. The firm makes different types of furniture. Let x ( x1,..., x n. If the firm produces nothing it rents out the entire space and so has a profit of

Similar documents
EVEN NUMBERED EXERCISES IN CHAPTER 4

Parametric Density Estimation: Maximum Likelihood Estimation

Overlapping Generations

5. Best Unbiased Estimators

Problem Set 1a - Oligopoly

Combining imperfect data, and an introduction to data assimilation Ross Bannister, NCEO, September 2010

Introduction to Probability and Statistics Chapter 7

Notes on Expected Revenue from Auctions

Maximum Empirical Likelihood Estimation (MELE)

Solutions to Problem Sheet 1

Monopoly vs. Competition in Light of Extraction Norms. Abstract

Insurance and Production Function Xingze Wang, Ying Hsuan Lin, and Frederick Jao (2007)

EC426 Class 5, Question 3: Is there a case for eliminating commodity taxation? Bianca Mulaney November 3, 2016

14.30 Introduction to Statistical Methods in Economics Spring 2009


FINM6900 Finance Theory How Is Asymmetric Information Reflected in Asset Prices?

Math 312, Intro. to Real Analysis: Homework #4 Solutions

Sequences and Series

- competitive economy with n consumption goods, and a single form of labor which is only input

Foreign Price Risk and Homogeneous Commodity Imports:

1 ECON4415: International Economics Problem Set 4 - Solutions

2.6 Rational Functions and Their Graphs

NPTEL DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING IIT KANPUR QUANTITATIVE FINANCE END-TERM EXAMINATION (2015 JULY-AUG ONLINE COURSE)

The Limit of a Sequence (Brief Summary) 1

Exam 1 Spring 2015 Statistics for Applications 3/5/2015

1 Basic Growth Models

1 The Power of Compounding

EXERCISE - BINOMIAL THEOREM

A random variable is a variable whose value is a numerical outcome of a random phenomenon.

Standard Deviations for Normal Sampling Distributions are: For proportions For means _

r i = a i + b i f b i = Cov[r i, f] The only parameters to be estimated for this model are a i 's, b i 's, σe 2 i

MA Lesson 11 Section 1.3. Solving Applied Problems with Linear Equations of one Variable

Sampling Distributions and Estimation

10.The Zero Lower Bound in a two period economy

11.7 (TAYLOR SERIES) NAME: SOLUTIONS 31 July 2018

Yoav Wachsman University of Hawaii

x. The saver is John Riley 7 December 2016 Econ 401a Final Examination Sketch of answers 1. Choice over time Then Adding,

Statistics for Economics & Business

Dr. Maddah ENMG 624 Financial Eng g I 03/22/06. Chapter 6 Mean-Variance Portfolio Theory

Chapter 8. Confidence Interval Estimation. Copyright 2015, 2012, 2009 Pearson Education, Inc. Chapter 8, Slide 1

Summary. Recap. Last Lecture. .1 If you know MLE of θ, can you also know MLE of τ(θ) for any function τ?

ECON 5350 Class Notes Maximum Likelihood Estimation

Lecture 9: The law of large numbers and central limit theorem

Competing Auctions with Endogenous Quantities

Price Discrimination through Multi-Level Loyalty Programs

III. RESEARCH METHODS. Riau Province becomes the main area in this research on the role of pulp

SOCIETY OF ACTUARIES FINANCIAL MATHEMATICS EXAM FM SAMPLE SOLUTIONS

ACTUARIAL RESEARCH CLEARING HOUSE 1990 VOL. 2 INTEREST, AMORTIZATION AND SIMPLICITY. by Thomas M. Zavist, A.S.A.

