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NCJ Number: 65762 Find in a Library
Title: ANALYZING SUSPECTED COLLUSION AMONG BIDDERS (FROM WHITE-COLLAR CRIME - THEORY AND RESEARCH, 1980, BY GILBERT GEIS AND EZRA STOTLAND - SEE NCJ-65757)
Author(s): M D MALTZ; S M POLLOCK
Corporate Author: Sage Publications, Inc
United States of America
Date Published: 1980
Page Count: 25
Sponsoring Agency: Sage Publications, Inc
Thousand Oaks, CA 91320
Type: Report (Study/Research)
Format: Document
Language: English
Country: United States of America
Annotation: STATISTICAL ANALYSIS TECHNIQUES USED TO ASCERTAIN PATTERNS OF COLLUSION BETWEEN COMPANIES BIDDING ON A GOVERNMENT CONTRACT ARE DESCRIBED.
Abstract: LAWS BEARING UPON BIDS FOR GOVERNMENT CONTRACTS ARE INTENDED TO REQUIRE COMPETITIVE BIDDING SO THAT THE GOVERNMENT WILL OBTAIN A SERVICE OR PRODUCE AT THE LOWEST MARKET PRICE. WHEN COLLUSIVE BIDDING OCCURS, COMPANIES JOINTLY SCHEME TO DISTRIBUTE BUSINESS AMONG THEMSELVES AT A HIGHER PRICE THAN WOULD RESULT FROM TRUE COMPETITIVE BIDDING. IN THE CASE DESCRIBED HERE, DESCRIPTIVE AND INFERENTIAL STATISTICAL ANALYSIS WAS APPLIED TO THE BID DATA. DESCRIPTIVE STATISTICS SUMMARIZE THE DATA IN A CONVENIENT FORM; INFERENTIAL STATISTICS USE THE DATA TO DRAW INFERENCES ABOUT HYPOTHESES OR PARAMETER ESTIMATES. NEITHER TECHNIQUE, HOWEVER, CAN SUBSTITUTE FOR EVIDENCE THAT LINKS THE ACTORS TO COLLUSIVE ACTS. THE ANALYTIC TECHNIQUES REPORTED CAN PROVIDE INVESTIGATORS WITH LEADS GENERATED BY THE HYPOTHETICAL SCENARIOS OF WHAT HAPPENED, WHEN IT HAPPENED, AND BY WHICH FIRMS. THEY CAN BE USED TO CONVINCE A JUDGE TO ISSUE WARRANTS AND SUBPOENAS AND DEMONSTRATE PROBABLE CAUSE TO A GRAND JURY FOR THE SECURING OF INDICTMENTS. THEY CAN ALSO BE USEFUL IN RULING OUT COLLUSIVE BEHAVIOR SO AS TO AVOID A FRUITLESS INVESTIGATION. GRAPHIC DATA, NOTES, AND REFERENCES ARE PROVIDED. (RCB)
Index Term(s): Antitrust offenses; Case studies; Criminal investigation; Government contracting; Statistical analysis; Trade practices; White collar crime
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=65762

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