f(x,y) = (4(x 2 4)x,2y) = 0 H(x,y) =
|
|
- Sybil Golden
- 5 years ago
- Views:
Transcription
1 Problem Set 3: Unconstraned mzaton n R N. () Fnd all crtcal ponts of f(x,y) (x 4) +y and show whch are ma and whch are mnma. () Fnd all crtcal ponts of f(x,y) (y x ) x and show whch are ma and whch are mnma. () The gradent at any crtcal pont s f(x,y) (4(x 4)x,y) 0 Thus y must be zero. x can be zero or ±. Ths gves us three crtcal ponts. The Hessan s x H(x,y) Thecrtcal pont (0,0) s nether a mum nor a mnmum, snce the Hessan has egenvalues 0 and. At (±,0), the Hessan has egenvalues and 3, so these crtcal ponts are mnma. () The gradent at any crtcal pont s f(x,y) ( 4(y x )x x,(y x )) 0 The second equaton gves y x, and substtutng ths nto the frst equaton gves 4(x x ) x 0 so x 0, y 0 s a crtcal pont. The Hessan s 4(y x H(x,y) )+x 4x 4x Evaluatng at (0, 0) yelds H(x,y) 0 0 whch has egenvalues and, so (0,0) s nether a mum nor a mnmum. 3. Suppose a frm produces two goods, q and q, whose prces are p and p, respectvely. The costs of producton are C(q,q ). () Provde necessary and suffcent condtons for a producton plan (q,q ) to be proft-mzng and show how q vares wth p. If C(q,q ) c (q ) + c (q ) + bq q, explan when a crtcal pont s a local mum of the proft functon. () If C(q,q ) c (q )+c (q )+bq q, how does q vary wth b and p? How do profts vary wth b and p? () The frm s proft-mzaton problem s p q +p q C(q,q ) q,q The FONCs are p C (q,q ) 0 p C (q,q ) 0
2 The SOSCs are that C (q,q ) C (q,q ) C (q,q ) C (q,q ) s negatve defnte. Wth the functonal form C(q,q ) c (q ) + c (q ) + bq q, we get a Hessan c (q ) b b c (q ) whch must satsfy c (q ) < 0, c (q ) < 0, and c (q )c (q ) b > 0 to be negatve defnte. So b cannot be too large relatve to the second dervatves of c (q ) and c (q ), or the economes of scope make the crtcal pont characterzed above a global mnmum. () Profts are easy. The proft functon s The envelope theorem mples V(b,p ) p q +p q c (q ) c (q ) bq q (q,q )(q,q ) V b q q < 0 V p q > 0 To compute the comparatve statcs, we totally dfferentate the FONCs, p c (q ) bq 0 p c (q ) bq 0 and re-wrte the result as a matrx equaton, c (q ) b b c (q ) q / b q / b q q Cramer s rule then mples q q det b b q c (q ) deth q c (q ) bq deth The denomnator deth s postve because we are at a mum, and the numerator s postve f q c (q ) bq > 0. Ths s ambguous, so we should expect changes n the spllover effect to have uncertan changes on frm behavor. Smlarly, c (q ) b q / p b c (q ) q / p 0 And usng Cramer s rule, q p b 0 c (q ) deth c (q ) deth > 0 Ths s unambguously postve (actually, ths s just the law of supply, rght? We ll see ths always holds for prce-takng frms).
