e t (IR) a arg max E e [t (ba)] (IC) ba t = w + fq 1 + sp

8 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD 48, subjet to max a a;w;f;s (w + fa + sa) w + fa + sa f q + s P + sf qp a t a arg max w + fba + sba ba f q + s P + sf qp ba : We an aly the rst-order aroah and substitute the rst order ondition a = f + s for the inentive omatibility onstraint. Introduing this e ient level of e ort and substituting the outside oortunity level lus the risk remium lus the ost of e ort for the wage, we obtain max f;s + s f f q + s (f + s) P + sf qp t: The rst order onditions with reset to f and s are resetively 4 f q + s qp s P + f qp After some rewriting, the equations beome f + s f + s = 0 = 0: and we nally nd f = s ( + qp ) 1 + q f = s ( + P 1 + qp ), f = s = q + P q + P P qp qp + ( P q qp ) q qp qp + ( P q qp ): 4.4. Comarison Comared to the examle in Chater 4, the imortane of the agent s e ort has doubled for the rinial. Among the ontratible variables, only the imat of a hange in e ort on the stok rie has doubled. Although the agent s e ort

9 CHAPTER 4. HIDDEN ACTION, MORAL HAZARD 49 now determines the outut in two eriods, the outut in the seond eriod is not ontratible. The stok rie therefore beomes a more reise indiator of e ort than the ontratible outut. If we onsider the relative size of the inentives at the otimum f s = P q qp qp and omare this to the equivalent ratio in Chater 4 1 f qp s = P, q qp we notie that the rinial uts relatively more weight on the stok ries. This weight is exatly double when both indiators are indeendent, qp = Question 14 Consider the following rinial-agent roblem. There is a rojet whose robability of suess is a (a is also the e ort made by the risk-neutral agent, at ost a ). In ase of suess the return is R, and in ase of failure the return is 0. The arameter R an take two values, X with robability and 1 with robability 1. To undertake the rojet, the agent needs to borrow an amount I from the rinial. The sequene of events is as follows: First, the rinial o ers the agent a debt ontrat, with fae value D 0. The agent aets or rejets this ontrat. Seond, nature determines the value R that would our in ase of suess. This value is observed by both rinial and agent. The rinial an then hoose to lower the debt from D 0 to D 1. The agent hooses a level of e ort a. This level is not observed by the rinial. The rojet sueeds or not. If the rojet sueeds, the agent ays the minimum of R and the fae value of debt D 1. Answer the following questions: 1. Comute the subgame-erfet equilibrium of this game as a funtion of I,, and X:. When do we have D 1 < D 0? Disuss. 1 In setion f and s and w and t are interhanged.

2.2 BUDGET-CONSTRAINED CHOICE WITH TWO COMMODITIES

2.2 BUDGET-CONSTRAINED CHOICE WITH TWO COMMODITIES Essential Miroeonomis -- 22 BUDGET-CONSTRAINED CHOICE WITH TWO COMMODITIES Continuity of demand 2 Inome effets 6 Quasi-linear, Cobb-Douglas and CES referenes 9 Eenditure funtion 4 Substitution effets and

More information

Panos Kouvelis Olin School of Business Washington University

Panos Kouvelis Olin School of Business Washington University Quality-Based Cometition, Profitability, and Variable Costs Chester Chambers Co Shool of Business Dallas, TX 7575 hamber@mailosmuedu -768-35 Panos Kouvelis Olin Shool of Business Washington University

More information

Product Policy in Markets with Word-of-Mouth Communication. Technical Appendix

Product Policy in Markets with Word-of-Mouth Communication. Technical Appendix rodut oliy in Markets with Word-of-Mouth Communiation Tehnial Appendix August 05 Miro-Model for Inreasing Awareness In the paper, we make the assumption that awareness is inreasing in ustomer type. I.e.,

More information

NONLINEAR MODEL: CELL FORMATION

NONLINEAR MODEL: CELL FORMATION ational Institute of Tehnology Caliut Deartment of Mehanial Engineering OLIEAR MODEL: CELL FORMATIO System Requirements and Symbols 0-Integer Programming Formulation α i - umber of interell transfers due

More information

Solutions to Problem Set 1

Solutions to Problem Set 1 Eon602: Maro Theory Eonomis, HKU Instrutor: Dr. Yulei Luo September 208 Solutions to Problem Set. [0 points] Consider the following lifetime optimal onsumption-saving problem: v (a 0 ) max f;a t+ g t t

More information

EE451/551: Digital Control. Relationship Between s and z Planes. The Relationship Between s and z Planes 11/10/2011

EE451/551: Digital Control. Relationship Between s and z Planes. The Relationship Between s and z Planes 11/10/2011 /0/0 EE45/55: Digital Control Chater 6: Digital Control System Design he Relationshi Between s and Planes As noted reviously: s j e e e e r s j where r e and If an analog system has oles at: s n jn a jd

More information

Microeconomic Theory I Assignment #7 - Answer key

Microeconomic Theory I Assignment #7 - Answer key Miroeonomi Theory I Assignment #7 - Answer key. [Menu priing in monopoly] Consider the example on seond-degree prie disrimination (see slides 9-93). To failitate your alulations, assume H = 5, L =, and

More information

CSC321: 2011 Introduction to Neural Networks and Machine Learning. Lecture 10: The Bayesian way to fit models. Geoffrey Hinton