18.S096 Problem Set 5 Fall 2013 Volatility Modeling Due Date: 10/29/2013

Consumer Tracking and E cient Matching in Online Advertising Markets

Managing Rentals with Usage-Based Loss

CHAPTER 8 Estimating with Confidence

CHAPTER 2 PRICING OF BONDS

Competing Auctions with Endogenous Quantities 1

Chapter 10 Counterexamples to Commonly Held Assumptions on Unit Commitment and Market Power Assessment

Cost centres and cost behaviour

B = A x z

Further Pure 1 Revision Topic 5: Sums of Series

Procurement, Cost Reduction, and Vertical Integration

SUPPLEMENTAL MATERIAL

Estimating Proportions with Confidence

Models of Asset Pricing

Models of Asset Pricing

ENGINEERING ECONOMICS

A New Approach to Obtain an Optimal Solution for the Assignment Problem

Estimating Forward Looking Distribution with the Ross Recovery Theorem

CD Appendix AC Index Numbers

Course FM/2 Practice Exam 1 Solutions

SOLVING OF PORTFOLIO OPTIMIZATION PROBLEMS WITH MATHEMATICA

STRAND: FINANCE. Unit 3 Loans and Mortgages TEXT. Contents. Section. 3.1 Annual Percentage Rate (APR) 3.2 APR for Repayment of Loans

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012

We characterize the trade-offs among firms compliance strategies in a market-based program where

MATH 205 HOMEWORK #1 OFFICIAL SOLUTION

Models of Asset Pricing

APPLICATION OF GEOMETRIC SEQUENCES AND SERIES: COMPOUND INTEREST AND ANNUITIES

Asymptotics: Consistency and Delta Method

CAPITAL PROJECT SCREENING AND SELECTION

The Balassa-Samuelson Effect and Pricing-to-Market: The Role of Strategic Complementarity

x satisfying all regularity conditions. Then

Mixed and Implicit Schemes Implicit Schemes. Exercise: Verify that ρ is unimodular: ρ = 1.

Course FM Practice Exam 1 Solutions

Exercise 1: Robinson Crusoe who is marooned on an island in the South Pacific. He can grow bananas and coconuts. If he uses

Unbiased estimators Estimators

Calculation of the Annual Equivalent Rate (AER)

Solution to Tutorial 6

Marking Estimation of Petri Nets based on Partial Observation

Appendix 1 to Chapter 5

between 1 and 100. The teacher expected this task to take Guass several minutes to an hour to keep him busy but

Pushing and Pulling Environmental Innovation: R&D Subsidies and Carbon Taxes

of Asset Pricing R e = expected return

An Incentive Effect of Multiple Sourcing *

INTERVAL GAMES. and player 2 selects 1, then player 2 would give player 1 a payoff of, 1) = 0.

CAUCHY'S FORMULA AND EIGENVAULES (PRINCIPAL STRESSES) IN 3-D

Profit Taxation, Monopolistic Competition and International Relocation of Firms

Chapter Four Learning Objectives Valuing Monetary Payments Now and in the Future

Chapter Six. Bond Prices 1/15/2018. Chapter 4, Part 2 Bonds, Bond Prices, Interest Rates and Holding Period Return.

Topic-7. Large Sample Estimation

RESOURCE ALLOCATION AND A FITTED PRODUCTION FUNCTION

Neighboring Optimal Solution for Fuzzy Travelling Salesman Problem

1 Itroductio South Tyrol i Norther Italy is the most importat apple growig regio i Europe. Apple growers have the possibility to sell their products t

Transcription:

Joh Riley F Maimizatio with a sigle costrait F3 The Ecoomic approach - - shadow prices Suppose that a firm has a log term retal of uits of factory space The firm ca ret additioal space at a retal rate of per uit or ret out some of the uits at this same rate If the firm produces othig it rets out the etire space ad so has a profit of The firm makes differet types of furiture Let ( 1,, ) be the quatities of each type the profit of the firm from furiture sales is f( ) The space required i the productio of is g ( ) Addig the reveue from retig out some of the space (or the cost of retig additioal space, the profit of the firm is L (, ) f ( ) ( bˆ g( )) For every shadow price 0 we ca solve the followig profit maimizatio problem Ma{ L (, ) f ( ) g( )} 0 Let ( ) be a solutio of the maimizatio problem The total demad for space is b ( ) g( ( )) Cosider furiture type If 0, the the margial profit must be zero If 0, the the margial profit caot be positive Therefore we have the followig ecessary coditios for a maimum L f g (, ) ( ) ( ) 0 with equality if 0 (11) The firm s demad for space is the mappig from the shadow price to demad b ( ) If we put b o the horizotal ais ad o the vertical price, the graph is of the demad price