3 4. A consumer wth utlty functon u(q,q,m) (q γ )q α + m and budget constrant w p q +p q +m s tryng to mze utlty. () Solve for the optmal bundle (q,q,m ) and check the second-order suffcent condtons. () Show how q vares wth p, and how q vares wth p, both usng the closed-form solutons and the mplct functon theorem. How does the value functon vary wth γ? Brefly provde an economc nterpretaton for the parameter γ. () The mzaton problem s wth FONCs The crtcal pont then s and m w p q p q. The Hessan s H(q,q ) q,q (q γ )q α +w p q p q q α p 0 (q γ )αq α p 0 q p/α q p αp (α )/α +γ 0 αq α αq α (q γ )α(α )q α whch has leadng determnants 0 and ( αq α ) < 0. So ths s, ykes, not negatve defnte. We cannot conclude ths s a mum (actually, we wll be able to prove t later, snce the objectve functon s quas-concave ). () As for comparatve statcs, we are n somewhat awkward terrtory because we are not surethat the proposed crtcal pont s an optmum. We can stll try to use the mplct functon theorem, but we cannot assume that the Hessan has the alternatng sgn pattern assocated wth a negatve defnte matrx. Dfferentatng the closed form soluton yelds q p αp (α )/α To use the IFT, we totally dfferentate the FONCs to get αq α q p 0 q p αq α +(q γ )α(α )q α q p 0 Rewrtng ths as a matrx equaton yelds 0 αq α αq α (q γ )α(α )q α q / p q / p 0 Usng Cramer s rule to solve for q / p yelds 0 αq α q det (q γ )α(α )q α p 3
4 or q α αq p (αq α ) αq α Whch gves the same result as dfferentatng the closed form soluton. The optmzed value of the consumer s utlty s gven by and the Envelope Theorem mples V(γ ) (q γ )q α +w p q p q (q,q )(q,q ) V (γ ) q α < 0 so that an ncrease n γ makes the consumer worse off. The parameter γ s the mnmum amount of q that the agent must consume to get postve utlty from consumng any q or q. Notce that f the consumer can t afford enough γ, he should just put all of hs wealth nto m, whch gves a constant margnal utlty of. Let s thnk about q as the qualty of a prmary good lke a computer, electrc gutar, or camera, and q as secondary or complementary goods lke software, an amplfer, or lenses; anythng that you also requre to make q worth ownng. Then the consumer needs to purchase a prmary good of qualty at least γ, or the payoff s actually negatve, and the consumer regrets makng the purchase, no matter how good the secondary goods are that he also purchases. 5. There s a consumer wth utlty functon u(q,q,m) v(q,q )+m and budget constrant w p q + p q + m. Let v() 0. Frm produces q wth cost functon c q, and frm produces q wth cost functon c q. All frms and the consumer are prce-takers. () Characterze the utlty-mzng demands for the consumer (q d,qd,md ) and the proft-mzng supply for each frm, q s and qs by provdng frst-order necessary condtons and second-order suffcent condtons. When are these condtons satsfed? () Solve for a perfectly compettve equlbrum (the markets for each good clear, so that qk s qd k for k,) q, q, m, p, p, assumng that q,q > 0. Explan how q vares wth c. When are the goods complements, and when are they substtutes? () Suppose there s an excse tax on good, pad by the consumer, so that the effectve prce the consumer pays s p + t. How does a change n the tax affect consumpton of good and good n equlbrum? () The consumer s demand functons are characterzed by the system of FONC s v (q d,qd ) p 0 v (q d,q d ) p 0 and The SOSCs are that the matrx m d w p q d p q d v (q d,qd ) v (q d,qd ) v (q d,qd ) v (q d,qd ) be negatve defnte. Ths requres that v (q d,qd ),v (q d,qd ) < 0, and v (q d,qd )v (q d,qd ) v (q d,qd ) > 0. 4
