Market structure and Innovation

Similar documents
Economics 101. Lecture 4 - Equilibrium and Efficiency

Welfare Properties of General Equilibrium. What can be said about optimality properties of resource allocation implied by general equilibrium?

Volume 29, Issue 4. Incomplete third-degree price discrimination, and market partition problem. Yann Braouezec ESILV

3.2. Cournot Model Cournot Model

Investment Secrecy and Competitive R&D

PROBLEM SET 7 GENERAL EQUILIBRIUM

k t+1 + c t A t k t, t=0

Hila Etzion. Min-Seok Pang

(1 ) (1 ) 0 (1 ) (1 ) 0

Economics 2450A: Public Economics Section 10: Education Policies and Simpler Theory of Capital Taxation

Price competition with capacity constraints. Consumers are rationed at the low-price firm. But who are the rationed ones?

CS294 Topics in Algorithmic Game Theory October 11, Lecture 7

University of California, Davis Date: June 22, 2009 Department of Agricultural and Resource Economics. PRELIMINARY EXAMINATION FOR THE Ph.D.

The oligopolistic markets

Lecture 3: Probability Distributions

j) = 1 (note sigma notation) ii. Continuous random variable (e.g. Normal distribution) 1. density function: f ( x) 0 and f ( x) dx = 1

Credit Card Pricing and Impact of Adverse Selection

Online Appendix. t=1 (p t w)q t. Then the first order condition shows that

3.1 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

Idiosyncratic Investment (or Entrepreneurial) Risk in a Neoclassical Growth Model. George-Marios Angeletos. MIT and NBER

How Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists *

Pricing and Resource Allocation Game Theoretic Models

The Second Anti-Mathima on Game Theory

Supporting Information for: Two Monetary Models with Alternating Markets

Conjectures in Cournot Duopoly under Cost Uncertainty

Uniqueness of Nash Equilibrium in Private Provision of Public Goods: Extension. Nobuo Akai *

Quantity Precommitment and Cournot and Bertrand Models with Complementary Goods

Lecture 17 : Stochastic Processes II

1 The Sidrauski model

Mixed Taxation and Production Efficiency

Endogenous timing in a mixed oligopoly consisting of a single public firm and foreign competitors. Abstract

Copyright (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

A Framework for Optimal Investment Strategies for Competing Camps in a Social Network

Perfect Competition and the Nash Bargaining Solution

Eigenvalues of Random Graphs

Tit-For-Tat Equilibria in Discounted Repeated Games with. Private Monitoring

Supporting Materials for: Two Monetary Models with Alternating Markets

Mergers among leaders and mergers among followers. Abstract

Equilibrium with Complete Markets. Instructor: Dmytro Hryshko

Econ674 Economics of Natural Resources and the Environment

Infinitely Split Nash Equilibrium Problems in Repeated Games

The Dynamic Approach to Heterogeneous Innovations. (Anton Bondarev)

Games of Threats. Elon Kohlberg Abraham Neyman. Working Paper

R&D investment, asymmetric costs, and research joint ventures

Information Acquisition in Global Games of Regime Change

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

CS286r Assign One. Answer Key

The Value of Demand Postponement under Demand Uncertainty

Cournot Equilibrium with N firms

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

A note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights

Modelli Clamfim Equazione del Calore Lezione ottobre 2014

Portfolios with Trading Constraints and Payout Restrictions

Constant Best-Response Functions: Interpreting Cournot

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification

Welfare Analysis of Cournot and Bertrand Competition With(out) Investment in R & D

6. Stochastic processes (2)

6. Stochastic processes (2)

Lecture Notes, January 11, 2010

Modelli Clamfim Equazioni differenziali 7 ottobre 2013

Mutual Insurance Networks and Unequal Resource Sharing in Communities, First Draft, February 2015

Environmental taxation: Privatization with Different Public Firm s Objective Functions

Discontinuous Extraction of a Nonrenewable Resource

Kernel Methods and SVMs Extension

Continuous Time Markov Chain

Lecture Notes on Linear Regression

Linear Regression Analysis: Terminology and Notation

Game Theory. Lecture Notes By Y. Narahari. Department of Computer Science and Automation Indian Institute of Science Bangalore, India February 2008

Outline. Communication. Bellman Ford Algorithm. Bellman Ford Example. Bellman Ford Shortest Path [1]

On Tacit Collusion among Asymmetric Firms in Bertrand Competition

Demand Response with Linear Bidding: Efficiency vs. Risk. Munther A. Dahleh MIT Institute for Data, Systems, and Society

Duopoly innovation under product externalities

Predictive Analytics : QM901.1x Prof U Dinesh Kumar, IIMB. All Rights Reserved, Indian Institute of Management Bangalore

Brander and Lewis (1986) Link the relationship between financial and product sides of a firm.

