SubsidiaryData (2002)
Import data (first 10000 rows) using the import delimited command. The delimiter should be a comma, which Stata can identify automatically. If the automatic delimiter does not work, spectate the data using the import window. The delimiter could be a period .. Choose encoding = utf8. If utf8 doesnt work, try Latin1. Tell Stata not to use the first row of data as variable names. In this way, you will get variable names like v1, v2, .
Consolidate the variable list. For example, we want to know:
In a particular file, what variable name (information contained in row 1) corresponds to the first variable (v1), the second variable (v2),
The ordering should be the same for all files in the same year, but there could be exceptional cases. If ordering and variables are the same for all files in the same year, you can simply keep one list for that year. If not, you need to keep multiple lists for different groups of files within that year.
An indicator that indicates which variables belong to the company profile module and the subsidiary module.
Divide the data into two modules.
Company profile module: general company information. One BvD ID should uniquely identify an observation.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Subsidiary module: one BvDID-subsidiary identifies an observation. Please use the carryforward command to fill in the missing BvDIDs.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
SubsidiaryData (2012)
Import data (first 10000 rows) using the import delimited command. The delimiter should be tab, which Stata can identify automatically. If the automatic delimiter does not work, spectate the data using the import window. Choose encoding = utf16. Tell Stata not to use the first row of data as variable names. In this way, you will get variable names like v1, v2, .
Consolidate the variable list. For example, we want to know:
In a particular file, what variable name (information contained in row 1) corresponds to the first variable (v1), the second variable (v2),
The ordering should be the same for all files in the same year, but there could be exceptional cases. If ordering and variables are the same for all files in the same year, you can simply keep one list for that year. If not, you need to keep multiple lists for different groups of files within that year.
An indicator that indicates which variables belong to the company profile module and the subsidiary module.
Divide the data into two modules.
Company profile module: general company information. One BvD ID should uniquely identify an observation.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Subsidiary module: one BvDID-subsidiary identifies an observation. Please use the carryforward command to fill in the missing BvDIDs.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
OwnershipData (2002)
Import data (first 10000 rows) using the import delimited command. The delimiter should be a comma, which Stata can identify automatically. If the automatic delimiter does not work, spectate the data using the import window. The delimiter could be a period .. Choose encoding = utf8. If utf8 doesnt work, try Latin1. Tell Stata not to use the first row of data as variable names. In this way, you will get variable names like v1, v2, .
Consolidate the variable list. For example, we want to know:
In a particular file, what variable name (information contained in row 1) corresponds to the first variable (v1), the second variable (v2),
The ordering should be the same for all files in the same year, but there could be exceptional cases. If ordering and variables are the same for all files in the same year, you can simply keep one list for that year. If not, you need to keep multiple lists for different groups of files within that year.
An indicator that indicates which variables belong to the company profile module, the shareholder module and the ultimate owner module.
Divide the data into three modules.
Company profile module: general company information. One BvD ID should uniquely identify an observation.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Shareholder module: one BvDID-shareholder identifies an observation. Please use the carryforward command to fill in the missing BvDIDs.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Ultimate owner module: in principle, one BvDID should uniquely identify an observation, but there may be exceptions. Lets not assume this is the case, but you can safely drop rows that have no information on domestic and global ultimate owners. After that, apply carryforward to BvDIDs. In this way, we keep all the rows even when the company has multiple ultimate owners.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
OwnershipData (2012)
Import data (first 10000 rows) using the import delimited command. The delimiter should be tab, which Stata can identify automatically. If the automatic delimiter does not work, spectate the data using the import window. Choose encoding = utf16. Tell Stata not to use the first row of data as variable names. In this way, you will get variable names like v1, v2, .
Consolidate the variable list. For example, we want to know:
In a particular file, what variable name (information contained in row 1) corresponds to the first variable (v1), the second variable (v2),
The ordering should be the same for all files in the same year, but there could be exceptional cases. If ordering and variables are the same for all files in the same year, you can simply keep one list for that year. If not, you need to keep multiple lists for different groups of files within that year.
An indicator that indicates which variables belong to the company profile module, the shareholder module and the controlling shareholder module.
Divide the data into three modules.
Company profile module: general company information. One BvD ID should uniquely identify an observation.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Shareholder module: one BvDID-shareholder identifies an observation. Please use the carryforward command to fill in the missing BvDIDs.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Controlling shareholder module: One BvDID controlling shareholder should uniquely identify an observation. Drop the rows without any controlling shareholder information. After that, apply carryforward to BvDIDs. In this way, we keep all the rows even when the company has multiple ultimate owners.
Save the data as a dta file. (name properly)
Use export delimited and save the data as an csv file. (delimiter=comma) (name properly)
Note: We need to merge in bvd_id_number in owner_2012 and owner_2017 by file name and mark.
Year
Main data file
File containing BvD ID
Merge using key
2012
hku_own_2012_NorthAmerica
hku_own_2012_NorthAmerica_BvD
mark
2012
hku_own_2012_WesternEurope1
hku_own_2012_WesternEurope1_BvD
mark
2012
hku_own_2012_WesternEurope2
hku_own_2012_WesternEurope2_BvD
mark
2012
hku_own_2012_EasternEurope
hku_own_2012_EasternEurope_BvD
mark
2012
hku_own_2012_remaining_countries
hku_own_2012_remaining_countries_BvD
mark
2017
hku_own_2017_CentralAsia_FarEast1
hku_own_2017_CentralAsia_FarEast1_BvD
mark
2017
hku_own_2017_SouthCentralAmerica1
hku_own_2017_SouthCentralAmerica1_BvD
mark
2017
hku_own_2017_SouthCentralAmerica2
hku_own_2017_SouthCentralAmerica2_BvD
mark
2017
hku_own_2017_AfricaOceaniaSupranational
hku_own_2017_AfricaOceaniaSupranational_new
mark
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