Delhi School of Economics Course 001: Microeconomic Theory Solutions to Problem Set 2.
|
|
- Justina Nash
- 5 years ago
- Views:
Transcription
1 Delh School of Economcs Corse 00: Mcroeconomc Theor Soltons to Problem Set.. Propertes of % extend to and. (a) Assme x x x. Ths mples: x % x % x ) x % x. Now sppose x % x. Combned wth x % x and transtvt of %, we get x % x, whch contradcts the fact that x x. Hence t s not tre that x % x. Combnng, we get x x. (b) x x x ) x % x % x ) x % x. x x x ) x % x % x ) x % x. Combnng, we get x x.. x x x ) x % x % x ) x % x. (a) Sppose x % x. Combned wth x % x and transtvt of %, we get x % x, whch contradcts the fact that x x. Hence t s not tre that x % x. Combnng, we get x x.. The contnt axom s volated. Consder the followng seqence of bndles: (x n ; x n ) (a; 0) and ( n ; n ) (a n ; b), where a; b > 0. For the preferences descrbed, (xn ; x n ) ( n ; n ) for an n. However, (x n ; x n ) (a; 0) and ( n ; n ) (a; b). Then (a; b) (a; 0),.e., preference s reversed n the lmt, whch s a volaton of contnt. These preferences cannot be represented b a contnos tlt fncton. 4. Ths s the Stone-gear tlt fncton. (a) After power and log transformatons: + (b) Solton wll be nteror. From the condton MRS prce rato, we get x p x The other eqaton s that of the bdget lne: p x + x Solvng these two eqatons gves s the Marshallan demand fnctons: 5. I wll skp some of the easer detals. x + p p x + p (a) For Cobb-Doglas preferences, note that MU as x 0, hence the solton wll alwas be nteror for an strctl postve prce vector. Also, snce the tlt fncton s strctl qasconcave, SOC wll alwas be sats ed. The FOC, sng the standard tangenc condton (MRS prce rato) gves x j p j x p j
2 Ths can be rewrtten as p x k for all () where k s some constant. The vale of k can be solved b sng the above n the bdget constrant: nx nx k ) k snce Usng ths n (), we get the Marshallan demand fnctons: x (p; ) p Plggng back these demands n the tlt fncton and smplfng, we get the ndrect tlt fncton: v(p; ) p For the dal problem (expendtre mnmzaton), () mst stll be sats ed bt the vale of k wll be d erent. To nd ths vale, nsert () nto the constrant of the problem to get p k Upon replacng back n (), we get the Hcksan demand fnctons: p x h (p; ) Plggng back these expressons nto the expresson for spendng,.e., n P n p x h, we get the expendtre fncton e(p; ) p (b) The tlt fncton s of a pecewse lnear form: p (x ; x ) ax + x for x x x + ax for x > x The slopes above and below the 45-degree lne are a and a respectvel. If a >, the nd erence crves are concave to the orgn. In ths case, optmal soltons wll alwas be at a corner. Leavng the detals to o, I wll focs on the case of convex preferences (a < ). Here, the optmal choce s ether at a corner or at the knk, dependng on the slope of the bdget lne. Spec call, Marshallan demands are gven b (x ; x ) 0; p > a ; f a < p < p + p + a ; 0 < a p In the case where the prce rato s ether a or a, the bdget lne concdes wth one of the arms of the nd erence crve and an choce on that arm s optmal. The ndrect tlt fncton s v(p; ) a > a (a + ) f a < p < p + a a < a p
3 The Hcksan demand fnctons are The expendtre fnctons s (x h ; x h ) e(p; ) a 0; > a a a + ; f a < p < a + a a ; 0 > a > a (p + ) a + p a > a f a < p < a (c) The tlt fnctons are concave to the orgn, hence the pont of tangenc represents a mnmm rather than a mm. Obvosl there wll be a corner solton. Marshallan Demand fnctons are: (x ; x ) ; 0 < p 0; p > When p, ether corner s optmal. Indrect tlt fncton: v(p; ) > Hcksan demand fnctons: Expendtre fncton: x h ; x h p ; 0 < 0; p > e(p; ) p p f p p f p > (d) Ths s the case of perfect sbstttes whch elds corner soltons for almost all prce vectors (draw the pctre). Marshallan demands are: (x ; x ) 0; p > a b The ndrect tlt fncton s ; 0 p < a b v(p; ) b a b a p < a b
