Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.



Similar documents
v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

Problem Set 3. a) We are asked how people will react, if the interest rate i on bonds is negative.

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

Support Vector Machines

1 Example 1: Axis-aligned rectangles

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

Fisher Markets and Convex Programs

Recurrence. 1 Definitions and main statements

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

Chapter 7: Answers to Questions and Problems

Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification

Multi-Product Price Optimization and Competition under the Nested Logit Model with Product-Differentiated Price Sensitivities

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2)

This circuit than can be reduced to a planar circuit

where the coordinates are related to those in the old frame as follows.

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Loop Parallelization

Cost Minimization and the Cost Function

OPTIMAL INVESTMENT POLICIES FOR THE HORSE RACE MODEL. Thomas S. Ferguson and C. Zachary Gilstein UCLA and Bell Communications May 1985, revised 2004

NON-CONSTANT SUM RED-AND-BLACK GAMES WITH BET-DEPENDENT WIN PROBABILITY FUNCTION LAURA PONTIGGIA, University of the Sciences in Philadelphia

Addendum to: Importing Skill-Biased Technology

Results from the Dixit/Stiglitz monopolistic competition model

Ring structure of splines on triangulations

Embedding lattices in the Kleene degrees

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

A Model of Intertemporal Emission Trading, Banking, and Borrowing*

Equlbra Exst and Trade S effcent proportionally

PERRON FROBENIUS THEOREM

Can Auto Liability Insurance Purchases Signal Risk Attitude?

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES

Hedging Interest-Rate Risk with Duration

The Greedy Method. Introduction. 0/1 Knapsack Problem

When Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services

What is Candidate Sampling

Cautiousness and Measuring An Investor s Tendency to Buy Options

Substitution Effects in Supply Chains with Asymmetric Information Distribution and Upstream Competition

BERNSTEIN POLYNOMIALS

Structural Estimation of Variety Gains from Trade Integration in a Heterogeneous Firms Framework

Trade Adjustment and Productivity in Large Crises. Online Appendix May Appendix A: Derivation of Equations for Productivity

Lecture 3: Force of Interest, Real Interest Rate, Annuity

Generalizing the degree sequence problem

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

The OC Curve of Attribute Acceptance Plans

17 Capital tax competition

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Extending Probabilistic Dynamic Epistemic Logic

SIMPLE LINEAR CORRELATION

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks

Point cloud to point cloud rigid transformations. Minimizing Rigid Registration Errors

How Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence

Elements of Advanced International Trade 1

Quantization Effects in Digital Filters

Portfolio Loss Distribution

Vasicek s Model of Distribution of Losses in a Large, Homogeneous Portfolio

Stability, observer design and control of networks using Lyapunov methods

Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers

How To Calculate The Accountng Perod Of Nequalty

A Lyapunov Optimization Approach to Repeated Stochastic Games

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch

Economic Models for Cloud Service Markets

reduce competition increase market power cost savings economies of scale and scope cost savings Oliver Williamson: the efficiency defense

Supply network formation as a biform game

Envelope Theorem. Kevin Wainwright. Mar 22, 2004

Optimality in an Adverse Selection Insurance Economy. with Private Trading. April 2015

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

How To Compare Frm To An Isac

This paper can be downloaded without charge from the Social Sciences Research Network Electronic Paper Collection:

A Probabilistic Theory of Coherence

Chapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT

General Auction Mechanism for Search Advertising

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

Latent Class Regression. Statistics for Psychosocial Research II: Structural Models December 4 and 6, 2006

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Leveraged Firms, Patent Licensing, and Limited Liability

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES

Transcription:

Producer Theory

Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set s closed f t contans ts boundary. We need ths for the soluton exstence n the proft maxmzaton problem. 3. No free lunch You cannot produce output wthout usng any nputs. In other words, any feasble producton plan y must have at least one negatve component. 4. Free dsposal The frm can always throw away nputs for free. For any pont n Y, ponts that use less of all components are also n Y. Thus f y Y, any pont below and to the left s also n Y (n the two dmensonal model). Ths s mostly a techncal assumpton and ensures that Y s not bounded below whch has somethng to do wth the second-order condtons n the proft maxmzng problem.