Online Appendix: Reciprocity with Many Goods

Module 17: Mechanism Design & Optimal Auctions

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

Statistics Chapter 4

Digital Signal Processing

Lossy Compression. Compromise accuracy of reconstruction for increased compression.

f(x,y) = (4(x 2 4)x,2y) = 0 H(x,y) =

Perron Vectors of an Irreducible Nonnegative Interval Matrix

find (x): given element x, return the canonical element of the set containing x;

Assortment Optimization under MNL

Upstream competition. Stéphane Caprice Toulouse School of Economics

Chapter 9: Statistical Inference and the Relationship between Two Variables

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Price Competition in Multi-sided Markets *

Allocative Efficiency Measurement with Endogenous Prices

Modelli Clamfim Equazioni differenziali 22 settembre 2016

Implementation and Detection

VQ widely used in coding speech, image, and video

Unit 5: Government policy in competitive markets I E ciency

Introduction. 1. The Model

Notes on Frequency Estimation in Data Streams

Queueing Networks II Network Performance

Price Discrimination of Digital Content

Transcription:

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. Introducton. The possblty of acqurng monopoly power and assocated quas rents s necessary to provde entrepreneurs an ncentve to pursue nnovatve actvty..both theoretcal and emprcal studes have suggested the exstence of a degree of concentraton ntermedate between pure monopoly and perfect competton that s best n terms of R&D performance..the present paper drawng on the work of Scherer and Kamen and Schwartz (1972,1976), formulates a model n whch each frm nvests n R&D under both technologcal and market uncertanty. 1

. Gven the ndustry s market structure, equlbrum occurs when each frm s nvestment decson maxmzes ts expected dscounted profts, subject to the other frm s R&D nvestment strateges beng gven.. The model s used to study the mpact of market structure on R&D performance at both the frm and ndustry level, as well as the consequent effect on socal welfare. 2

II The model Assumptons: 1. n dentcal frms compete for the constant flow of rewards V that wll become avalable only to the frst frm that ntroduces an nnovaton. 2.nfnte patent protecton so that belated nnovators get no net rewards.. Frm makes an nvestment n R&D wth a present value of cost x. And τ ( ) represents the uncertan date at x whch the R&D project wll be successfully completed..assume the followng technologcal relatonshp: hx ( ) t pr[ τ ( x ) t] = 1 e (1 ) That s, τ ( x ) s exponentally dstrbuted wth an expected tme of ntroducton gven by 3

Eτ ( x ) = Thus, hx ( ) 1 h ( x ) (2 ) s the nstantaneous probablty that the nnovaton wll be successfully completed (or ready for the market) at any subsequent moment..we take h (.) to be twce contnuously dfferentable, strctly ncreasng, satsfyng h ' (0) 0 lm ( ) x = = h x (3 ) and '' ()0 hx < as xx > 4

Equaton (3) expresses the assumpton that whle there may be an ntal range of ncreasng returns to scale n the R&D technology, dmnshng returns are encountered eventually. Let x% denote the pont where hx ()/ x s greatest..defne ˆ τ as the random varable representng the th frm s market uncertanty regardng the tme at whch any rval wll ntroduce the nnovaton. τ ˆ s related to the behavor of other frms by ˆ τ = mn { τ ( xj)} (4) 1 j < n. Assume the random varables τ ( x ) ndependent pr[ ˆ τ t] = 1 exp( t h( x )) = 1 e, =1,2,..,n are at j (5) j where a h( xj) and a s taken as constant by the th frm. j. At any tme t 0 the th frm earns a revenue flow V n the event thatτ ( x ) mn( ˆ τ, t). 5

Integratng the jont densty of ( τ ( ), ˆ τ ) over the relevant x regon, we have ( 6 ) pr[( τ x ) mn( ˆ τ,)] t t at h( x) t h( x) s as (1 ) (1 ) 0 = e e + a e e hx ( ) = (1 exp( ta [ + hx ( )])) a + h( x) ds The th frm chooses x, gven (dscount rate) and V to maxmze expected dscounted profts, t must solve the followng problem: ar, Vh( x) Max{ x} Max ( a, x; V, r) ra ( + r+ hx ( )) (7) F.O.C: h ( xˆ )( a+ r) r = 0 2 [ a+ r+ h( xˆ )] V (8) S.O.C : ) h x a r ) h x h xˆ ) ) (8) defnes x = x( a, r, V) mplctly 2 ( ).[ + + ( )] 2 ( ) 0 (9 ) 6