CSC321: 2011 Introduction to Neural Networks and Machine Learning. Lecture 10: The Bayesian way to fit models. Geoffrey Hinton CSC31: 011 Introdution to Neural Networks and Mahine Learning Leture 10: The Bayesian way to fit models Geoffrey Hinton The Bayesian framework The Bayesian framework assumes that we always have a rior

More information

Methods of evaluating tests

Methods of evaluating tests Methods of evaluating tests Let X,, 1 Xn be i.i.d. Bernoulli( p ). Then 5 j= 1 j ( 5, ) T = X Binomial p. We test 1 H : p vs. 1 1 H : p>. We saw that a LRT is 1 if t k* φ ( x ) =. otherwise (t is the observed

More information

CONSTRUCTION OF MIXED SAMPLING PLAN WITH DOUBLE SAMPLING PLAN AS ATTRIBUTE PLAN INDEXED THROUGH (MAPD, MAAOQ) AND (MAPD, AOQL)

CONSTRUCTION OF MIXED SAMPLING PLAN WITH DOUBLE SAMPLING PLAN AS ATTRIBUTE PLAN INDEXED THROUGH (MAPD, MAAOQ) AND (MAPD, AOQL) Global J. of Arts & Mgmt., 0: () Researh Paer: Samath kumar et al., 0: P.07- CONSTRUCTION OF MIXED SAMPLING PLAN WITH DOUBLE SAMPLING PLAN AS ATTRIBUTE PLAN INDEXED THROUGH (MAPD, MAAOQ) AND (MAPD, AOQL)

More information

On the Licensing of Innovations under Strategic Delegation

On the Licensing of Innovations under Strategic Delegation On the Liensing of Innovations under Strategi Delegation Judy Hsu Institute of Finanial Management Nanhua University Taiwan and X. Henry Wang Department of Eonomis University of Missouri USA Abstrat This

More information

Risk Analysis in Water Quality Problems. Souza, Raimundo 1 Chagas, Patrícia 2 1,2 Departamento de Engenharia Hidráulica e Ambiental

Risk Analysis in Water Quality Problems. Souza, Raimundo 1 Chagas, Patrícia 2 1,2 Departamento de Engenharia Hidráulica e Ambiental Risk Analysis in Water Quality Problems. Downloaded from aselibrary.org by Uf - Universidade Federal Do Ceara on 1/29/14. Coyright ASCE. For ersonal use only; all rights reserved. Souza, Raimundo 1 Chagas,

More information

CSC321: 2011 Introduction to Neural Networks and Machine Learning. Lecture 11: Bayesian learning continued. Geoffrey Hinton

CSC321: 2011 Introduction to Neural Networks and Machine Learning. Lecture 11: Bayesian learning continued. Geoffrey Hinton CSC31: 011 Introdution to Neural Networks and Mahine Learning Leture 11: Bayesian learning ontinued Geoffrey Hinton Bayes Theorem, Prior robability of weight vetor Posterior robability of weight vetor

More information

Honest Agents in a Corrupt Equilibrium *

Honest Agents in a Corrupt Equilibrium * Honest Agents in a Corrut Equilibrium * ALEX HENKE Deartment of Eonomis University of Washington November 2015 Abstrat I onstrut a rinial agent auditor taxation model with adverse seletion in whih the

More information

Taste for variety and optimum product diversity in an open economy

Taste for variety and optimum product diversity in an open economy Taste for variety and optimum produt diversity in an open eonomy Javier Coto-Martínez City University Paul Levine University of Surrey Otober 0, 005 María D.C. Garía-Alonso University of Kent Abstrat We

More information

EXTENDED MATRIX CUBE THEOREMS WITH APPLICATIONS TO -THEORY IN CONTROL

EXTENDED MATRIX CUBE THEOREMS WITH APPLICATIONS TO -THEORY IN CONTROL MATHEMATICS OF OPERATIONS RESEARCH Vol. 28, No. 3, August 2003,. 497 523 Printed in U.S.A. EXTENDED MATRIX CUBE THEOREMS WITH APPLICATIONS TO -THEORY IN CONTROL AHARON BEN-TAL, ARKADI NEMIROVSKI, and CORNELIS

More information

Theory of Externalities Partial Equilibrium Analysis

Theory of Externalities Partial Equilibrium Analysis Theory of Externalities Partial Equilibrium Analysis Definition: An externality is resent whenever the well being of a consumer or the roduction ossibilities of a firm are directly affected by the actions

More information

Proportional-Integral-Derivative PID Controls

Proportional-Integral-Derivative PID Controls Proortional-Integral-Derivative PID Controls Dr M.J. Willis Det. of Chemial and Proess Engineering University of Newastle e-mail: mark.willis@nl.a.uk Written: 7 th November, 998 Udated: 6 th Otober, 999

More information

kids (this case is for j = 1; j = 2 case is similar). For the interior solution case, we have 1 = c (x 2 t) + p 2

kids (this case is for j = 1; j = 2 case is similar). For the interior solution case, we have 1 = c (x 2 t) + p 2 Problem 1 There are two subgames, or stages. At stage 1, eah ie ream parlor i (I all it firm i from now on) selets loation x i simultaneously. At stage 2, eah firm i hooses pries p i. To find SPE, we start

More information

A Queueing Model for Call Blending in Call Centers

A Queueing Model for Call Blending in Call Centers A Queueing Model for Call Blending in Call Centers Sandjai Bhulai and Ger Koole Vrije Universiteit Amsterdam Faulty of Sienes De Boelelaan 1081a 1081 HV Amsterdam The Netherlands E-mail: {sbhulai, koole}@s.vu.nl

More information

Econ 101A Midterm 2 Th 8 April 2009.