5 The frms proft functons are lnear n ther quanttes, so that the soluton s π (p c )q 0 p < c q 0, ) p c p > c Snce π (q) s zero, we cannot verfy the SOSC s. () In equlbrum, t must be the case that p c, or otherwse the market wll fal to clear. Ths mples that equlbrum s characterzed by the system of equatons and v (q,q ) c 0 v (q,q ) c 0 m w c q c q If we totally dfferentate the frst two equatons wth respect to c, we get a system v (q,q ) v (q,q ) q / c 0 v (q,q ) v (q,q ) q / c To solve the system, we use Cramer s rule, to get 0 v (q q det,q ) v (q,q ) c v (q,q ) So the sgn s determned by v (q,q ), snce the denomnator s postve. Snce p c n equlbrum, ths also tells us whether the goods are (gross) complements or (gross) substtutes. If v s negatve, the whole term wll be postve, and the goods are (gross) substtutes. If v s postve, the whole term wll be negatve, and the goods are (gross) complements. () If there s a tax on good one, the equlbrum equatons become v (q,q ) c t 0 v (q,q ) c 0 Totally dfferentatng wth respect to t, we get a system v (q,q ) v (q,q ) q / t v (q,q ) v (q,q ) q / t Solvng the system wth Cramer s rule, v (q q det,q ) t 0 v (q,q ) q det t v (q,q ) v (q,q ) 0 0 v (q,q ) < 0 v (q,q ) 5
6 6. An agent s tryng to decde how to nvest. There are K rsky assets avalable, and a safe asset that gves a return R > 0. The return on each s normally dstrbuted wth mean µ k, varance σk, and prce p k. A portfolo s a vector π (π,π ) gvng the amount of each asset purchased. () Suppose the covarance between the goods s zero, so that the varance-covarance matrx σ Σ 0 0 σ s dagonal. If the agent mzes the mean-less-the-varance of the portfolo, π µ π Σπ +Rm subject to the constrant w m+ k p kπ k, what s the optmal portfolo? (If π k < 0, what does that mean economcally?). How does the agent s optmal portfolo vary n R? How does the agent s payoff vary n R? () Suppose there are non-trval covarances between the assets, so that σ Σ σ σ σ s not dagonal, but t s symmetrc. Are the frst-order necessary condtons suffcent for a crtcal pont to be a mum n ths problem? How does a change n the covarance between the returns σ affect the optmal portfolo? How does a change n the covarance σ affect the agent s payoff? () If K s arbtrary, derve frst-order necessary condtons and second-order suffcent for the optmal portfolo problem. Are the second-order suffcent condtons satsfed for any varancecovarance matrx Σ? () If the VCV matrx s dagonal, we get the objectve functon whch has FONC s and Hessan π π µ σ π +R(w µ σ π Rp 0 µ σ π Rp 0 σ H 0 0 σ whch s negatve defnte for sure. So the optmal portfolo s π Rp µ σ p π ) The agent s payoff satsfes whle the optmal portfolo satsfes V (R) m > 0 π R p /σ > 0 Bascally, a hgher nterest rate on the safe asset ncreases the value of the agent s wealth, and he s happy to take on more rsk. 6
7 () The objectve s π π µ +π µ π σ π π σ +R(w p π p π ) wth FONCs µ p π σ π σ 0 µ p π σ π σ 0 and SOSCs that the matrx σ H σ σ σ Σ be negatve defnte. Snce Σ s a VCV matrx, t s postve defnte, so that Σ s negatve defnte, and the FONCs are automatcally satsfed. The closed form solutons are π (µ p )σ (µ p )σ σ σ σ π (µ p )σ (µ p )σ σ σ σ The change n the agent s payoff wth respect to σ s V (σ ) π π < 0 so he s unambguously worse off. The change n π wth respect to σ s (µ p )det(σ)+σ (µ p )σ σ (µ p ) det(σ) whch appears to be ambguous. The problem s that σ enters the both the numerator and denomnator of π negatvely, so that an ncrease n σ shrnks the denomnator and numerator at the same tme, so t s hard to tell whch effect domnates as long as µ p > 0. If µ p < 0, then we could get unambguous comparatve statcs, but ths seems to be a werd stuaton (shouldn t the expected return on an asset be above the prce, to compensate the agent for holdng rsk?). () For arbtrary K the objectve s π π µ π Σ π +R(w π p) wth FONCs or µ Σ π Rp 0 π Σ (µ Rp) and the SOSC s are that Σ be negatve defnte. However, Σ s a VCV matrx, so t s postve (sem-)defnte, so Σ s negatve (sem-)defnte, so the SOSCs are automatcally satsfed. If any of the assets were exactly correlated, we could get a postve defnte VCV matrx by smply mergng those assets together, and sayng that f the optmal portfolo requres buyng π k unts of the merged asset, any lnear combnaton of those assets that adds up to π k wll do. 7
Welfare Properties of General Equilibrium. What can be said about optimality properties of resource allocation implied by general equilibrium?