Producton ASSUMPTION 2.2 Propertes of the producton functon n The producton functon f : + + s contnuous, strctly ncreasng and strctly n quasconcave on +, and f (0) = 0.

Elastcty of Substtuton DEFINITION 2.1 The Elastcty of Substtuton For a producton functon f ( x ), the elastcty of substtuton between nputs and j at the pont x s defned as dln( xj / x) d( xj / x) f( x) / f j( x) σ, j= = dln( f ( x)/ f ( x)) x / x d( f ( x)/ f ( x)) j j j where f and f j are the margnal products of nputs and j.

ΤΗΕΟREM 2.1 Lnear Homogeneous Producton Functons are Concave Let : n f + + be a contnuous, ncreasng and quasconcave producton functon, wth f(0) = 0. Suppose f(.) s homogeneous of degree 1. Then f(.) s a concave functon.

Returns to scale DEFINITION 2.2 (Global) Returns to Scale Α producton functon f(x) has the property of 1. CRS f f ( tx) = tf ( x), t > 0, x 2. IRS f f( tx) > tf( x), t > 1, x 3. DRS f f ( tx) < tf ( x), t > 1, x

Local Returns to scale DEFINITION 2.3 (Local) Returns to Scale The elastcty of scale at pont x s defned as [ f tx ] 1 dln ( ) = μ ( x) = lm = t 1 f ( xx ) dln( t) f( x) = 1 LCRS μ( x) > 1 LIRS < 1 LDRS The elastcty of scale and the output elastctes of the nputs are related as follows: n μ( x) = μ ( x) n = 1

Homothetc Functon DEFINITION 2.3 Homothetc Functon Α homothetc functon s a postve monotonc transformaton of a functon that s homogeneous of degree 1.

COST

ΤΗΕΟREM 2.2 Propertes of the Cost Functon If f(.) s contnuous and strctly ncreasng, then (, ) cwy s: 1. zero when y = 0 2. contnuous on w and y 3. Homogeneous of degree 1 n w 4. For all w >> 0 5. ncreasng n w 6. concave n w, strctly ncreasng n y Moreover, f f(.) s strctly quasconcave we have 7. Shephard s lemma: cwy (, ) s dfferentable n w and cw dw 0 0 (, y) 0 0 (, y ) x w = = 1,... n

ΤΗΕΟREM 2.3 Propertes of the Condtonal Input Demands Suppose the producton functon f(.) s contnuous, strctly ncreasng and strctly quasconcave on, and f (0) = 0 contnuously dfferentable. Then n + 1. x( wy, ) s homogeneous of degree zero n w 2. The substtuton matrx, defned and denoted x1( w, y) x1( w, y)... w1 w n *. σ ( wy, ) =. xn( w, y) xn( w, y)... w1 wn and that the assocated cost functon s twce partcular the negatve semdefnteness property mples that s symmetrc and negatve semdefnte. In x ( w, y) w 0,

ΤΗΕΟREM 2.4 Cost and Condtonal Input Demands when Producton s Homethetc 1. When the producton functon s contnuous, strctly ncreasng and strctly n quasconcave on +, and f (0) = 0 and t s homothetc (a) the cost functon s multplcatvely separable n nput prces and output and can be wrtten cwy (, ) = h( y) cw (,1), where h(y) s strctly ncreasng functon and cw (,1) s the unt cost functon (the cost of 1 unt of output) (b) the condtonal nput demands are multplcatvely separable n nput prces and output and can be wrtten xwy (, ) = h( y) xw (,1), where h(y) s strctly ncreasng functon and x( w,1) s the condtonal nput demand for 1 unt of output. 2. When the producton functon s homogeneous of degree a > 0 (a) (b) cwy y cw 1/ a (, ) = (,1) x wy y xw 1/ a (, ) = (,1)

