Presentation on theme: "Lecture #11: Introduction to the New Empirical Industrial Organization (NEIO) modified from: nWhat."— Presentation transcript:
Lecture #11: Introduction to the New Empirical Industrial Organization (NEIO) modified from: nWhat is the old empirical IO? lThe old empirical IO refers to studies that tried to draw inferences about the relationship between the structure of an industry (in particular, its concentration level) and its profitability. nProblems with those studies are that lit is hard to measure profitability, lindustry structure may be endogenous, and lthere is little connection between empirical work and theory. nThe NEIO is in many ways a reaction to that empirical tradition. NEIO works “in harmony” with (game) theory.
The Structure-Conduct-Performance (SCP) Paradigm: The Old Empirical IO nHow does industry concentration affect price-cost margins or other similar measures? lThe “plain vanilla” SCP regression regresses profitability on concentration. nThe Cournot model of non-cooperative oligopolistic competition in homogeneous product industries relates market structure to performance. lIt can be shown that shared weighted average markup in an industry is a function of its Herfindahl index and the elasticity of demand.
nThis implies: ln(PCM) = 0 + 1 ln(HHI) + 2 ln( ) + (1) where PCM = the share weighted average firm markup. nUsing cross section data, (1) could be estimated and a test for Cournot would be 0 = 0, 1 = 1, and 2 = -1. nIn practice, regressions of the following form were performed: ln(PCM) = 0 + 1 C4 + (2) where C4 was the share of the four largest firms in the industry.
nWhat are the problems with these regressions? lData: Price cost margins are not available, hence accounting returns on assets (as well as census data on manufacturer margins) were often used. lData: Additional RHS variables such as the elasticity of demand are hard to measure for many industries. lData: Market definitions were problematic. (When using a single industry more thought can be put into the issue.) lSimultaneity: Both margins and concentration are endogenous. Demsetz (J. Law and Econ., 1973) noted that some firms have a cost advantage, leading to a large share and high profits. Hence, there could be a correlation between C4 and profits.
The New Empirical Industrial Organization (NEIO) Paradigm: The New Empirical IO n The NEIO studies lbuild on the econometric progress made by SCP paradigm, luse economic theory, ldescribe techniques for estimating the degree of competitiveness in an industry, luse bare bones prices and quantities, and do not rely on cost or profit data, ltypically assume that the firms are behaving as if they are Bertrand competition, luse comparative statics of equilibria to draw inferences about profits and costs, and lfocus mainly on a single industry in order to deal better with product heterogeneity, institutional details, etc.
Bresnahan (Economic Letters, 1982): The Oligopoly Solution Concept is Identified This paper and others (e.g., A. Nevo, “Identification of the Oligopoly Solution Concept in a Differentiated Products Industry,” Economics Letters, 1998, ) show that the oligopoly solution concept can be identified econometrically. nDemand:Q = 0 + 1 P + 2 Y + (1) MC:MC = 0 + 1 Q + 2 W+ (2) where Y and W are exogenous. nFOC for a PC firm:MC = P ( MR is: P) FOC for a monopoly:MC = P + Q/ 1 ( MR is: P + Q * P/ Q) FOC for the oligopolistic firm: MC = (1 - ) P + (P + Q/ 1 ) where = 0 if the industry is competitive = 1 if the industry is a monopoly
l Demand:Q = 0 + 1 P + 2 Y + (1) MC:MC = 0 + 1 Q + 2 W + (2) FOC:MC = (1 - ) P + (P + Q/ 1 ) nSubstituting FOC into (2), the supply relationship is: (1 - ) P + (P + Q/ 1 ) = 0 + 1 Q + 2 W + YP = (- Q/ 1 ) + 1 Q + 0 + 2 W + (3) nSince both (1) and (3) have one endogenous variable and since there is one excluded exogenous variable from each equation, both equations are identified. But, are we estimating P = MC (competitive) or MR = MC (monopoly)? Rewrite (3) as: P = ( 1 - / 1 ) Q + 0 + 2 W + We can obtain a coefficient for ( 1 - / 1 ) since (3) is identified and we can get 1 by estimating (1). But, we cannot estimate 1 and . Identification problems!!!
nIn the figure, E 1 could either be an equilibrium for a monopolist with marginal cost MC M, or for a perfectly competitive industry with cost MC C. nIncrease Y to shift the demand curve out to D 2 and both the monopolistic and competitive equilibria move to E 2. nUnless we know marginal costs, we cannot distinguish between competitive or monopoly (nor anything in between). MC M D1D1 MR 1 E1E1 MC C E2E2 D2D2 MR 2
The solution to the identification problem nMC:MC = 0 + 1 Q + 2 W + (2) nLet demand be:Q = 0 + 1 P + 2 Y + 3 P Z + 4 Z + where Z is another exogenous variable. The key is that Z enters interactively with P, so that changes in P and Z both rotate and vertically shift demand. (Note: Z might be the price of a substitute good, which makes the interaction term intuitive.) nGiven the new demand, the marginal revenue for a monopolist, (P + Q * P/ Q), is no longer P + Q/ 1. It is now: P + Q / ( 1 + 3 Z). nThus, the oligopolistic firm’s FOC becomes MC = (1 - ) P + [P + Q / ( 1 + 3 Z)] nSubstituting FOC into (2), the supply relationship becomes: P= - [Q / ( 1 + 3 Z)] + 1 Q + 0 + 2 W + - Q * + 1 Q + 0 + 2 W +
nDemand: Q = 0 + 1 P + 2 Y + 3 P Z + 4 Z + Supply Relation: ` P= - [Q / ( 1 + 3 Z)] + 1 Q + 0 + 2 W + - Q * + 1 Q + 0 + 2 W + lSince the demand is still identified, we can estimate 1 and 3. Thus, we can identify both and 1 in the supply relation. nNote 1: This result can be generalized beyond linear functions. Note 2: There are other assumptions that can generate identification. e.g.Marginal cost that does not vary with quantity ( 1 = 0) e.g.Use of supply shocks (Porter, 1983)
MC M D1D1 MR 1 E1E1 MC C nGraphically, an exogenous change in the price of the substitute rotates the demand curve around E 1. nIf there is perfect competition, this will have no effect on the equilibrium price and it will stay at the point associated with E 1. nBut, if there is monopoly power, the equilibrium will change to E 3. E2E2 D2D2 MR 2
Why do we care about the structural model? nWe want to estimate parameters or effects not directly observed in the data (e.g., returns to scale, elasticity of demand). nWe want to perform welfare analysis (e.g., measure welfare gains due to entry or welfare losses due to market power). nWe want to simulate changes in the equilibrium (e.g., impact of mergers). nWe want to compare relative predictive performance of competing theories.