Objective. Estimate market impacts of "1+" dialing parity plus eliminating traditional LATA boundary.
Model. Measure shifts in market dominance between major competitors, by assuming...
simply to set prices at or near P*.
Empirical work shows that the long-distance industry has behaved this way. Fringe carriers respond to AT&T's pricing decisions, but AT&T responds only slightly, if at all, to its rivals' choices of price and output.
At first blush, one might express surprise at prices set above the naive profit-maximizing level (P). However, a public policy that protects "competitors" at the expense of competition necessarily compels this result. Pricing at P* (the observed price level) cuts across the conventional presumption that regulation has held AT&T's prices below the profit-maximizing level; i.e., as KK&M note in their study, "To the extent that regulation may be binding, the profit-maximizing price of the dominant firm will be higher than observed prices." %n9%n
Finally, notice how the choice of method can dictate the conclusions of an empirical study. Any restriction in output brought about by raising price would increase AT&T's observed price elasticity of demand from E to E*. This violates the a priori assumption of a nexus between price elasticity and profit margin. A study that observes the high price elasticity (and, consequently, the low Lerner Index value) at E* may conclude that AT&T lacks market power. Conversely, a study that observes the high profit margin at price P* would conclude that market power and tacit collusion have boosted AT&T's profits, %n10%n but would miss the fact that P* actually lies above AT&T's unconstrained profit-maximizing price. Neither study necessarily would recognize that the effects being observed followed from a pricing strategy designed to avoid litigation and regulatory costs.
Four implications follow from this interpretation of conduct and performance.
First, empirical studies that use historical price and quantity data drawn from tariffs and other industry sources may yield results that cannot be interpreted, at least in AT&T's case, in the simple economic sense. Embedded in these data are the effects of either an avoided regulatory cost or a significant X-inefficiency %n11%n (em i.e., insurance against renewed regulatory and antitrust action. These effects must be controlled in empirical studies lest they vitiate conclusions.
Second, the contention that the long-distance industry performs as a tacitly collusive oligopoly is less sinister than at first appears. A market price at P* clearly sits above the competitive price, which is expected to lie somewhere between price and marginal cost on Figure 1. But price P* results, not from a tacit conspiracy to build profits, but from a decision by AT&T to constrain its market share. Conjectural variations by fringe competitors still come into play, %n12%n but these too are fueled by AT&T's pursuit of safe-harbor objectives. Tariff filing requirements do facilitate the coordination of price and output levels among fringe carriers, but the consequences are less ominous than might be imagined.
Third, public policies that expose large firms to tactical rent-seeking by predatory rivals and ambitious bureaucrats may provoke super-competitive prices as a perverse and unintended consequence. %n13%n
Fourth, past antitrust policy to exclude local Bell companies from the long-distance market may be the most significant cause of super-competitive pricing. A market survey commissioned