DEFINITION 2.4 The Short-Run Cost Functon Let the producton functon be f( x, x ). Suppose that x s a subvector of varable nputs and x s a subvector of fxed nputs. Let w and w be the assocated nput prces for the varable and fxed nputs, respectvely. The short-run total cost functon s defned as sc( w, w, y; x) mn wx + wx s. t. f ( x, x) y x If x( wwyx,, ; ) solves ths mnmzaton problem, then sc( w, w, y; x) wx( w, w, y; x) + wx total varable cost total fxed cost

THE COMPETITIVE FIRM

PROFIT MAXIMIZATION wth producton sets max py s.t. y Y y m max py s.t. F(y)=0 y m y( p ) frm s net supply functon proft functon π ( p) = py( p)

PROFIT MAXIMIZATION wth producton sets

ΤΗΕΟREM 2.5 Propertes of the Net Supply Functon If the producton set Y satsfes assumpton 2.1, then the net supply functon y( p ) has the followng propertes: (a) y( p ) s homogeneous of degree 0 n p The producton set Y s not affected by re-scalng all prces by the same amount, hence the optmal soluton of the PMP does not change. y( p) y( λ p), λ > 0. (b) If Y s a convex set, y( p ) s a convex set. If Y s strctly convex, then y( p ) s a sngle pont (a vector). The reason for ths s the same as n the UMP. Recall that a strctly convex set Y corresponds to decreasng returns technology.

PROFIT MAXIMIZATION wth a sngle output Profts = Revenues Cost Revenues = R( y) = py Cost = wx max py wx s.t. f ( x) y x n +, y 0

ΤΗΕΟREM 2.6 Propertes of the Proft Functon A. If the producton set Y satsfes assumpton 2.1, then the proft functon π ( p) followng propertes: has the 1. ncreasng n p (whch means ncreasng n output prces and decreasng n nput prces, snce n π ( p) = py = p1y1+... + py... p jy j... pmym ) 2. homogeneous of degree 1 n p 3. convex n p 4. (Hotellng s lemma) If y( p ) s a sngle pont (mpled when Y s a strctly convex set), then π (.) s dfferentable at p and π ( p) p = y ( p), = 1,... m

B. If the producton functon f(.) satsfes assumpton 2.2, then the proft functon π ( p, w), where well-defned, s contnuous and 1. ncreasng n p and decreasng n w 2. homogeneous of degree 1 n (p,w) 3. convex n (p,w) 4. dfferentable n (p,w). Moreover, π ( pw, ) p π ( pw, ) w = y( p, w) = x ( pw, ) = 1,..., n

ΤΗΕΟREM 2.7 Propertes of Output Supply and Input Demand Functons Let π ( p, w) be a twce contnuously dfferentable proft functon for some compettve frm. Then 1. Homogenety of degree 0: y( tp, tw) = y( pw, ), t> 0 x ( tp, tw) = x ( p, w), t > 0, = 1,2,... n The substtuton matrx y( p, w) y( p, w) y( p, w)... p w1 w n x1( pw, ) x1( pw, ) x1( pw, )... p w1 w n............ xn( pw, ) xn( pw, ) xn( pw, )... p w1 w n y( p, w) 0 2. Own-prce effects: p x ( p, w) w s symmetrc and postve semdefnte 0 = 1, 2,.., n

ΤΗΕΟREM 2.8 The Short-Run Proft Functon Let the producton functon be f ( xx, ), where x s a subvector of varable nputs and x s a subvector of fxed nputs. Let w and w be the assocated nput prces for varable and fxed nputs, respectvely. The short run, proft functon s defned as π ( pwwx,,, ) max py wx wx s.t. f( xx, ) y yx, The solutons y( p, w, w, x ) and x( pwwx,,, ) are called the short-run output supply and varable nput demand functons, respectvely. For all p > 0 and 0 w >>, ( p, wwx,, ) π where well-defned s contnuous n p and w, ncreasng n p, decreasng n w, and convex n (p,w). If π ( p, wwx,, ) s twce contnuously dfferentable, y( p, w, w, x ) and xpwwx (,,, ) possess all three propertes lsted n Theorem 2.7 wth respect to output and varable nput prces.