Econ 101A Midterm 2 Th 8 April 2009. Econ A Midterm Th 8 Aril 9. You have aroximately hour and minutes to answer the questions in the midterm. I will collect the exams at. shar. Show your work, and good luck! Problem. Production (38 oints).

More information

Optimal Sales Force Compensation

Optimal Sales Force Compensation University of Konstanz Department of Eonomis Optimal Sales Fore Compensation Matthias Kräkel and Anja Shöttner Working Paper Series 2014-09 http://www.wiwi.uni-konstanz.de/eondo/working-paper-series/ Konstanzer

More information

WEIGHTED MAXIMUM OVER MINIMUM MODULUS OF POLYNOMIALS, APPLIED TO RAY SEQUENCES OF PADÉ APPROXIMANTS

WEIGHTED MAXIMUM OVER MINIMUM MODULUS OF POLYNOMIALS, APPLIED TO RAY SEQUENCES OF PADÉ APPROXIMANTS WEIGHTED MAXIMUM OVER MINIMUM MODULUS OF POLYNOMIALS, APPLIED TO RAY SEQUENCES OF PADÉ APPROXIMANTS D.S. LUBINSKY Abstrat. Let a 0; " > 0. We use otential theory to obtain a shar lower bound for the linear

More information

Subject: Modeling of Thermal Rocket Engines; Nozzle flow; Control of mass flow. p c. Thrust Chamber mixing and combustion

Subject: Modeling of Thermal Rocket Engines; Nozzle flow; Control of mass flow. p c. Thrust Chamber mixing and combustion 16.50 Leture 6 Subjet: Modeling of Thermal Roket Engines; Nozzle flow; Control of mass flow Though onetually simle, a roket engine is in fat hysially a very omlex devie and diffiult to reresent quantitatively

More information

The Hanging Chain. John McCuan. January 19, 2006

The Hanging Chain. John McCuan. January 19, 2006 The Hanging Chain John MCuan January 19, 2006 1 Introdution We onsider a hain of length L attahed to two points (a, u a and (b, u b in the plane. It is assumed that the hain hangs in the plane under a

More information

Trading OTC and Incentives to Clear Centrally

Trading OTC and Incentives to Clear Centrally Trading OTC and Incentives to Clear Centrally Gaetano Antinolfi Francesca Caraella Francesco Carli March 1, 2013 Abstract Central counterparties CCPs have been art of the modern financial system since

More information

Complete Shrimp Game Solution

Complete Shrimp Game Solution Complete Shrimp Game Solution Florian Ederer Feruary 7, 207 The inverse demand urve is given y P (Q a ; Q ; Q ) = 00 0:5 (Q a + Q + Q ) The pro t funtion for rm i = fa; ; g is i (Q a ; Q ; Q ) = Q i [P

More information

INCOME AND SUBSTITUTION EFFECTS

INCOME AND SUBSTITUTION EFFECTS 3076-C5.df 3/12/04 10:56 AM Page 121 121 Chater 5 INCOME AND SUBSTITUTION EFFECTS In this hater we will use the utility-maimization model to study how the quantity of a good that an individual hooses is

More information

Economics 101. Lecture 7 - Monopoly and Oligopoly

Economics 101. Lecture 7 - Monopoly and Oligopoly Economics 0 Lecture 7 - Monooly and Oligooly Production Equilibrium After having exlored Walrasian equilibria with roduction in the Robinson Crusoe economy, we will now ste in to a more general setting.

More information

Too Poor for School? Social Background E ects on School and University Opportunities

Too Poor for School? Social Background E ects on School and University Opportunities Too Poor for Shool? Soial Bakground E ets on Shool and University Oortunities Alessandro Tamieri y University of Leiester June 7, 2010 Abstrat This aer studies how students soial bakground a ets shool

More information

Internet Appendix for Proxy Advisory Firms: The Economics of Selling Information to Voters

Internet Appendix for Proxy Advisory Firms: The Economics of Selling Information to Voters Internet Appendix for Proxy Advisory Firms: The Eonomis of Selling Information to Voters Andrey Malenko and Nadya Malenko The first part of the Internet Appendix presents the supplementary analysis for

More information

Complexity of Regularization RBF Networks

Complexity of Regularization RBF Networks Complexity of Regularization RBF Networks Mark A Kon Department of Mathematis and Statistis Boston University Boston, MA 02215 mkon@buedu Leszek Plaskota Institute of Applied Mathematis University of Warsaw

More information

arxiv: v1 [cs.db] 30 Jun 2012

arxiv: v1 [cs.db] 30 Jun 2012 Mining Statistially Signifiant Substrings using the Chi-Square Statisti Mayank Sahan mayasa@se.iitk.a.in Det. of Comuter Siene and Engineering Indian Institute of Tehnology, Kanur INDIA Arnab Bhattaharya

More information

Appendix A Market-Power Model of Business Groups. Robert C. Feenstra Deng-Shing Huang Gary G. Hamilton Revised, November 2001

