Working Paper: NBER ID: w10895
Authors: Daewook Kim; Christopher R. Knittel
Abstract: Estimating market power is often complicated by the lack of reliable measures of marginal cost. Instead, policy-makers often rely on other summary statistics of the market, thought to be correlated with price cost margins---such as concentration ratios or the HHI. In many industries, these summary statistics may be only weakly correlated with deviations from perfectly competitive pricing. Beginning with Gollop and Roberts (1979), a number of empirical studies have allowed the data to identify industry competition and marginal cost levels by estimating the firms' first order condition within a conjectural variations framework. Despite the prevalence of such "New Empirical Industrial Organization" (NEIO) studies, Corts (1999) illustrates the estimated mark-up levels may be biased, since the estimated conjectural variations model forces the supply relationship to be a ray through the marginal cost intercept, whereas this need not be true in dynamic games. In this paper, we use direct measures of marginal cost for the California electricity market to measure the extent to which estimated mark-ups and marginal costs are biased. Our results suggest that the NEIO technique poorly estimates the level of mark-ups and the sensitivity of marginal cost to cost shifters.
Keywords: No keywords provided
JEL Codes: L1; L5; L9
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Market price (D41) | Marginal cost (D40) |
| Cost shifters (H22) | Marginal cost (D40) |
| NEIO estimates (C13) | Market power levels (L11) |
| NEIO estimates (C13) | Marginal cost sensitivity (D40) |
| Static model conditions (C62) | NEIO estimates of marginal cost (F11) |
| Low demand periods (L97) | NEIO estimates of marginal cost (F11) |
| High demand periods (J23) | NEIO estimates of marginal cost (F11) |
| NEIO estimates (C13) | Elasticity of demand (D12) |