Index

• Pages: 475-498

475

INDEX

A

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

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

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

AGGREGATION............................................. SeeDATA; DEMAND MODELS

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

ALMOST IDEAL DEMAND SYSTEM (AIDS) ..............SeeDEMAND 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)..........................SeeDEMAND 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

476Econometrics 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

BERTRANDOLIGOPOLY 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