Appendix A Market-Power Model of Business Groups. Robert C. Feenstra Deng-Shing Huang Gary G. Hamilton Revised, November 2001 Appendix A Market-Power Model of Business Groups Roert C. Feenstra Deng-Shing Huang Gary G. Hamilton Revised, Novemer 200 Journal of Eonomi Behavior and Organization, 5, 2003, 459-485. To solve for the

More information

Fundamental Theorem of Calculus

Fundamental Theorem of Calculus Chater 6 Fundamental Theorem of Calulus 6. Definition (Nie funtions.) I will say that a real valued funtion f defined on an interval [a, b] is a nie funtion on [a, b], if f is ontinuous on [a, b] and integrable

More information

Subject: Introduction to Component Matching and Off-Design Operation % % ( (1) R T % (

Subject: Introduction to Component Matching and Off-Design Operation % % ( (1) R T % ( 16.50 Leture 0 Subjet: Introdution to Component Mathing and Off-Design Operation At this point it is well to reflet on whih of the many parameters we have introdued (like M, τ, τ t, ϑ t, f, et.) are free

More information

Chapter 8 Hypothesis Testing

Chapter 8 Hypothesis Testing Leture 5 for BST 63: Statistial Theory II Kui Zhang, Spring Chapter 8 Hypothesis Testing Setion 8 Introdution Definition 8 A hypothesis is a statement about a population parameter Definition 8 The two

More information

Handout #3: Peak Load Pricing

Handout #3: Peak Load Pricing andout #3: Peak Load Pricing Consider a firm that exeriences two kinds of costs a caacity cost and a marginal cost ow should caacity be riced? This issue is alicable to a wide variety of industries, including

More information

Moral Hazard: Hidden Action

Moral Hazard: Hidden Action Moral Hazard: Hidden Action Part of these Notes were taken (almost literally) from Rasmusen, 2007 UIB Course 2013-14 (UIB) MH-Hidden Actions Course 2013-14 1 / 29 A Principal-agent Model. The Production

More information

Common Value Auctions with Costly Entry

Common Value Auctions with Costly Entry Common Value Autions with Costly Entry Pauli Murto Juuso Välimäki June, 205 preliminary and inomplete Abstrat We onsider a model where potential bidders onsider paying an entry ost to partiipate in an

More information

MULTIPLE SOLUTIONS FOR A CLASS OF DIRICHLET QUASILINEAR ELLIPTIC SYSTEMS DRIVEN BY A (P, Q)-LAPLACIAN OPERATOR

MULTIPLE SOLUTIONS FOR A CLASS OF DIRICHLET QUASILINEAR ELLIPTIC SYSTEMS DRIVEN BY A (P, Q)-LAPLACIAN OPERATOR Dynami Systems Aliations 20 (2011) 89-100 MULTIPLE SOLUTIONS FOR A CLASS OF DIRICHLET QUASILINEAR ELLIPTIC SYSTEMS DRIVEN BY A (P, Q)-LAPLACIAN OPERATOR GABRIELE BONANNO a, SHAPOUR HEIDARKHANI b, AND DONAL

More information

Journal of Inequalities in Pure and Applied Mathematics

Journal of Inequalities in Pure and Applied Mathematics Journal of Inequalities in Pure and Applied Mathematis A NEW ARRANGEMENT INEQUALITY MOHAMMAD JAVAHERI University of Oregon Department of Mathematis Fenton Hall, Eugene, OR 97403. EMail: javaheri@uoregon.edu

More information

Regulating the Natural Gas Transportation Industry : Optimal Pricing Policy of a Monopolist with Advance-Purchase and Spot Markets

Regulating the Natural Gas Transportation Industry : Optimal Pricing Policy of a Monopolist with Advance-Purchase and Spot Markets Regulating the Natural Gas Transortation Industry : Otimal Priing Poliy of a Monoolist with Advane-Purhase and Sot Markets Laurent David Mihel Le Breton y Olivier Merillon z Aril 007 - Preliminary Version.

More information

Emergence of Superpeer Networks: A New Perspective

Emergence of Superpeer Networks: A New Perspective Emergene o Suereer Networs: A New Persetive Bivas Mitra Deartment o Comuter Siene & Engineering Indian Institute o Tehnology, Kharagur, India Peer to Peer arhiteture Node Node Node Internet Node Node All

More information

Private Label Positioning and Product Line

Private Label Positioning and Product Line 17 816 May 2017 Private Label Positioning and Produt Line Stéphane Caprie Private Label Positioning and Produt Line Stéphane Caprie 29 May 2017 Abstrat This artile examines i) how retailers position private

More information

INFORMATION TRANSFER THROUGH CLASSIFIERS AND ITS RELATION TO PROBABILITY OF ERROR

INFORMATION TRANSFER THROUGH CLASSIFIERS AND ITS RELATION TO PROBABILITY OF ERROR IFORMATIO TRAFER TROUG CLAIFIER AD IT RELATIO TO PROBABILITY OF ERROR Deniz Erdogmus, Jose C. Prini Comutational euroengineering Lab (CEL, University of Florida, Gainesville, FL 6 [deniz,rini]@nel.ufl.edu

More information

Planar Undulator Considerations

Planar Undulator Considerations LCC-0085 July 2002 Linear Collider Collaboration Teh Notes Planar Undulator Considerations John C. Sheard Stanford Linear Aelerator Center Stanford University Menlo Park, California Abstrat: This note

More information

4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS

4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS STATIC GAMES 4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS Universidad Carlos III de Madrid CONTINUOUS VARIABLES In many games, ure strategies that layers can choose are not only, 3 or any other finite

More information

5.1 Composite Functions

5.1 Composite Functions SECTION. Composite Funtions 7. Composite Funtions PREPARING FOR THIS SECTION Before getting started, review the following: Find the Value of a Funtion (Setion., pp. 9 ) Domain of a Funtion (Setion., pp.