4 The Hcksan demands are: x h ; x h 0; b a ; 0 > a b < a b The expendtre fncton s e(p; ) b p a a b < a b (e) Frst, focs on cases where there s an nteror.solton. Applng the prncple M RS prce rato, we get + x p + x Combnng wth the eqaton of the bdget lne, we get the Marshallan demands p + (x ; x ) ; p + p p Stckng wth the nteror solton case, the other fnctons are eas to derve (o can explot the smmetr to smplf calclatons): x h ; x h v(p; ) + (p + ) p e(p; ) p p ( + ) s s ( + ) p ( + ) ; p Some caveat has to be added to the solton, however. Sometmes, there wll be corner soltons. Note from the Marshallan demand expressons above, whenever < p, we have x < 0. Ths s nadmssble snce negatve qanttes are not allowed. In ths case, the optmal choce wll nvolve x 0 and all the ncome spent on good,.e., x. The opposte corner solton arses whenever < p. A compact and accrate descrpton of the Marshallan demands wll then be p + x (p; ) 0; mn ; p p p + p x (p; ) 0; mn ; The other fnctons have to be smlarl adjsted to take accont of corner soltons. The detals are ommtted. 6. Frst, we arge that wth addtvel separable tlt, all goods mst be normal goods. Sppose x falls when ncome goes p. For an par (; j), the FOC s 0 (x ) 0 j (x j) p p j If x decreases, b concavt, x j mst also decrease to keep the MRS constant (remember prces haven t changed, onl ncome). Hence, f an one good s nferor, all goods are nferor. Bt ths volates the monotonct axom, so we have a contradcton. Hence none of the goods can be nferor. The argment s completed b notng onl nferor goods can be G en goods. 4
5 7. The agent solves (takng log transformaton of the tlt fncton to smplf calclatons): sbject to the bdget constrant L;F m + w(t ln L + ln F L) pf Sbstttng ths nto the objectve fncton, the problem redces to L and the FOC for nteror solton s ln L + ln [m + w(t L)] ln p L w m + w(t L ) The solton for optmal choce of lesre s m + wt L mn w ; T snce total lesre cannot exceed the tme endowment T. Therefor labor sppl (T wt m ; 0 w L ) s gven b For strctl postve labor sppl, we need w > m T The agent needs a hgh enogh wage and ns cent non-wage ncome to be wllng to work. Food demand s obtaned b replacng (T L ) n the bdget constrant: F p (wt + m); m 8. The agent s problem s (agan takng log transformaton): sbject to the bdget constrant x ;x ln x + ( ) ln x p x + x 5p + Usal tangenc condton (MRS prce rato) gves x ( )x p (a) Usng ths n the eaton for the bdget lne, we get the demands: x (5p + ) p x ( ) (5p + ) (b) The agent s a net ber of good f x > 5,.e., p < 5( ) 5
6 9. Ths exercse focses on the cash-vs-knd debate. The man pont s that the best means of delverng ad depends on whether the donor jdges the recpent s welfare b the recpent s preferences (welfarsm) or the donor s (paternalsm). (a) The tlt fncton can be transformed nto: whch gves rse to demand fnctons (x; ) x I x(p x ; p ; I) p x (p x ; p ; I) I p Indrect tlt s obtaned b sbstttng demands nto the tlt fncton: (b) From the demand fnctons: x,. I v(p x ; p ; I) (p x ) (p ) (c) Let the sbsd be s per school. Banana Repblc s demand fnctons become: I x(p x ; p ; I) (p x s) (p x ; p ; I) I p Here s 0. Usng ths, we can calclate: x 4,. The vale of the sbsd s xs 40. The tlt attaned s 6. (d) Calclate the expendtre fncton for these preferences: The FOC are Solvng, we get the Hcksan demand fnctons e(p x ; p ; ) mn (p x x + p ) sb to x : x p x p and x x(p x ; p ; ) (p x ; p ; ) p p x px p Usng these expressons gves s the expendtre fncton e(p x ; p ; ) + (p x ) (p ) : Insert the prces and target tlt ( 6 ) to calclate the mnmm expendtre. The d erence between ths amont and the ncome I 0 s the cash grant that wll be necessar. Show that ths s less than the 40 Bleedng Heart was spendng n sbsdes. (e) For an cash award c, the demand fncton for schools wold become x(p x ; p ; I) I + c p x To ncrease the demand for schools from to 4, we mst have c 0, whch s mch more than the 40 spent b the agenc nder the sbsd scheme. 6
7 0. Ths qeston tres to nderstand the e ect of tax rates and laws on chartable donatons. (a) It s eas to show that at the optmm: x ( t) x ( )( t) A tax cts ncreases chartable donatons becase t has a pre ncome e ect. (b) The problem can be wrtten as ln x + ( ) ln x sbject to x + x ( t) + tx The bdget constrant can be rewrtten as x t + x where t can be nterpreted as the prce of own consmpton n the sense of opportnt cost (the amont of chartable donatons forgone for ever rpee spent on own needs). Ths gves rse to optmal choces: x ( t) x ( ) (c) A tax ct makes own consmpton cheaper and hence the sbsttton e ect tends to ncrease sel sh spendng and redce donatons. However, the tax ct also leaves more dsposable ncome n the agent s pocket and so the ncome e ect tends to ncrease donatons. For Cobb-Doglas tlt, the two e ects exactl cancel each other ot. (d) Yes. It s the propert that nder Cobb-Doglas preferences, total spendng on each good s a constant. In general, ncome and sbsttton e ects ma not cancel ot exactl and the e ect of tax cts (when donatons are tax dedctble) wold be theoretcall ambgos. 7
Solutions to selected problems from homework 1.