fuctio This is the price that clears the market for ay supply of space Suppose that for all b there is some demad price () b 1 Figure 3-1: Demad price fuctio for The for ay there is a demad price firm chooses the productio vector b () ˆ ˆ Thus, with this market price, the profit maimizig ad uses the leased space b ˆ g( ( b ˆ )) Cosider ay that satisfies the space costrait g() bˆ Sice is profit maimizig, it follows that f ( ) ˆ ( bˆ g( )) f ( ˆ) ˆ ( bˆ g( ˆ)) Rearragig this iequality, f ( ) f ( ˆ) ˆ ( g( ) g( ˆ)) For ay satisfyig the space costrait, the right had side is egative Therefore f ( ) f ( ˆ ) 0 1 This will ecessarily be the case if the profit fuctio is cocave 2

We have therefore proved the followig result Propositio: Solutio to the costraied maimizatio problem Ma{ f ( ) bˆ g( ) 0} 0 Let ( ) solve the profit maimizatio problem whe it is possible to buy or sell the iput, ie Ma{ L (, ) f ( ) ( bˆ g( ))} 0 ad let b( ) g( ( )) be the implied demad for the iput If there is a shadow price that b( ˆ ) bˆ, the ( ˆ ) solves the costraied maimizatio problem ˆ such Remark: College courses o calculus, such as at UCLA, do ot cover maimizatio problems with o-egativity ad iequality costraits If a College level tet book cosiders a costraied maimizatio problem, the costrait holds with equality ad is ay vector of real umbers, ie the problem aalyzed is the closely related but simpler optimizatio problem Ma{ f ( ) bˆ g( ) 0} We have iterpreted L(, ) f ( ) ( bˆ g( )) as the profit of a firm To a mathematicia, this is the Lagragia of the costraied maimizatio problem The price (or shadow price), is called the Lagrage multiplier Eample 1: Divisio of a firm with a budget costrait A firm ca produce output q f () z usig the iput vector z The iput price vector is r The divisio maager is give b dollars ad istructed to maimize output, q f () z without violatig the budget costrait r z r ˆ z b 1 Eample 2: The cost fuctio of the firm A firm ca produce output q f () z usig the iput vector z The iput price vector is r The 3

divisio maager is asked to solve for the miimum cost of producig ay output ˆq, give that the iput price vector is r Remark: Suppose that you have already solved the maimum output problem for some productio fuctio f( ) Let z * ( b, r) be the output maimizig iputs so that q b * ( ) f ( ( b, r)) This mappig is depicted below Figure 3-2: Maimum output with a fied budget Thus for ay ˆq we ca choose so that qˆ q() bˆ Thus the miimum cost is o more tha Sice q * ( b ) is strictly icreasig, it follows that for ay bˆ bˆ, the maimum output is strictly less the ˆq Thus the miimized cost is Havig solved for the mappig qˆ q() bˆ, the miimized total cost is the iverse of this fuctio 1 C( r, qˆ) q ( qˆ) 4

Eample 3: Utility maimizatio with Cobb-Douglas prefereces Prefereces are represeted by the followig strictly icreasig fuctio U( ) l 1 i i The budget costrait is 1 p p I Sice utility is strictly icreasig the solutio equality The Lagragia of the problem is must satisfy the budget costrait with L (, ) l ( I p ) 1 1 FOC L (, ) p 0, 1,,, with equality if 0 (12) Sice p I, there is some k for which k 0 Therefore Therefore L k (, ) pk 0 k k L p k (, ) 0, 1,, p k k Note that U L as 0 so (, ) is strictly positive for sufficietly small Thus there is o corer solutio where oe or more compoets of the solutio is zero Hece 5

p 1 (13) 1 1 p Therefore p (14) Substitutig ito the budget costrait, p I 1 1 1 Therefore 1 I `1 Substitutig for i (14), p I `1 Remark: if you ca see how to prove the followig rule for 2, the you might like to use it Ratio Rule: Equal ratios are also equal to the ratio of sums of the umerators ad deomiators a If r, 1,, b ad b 0 the 1 1 1 a b r From (13) ad the Ratio Rule 6

1 1 1 1 1 p 1 p p I Oe ca the solve immediately for the demad fuctios 7