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A Novel Algorithm for Generating GVKEY-CIK Link Table

Authors: K. C. Kenneth Chu; Sipeng Chen; Tommy Leung;

A Novel Algorithm for Generating GVKEY-CIK Link Table

Abstract

ABSTRACT This paper presents a do-it-yourself algorithm to generate the historical GVKEY-CIK link table. The proposed algorithm features a technique of pre-classifying sample data into different treatment subgroups and utilizing historical firm information available from the source data to increase (reduce) matching efficiency (errors). Simulation results show that our algorithm is superior to applying only conventional name matching operations over the whole sample: 57.5 percent of the overall matching results are error free ex ante, and for the remaining 42.5 percent of data, records without Type I errors (with Type II errors) increase (decrease) by 34.0 percent (59.4 percent) when the optimal threshold is used. JEL Classifications: C89; M40; G10; G18.

Country
China (People's Republic of)
Related Organizations
Keywords

Link table, 330, Compustat, EDGAR, 10-K, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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