Javier García-Bernardo

The University of Amsterdam

Brighton 2018

Interdisciplinary team

Relationships between corporations, and corporations-State

corporate networks

Nodes:

  • Companies

 

 

 

Links:

  • Shared directors
E.M. Heemskerk, F.W. Takes, J. Garcia-Bernardo and M.J. Huijzer ‘Where is the global corporate elite? A large-scale network study of local and nonlocal interlocking directorates‘, Sociologica 2016. 
Mr. Jorge Paulo Lemann
- Heinz
- 3G Capital
- AB Inbev
- And another 70 positions

corporate networks

Nodes:

  • Companies

Links:

  • Ownership

our interest in ofc

D. Valeeva

work pipeline

1. data (Orbis) and cleaning steps

2. comparison with other databases

3. data exploration

4. projects

1. data (ORBIS)

Flat files: 750 Gb in ~50 files

  • Entities: Sector, addresses, type of entity. 200m, 10y.
  • Financial: Revenue, employees, assets, profit, taxation, etc
  • Ownership: Direct/Total ownership relationships
  • Directors: Name, nationality, age, gender
  • Positions: Type of position, company and director

Cleaning steps

  • Entities: Delete branches and foreign companies
  • Financial: De-consolidation (avoid double counting)
  • Positions: Keep important positions and de-duplication
  • Quantify the unknown: https://arxiv.org/abs/1612.01510

Tools: http://github.com/uvacorpnet

  • Gephi (network visualization)
  • Inkscape (improve visualizations)
  • Python (cleaning and analysis)
  • HTML / Javascript (D3, data exploration)

2. comparison with other databases

2. comparison with other databases

The effects of data quality on the analysis of corporate board interlock networks
https://www.sciencedirect.com/science/article/pii/S0306437917302272
https://arxiv.org/abs/1612.01510

3. data exploration

https://github.com/uvacorpnet/interactive_visualizations

index_data.html

http://corpnet.uva.nl/ccs2016/

4. projects involving ofcs

4.1 UNCOVERING OfC

``Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network''

https://www.nature.com/articles/s41598-017-06322-9

Characterize OFCs

  • sinks:
    • UK territories / former colonies
    • LU, HK
  • conduits:
    • NL / UK / IE / CH / SG

4. projects involving ofcs

4.2 incentives to attract investment / varieties of ofcs

4. projects involving ofcs

4.2 incentives to attract investment / varieties of ofcs

4. projects involving ofcs

4.3 role of OfCs in the reduction of TAX (consequences)

4. projects involving ofcs

4.3 role of OfCs in the reduction of TAX (consequences)

            
                Pioneers:
- Ireland ('00,'01,'02,'03)
- UK ('97,'12,'14)
- Poland ('00,'03)
- Bulgaria ('05,'07)
- Hungary ('04,'17)
- Romania ('00,'05)
- Lithuania ('02,'08)
- Latvia ('04)
- Poland ('04)
- Slovakia ('04)
- Cyprus ('03)
            
        

4. projects involving ofcs

4.4 tax competition

4. projects involving ofcs

4.5 detecting money flows indirectly

FDI is great, but what happens to the money

Who competes at country level?

5. last thoughts

  • New databases with increasing quality are becoming available
  • New analyses are possible:
    • Other units of analysis (firm, city, region)
    • Other methods (network analysis, machine learning)
  • New challenges associated to large size:
    • Data management
    • Data quality:
      • Non-uniform data quality
      • Manual exploration is not possible
    • Statistics:
      • Most regressions will find some effect
      • Corrections, e.g. train/split
    • Others:
      • Require interdisciplinary teams
      • Communication is hard

corpnet.uva.nl

@javiergb_com

@uvaCORPNET

javiergb.com

corpnet@uva.nl

garcia@uva.nl

https://slides.com/jgarciab/brighton

Brighton 2018

By Javier GB

Brighton 2018

Big data, OFC and visualization

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