More information

Any AND-OR formula of size N can be evaluated in time N 1/2+o(1) on a quantum computer

Any AND-OR formula of size N can be evaluated in time N 1/2+o(1) on a quantum computer Any AND-OR formula of size N an be evaluated in time N /2+o( on a quantum omuter Andris Ambainis, ambainis@math.uwaterloo.a Robert Šalek salek@ees.berkeley.edu Andrew M. Childs, amhilds@uwaterloo.a Shengyu

More information

ON THE LEAST PRIMITIVE ROOT EXPRESSIBLE AS A SUM OF TWO SQUARES

ON THE LEAST PRIMITIVE ROOT EXPRESSIBLE AS A SUM OF TWO SQUARES #A55 INTEGERS 3 (203) ON THE LEAST PRIMITIVE ROOT EPRESSIBLE AS A SUM OF TWO SQUARES Christopher Ambrose Mathematishes Institut, Georg-August Universität Göttingen, Göttingen, Deutshland ambrose@uni-math.gwdg.de

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Physics Physics IC-W08D2-11 Jumping Off as Flatcar Solution

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Physics Physics IC-W08D2-11 Jumping Off as Flatcar Solution N eole, eah o mass MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deartment o Physis Physis 8.01 IC-W08D2-11 Juming O as Flatar Solution m, stand on a railway latar o mass m. They jum o one end o the latar with

More information

arxiv: v1 [cs.gt] 21 Jul 2017

arxiv: v1 [cs.gt] 21 Jul 2017 RSU II ommuniation Cyber attaks Otimal Seure Multi-Layer IoT Network Design Juntao Chen, Corinne Touati, and Quanyan Zhu arxiv:1707.07046v1 [s.gt] 1 Jul 017 Abstrat With the remarkable growth of the Internet

More information

Transmission charging and market distortion

Transmission charging and market distortion Transmission charging and market distortion Andy Philott Tony Downward Keith Ruddell s Electric Power Otimization Centre University of Auckland www.eoc.org.nz IPAM worksho, UCLA January 13, 2016 1/56 Outline

More information

Determination of the reaction order

Determination of the reaction order 5/7/07 A quote of the wee (or amel of the wee): Apply yourself. Get all the eduation you an, but then... do something. Don't just stand there, mae it happen. Lee Iaoa Physial Chemistry GTM/5 reation order

More information

6 Dynamic Optimization in Continuous Time

6 Dynamic Optimization in Continuous Time 6 Dynami Optimization in Continuous Time 6.1 Dynami programming in ontinuous time Consider the problem Z T max e rt u (k,, t) dt (1) (t) T s.t. k ú = f (k,, t) (2) k () = k, (3) with k (T )= k (ase 1),

More information

Problem 1(a): At equal times or in the Schrödinger picture the quantum scalar fields ˆΦ a (x) and ˆΠ a (x) satisfy commutation relations

Problem 1(a): At equal times or in the Schrödinger picture the quantum scalar fields ˆΦ a (x) and ˆΠ a (x) satisfy commutation relations PHY 396 K. Solutions for homework set #7. Problem 1a: At equal times or in the Shrödinger iture the quantum salar fields ˆΦ a x and ˆΠ a x satisfy ommutation relations ˆΦa x, ˆΦ b y 0, ˆΠa x, ˆΠ b y 0,

More information

2. The Energy Principle in Open Channel Flows

2. The Energy Principle in Open Channel Flows . The Energy Priniple in Open Channel Flows. Basi Energy Equation In the one-dimensional analysis of steady open-hannel flow, the energy equation in the form of Bernoulli equation is used. Aording to this

More information

Lecture 3 - Lorentz Transformations

Lecture 3 - Lorentz Transformations Leture - Lorentz Transformations A Puzzle... Example A ruler is positioned perpendiular to a wall. A stik of length L flies by at speed v. It travels in front of the ruler, so that it obsures part of the

More information

Internal Model Control

Internal Model Control Internal Model Control Part o a et o leture note on Introdution to Robut Control by Ming T. Tham 2002 The Internal Model Prinile The Internal Model Control hiloohy relie on the Internal Model Prinile,

More information

Takeshi Kurata Jun Fujiki Katsuhiko Sakaue. 1{1{4 Umezono, Tsukuba-shi, Ibaraki , JAPAN. fkurata, fujiki,

Takeshi Kurata Jun Fujiki Katsuhiko Sakaue. 1{1{4 Umezono, Tsukuba-shi, Ibaraki , JAPAN. fkurata, fujiki, Ane Eiolar Geometry via Fatorization Method akeshi Kurata Jun Fujiki Katsuhiko Sakaue Eletrotehnial Laboratory {{4 Umezono, sukuba-shi, Ibaraki 305-8568, JAPAN fkurata, fujiki, sakaueg@etl.go.j Abstrat

