CHAPTER 3: OPTIMIZATION

Similar documents
Microeconomic Theory -1- Introduction

CHAPTER 1-2: SHADOW PRICES

Walrasian Equilibrium in an exchange economy

1.4 FOUNDATIONS OF CONSTRAINED OPTIMIZATION

Economics 205 Exercises

Mathematical Foundations -1- Constrained Optimization. Constrained Optimization. An intuitive approach 2. First Order Conditions (FOC) 7

The Kuhn-Tucker and Envelope Theorems

3.2 THE FUNDAMENTAL WELFARE THEOREMS

It is convenient to introduce some notation for this type of problems. I will write this as. max u (x 1 ; x 2 ) subj. to. p 1 x 1 + p 2 x 2 m ;

The Kuhn-Tucker and Envelope Theorems

STATIC LECTURE 4: CONSTRAINED OPTIMIZATION II - KUHN TUCKER THEORY

is a maximizer. However this is not the case. We will now give a graphical argument explaining why argue a further condition must be satisfied.

Mathematics Review For GSB 420. Instructor: Tim Opiela

14 March 2018 Module 1: Marginal analysis and single variable calculus John Riley. ( x, f ( x )) are the convex combinations of these two

Mathematical Foundations II

, αβ, > 0 is strictly quasi-concave on

INTRODUCTORY MATHEMATICS FOR ECONOMICS MSCS. LECTURE 3: MULTIVARIABLE FUNCTIONS AND CONSTRAINED OPTIMIZATION. HUW DAVID DIXON CARDIFF BUSINESS SCHOOL.

Chapter 2 THE MATHEMATICS OF OPTIMIZATION. Copyright 2005 by South-Western, a division of Thomson Learning. All rights reserved.

1. Sets A set is any collection of elements. Examples: - the set of even numbers between zero and the set of colors on the national flag.

Gi en Demand for Several Goods

Basic mathematics of economic models. 3. Maximization

Exercise 2: Equivalence of the first two definitions for a differentiable function. is a convex combination of

Section A (Basic algebra and calculus multiple choice)

Exercises - SOLUTIONS UEC Advanced Microeconomics, Fall 2018 Instructor: Dusan Drabik, de Leeuwenborch 2105

ε and ε > 0 we can find a δ > 0 such that

Question 1. (8 points) The following diagram shows the graphs of eight equations.

September Math Course: First Order Derivative

Math 1325 Final Exam Review. (Set it up, but do not simplify) lim

3. THE EXCHANGE ECONOMY

Test code: ME I/ME II, 2004 Syllabus for ME I. Matrix Algebra: Matrices and Vectors, Matrix Operations, Determinants,

Econ Slides from Lecture 10

Universidad Carlos III de Madrid

Introduction to General Equilibrium: Framework.

Chiang/Wainwright: Fundamental Methods of Mathematical Economics

Graphing and Optimization

QUADRATIC FUNCTIONS. ( x 7)(5x 6) = 2. Exercises: 1 3x 5 Sum: 8. We ll expand it by using the distributive property; 9. Let s use the FOIL method;

Economics 501B Final Exam Fall 2017 Solutions

THE INSTITUTE OF FINANCE MANAGEMENT (IFM) Department of Mathematics. Mathematics 01 MTU Elements of Calculus in Economics

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems

GARP and Afriat s Theorem Production

Urban Economics. Yves Zenou Research Institute of Industrial Economics. July 17, 2006

Microeconomic Theory-I Washington State University Midterm Exam #1 - Answer key. Fall 2016

3 Additional Applications of the Derivative

MATH 1325 Business Calculus Guided Notes

The questions listed below are drawn from midterm and final exams from the last few years at OSU. As the text book and structure of the class have

Equilibrium in a Production Economy

Properties of Walrasian Demand

You are responsible for upholding the University of Maryland Honor Code while taking this exam.

You are responsible for upholding the University of Maryland Honor Code while taking this exam.

