Screening for collusion: A spatial statistics approach

Pim Heijnen; Marco A. Haan; Adriaan R. Soetevent

doi:10.1093/jeg/lbu012

Screening for collusion: A spatial statistics approach

Pim Heijnen^*, Marco A. Haan, Adriaan R. Soetevent

^*Corresponding author voor dit werk

Economics, Econometrics and Finance

Onderzoeksoutput › Academic › peer review

6 Citaten (Scopus)

135 Downloads (Pure)

Samenvatting

We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust investigation would be warranted. We apply our method to build a variance screen for the Dutch gasoline market.

Originele taal-2	English
Pagina's (van-tot)	417-448
Aantal pagina's	32
Tijdschrift	Journal of Economic Geography
Volume	15
Nummer van het tijdschrift	2
Vroegere onlinedatum	10-mei-2014
DOI's	https://doi.org/10.1093/jeg/lbu012
Status	Published - 2015

Toegang tot document

10.1093/jeg/lbu012

Screening for collusion: a spatial statistics approachFinal publisher's version, 747 KBLicentie: Taverne

Handle.net

Permanente koppeling

Document onder embargo

J Econ Geogr-2015-Heijnen-417-48
Submitted manuscript, 742 KB
Kopie aanvragen

Retail gasoline prices in the Netherlands 2005 - 2011
Heijnen, P. (Creator) & Soetevent, A. (Contributor), DANS - Data Archiving and Networking Services, 1-jun.-2016
DOI: 10.17026/dans-25c-56vs
Dataset

Citeer dit

@article{976b680c5b084d99b5d1a9f2c51cf5fb,

title = "Screening for collusion: A spatial statistics approach",

abstract = "We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust investigation would be warranted. We apply our method to build a variance screen for the Dutch gasoline market.",

keywords = "Collusion, variance screen, spatial statistics",

author = "Pim Heijnen and Haan, {Marco A.} and Soetevent, {Adriaan R.}",

year = "2015",

doi = "10.1093/jeg/lbu012",

language = "English",

volume = "15",

pages = "417--448",

journal = "Journal of Economic Geography",

issn = "1468-2702",

publisher = "Oxford University Press",

number = "2",

}

TY - JOUR

T1 - Screening for collusion

T2 - A spatial statistics approach

AU - Heijnen, Pim

AU - Haan, Marco A.

AU - Soetevent, Adriaan R.

PY - 2015

Y1 - 2015

N2 - We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust investigation would be warranted. We apply our method to build a variance screen for the Dutch gasoline market.

AB - We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust investigation would be warranted. We apply our method to build a variance screen for the Dutch gasoline market.

KW - Collusion

KW - variance screen

KW - spatial statistics

U2 - 10.1093/jeg/lbu012

DO - 10.1093/jeg/lbu012

M3 - Article

SN - 1468-2702

VL - 15

SP - 417

EP - 448

JO - Journal of Economic Geography

JF - Journal of Economic Geography

IS - 2

ER -

Screening for collusion: A spatial statistics approach

Samenvatting

Toegang tot document

Handle.net

Document onder embargo

Vingerafdruk

Datasets

Retail gasoline prices in the Netherlands 2005 - 2011

Citeer dit