More information

Strauss PDEs 2e: Section Exercise 3 Page 1 of 13. u tt c 2 u xx = cos x. ( 2 t c 2 2 x)u = cos x. v = ( t c x )u

Strauss PDEs 2e: Section Exercise 3 Page 1 of 13. u tt c 2 u xx = cos x. ( 2 t c 2 2 x)u = cos x. v = ( t c x )u Strauss PDEs e: Setion 3.4 - Exerise 3 Page 1 of 13 Exerise 3 Solve u tt = u xx + os x, u(x, ) = sin x, u t (x, ) = 1 + x. Solution Solution by Operator Fatorization Bring u xx to the other side. Write

More information

Volume 29, Issue 3. On the definition of nonessentiality. Udo Ebert University of Oldenburg

Volume 29, Issue 3. On the definition of nonessentiality. Udo Ebert University of Oldenburg Volume 9, Issue 3 On the definition of nonessentiality Udo Ebert University of Oldenburg Abstrat Nonessentiality of a good is often used in welfare eonomis, ost-benefit analysis and applied work. Various

More information

Designing Social Norm Based Incentive Schemes to Sustain Cooperation in a Large Community

Designing Social Norm Based Incentive Schemes to Sustain Cooperation in a Large Community Designing Soial Norm Based Inentive Shemes to Sustain Cooperation in a arge Community Yu Zhang, Jaeo Par, Mihaela van der Shaar Eletrial Engineering Department, University of California, os Angeles yuzhang@ula.edu,

More information

Microeconomic Theory (501b) Problem Set 10. Auctions and Moral Hazard Suggested Solution: Tibor Heumann

Microeconomic Theory (501b) Problem Set 10. Auctions and Moral Hazard Suggested Solution: Tibor Heumann Dirk Bergemann Department of Economics Yale University Microeconomic Theory (50b) Problem Set 0. Auctions and Moral Hazard Suggested Solution: Tibor Heumann 4/5/4 This problem set is due on Tuesday, 4//4..

More information

COMMUNICATION BETWEEN SHAREHOLDERS 1

COMMUNICATION BETWEEN SHAREHOLDERS 1 COMMUNICATION BTWN SHARHOLDRS 1 A B. O A : A D Lemma B.1. U to µ Z r 2 σ2 Z + σ2 X 2r ω 2 an additive constant that does not deend on a or θ, the agents ayoffs can be written as: 2r rθa ω2 + θ µ Y rcov

More information

The Hyperbolic Region for Restricted Isometry Constants in Compressed Sensing

The Hyperbolic Region for Restricted Isometry Constants in Compressed Sensing INTERNATIONAL JOURNAL OF CIRCUITS SYSTEMS AND SIGNAL PROCESSING Volume 8 Te Hyeroli Region for Restrited Isometry Constants in Comressed Sensing Siqing Wang Yan Si and Limin Su Astrat Te restrited isometry

More information

Simple Cyclic loading model based on Modified Cam Clay

Simple Cyclic loading model based on Modified Cam Clay Simle li loading model based on Modified am la Imlemented in RISP main rogram version 00. and higher B Amir Rahim, The RISP onsortium Ltd Introdution This reort resents a simle soil model whih rovides

More information

Lecture Notes - Dynamic Moral Hazard

Lecture Notes - Dynamic Moral Hazard Lecture Notes - Dynamic Moral Hazard Simon Board and Moritz Meyer-ter-Vehn October 23, 2012 1 Dynamic Moral Hazard E ects Consumption smoothing Statistical inference More strategies Renegotiation Non-separable

More information

x ax 1 2 bx2 a bx =0 x = a b. Hence, a consumer s willingness-to-pay as a function of liters on sale, 1 2 a 2 2b, if l> a. (1)

x ax 1 2 bx2 a bx =0 x = a b. Hence, a consumer s willingness-to-pay as a function of liters on sale, 1 2 a 2 2b, if l> a. (1) Answers to Exam Economics 201b First Half 1. (a) Observe, first, that no consumer ever wishes to consume more than 3/2 liters (i.e., 1.5 liters). To see this, observe that, even if the beverage were free,

More information

Game Theory and Economics of Contracts Lecture 5 Static Single-agent Moral Hazard Model

Game Theory and Economics of Contracts Lecture 5 Static Single-agent Moral Hazard Model Game Theory and Economics of Contracts Lecture 5 Static Single-agent Moral Hazard Model Yu (Larry) Chen School of Economics, Nanjing University Fall 2015 Principal-Agent Relationship Principal-agent relationship

More information

Real-time Hand Tracking Using a Sum of Anisotropic Gaussians Model

Real-time Hand Tracking Using a Sum of Anisotropic Gaussians Model Real-time Hand Traking Using a Sum of Anisotroi Gaussians Model Srinath Sridhar 1, Helge Rhodin 1, Hans-Peter Seidel 1, Antti Oulasvirta 2, Christian Theobalt 1 1 Max Plank Institute for Informatis Saarbrüken,

More information

Solutions to exercises on delays. P (x = 0 θ = 1)P (θ = 1) P (x = 0) We can replace z in the first equation by its value in the second equation.