Microeconomic Theory. Microeconomic Theory. Everyday Economics. The Course:

Firms and returns to scale -1- John Riley

EC487 Advanced Microeconomics, Part I: Lecture 2

Name: MA 160 Dr. Katiraie (100 points) Test #3 Spring 2013

Calculus One variable

Part 2A. 3. Indifference Curves

Part I Analysis in Economics

The Ohio State University Department of Economics. Homework Set Questions and Answers

Economics 101. Lecture 2 - The Walrasian Model and Consumer Choice

Optimization Methods: Optimization using Calculus - Equality constraints 1. Module 2 Lecture Notes 4

Optimization, constrained optimization and applications of integrals.

Index. Cambridge University Press An Introduction to Mathematics for Economics Akihito Asano. Index.

BEE1004 / BEE1005 UNIVERSITY OF EXETER FACULTY OF UNDERGRADUATE STUDIES SCHOOL OF BUSINESS AND ECONOMICS. January 2002

to maximize a function

Simplifying this, we obtain the following set of PE allocations: (x E ; x W ) 2

Mathematical Foundations -1- Convexity and quasi-convexity. Convex set Convex function Concave function Quasi-concave function Supporting hyperplane

Hicksian Demand and Expenditure Function Duality, Slutsky Equation

Microeconomics II. MOSEC, LUISS Guido Carli Problem Set n 3

ECONOMIC OPTIMALITY. Date: October 10, 2005.

Practice Questions for Mid-Term I. Question 1: Consider the Cobb-Douglas production function in intensive form:

3. Neoclassical Demand Theory. 3.1 Preferences

Solutions. ams 11b Study Guide 9 econ 11b

BARUCH COLLEGE MATH 2207 FALL 2007 MANUAL FOR THE UNIFORM FINAL EXAMINATION. No calculator will be allowed on this part.

Rice University. Answer Key to Mid-Semester Examination Fall ECON 501: Advanced Microeconomic Theory. Part A

Department of Economics The Ohio State University Final Exam Questions and Answers Econ 8712

New Notes on the Solow Growth Model

ECON501 - Vector Di erentiation Simon Grant

Equilibrium and Pareto Efficiency in an exchange economy

If C(x) is the total cost (in dollars) of producing x items of a product, then

Firms and returns to scale -1- Firms and returns to scale

Monetary Economics: Solutions Problem Set 1

Universidad Carlos III de Madrid

Optimization Paul Schrimpf September 12, 2018

Econ 401A: Economic Theory Mid-term. Answers

Optimization. A first course on mathematics for economists

The Envelope Theorem

General Equilibrium. General Equilibrium, Berardino. Cesi, MSc Tor Vergata

Chapter 1. Functions, Graphs, and Limits

Chiang/Wainwright: Fundamental Methods of Mathematical Economics

Week 6: Consumer Theory Part 1 (Jehle and Reny, Chapter 1)

IMPORTANT NOTES HERE IS AN EXAMPLE OF A SCANTRON FORM FOR YOUR EXAM.

Comments on Problems. 3.1 This problem offers some practice in deriving utility functions from indifference curve specifications.

Lecture 05 Cost Concepts for Decision Making. C r = MRTS LK, w MPL

EconS 501 Final Exam - December 10th, 2018

AP Exam Practice Questions for Chapter 3

Lecture 1: Labour Economics and Wage-Setting Theory

Math 115 Second Midterm November 12, 2018

PhD Qualifier Examination

Econ 101A Midterm 1 Th 29 September 2004.

Mathematical Foundations -1- Supporting hyperplanes. SUPPORTING HYPERPLANES Key Ideas: Bounding hyperplane for a convex set, supporting hyperplane

f x (prime notation) d dx

Transcription:

John Riley 8 February 7 CHAPTER 3: OPTIMIZATION 3. TWO VARIABLES 8 Second Order Conditions Implicit Function Theorem 3. UNCONSTRAINED OPTIMIZATION 4 Necessary and Sufficient Conditions 3.3 CONSTRAINED OPTIMIZATION- an intuitive approach 4 FOC for a Constrained Maimum Sufficient Conditions 3.4 THE ENVELOPE THEOREM 8 4 pages