Jan Hagemejer 1 Soltons to selected problems from homeork 1. Qeston 1 Let be a tlty fncton hch generates demand fncton xp, ) and ndrect tlty fncton vp, ). Let F : R R be a strctly ncreasng fncton. If the
More informationAE/ME 339. K. M. Isaac. 8/31/2004 topic4: Implicit method, Stability, ADI method. Computational Fluid Dynamics (AE/ME 339) MAEEM Dept.
AE/ME 339 Comptatonal Fld Dynamcs (CFD) Comptatonal Fld Dynamcs (AE/ME 339) Implct form of dfference eqaton In the prevos explct method, the solton at tme level n,,n, depended only on the known vales of,
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 informationComplex Numbers Practice 0708 & SP 1. The complex number z is defined by
IB Math Hgh Leel: Complex Nmbers Practce 0708 & SP Complex Nmbers Practce 0708 & SP. The complex nmber z s defned by π π π π z = sn sn. 6 6 Ale - Desert Academy (a) Express z n the form re, where r and
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 informationMathematics Intersection of Lines
a place of mnd F A C U L T Y O F E D U C A T I O N Department of Currculum and Pedagog Mathematcs Intersecton of Lnes Scence and Mathematcs Educaton Research Group Supported b UBC Teachng and Learnng Enhancement
More informationC PLANE ELASTICITY PROBLEM FORMULATIONS
C M.. Tamn, CSMLab, UTM Corse Content: A ITRODUCTIO AD OVERVIEW mercal method and Compter-Aded Engneerng; Phscal problems; Mathematcal models; Fnte element method. B REVIEW OF -D FORMULATIOS Elements and
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 informationBAR & TRUSS FINITE ELEMENT. Direct Stiffness Method
BAR & TRUSS FINITE ELEMENT Drect Stness Method FINITE ELEMENT ANALYSIS AND APPLICATIONS INTRODUCTION TO FINITE ELEMENT METHOD What s the nte element method (FEM)? A technqe or obtanng approxmate soltons
More informationC PLANE ELASTICITY PROBLEM FORMULATIONS
C M.. Tamn, CSMLab, UTM Corse Content: A ITRODUCTIO AD OVERVIEW mercal method and Compter-Aded Engneerng; Phscal problems; Mathematcal models; Fnte element method. B REVIEW OF -D FORMULATIOS Elements and
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 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 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 informationConsumer Theory. 1 Consumption set. 2 Preferences and utility. These notes essentially correspond to chapter 1 of Jehle and Reny.