Solutions to exercises on delays. P (x = 0 θ = 1)P (θ = 1) P (x = 0) We can replace z in the first equation by its value in the second equation. Ec 517 Christohe Chamley Solutions to exercises on delays Ex 1: P (θ = 1 x = 0) = P (x = 0 θ = 1)P (θ = 1) P (x = 0) = 1 z)µ (1 z)µ + 1 µ. The value of z is solution of µ c = δµz(1 c). We can relace z

More information

Public School Choice: An Economic Analysis

Public School Choice: An Economic Analysis Publi Shool Choie: An Eonomi Analysis Levon Barseghyan, Damon Clark and Stephen Coate May 25, 2018 Abstrat Publi shool hoie programs give households a hoie of publi shool and enourage shools to ompete

More information

Teoria das organizações e contratos

Teoria das organizações e contratos Teoria das organizações e contratos Chapter 6: Adverse Selection with two types Mestrado Profissional em Economia 3 o trimestre 2015 EESP (FGV) Teoria das organizações e contratos 3 o trimestre 2015 1

More information

Fast, Approximately Optimal Solutions for Single and Dynamic MRFs

Fast, Approximately Optimal Solutions for Single and Dynamic MRFs Fast, Aroximately Otimal Solutions for Single and Dynami MRFs Nikos Komodakis, Georgios Tziritas University of Crete, Comuter Siene Deartment {komod,tziritas}@sd.uo.gr Nikos Paragios MAS, Eole Centrale

More information

On Some Coefficient Estimates For Certain Subclass of Analytic And Multivalent Functions

On Some Coefficient Estimates For Certain Subclass of Analytic And Multivalent Functions IOSR Journal of Mathematis (IOSR-JM) e-issn: 78-578, -ISSN: 9-765X. Volume, Issue 6 Ver. I (Nov. - De.06), PP 58-65 www.iosrournals.org On Some Coeffiient Estimates For Certain Sublass of nalyti nd Multivalent

More information

7 Max-Flow Problems. Business Computing and Operations Research 608

7 Max-Flow Problems. Business Computing and Operations Research 608 7 Max-Flow Problems Business Computing and Operations Researh 68 7. Max-Flow Problems In what follows, we onsider a somewhat modified problem onstellation Instead of osts of transmission, vetor now indiates

More information

Essays on Competition: Contests, Personnel Economics, and Corporate Citizenship. Dylan Blu Minor

Essays on Competition: Contests, Personnel Economics, and Corporate Citizenship. Dylan Blu Minor Essays on Competition: Contests, Personnel Eonomis, and Corporate Citizenship By Dylan Blu Minor A dissertation submitted in partial satisfation of the requirements for the degree of Dotor of Philosophy

More information

A NETWORK SIMPLEX ALGORITHM FOR THE MINIMUM COST-BENEFIT NETWORK FLOW PROBLEM

A NETWORK SIMPLEX ALGORITHM FOR THE MINIMUM COST-BENEFIT NETWORK FLOW PROBLEM NETWORK SIMPLEX LGORITHM FOR THE MINIMUM COST-BENEFIT NETWORK FLOW PROBLEM Cen Çalışan, Utah Valley University, 800 W. University Parway, Orem, UT 84058, 801-863-6487, en.alisan@uvu.edu BSTRCT The minimum

More information

Module 8: Multi-Agent Models of Moral Hazard

Module 8: Multi-Agent Models of Moral Hazard Module 8: Multi-Agent Models of Moral Hazard Information Economics (Ec 515) George Georgiadis Types of models: 1. No relation among agents. an many agents make contracting easier? 2. Agents shocks are

More information

Lecture Notes - Dynamic Moral Hazard

Lecture Notes - Dynamic Moral Hazard Lecture Notes - Dynamic Moral Hazard Simon Board and Moritz Meyer-ter-Vehn October 27, 2011 1 Marginal Cost of Providing Utility is Martingale (Rogerson 85) 1.1 Setup Two periods, no discounting Actions

More information

Copyright protection and innovation in the presence of. commercial piracy *

Copyright protection and innovation in the presence of. commercial piracy * Coyright rotetion and innovation in the resene of oerial iray Dyuti S Banerjee Deartent of Eonois, Monash University, Australia E-ail: dyutibanerjee@buseoeduau Teyu Chou Deartent of Publi Finane, National

More information

1 Riskaversion and intertemporal substitution under external habits.

1 Riskaversion and intertemporal substitution under external habits. Riskaversion and intertemporal substitution under external habits. Reall that e de ne the oe ient of relative riskaversion as R r u00 ( ) u 0 ( ) so for CRRA utility e have u () R r t ; hih determines

More information

silicon wafers p b θ b IR heater θ h p h solution bath cleaning filter bellows pump

silicon wafers p b θ b IR heater θ h p h solution bath cleaning filter bellows pump An Analysis of Cometitive Assoiative Net for Temerature Control of RCA Cleaning Solutions S Kurogi y, H Nobutomo y, T Nishida y, H Sakamoto y, Y Fuhikawa y, M Mimata z and K Itoh z ykyushu Institute of

More information

Lesson 23: The Defining Equation of a Line

Lesson 23: The Defining Equation of a Line Student Outomes Students know that two equations in the form of ax + y = and a x + y = graph as the same line when a = = and at least one of a or is nonzero. a Students know that the graph of a linear

More information

Maintaining prediction quality under the condition of a growing knowledge space. A probabilistic dynamic model of knowledge spaces quality evolution