John Riley March 7 3. TWO VARIABLES Rather than leap directly to the analysis of multi-variable optimization problems we begin by eamining the two variable case. Maimization Suppose that the function f takes on its maimum over R at = (, ). Taking one variable at a time, we know that each of the first partial derivatives must be zero and each of the second partial derivatives must be negative. To obtain a further necessary condition we consider the change in f as changes from.we do this by considering the weighted average λ of λ = ( λ) + λ = + λ( ), in the direction of some other vector and, that is and define g( λ) = f ( + λ( ). This function is depicted below. f g( λ ) O λ ( b, b ) Fig. 3.-: Cross-section of f The mapping, g( λ ), depicted in the cross-section is a function from R into R. Then we can appeal to the necessary conditions for one-variable maimization. In particular, for a maimum at derivative of g is, the second derivative of g( λ) must be negative at λ =. The first Section 3. page

John Riley March 7 g ( λ) = ( ) z + ( ) z, where λ λ z. For a maimum this must be zero for all z, hence the partial derivatives must both be zero. Differentiating again, f λ f λ f λ g ( λ) = z ( ) + z z ( ) + z ( ) = [ z z ] f f z z f f Note that the right hand side of the last equation is a quadratic form. Appealing to Proposition.- we have the following result. Proposition 3.-: Second Order Conditions for a Maimum If f (, ) takes on its maimum over R at, then f f f f ( i) ( ), i =, and ( ii) ( ) ( ) ( ( )). i Implicit Function Rule Consider an economy where inputs can be used to produce commodity (guns) or commodity (roses). For any level of gun production, the maimum output of roses is ( ) 4 = f =. This is depicted below. Consider the point = (,3). Differentiating the function f ( ), we can determine the opportunity cost of additional gun production, in terms of roses foregone. = = at (,3). Section 3. page

John Riley March 7 roses = (,3) Fig. 3.-: Guns-roses trade-off guns Note also that the higher the production of guns, the greater the opportunity cost in terms of roses. constraint More generally, we can represent the feasible outputs of guns and roses with the g(, ) b where the derivatives of g are strictly positive. For any, let = h( ) be the maimum output of roses. That is, g(, h( )) = b. Differentiating by, Therefore dg g g = + = g dh = =. g. This is known as the Implicit Function Rule. For eample, suppose 4 3 g(, ) = + + + and b = 33. Since g (, 3) = 33, the point (,3) lies on the boundary curve. Both partial derivatives are Section 3. page 3

John Riley March 7 positive for all so the constraint g( ) the Implicit Function Rule, g 3 4 + 4 = = g + 3. = b implicitly defines a function h( ). By Thus the opportunity cost at (,3) is /7. Note that even without solving eplicitly, we can learn a lot about the function from its slope. As increases, declines. Thus the numerator increases and the denominator declines. Thus as increases the slope becomes more negative and so the opportunity cost rises. Qualitatively, the guns-roses trade-off is again as depicted in Fig. 3.-. Rule applies. The following proposition provides conditions under which the Implicit Function Proposition 3.-: Implicit Function Theorem If the partial derivatives of g are continuous in some neighborhood of g ( ) then the slope of the function = h( ) implied by the equation g(, ) g g = b is = /. = (, ) and Constrained Maimization As an application of the Implicit Function Rule consider the following maimization problem. Ma{ f ( ) g( ) b, } We will assume that the partial derivatives of f and g are both strictly positive. Since the sum of conve functions is conve, g( ) is conve, thus the function f ( ) = b g( ) is concave. It follows that the upper contour set f ( ) is conve as depicted. Section 3. page 4