APPLIED WELFARE ECONOMICS AND POLICY ANALYSIS Welfare Propertes of General Equlbrum What can be sad about optmalty propertes of resource allocaton mpled by general equlbrum? Any crteron used to compare
More information,, MRTS is the marginal rate of technical substitution
Mscellaneous Notes on roducton Economcs ompled by eter F Orazem September 9, 00 I Implcatons of conve soquants Two nput case, along an soquant 0 along an soquant Slope of the soquant,, MRTS s the margnal
More informationPROBLEM SET 7 GENERAL EQUILIBRIUM
PROBLEM SET 7 GENERAL EQUILIBRIUM Queston a Defnton: An Arrow-Debreu Compettve Equlbrum s a vector of prces {p t } and allocatons {c t, c 2 t } whch satsfes ( Gven {p t }, c t maxmzes βt ln c t subject
More informationLecture Notes, January 11, 2010
Economcs 200B UCSD Wnter 2010 Lecture otes, January 11, 2010 Partal equlbrum comparatve statcs Partal equlbrum: Market for one good only wth supply and demand as a functon of prce. Prce s defned as the
More information1 The Sidrauski model
The Sdrausk model There are many ways to brng money nto the macroeconomc debate. Among the fundamental ssues n economcs the treatment of money s probably the LESS satsfactory and there s very lttle agreement
More informationEconomics 101. Lecture 4 - Equilibrium and Efficiency
Economcs 0 Lecture 4 - Equlbrum and Effcency Intro As dscussed n the prevous lecture, we wll now move from an envronment where we looed at consumers mang decsons n solaton to analyzng economes full of
More informationEconomics 2450A: Public Economics Section 10: Education Policies and Simpler Theory of Capital Taxation
Economcs 2450A: Publc Economcs Secton 10: Educaton Polces and Smpler Theory of Captal Taxaton Matteo Parads November 14, 2016 In ths secton we study educaton polces n a smplfed verson of framework analyzed
More information3.2. Cournot Model Cournot Model
Matlde Machado Assumptons: All frms produce an homogenous product The market prce s therefore the result of the total supply (same prce for all frms) Frms decde smultaneously how much to produce Quantty
More informationCopyright (C) 2008 David K. Levine This document is an open textbook; you can redistribute it and/or modify it under the terms of the Creative
Copyrght (C) 008 Davd K. Levne Ths document s an open textbook; you can redstrbute t and/or modfy t under the terms of the Creatve Commons Attrbuton Lcense. Compettve Equlbrum wth Pure Exchange n traders
More informationUniversity of California, Davis Date: June 22, 2009 Department of Agricultural and Resource Economics. PRELIMINARY EXAMINATION FOR THE Ph.D.
Unversty of Calforna, Davs Date: June 22, 29 Department of Agrcultural and Resource Economcs Department of Economcs Tme: 5 hours Mcroeconomcs Readng Tme: 2 mnutes PRELIMIARY EXAMIATIO FOR THE Ph.D. DEGREE
More informationSupporting Materials for: Two Monetary Models with Alternating Markets
Supportng Materals for: Two Monetary Models wth Alternatng Markets Gabrele Camera Chapman Unversty Unversty of Basel YL Chen Federal Reserve Bank of St. Lous 1 Optmal choces n the CIA model On date t,
More informationSupporting Information for: Two Monetary Models with Alternating Markets
Supportng Informaton for: Two Monetary Models wth Alternatng Markets Gabrele Camera Chapman Unversty & Unversty of Basel YL Chen St. Lous Fed November 2015 1 Optmal choces n the CIA model On date t, gven
More informationA NOTE ON CES FUNCTIONS Drago Bergholt, BI Norwegian Business School 2011
A NOTE ON CES FUNCTIONS Drago Bergholt, BI Norwegan Busness School 2011 Functons featurng constant elastcty of substtuton CES are wdely used n appled economcs and fnance. In ths note, I do two thngs. Frst,
More informationHow Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists *
How Strong Are Weak Patents? Joseph Farrell and Carl Shapro Supplementary Materal Lcensng Probablstc Patents to Cournot Olgopolsts * September 007 We study here the specal case n whch downstream competton
More informationEquilibrium with Complete Markets. Instructor: Dmytro Hryshko
Equlbrum wth Complete Markets Instructor: Dmytro Hryshko 1 / 33 Readngs Ljungqvst and Sargent. Recursve Macroeconomc Theory. MIT Press. Chapter 8. 2 / 33 Equlbrum n pure exchange, nfnte horzon economes,
More informationHila Etzion. Min-Seok Pang
RESERCH RTICLE COPLEENTRY ONLINE SERVICES IN COPETITIVE RKETS: INTINING PROFITILITY IN THE PRESENCE OF NETWORK EFFECTS Hla Etzon Department of Technology and Operatons, Stephen. Ross School of usness,
More informationProblem Set 4: Sketch of Solutions
Problem Set 4: Sketc of Solutons Informaton Economcs (Ec 55) George Georgads Due n class or by e-mal to quel@bu.edu at :30, Monday, December 8 Problem. Screenng A monopolst can produce a good n dfferent
More informationk t+1 + c t A t k t, t=0
Macro II (UC3M, MA/PhD Econ) Professor: Matthas Kredler Fnal Exam 6 May 208 You have 50 mnutes to complete the exam There are 80 ponts n total The exam has 4 pages If somethng n the queston s unclear,
More informationLet p z be the price of z and p 1 and p 2 be the prices of the goods making up y. In general there is no problem in grouping goods.
