Bhuyan, Sanjib, and Lopez Oligopoly power in the food and tobacco industries Method: Theoretical Model Specify a general profit function Derive several parameters related to MARKET POWER Empirical Model Specify a specific profit function, demand function Collect data Estimation of parameters - statistical methods

Method: Theoretical Model -Profit function Differentiate profit with respect to output

Method: Theoretical Model: Parameters Output elasticity of cost - reciprocal of “ economies of size ” eg. for a 1% increase in output, is there more or less percent change in cost?

Method: Theoretical Model: Lerner Index (L) Measures degree of the exercise of oligopoly power

Method: Empirical Model Specify a Translog Cost function (Transcendental-logarithmic) Ln(C) = f(W,Y,T) C = industry total cost Y = industry output T = time trend W = vector of input prices (w i ) Logarithmic differentiation (Shephard’s Lemma) factor (input) share equations

Method: Empirical Model Specify a Cobb-Douglas output demand function (derived demand facing industry)

Method: Estimation Statistical methods - estimate the parameters of a system of equations L - Lerner index  - elasticity of returns to scale  - conjectural variation elasticity for the industry (  = 0 => no strategic activity e.g. price taking)  - output demand elasticity 4 input share equations (KLEM) (derived from C=C (W,Y,T) 1 demand function (Cobb-Douglas) 1 equation representing profit max criterion Annual data 1972 – food and tobacco processing industries: SIC 4 digit level

Results: 1)Testing the Lerner index H 0 : L = 0 Reject => evidence of oligopoly power (price distortion) Rejected - 37 of 40 industries (average L = 0.33) "degree of oligopoly power is significant"

Results: 2) Other Parameters  - conjectural variation elasticity - mostly greater than zero and significant - evidence of strategic behaviour  - output demand elasticity – inelastic in all cases  - elasticity of scale..... mostly increasing returns e.g.  > 1 Constant returns to scale - CRS rejected for 33 industries H o :  = 0 20 industries – increasing returns  > 1 13 industries – decreasing returns  > 1

Statistical Significance – high in most cases

Aggregate Industries SIC 2: - Food Industries - Tobacco Industries - Food & Tobacco

Comparisons with Previous Research