Index

• Pages: 475-498

475

INDEX

A

ACCOUNTING DATA ...................................................................See DATA

ADDING-UP...................................................... See CONSUMER BEHAVIOR

ADVERTISING ...............................................See NONPRICE COMPETITION

AGGREGATION............................................. See DATA; DEMAND MODELS

ALL COMMODITY VOLUME (ACV) .................................................... 434

ALMOST IDEAL DEMAND SYSTEM (AIDS) ..............See DEMAND MODELS

AMERICAN STOCK EXCHANGE, PROPOSED MERGER WITH

PHILADELPHIA STOCK EXCHANGE ............................... 132, 143–146

use of econometric evidence to study options exchange

seat prices .........................................................................144–146

ANTICOMPETITIVE EFFECTS ............................ See COMPETITIVE EFFECTS

ANTITRUST DIVISION..................................See DEPARTMENT OF JUSTICE

ANTITRUST LOGIT MODEL (ALM)..........................See DEMAND MODELS

ASSUMPTIONS

importance of......................................................6, 20, 21, 63, 76, 93

modeling assumptions

as possible substitute for unavailable data ......................133, 153

examples of ...................................................................145–146

violation of ..............................................................................20, 93

AUCTIONS...................................................................................225–245

advantages of .......................................................................227, 228

bid rotation in ............................................................................. 236

collusion in ...........................................225, 230–231, 233–240, 244

common analytic assumptions...................................... 240, 241, 245

476 Econometrics in Antitrust

common value auctions ............................................................... 230

conditional independence (property of competitive bidding)........ 237

conspiracy in.................................................................. 233, 234–37

detection of collusion in .........................................................237–39

Dutch auction.............................................................................. 227

English (ascending bid) auction................................................... 227

estimating merger effects in auction markets ..........................239–44

exchangeability (property of competitive bidding)....................... 238

private value auctions...........................................................229, 244

procurement auction.................................................................... 227

reserve price................................................................................ 240

sealed-bid auction ................................................................227, 229

second-price auction

selling auction........................................................................226–27

symmetric models, use of............................................................ 243

value distribution ................................................. 229, 241, 242, 243

winning probabilities............................................................241, 242

AUTOCORRELATION...................................................................... 93, 450

Cochrane-Orcutt procedure ........................................................ 450

AUTOREGRESSIVE MODELS............................................14, 174, 176–177

AUXILIARY MODELING ASSUMPTIONS ................................See PRECISION

B

BERTRAND OLIGOPOLY MODEL ..................................270–272, 329, 432

Bertrand competition with differentiated products ................325–326

Bertrand equilibrium ............................................................270–283

Bertrand-Nash oligopoly behavior............................................... 313

Bertrand-Nash pricing equilibrium .............................................. 152

degree of fit with real-world conditions of............................ 270–271

BEST LINEAR UNBIASED ESTIMATORS (BLUE)

............................................................... See ORDINARY LEAST SQUARES

BEST RESPONSE FUNCTIONS............................................................... 313

BIAS .............................................. 9, 23, 25, 66, 69, 93, 275–276, 286,

....................................................... 297, 306, 318, 331, 442, 461