Economcs 90 Prce Theory ON THE QUESTION OF SEPARABILITY What we would lke to be able to do s estmate demand curves by segmentng consumers purchases nto groups. In one applcaton, we aggregate purchases
More informationTopic 5: Non-Linear Regression
Topc 5: Non-Lnear Regresson The models we ve worked wth so far have been lnear n the parameters. They ve been of the form: y = Xβ + ε Many models based on economc theory are actually non-lnear n the parameters.
More informationMixed Taxation and Production Efficiency
Floran Scheuer 2/23/2016 Mxed Taxaton and Producton Effcency 1 Overvew 1. Unform commodty taxaton under non-lnear ncome taxaton Atknson-Stgltz (JPubE 1976) Theorem Applcaton to captal taxaton 2. Unform
More information( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1
Problem Set 4 Suggested Solutons Problem (A) The market demand functon s the soluton to the followng utlty-maxmzaton roblem (UMP): The Lagrangean: ( x, x, x ) = + max U x, x, x x x x st.. x + x + x y x,
More informationWelfare Analysis of Cournot and Bertrand Competition With(out) Investment in R & D
MPRA Munch Personal RePEc Archve Welfare Analyss of Cournot and Bertrand Competton Wth(out) Investment n R & D Jean-Baptste Tondj Unversty of Ottawa 25 March 2016 Onlne at https://mpra.ub.un-muenchen.de/75806/
More informationSolutions to exam in SF1811 Optimization, Jan 14, 2015
Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable
More informationSolutions HW #2. minimize. Ax = b. Give the dual problem, and make the implicit equality constraints explicit. Solution.
Solutons HW #2 Dual of general LP. Fnd the dual functon of the LP mnmze subject to c T x Gx h Ax = b. Gve the dual problem, and make the mplct equalty constrants explct. Soluton. 1. The Lagrangan s L(x,
More information1 Matrix representations of canonical matrices
1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:
More informationACTM State Calculus Competition Saturday April 30, 2011
ACTM State Calculus Competton Saturday Aprl 30, 2011 ACTM State Calculus Competton Sprng 2011 Page 1 Instructons: For questons 1 through 25, mark the best answer choce on the answer sheet provde Afterward
More informationAPPROXIMATE PRICES OF BASKET AND ASIAN OPTIONS DUPONT OLIVIER. Premia 14
APPROXIMAE PRICES OF BASKE AND ASIAN OPIONS DUPON OLIVIER Prema 14 Contents Introducton 1 1. Framewor 1 1.1. Baset optons 1.. Asan optons. Computng the prce 3. Lower bound 3.1. Closed formula for the prce
More informationLectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix
Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could
More informationEconomics 8105 Macroeconomic Theory Recitation 1
Economcs 8105 Macroeconomc Theory Rectaton 1 Outlne: Conor Ryan September 6th, 2016 Adapted From Anh Thu (Monca) Tran Xuan s Notes Last Updated September 20th, 2016 Dynamc Economc Envronment Arrow-Debreu
More information3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X
Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number
More informationOnline Appendix. t=1 (p t w)q t. Then the first order condition shows that
Artcle forthcomng to ; manuscrpt no (Please, provde the manuscrpt number!) 1 Onlne Appendx Appendx E: Proofs Proof of Proposton 1 Frst we derve the equlbrum when the manufacturer does not vertcally ntegrate
More informationDifference Equations
Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1
More informationMathematical Economics MEMF e ME. Filomena Garcia. Topic 2 Calculus
Mathematcal Economcs MEMF e ME Flomena Garca Topc 2 Calculus Mathematcal Economcs - www.seg.utl.pt/~garca/economa_matematca . Unvarate Calculus Calculus Functons : X Y y ( gves or each element X one element
More informationIn the figure below, the point d indicates the location of the consumer that is under competition. Transportation costs are given by td.
UC Berkeley Economcs 11 Sprng 006 Prof. Joseph Farrell / GSI: Jenny Shanefelter Problem Set # - Suggested Solutons. 1.. In ths problem, we are extendng the usual Hotellng lne so that now t runs from [-a,
More information1. relation between exp. function and IUF
Dualty Dualty n consumer theory II. relaton between exp. functon and IUF - straghtforward: have m( p, u mn'd value of expendture requred to attan a gven level of utlty, gven a prce vector; u ( p, M max'd
More informationEcon107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)
I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes
More informationChapter Newton s Method
Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve
More informationThe exam is closed book, closed notes except your one-page cheat sheet.