Consumer Theor These notes essentall correspond to chapter of Jehle and Ren. Consumpton set The consumpton set, denoted X, s the set of all possble combnatons of goods and servces that a consumer could
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 informationSolutions to Homework 7, Mathematics 1. 1 x. (arccos x) (arccos x) 1
Solutons to Homework 7, Mathematcs 1 Problem 1: a Prove that arccos 1 1 for 1, 1. b* Startng from the defnton of the dervatve, prove that arccos + 1, arccos 1. Hnt: For arccos arccos π + 1, the defnton
More informationBruce A. Draper & J. Ross Beveridge, January 25, Geometric Image Manipulation. Lecture #1 January 25, 2013
Brce A. Draper & J. Ross Beerdge, Janar 5, Geometrc Image Manplaton Lectre # Janar 5, Brce A. Draper & J. Ross Beerdge, Janar 5, Image Manplaton: Contet To start wth the obos, an mage s a D arra of pels
More informationWelfare 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 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 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 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 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 informationEMISSION MEASUREMENTS IN DUAL FUELED INTERNAL COMBUSTION ENGINE TESTS
XVIII IEKO WORLD NGRESS etrology for a Sstanable Development September, 17, 006, Ro de Janero, Brazl EISSION EASUREENTS IN DUAL FUELED INTERNAL BUSTION ENGINE TESTS A.F.Orlando 1, E.Santos, L.G.do Val
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 informationSIMPLE LINEAR REGRESSION
Smple Lnear Regresson and Correlaton Introducton Prevousl, our attenton has been focused on one varable whch we desgnated b x. Frequentl, t s desrable to learn somethng about the relatonshp between two
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 informationSELECTED SOLUTIONS, SECTION (Weak duality) Prove that the primal and dual values p and d defined by equations (4.3.2) and (4.3.3) satisfy p d.
SELECTED SOLUTIONS, SECTION 4.3 1. Weak dualty Prove that the prmal and dual values p and d defned by equatons 4.3. and 4.3.3 satsfy p d. We consder an optmzaton problem of the form The Lagrangan for ths
More informationprinceton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg
prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there
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 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 informationOPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming
OPTIMIATION Introducton ngle Varable Unconstraned Optmsaton Multvarable Unconstraned Optmsaton Lnear Programmng Chapter Optmsaton /. Introducton In an engneerng analss, sometmes etremtes, ether mnmum or
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 informationAffine transformations and convexity
Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/
More informationComplex Variables. Chapter 18 Integration in the Complex Plane. March 12, 2013 Lecturer: Shih-Yuan Chen
omplex Varables hapter 8 Integraton n the omplex Plane March, Lecturer: Shh-Yuan hen Except where otherwse noted, content s lcensed under a BY-N-SA. TW Lcense. ontents ontour ntegrals auchy-goursat theorem
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 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 informationThe Fundamental Theorem of Algebra. Objective To use the Fundamental Theorem of Algebra to solve polynomial equations with complex solutions
5-6 The Fundamental Theorem of Algebra Content Standards N.CN.7 Solve quadratc equatons wth real coeffcents that have comple solutons. N.CN.8 Etend polnomal denttes to the comple numbers. Also N.CN.9,
More informationChapter 9: Statistical Inference and the Relationship between Two Variables
Chapter 9: Statstcal Inference and the Relatonshp between Two Varables Key Words The Regresson Model The Sample Regresson Equaton The Pearson Correlaton Coeffcent Learnng Outcomes After studyng ths chapter,
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 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 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 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 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 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 informationPhysics 4B. A positive value is obtained, so the current is counterclockwise around the circuit.
Physcs 4B Solutons to Chapter 7 HW Chapter 7: Questons:, 8, 0 Problems:,,, 45, 48,,, 7, 9 Queston 7- (a) no (b) yes (c) all te Queston 7-8 0 μc Queston 7-0, c;, a;, d; 4, b Problem 7- (a) Let be the current
More informationThe Bellman Equation
The Bellman Eqaton Reza Shadmehr In ths docment I wll rovde an elanaton of the Bellman eqaton, whch s a method for otmzng a cost fncton and arrvng at a control olcy.. Eamle of a game Sose that or states
More informationXiangwen Li. March 8th and March 13th, 2001
CS49I Approxaton Algorths The Vertex-Cover Proble Lecture Notes Xangwen L March 8th and March 3th, 00 Absolute Approxaton Gven an optzaton proble P, an algorth A s an approxaton algorth for P f, for an
More informationCase A. P k = Ni ( 2L i k 1 ) + (# big cells) 10d 2 P k.