John Riley March 7 A special case is the standard commodity consumer choice problem. The consumer has a utility function f ( ) and must pick a point satisfying the budget constraint, p + p I. The feasible set is depicted below, along with the sets of points satisfying f ( ) = f ( ) and f ( ) = f ( ). f ( ) f ( ) g( ) b f ( ) = f ( ) As depicted, is optimal since for all other feasible points, f ( ) < f ( ). Let h( ) be the maimum feasible, for any given. This is depicted above along with level curves for f. Suppose that Fig. 3.-3: Constrained maimum, the maimizing value of, is not at a corner. The set of points satisfying, f ( ) = f ( ) also implicitly defines a function l( ). Graphically, at the maimum, the slopes of the two implicit functions must be equal. Appealing to the Implicit Function Theorem, we have the following first order condition. g dl dh = ( ) = ( ) = g (3.-) Formally, since f is increasing, for any it is optimal to choose the maimum feasible, that is, = h( ). Substituting for in f, we can rewrite the maimization problem as follows. Section 3. page 5

John Riley March 7 Ma{ f (, h( ))}. Differentiating the maimand by, df f dh = +. Appealing to the Implicit Function Theorem, g g df = = ( ) g f g Assuming that the maimizing value of is not at a corner, the FOC, be satisfied. Hence condition (3.-) must hold. g( ) df ( ) =, must In the special case of consumer maimization subect to a budget constraint, = p so the first order condition becomes p =. p If the consumer purchases one more unit of commodity he increases spending by p. He must then reduce his consumption of commodity by p / p units. This is the market trade-off. Also and is the utility he gains if he consumes one more of commodity is the utility he loses if he consumes one less unit of commodity. Thus the ratio is the number of units of commodity he is willing to sacrifice in order to consume one additional unit of commodity. At the maimum this willingness to substitute or marginal rate of substitution must be equal to the market trade-off. Alternatively, the first order condition can be rewritten as follows. = p p Section 3. page 6

John Riley March 7 The term ( ) p is the number of additional units that can be purchased if an additional dollar is spent on commodity and is the marginal benefit of an additional unit. Thus the consumer equates the marginal utility per dollar on each commodity that he consumes. Eercise 3.-: Consumer Choice Bev faces prices p and p and her income is I. Her utility function U (, ) satisfies U ( ) >, =,, R +. (a) Etend the argument in this section to obtain necessary conditions for a corner solution. (b) Suppose that U lim ( ) =, =,, that is, the marginal utility of each commodity increases without bound as consumption of the commodity declines to zero. Show that the necessary conditions for a maimum cannot be satisfied at a corner. (c) If U ( ) = α ln, where α >, =,..., n, show that the solution cannot be at a corner. = (d) Hence solve for Bev s optimal choice. (e) What if instead U ( ) =? α α Eercise 3.-: Firm with interdependent demands A firm sells two products. Demand prices for these products are as follows. p = 8 q q, p = 8 q q The cost of production is C( q) = q + αq q + q. (a) If α =, show that the profit function is concave and solve for the outputs that satisfy the first order conditions. Section 3. page 7

John Riley March 7 (b) Show that the first order conditions for profit maimization are satisfied at q = (, ) if α = 4. (c) Are the second order (necessary) conditions satisfied at q = (, )? (f) Show that there are two corner solutions to the FOC. Eplain why profit must be maimized at these outputs. (e) Show that, fiing q, profit is a concave function of q and hence solve for the profit maimizing output of commodity. (d) Substitute for q and hence epress profit as a function of q, q π q q q π ( ) = ( ( ), ). Solve for the profit maimizing output a neat figure. q and hence q. Depict the function q ( q ), q π ( ) in Eercise 3.-3: Quality and quantity choice A firm that produces q units of quality z commands a demand price p( q, z) = 8z q. The cost of production is C( q, z) = z α q, where z. (a) If α =, fi q and write down the first order condition for a profit maimum and solve for the profit maimizing quality as a function of q hence solve for the profit maimizing output and quality. (b) Confirm that the first order conditions hold at is concave in some neighborhood of this point. Thus maimum. ( q, z ) = (4,4) and show that profit ( q, z ) = (4,4) is a local (c) Show that, for any output, it is optimal to choose a quality level of 4. Hence or otherwise, eplain why the local maimum must also be the (global) maimum. (d) Re-eamine the problem if α =. Hint: If you like spread-sheet analysis you could first plot the graph of the profit function. Section 3. page 8