CS 89 Fall 206 Introducton to Machne Learnng Fnal Do not open the exam before you are nstructed to do so The exam s closed book, closed notes except your one-page cheat sheet Usage of electronc devces
More informationPerfect Competition and the Nash Bargaining Solution
Perfect Competton and the Nash Barganng Soluton Renhard John Department of Economcs Unversty of Bonn Adenauerallee 24-42 53113 Bonn, Germany emal: rohn@un-bonn.de May 2005 Abstract For a lnear exchange
More informationCS294 Topics in Algorithmic Game Theory October 11, Lecture 7
CS294 Topcs n Algorthmc Game Theory October 11, 2011 Lecture 7 Lecturer: Chrstos Papadmtrou Scrbe: Wald Krchene, Vjay Kamble 1 Exchange economy We consder an exchange market wth m agents and n goods. Agent
More informationIntroduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:
CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and
More informationThe Second Anti-Mathima on Game Theory
The Second Ant-Mathma on Game Theory Ath. Kehagas December 1 2006 1 Introducton In ths note we wll examne the noton of game equlbrum for three types of games 1. 2-player 2-acton zero-sum games 2. 2-player
More informationSection 8.3 Polar Form of Complex Numbers
80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the
More informationWinter 2008 CS567 Stochastic Linear/Integer Programming Guest Lecturer: Xu, Huan
Wnter 2008 CS567 Stochastc Lnear/Integer Programmng Guest Lecturer: Xu, Huan Class 2: More Modelng Examples 1 Capacty Expanson Capacty expanson models optmal choces of the tmng and levels of nvestments
More informationLecture 3: Probability Distributions
Lecture 3: Probablty Dstrbutons Random Varables Let us begn by defnng a sample space as a set of outcomes from an experment. We denote ths by S. A random varable s a functon whch maps outcomes nto the
More informationCSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography
CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve
More informationAssortment Optimization under MNL
Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.
More information(1 ) (1 ) 0 (1 ) (1 ) 0
Appendx A Appendx A contans proofs for resubmsson "Contractng Informaton Securty n the Presence of Double oral Hazard" Proof of Lemma 1: Assume that, to the contrary, BS efforts are achevable under a blateral
More information6.854J / J Advanced Algorithms Fall 2008
MIT OpenCourseWare http://ocw.mt.edu 6.854J / 18.415J Advanced Algorthms Fall 2008 For nformaton about ctng these materals or our Terms of Use, vst: http://ocw.mt.edu/terms. 18.415/6.854 Advanced Algorthms
More informationUnit 5: Government policy in competitive markets I E ciency
Unt 5: Government polcy n compettve markets I E cency Prof. Antono Rangel January 2, 2016 1 Pareto optmal allocatons 1.1 Prelmnares Bg pcture Consumers: 1,...,C,eachw/U,W Frms: 1,...,F,eachw/C ( ) Consumers
More informationU.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017
U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that
More informationGame Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India February 2008
Game Theory Lecture Notes By Y. Narahar Department of Computer Scence and Automaton Indan Insttute of Scence Bangalore, Inda February 2008 Chapter 10: Two Person Zero Sum Games Note: Ths s a only a draft
More informationLecture 12: Discrete Laplacian
Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly
More informationTHE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens
THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of
More informationn α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0
MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector
More informationMath1110 (Spring 2009) Prelim 3 - Solutions
Math 1110 (Sprng 2009) Solutons to Prelm 3 (04/21/2009) 1 Queston 1. (16 ponts) Short answer. Math1110 (Sprng 2009) Prelm 3 - Solutons x a 1 (a) (4 ponts) Please evaluate lm, where a and b are postve numbers.
More informationTHE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions
THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructons by George Hardgrove Chemstry Department St. Olaf College Northfeld, MN 55057 hardgrov@lars.acc.stolaf.edu Copyrght George
More informationLINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity
LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased
More informationConjectures in Cournot Duopoly under Cost Uncertainty
Conjectures n Cournot Duopoly under Cost Uncertanty Suyeol Ryu and Iltae Km * Ths paper presents a Cournot duopoly model based on a condton when frms are facng cost uncertanty under rsk neutralty and rsk
More informationCS286r Assign One. Answer Key
CS286r Assgn One Answer Key 1 Game theory 1.1 1.1.1 Let off-equlbrum strateges also be that people contnue to play n Nash equlbrum. Devatng from any Nash equlbrum s a weakly domnated strategy. That s,
More informationEndogenous timing in a mixed oligopoly consisting of a single public firm and foreign competitors. Abstract
Endogenous tmng n a mxed olgopoly consstng o a sngle publc rm and oregn compettors Yuanzhu Lu Chna Economcs and Management Academy, Central Unversty o Fnance and Economcs Abstract We nvestgate endogenous
More informationCHAPTER 6 CONSTRAINED OPTIMIZATION 1: K-T CONDITIONS
Chapter 6: Constraned Optzaton CHAPER 6 CONSRAINED OPIMIZAION : K- CONDIIONS Introducton We now begn our dscusson of gradent-based constraned optzaton. Recall that n Chapter 3 we looked at gradent-based
More informationA Geometric Analysis of Global Profit Maximization for a Two-Product Firm
JOURNAL OF ECONOMICS AND FINANCE EDUCATION Volume 6 Number Summer 007 7 A Geometrc Analyss of Global Proft Maxmzaton for a Two-Product Frm Stephen K. Layson ABSTRACT Ths paper analyzes several fundamental
More informationRadar Trackers. Study Guide. All chapters, problems, examples and page numbers refer to Applied Optimal Estimation, A. Gelb, Ed.
