| Author : | K. C. K. Chu; S. Chen and T. Leung |
|---|---|
| Category : | Journal Article |
| Department : | Accountancy |
| Year / Month : | 2021 / 01 |
| ISSN: | 0888-7985 |
| Source : | Journal of Information Systems, 35(1) |
Abstract
- This paper presents a do-it-yourself algorithm to generate the historical GVKEY-CIK link table. The proposed algorithm features to pre-classify sample data into different treatment subgroups and utilizes 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.
Keywords
Related Publication
- Statistical inference for risk difference in an incomplete correlated 2x2 table
- Influence measures in contingency table with application in sampling zeros
- Exact power of conditional tests for several binomial populations
- Identities and Decentered Transnational Linkages: Returned Migrants in Hong Kong
- Mediating Links between HRM Bundle and Individual Innovative Behavior