THE CELLULAR METHOD In ths lecture, we ntroduce the cellular method as an approach to ncdence geometry theorems lke the Szemeréd-Trotter theorem. The method was ntroduced n the paper Combnatoral complexty
More informationESS 265 Spring Quarter 2005 Time Series Analysis: Error Analysis
ESS 65 Sprng Qarter 005 Tme Seres Analyss: Error Analyss Lectre 9 May 3, 005 Some omenclatre Systematc errors Reprodcbly errors that reslt from calbraton errors or bas on the part of the obserer. Sometmes
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 informationPreference and Demand Examples
Dvson of the Huantes and Socal Scences Preference and Deand Exaples KC Border October, 2002 Revsed Noveber 206 These notes show how to use the Lagrange Karush Kuhn Tucker ultpler theores to solve the proble
More informationAPPENDIX A Some Linear Algebra
APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,
More informationThe Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction
ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also
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 informationNotes on Analytical Dynamics
Notes on Analytcal Dynamcs Jan Peters & Mchael Mstry October 7, 004 Newtonan Mechancs Basc Asssumptons and Newtons Laws Lonely pontmasses wth postve mass Newtons st: Constant velocty v n an nertal frame
More informationEQUATION CHAPTER 1 SECTION 1STRAIN IN A CONTINUOUS MEDIUM
EQUTION HPTER SETION STRIN IN ONTINUOUS MEIUM ontent Introdcton One dmensonal stran Two-dmensonal stran Three-dmensonal stran ondtons for homogenety n two-dmensons n eample of deformaton of a lne Infntesmal
More informationWhat is LP? LP is an optimization technique that allocates limited resources among competing activities in the best possible manner.
(C) 998 Gerald B Sheblé, all rghts reserved Lnear Prograng Introducton Contents I. What s LP? II. LP Theor III. The Splex Method IV. Refneents to the Splex Method What s LP? LP s an optzaton technque that
More informationPhysics 2A Chapter 3 HW Solutions
Phscs A Chapter 3 HW Solutons Chapter 3 Conceptual Queston: 4, 6, 8, Problems: 5,, 8, 7, 3, 44, 46, 69, 70, 73 Q3.4. Reason: (a) C = A+ B onl A and B are n the same drecton. Sze does not matter. (b) C
More informationExact Solutions for Nonlinear D-S Equation by Two Known Sub-ODE Methods
Internatonal Conference on Compter Technology and Scence (ICCTS ) IPCSIT vol. 47 () () IACSIT Press, Sngapore DOI:.7763/IPCSIT..V47.64 Exact Soltons for Nonlnear D-S Eqaton by Two Known Sb-ODE Methods
More informationRockefeller College University at Albany
Rockefeller College Unverst at Alban PAD 705 Handout: Maxmum Lkelhood Estmaton Orgnal b Davd A. Wse John F. Kenned School of Government, Harvard Unverst Modfcatons b R. Karl Rethemeer Up to ths pont n
More informationUtility maximization. Conditions for utility maximization. Consumer theory: Utility maximization and expenditure minimization
Consmer theory: Utlty mmzton nd ependtre mnmzton Lectres n Mcroeconomc Theory Fll 006 Prt 7 0006 GB Ashem ECON430-35 #7 Utlty mmzton Assme prce-tng ehvor n good mrets m p Bdget set : { X p m} where m s
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 informationInner Product. Euclidean Space. Orthonormal Basis. Orthogonal
Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,
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 informationResource Allocation and Decision Analysis (ECON 8010) Spring 2014 Foundations of Regression Analysis
Resource Allocaton and Decson Analss (ECON 800) Sprng 04 Foundatons of Regresson Analss Readng: Regresson Analss (ECON 800 Coursepak, Page 3) Defntons and Concepts: Regresson Analss statstcal technques
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 informationCentre for Efficiency and Productivity Analysis
Centre for Effcency and Prodctty Analyss Workng Paper Seres No. WP/7 Ttle On The Dstrbton of Estmated Techncal Effcency n Stochastc Fronter Models Athors We Sang Wang & Peter Schmdt Date: May, 7 School
More informationExpected Value and Variance
MATH 38 Expected Value and Varance Dr. Neal, WKU We now shall dscuss how to fnd the average and standard devaton of a random varable X. Expected Value Defnton. The expected value (or average value, or
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 informationMore metrics on cartesian products
More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of
More informationThe Existence and Optimality of Equilibrium
The Exstence and Optmalty of Equlbrum Larry Blume March 29, 2006 1 Introducton These notes quckly survey two approaches to the exstence. The frst approach works wth excess demand, whle the second works
More informationCOMPLEX NUMBERS AND QUADRATIC EQUATIONS
COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not
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 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 information1 i. δ ε. so all the estimators will be biased; in fact, the less correlated w. (i.e., more correlated to ε. is perfectly correlated to x 4 i.