Maintaining prediction quality under the condition of a growing knowledge space. A probabilistic dynamic model of knowledge spaces quality evolution Maintaining redition quality under the ondition of a growing knowledge sae Christoh Jahnz ORCID: 0000-0003-3297-7564 Email: jahnz@gmx.de Intelligene an be understood as an agent s ability to redit its

More information

Hong Chen. and. Murray Frank 1. and. Hong Kong University of Science and Technology. March 30, Abstract

Hong Chen. and. Murray Frank 1. and. Hong Kong University of Science and Technology. March 30, Abstract Monopoly Priing When Customers Queue Hong Chen Faulty of Commere and Business Administration University of British Columbia, Vanouver, B.C. Canada and Murray Frank Faulty of Commere and Business Administration

More information

1 C 6, 3 4, 4. Player S 5, 2 3, 1

1 C 6, 3 4, 4. Player S 5, 2 3, 1 University of alifornia, Davis - Deartment of Economics PRING EN / ARE : MIROEONOMI TEORY Professor Giacomo Bonanno ====================================================================== MIDTERM EXAM ANWER

More information

Screening. Diego Moreno Universidad Carlos III de Madrid. Diego Moreno () Screening 1 / 1

Screening. Diego Moreno Universidad Carlos III de Madrid. Diego Moreno () Screening 1 / 1 Screening Diego Moreno Universidad Carlos III de Madrid Diego Moreno () Screening 1 / 1 The Agency Problem with Adverse Selection A risk neutral principal wants to o er a menu of contracts to be o ered

More information

Word of Mass: The Relationship between Mass Media and Word-of-Mouth

Word of Mass: The Relationship between Mass Media and Word-of-Mouth Word of Mass: The Relationship between Mass Media and Word-of-Mouth Roman Chuhay Preliminary version Marh 6, 015 Abstrat This paper studies the optimal priing and advertising strategies of a firm in the

More information

Most results in this section are stated without proof.

Most results in this section are stated without proof. Leture 8 Level 4 v2 he Expliit formula. Most results in this setion are stated without proof. Reall that we have shown that ζ (s has only one pole, a simple one at s =. It has trivial zeros at the negative

More information

Maximum entropy generation rate in a heat exchanger at constant inlet parameters

Maximum entropy generation rate in a heat exchanger at constant inlet parameters Maximum entroy generation rate in a heat exhanger at onstant inlet arameters Rafał LASKOWSKI, Maiej JAWORSKI Online: htt://www.jmee.tu.koszalin.l/download_artile/jmee_7 7986.df Cite this artile as: Laskowski

More information

Working Paper. Middlemen, Non-Profits, and Poverty. Nancy H. Chau, Hideaki Goto, and Ravi Kanbur. WP September 2009

Working Paper. Middlemen, Non-Profits, and Poverty. Nancy H. Chau, Hideaki Goto, and Ravi Kanbur. WP September 2009 WP 2009-30 Setember 2009 Working Paer Deartment of Alied Eonomis and Management Cornell University, Ithaa, New York 14853-7801 USA Middlemen, Non-Profits, and Poverty Nany H. Chau, Hideaki Goto, and Ravi

More information

SOLVED QUESTIONS 1 / 2. in a closed container at equilibrium. What would be the effect of addition of CaCO 3 on the equilibrium concentration of CO 2?

SOLVED QUESTIONS 1 / 2. in a closed container at equilibrium. What would be the effect of addition of CaCO 3 on the equilibrium concentration of CO 2? SOLVED QUESTIONS Multile Choie Questions. and are the veloity onstants of forward and bakward reations. The equilibrium onstant k of the reation is (A) (B) (C) (D). Whih of the following reations will

More information

Incentives in Crowdsourcing

Incentives in Crowdsourcing Inentives in Crowdsouring J. Aislinn Bohren University of California, San Diego Troy Kravitz University of California, San Diego January 2, 202 Abstrat Crowdsouring is the proess of delegating tasks to

More information

A Characterization of Wavelet Convergence in Sobolev Spaces

A Characterization of Wavelet Convergence in Sobolev Spaces A Charaterization of Wavelet Convergene in Sobolev Spaes Mark A. Kon 1 oston University Louise Arakelian Raphael Howard University Dediated to Prof. Robert Carroll on the oasion of his 70th birthday. Abstrat

More information

EC476 Contracts and Organizations, Part III: Lecture 2

EC476 Contracts and Organizations, Part III: Lecture 2 EC476 Contracts and Organizations, Part III: Lecture 2 Leonardo Felli 32L.G.06 19 January 2015 Moral Hazard: Consider the contractual relationship between two agents (a principal and an agent) The principal

More information

A General Approach for Analysis of Actuator Delay Compensation Methods for Real-Time Testing

A General Approach for Analysis of Actuator Delay Compensation Methods for Real-Time Testing The th World Conferene on Earthquake Engineering Otober -7, 8, Beijing, China A General Aroah for Analysis of Atuator Delay Comensation Methods for Real-Time Testing Cheng Chen and James M. Riles Post-dotoral

More information

Sensitivity Analysis in Markov Networks

Sensitivity Analysis in Markov Networks Sensitivity Analysis in Markov Networks Hei Chan and Adnan Darwihe Computer Siene Department University of California, Los Angeles Los Angeles, CA 90095 {hei,darwihe}@s.ula.edu Abstrat This paper explores

More information