A symmetrc Nash equlbrum mples each frm pursue the same nvestment strategy. For each frm, we have that a= ( n 1) h( x ) ) x = x(( n 1) hx ( ), rv, ). From (8), we have: (10 ) Equaton (10) mplctly defnes the equlbrum level of frm R&D nvestment x = x ( n, r, V) Now, we examne the mpact of greater rvalry on a frm s nnovatve actvty by studyng the dependency of n. x on Proposton I: As the number of frms n the ndustry ncreases, the equlbrum level of frm nvestment declnes. Proof: Regardng n as a contnuous varable, totally dfferentate (10) to fnd ( n 2 ) that x xˆ / ah( x ) = < 0 n 1 ( n 1) h ( x ) xˆ / a Thus, we have found that ncreasng the extent of rvalry reduces an ndvdual frm s ncentve to nvest n R&D 7

Proposton II : Suppose that wth the ndustry n equlbrum, a margnal ncrease n R&D nvestment by any sngle frm causes the nvestment of each other frm to fall by a smaller amount. Then ncreasng the number of frms always reduces the expected ndustry ntroducton date ( the date on whch the nnovaton frst becomes avalable to socety). Proof: Defne a random varable τ ( n) mn{ τ( )} 1 n x, the random date on whch the nnovaton frst becomes avalable to Eτ ( n) = 1 nh[ x ( n)] socety. In equlbrum, we have Industry expected ntroducton date declnes wth the number of frms f and only f d = + dn xˆ = hx n + 1 ( n 1) h [ x ( n)] a d dn ( nh[ x ( n)]) h[ x ( n)] nh [ x ( n)] nh [ x ( n)] [ ( )][1 a ] xˆ ( nh [ x ( n )]) > 0 x n 8

From the proof of Proposton I, thus xˆ h ( x ) 1 a > d nh x n dn ( [ ( )]) 0 < as Ths proposton shows that gven a reasonable stablty condton, ncreasng the number of compettors n an ndustry reduces the expected tme that socety has to wat for the nnovaton despte the fact that each compettor nvests less n R&D. III. Welfare analyss of ndustry equlbrum. Now consder the effcency propertes of short-run and long-run equlbrum 1. In the short run, duplcaton effort wll cause neffcency. Each frm chooses an nvestment level to maxmze ( ax, ) Nash equlbrum, π, takng a as gven. In a symmetrc a = ( n 1) h( x). The expected present value of socal benefts at an equlbrum s equal to nπ (( n 1) h( x ), x ( n)). Each frm faces probablty 1 n 9

of beng frst, but socety s ndfferent as to whch frms wn the race. Then n short-run equlbrum frms tend to overnvest n R&D because they do not take account of the parallel nature of ther actvtes. Proposton III : Gven a fxed market structure ( ), n ndustry equlbrum each frm nvests more n R&D than s socally optmal. n Proof: Let x ( n) denote the socally effcent frm nvestment level when market structure s fxed at. Gven, socal welfare s maxmzed when π π (( n 1) h( x), x) + ( n 1) h ( x) (( n 1) h( x), x) = 0 x a but ndustry equlbrum s characterzed by π (( n 1) h( x), x) = 0 x Snce π / a < 0 and x n > x n ( ) ( ) 2 2 π / x 0. It follows that n n 10

2. In long-run ndustry equlbrum, there s also a source of neffcency. Proposton IV: If x >0 ( see equaton (3) ), then compettve entry nduces too many frms to jon the nnovaton race. When entry s unmpeded, f the technology possesses economes of scale ntally, and f nnovatng frms struggle for the entre socal payoff, there wll be too much competton. In ths nstance, no scale economes are beng exploted, and mergers of parallel R&D efforts would obvously mprove performance. These neffcences may be corrected through the judcous choce of a patent lfe and an entry tax-subsdy. Proposton V : There exsts a fnte patent lfe and an entry tax (possbly negatve) n the presence of whch the long-run ndustry equlbrum s socally optmal 11

IV concluson. Ths s an equlbrum model of nvestment n R&D under rvalry. In ths model, frms are assumed to maxmze ther expected profts under condtons of technologcal and market uncertanty..more competton reduces ndvdual frm s nvestment ncentves n equlbrum, yet leads ( under certan reasonable condtons ) to an ncreased probablty that the nnovaton wll be ntroduced by any future date..more competton s not necessarly socally desrable. In equlbrum, more frms wll enter the nnovaton race than socally optmal. Competng frms also nvest more n R&D than socally optmal because they do not take account of the parallel nature of ther efforts. 12

Some shortcomngs of ths model:. Imtaton may reduce prvate nvestment ncentves. In ths case, compettve frms may not overnvest. But ths model ddn t take ths effect nto account..ths model assume that competng frms lose nothng but ther R&D nvestment when a rval beats them to the nnovaton. In realty the market shares of competng frms are constantly changng as new nnovatons attract compettors customers. 13