Specal Topcs I. Use Instrmental Varable to F Specfcaton Problem (e.g., omtted varable 3 3 Assme we don't have data on If s correlated to,, or s mssng from the regresson Tradtonal Solton - pro varable:
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 informationCHAPTER 4. Vector Spaces
man 2007/2/16 page 234 CHAPTER 4 Vector Spaces To crtcze mathematcs for ts abstracton s to mss the pont entrel. Abstracton s what makes mathematcs work. Ian Stewart The man am of ths tet s to stud lnear
More informationCanonical transformations
Canoncal transformatons November 23, 2014 Recall that we have defned a symplectc transformaton to be any lnear transformaton M A B leavng the symplectc form nvarant, Ω AB M A CM B DΩ CD Coordnate transformatons,
More informationKinematics in 2-Dimensions. Projectile Motion
Knematcs n -Dmensons Projectle Moton A medeval trebuchet b Kolderer, c1507 http://members.net.net.au/~rmne/ht/ht0.html#5 Readng Assgnment: Chapter 4, Sectons -6 Introducton: In medeval das, people had
More informationÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE
ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE School of Computer and Communcaton Scences Handout 0 Prncples of Dgtal Communcatons Solutons to Problem Set 4 Mar. 6, 08 Soluton. If H = 0, we have Y = Z Z = Y
More informationMAE140 - Linear Circuits - Fall 13 Midterm, October 31
Instructons ME140 - Lnear Crcuts - Fall 13 Mdterm, October 31 () Ths exam s open book. You may use whatever wrtten materals you choose, ncludng your class notes and textbook. You may use a hand calculator
More informationPerron Vectors of an Irreducible Nonnegative Interval Matrix
Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of
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 informationG4023 Mid-Term Exam #1 Solutions
Exam1Solutons.nb 1 G03 Md-Term Exam #1 Solutons 1-Oct-0, 1:10 p.m to :5 p.m n 1 Pupn Ths exam s open-book, open-notes. You may also use prnt-outs of the homework solutons and a calculator. 1 (30 ponts,
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 informationComplex Numbers. x = B B 2 4AC 2A. or x = x = 2 ± 4 4 (1) (5) 2 (1)
Complex Numbers If you have not yet encountered complex numbers, you wll soon do so n the process of solvng quadratc equatons. The general quadratc equaton Ax + Bx + C 0 has solutons x B + B 4AC A For
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 informationLecture 4: November 17, Part 1 Single Buffer Management
Lecturer: Ad Rosén Algorthms for the anagement of Networs Fall 2003-2004 Lecture 4: November 7, 2003 Scrbe: Guy Grebla Part Sngle Buffer anagement In the prevous lecture we taled about the Combned Input
More informationBernoulli Numbers and Polynomials
Bernoull Numbers and Polynomals T. Muthukumar tmk@tk.ac.n 17 Jun 2014 The sum of frst n natural numbers 1, 2, 3,..., n s n n(n + 1 S 1 (n := m = = n2 2 2 + n 2. Ths formula can be derved by notng that
More informationCHAPTER-5 INFORMATION MEASURE OF FUZZY MATRIX AND FUZZY BINARY RELATION
CAPTER- INFORMATION MEASURE OF FUZZY MATRI AN FUZZY BINARY RELATION Introducton The basc concept of the fuzz matr theor s ver smple and can be appled to socal and natural stuatons A branch of fuzz matr
More information(2mn, m 2 n 2, m 2 + n 2 )
MATH 16T Homewk Solutons 1. Recall that a natural number n N s a perfect square f n = m f some m N. a) Let n = p α even f = 1,,..., k. be the prme factzaton of some n. Prove that n s a perfect square f
More informationPhysics 5153 Classical Mechanics. Principle of Virtual Work-1
P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal
More informationMMA and GCMMA two methods for nonlinear optimization
MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons
More informationUsing Spectrophotometric Methods to Determine an Equilibrium Constant Prelab
Usng Spectrophotometrc Methods to Determne an Equlbrum Constant Prelab 1. What s the purpose of ths experment? 2. Wll the absorbance of the ulbrum mxture (at 447 nm) ncrease or decrease as Fe soluton s
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 informationExercise 1 The General Linear Model : Answers
Eercse The General Lnear Model Answers. Gven the followng nformaton on 67 pars of values on and -.6 - - - 9 a fnd the OLS coeffcent estmate from a regresson of on. Usng b 9 So. 9 b Suppose that now also
More informationWeek 2. This week, we covered operations on sets and cardinality.
Week 2 Ths week, we covered operatons on sets and cardnalty. Defnton 0.1 (Correspondence). A correspondence between two sets A and B s a set S contaned n A B = {(a, b) a A, b B}. A correspondence from
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 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 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 information