Radar rackers Study Gude All chapters, problems, examples and page numbers refer to Appled Optmal Estmaton, A. Gelb, Ed. Chapter Example.0- Problem Statement wo sensors Each has a sngle nose measurement
More informationChapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise.
Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where y + = β + β e for =,..., y and are observable varables e s a random error How can an estmaton rule be constructed for the
More informationANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)
Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of
More informationWhich Separator? Spring 1
Whch Separator? 6.034 - Sprng 1 Whch Separator? Mamze the margn to closest ponts 6.034 - Sprng Whch Separator? Mamze the margn to closest ponts 6.034 - Sprng 3 Margn of a pont " # y (w $ + b) proportonal
More information6) Derivatives, gradients and Hessian matrices
30C00300 Mathematcal Methods for Economsts (6 cr) 6) Dervatves, gradents and Hessan matrces Smon & Blume chapters: 14, 15 Sldes by: Tmo Kuosmanen 1 Outlne Defnton of dervatve functon Dervatve notatons
More information14 Lagrange Multipliers
Lagrange Multplers 14 Lagrange Multplers The Method of Lagrange Multplers s a powerful technque for constraned optmzaton. Whle t has applcatons far beyond machne learnng t was orgnally developed to solve
More informationLinear Approximation with Regularization and Moving Least Squares
Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...
More informationCredit Card Pricing and Impact of Adverse Selection
Credt Card Prcng and Impact of Adverse Selecton Bo Huang and Lyn C. Thomas Unversty of Southampton Contents Background Aucton model of credt card solctaton - Errors n probablty of beng Good - Errors n
More informatione - c o m p a n i o n
OPERATIONS RESEARCH http://dxdoorg/0287/opre007ec e - c o m p a n o n ONLY AVAILABLE IN ELECTRONIC FORM 202 INFORMS Electronc Companon Generalzed Quantty Competton for Multple Products and Loss of Effcency
More informationChapter 7 Generalized and Weighted Least Squares Estimation. In this method, the deviation between the observed and expected values of
Chapter 7 Generalzed and Weghted Least Squares Estmaton The usual lnear regresson model assumes that all the random error components are dentcally and ndependently dstrbuted wth constant varance. When
More informationThe oligopolistic markets
ernando Branco 006-007 all Quarter Sesson 5 Part II The olgopolstc markets There are a few supplers. Outputs are homogenous or dfferentated. Strategc nteractons are very mportant: Supplers react to each
More informationMarket structure and Innovation
Market structure and Innovaton Ths presentaton s based on the paper Market structure and Innovaton authored by Glenn C. Loury, publshed n The Quarterly Journal of Economcs, Vol. 93, No.3 ( Aug 1979) I.
More informationChapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems
Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons
More informationThree views of mechanics
Three vews of mechancs John Hubbard, n L. Gross s course February 1, 211 1 Introducton A mechancal system s manfold wth a Remannan metrc K : T M R called knetc energy and a functon V : M R called potental
More informationAdditional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty
Addtonal Codes usng Fnte Dfference Method Benamn Moll 1 HJB Equaton for Consumpton-Savng Problem Wthout Uncertanty Before consderng the case wth stochastc ncome n http://www.prnceton.edu/~moll/ HACTproect/HACT_Numercal_Appendx.pdf,
More informationMACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression
11 MACHINE APPLIED MACHINE LEARNING LEARNING MACHINE LEARNING Gaussan Mture Regresson 22 MACHINE APPLIED MACHINE LEARNING LEARNING Bref summary of last week s lecture 33 MACHINE APPLIED MACHINE LEARNING
More informationSome Notes on Consumer Theory
Some Notes on Consumer Theory. Introducton In ths lecture we eamne the theory of dualty n the contet of consumer theory and ts use n the measurement of the benefts of rce and other changes. Dualty s not
More informationLimited Dependent Variables
Lmted Dependent Varables. What f the left-hand sde varable s not a contnuous thng spread from mnus nfnty to plus nfnty? That s, gven a model = f (, β, ε, where a. s bounded below at zero, such as wages
More informationCollege of Computer & Information Science Fall 2009 Northeastern University 20 October 2009
College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmal-dual schema Network Desgn:
More informationPHYS 705: Classical Mechanics. Calculus of Variations II
1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary
More informationx i1 =1 for all i (the constant ).
Chapter 5 The Multple Regresson Model Consder an economc model where the dependent varable s a functon of K explanatory varables. The economc model has the form: y = f ( x,x,..., ) xk Approxmate ths by
More informationLecture 21: Numerical methods for pricing American type derivatives
Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)
More informationOnline Appendix: Reciprocity with Many Goods
T D T A : O A Kyle Bagwell Stanford Unversty and NBER Robert W. Stager Dartmouth College and NBER March 2016 Abstract Ths onlne Appendx extends to a many-good settng the man features of recprocty emphaszed
More informationLecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2
P470 Lecture 6/7 (February 10/1, 014) DIRAC EQUATION The non-relatvstc Schrödnger equaton was obtaned by notng that the Hamltonan H = P (1) m can be transformed nto an operator form wth the substtutons
More informatione i is a random error
Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where + β + β e for,..., and are observable varables e s a random error How can an estmaton rule be constructed for the unknown
More informationOnline Appendix for Trade and Insecure Resources
B Onlne ppendx for Trade and Insecure Resources Proof of Lemma.: Followng Jones 965, we denote the shares of factor h = K, L n the cost of producng good j =, 2 by θ hj : θ Kj = r a Kj /c j and θ Lj = w
More informationCOS 521: Advanced Algorithms Game Theory and Linear Programming
COS 521: Advanced Algorthms Game Theory and Lnear Programmng Moses Charkar February 27, 2013 In these notes, we ntroduce some basc concepts n game theory and lnear programmng (LP). We show a connecton
More informationGames and Market Imperfections
Games and Market Imperfectons Q: The mxed complementarty (MCP) framework s effectve for modelng perfect markets, but can t handle mperfect markets? A: At least part of the tme A partcular type of game/market
More information1 GSW Iterative Techniques for y = Ax
1 for y = A I m gong to cheat here. here are a lot of teratve technques that can be used to solve the general case of a set of smultaneous equatons (wrtten n the matr form as y = A), but ths chapter sn
More informationNorm Bounds for a Transformed Activity Level. Vector in Sraffian Systems: A Dual Exercise
ppled Mathematcal Scences, Vol. 4, 200, no. 60, 2955-296 Norm Bounds for a ransformed ctvty Level Vector n Sraffan Systems: Dual Exercse Nkolaos Rodousaks Department of Publc dmnstraton, Panteon Unversty
More informationPhysics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1
P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the
More informationModule 9. Lecture 6. Duality in Assignment Problems
Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept
More informationPROBABILITY PRIMER. Exercise Solutions
PROBABILITY PRIMER Exercse Solutons 1 Probablty Prmer, Exercse Solutons, Prncples of Econometrcs, e EXERCISE P.1 (b) X s a random varable because attendance s not known pror to the outdoor concert. Before
More informationECE559VV Project Report
ECE559VV Project Report (Supplementary Notes Loc Xuan Bu I. MAX SUM-RATE SCHEDULING: THE UPLINK CASE We have seen (n the presentaton that, for downlnk (broadcast channels, the strategy maxmzng the sum-rate
More informationLossy Compression. Compromise accuracy of reconstruction for increased compression.
Lossy Compresson Compromse accuracy of reconstructon for ncreased compresson. The reconstructon s usually vsbly ndstngushable from the orgnal mage. Typcally, one can get up to 0:1 compresson wth almost
More informationFrom Biot-Savart Law to Divergence of B (1)
From Bot-Savart Law to Dvergence of B (1) Let s prove that Bot-Savart gves us B (r ) = 0 for an arbtrary current densty. Frst take the dvergence of both sdes of Bot-Savart. The dervatve s wth respect to
More information