In my thesis I'm trying to discover which factors influence the CSR (corporate social responsibility, GSE_RAW
) behavior of companies. Two groups of possible factors / variables have been identified: company-specific and country-specific.
First, company-specific variables are (among others)
MKT_AVG_LN
: the marketvalue of the companySIGN
: the number of CSR treaties the company has signedINCID
: the number of reported CSR incidents the company has been involved in
Second, each of the 4,000 companies in the dataset is headquartered in one of 35 countries. For each country, I have gathered some country-specific data, among others:
LAW_FAM
: the legal family the countries' legal system stems from (either French, English, Scandinavian, or German)LAW_SR
: relative protection the countries' company law gives to shareholders (for instance, in case of company default)LAW_LE
: the relative effectiveness of the countries' legal system (higher value means more effective, thus for instance less corrupted)COM_CLA
: a measurement for the intensity of internal market competitionGCI_505
: mesurement for the quality of primary educationGCI_701
: measurement for the quality of secondary educationHOF_PDI
: power distance (higher value means more hierarchical society)HOF_LTO
: country time orientation (higher means more long-term orientation)DEP_AVG
: the countries' GDP per capitaCON_AVG
: the countries' average inflation over the 2008-2010 timeframe
In order to make an analysis on this data, I "raised" the country-level data to the company-level. For instance, if Belgium has a COM_CLA
value of 23, then all Belgian companies in the dataset have their COM_CLA
value set to 23. The variable LAW_FAM
is split up into 4 dummy variables (LAW_FRA
, LAW_SCA
, LAW_ENG
, LAW_GER
), giving each company a 1 for one of these dummies.
This all results in a dataset like this:
COMPANY MKT_AVG_LN .. INCID .. LAW_FRA LAW_SCA .. LAW_SR LAW_LE COM_CLA .. etc
------------------------------------------------------------------------------
1 1.54 55 0 1 34 65 53
2 1.44 16 0 1 34 65 53
3 0.11 2 0 1 34 65 53
4 0.38 12 1 0 18 40 27
5 1.98 114 1 0 18 40 27
. . . . . . . .
. . . . . . . .
4,000 0.87 9 0 1 5 14 18
Here, companies 1 to 3 are from the same country A, and 4 and 5 from country B.
First, I tried analyzing using OLS, but the model seemed very "unstable", as is shown below. The first model has a r-squared of .516:
Adding only two variables changes many of the beta's and significance levels, as well as the r-squared (.591). Of course the r-squared increases when variables are added, but this is quite an increase from .516:
Eventually, it was suggested in another post that I should not use OLS here but mixed models, because of the categorical countly-level data. However, I am confused as to how perform this in SPSS. The examples I found online are not comparable to mine, so I don't know what to fill in, amongst others, in the below mixed model dialogue:
Could somebody using SPSS please help me explain how to perform this analysis so that I may come to a regression model (CSR = b1*MKT_AVG_LN + b2*SIGN + ... + b13*CON_AVG) so that I can conclude wheter CSR is determined by company-features or country-features (or by neither or both)?
I believe I have to insert the company-level variables as covariates and the country-level variables as factors. Is this correct? Second, I am unsure what to do with the LAW_SCA
to LAW_ENG
dummy variables.
Any help is greatly appreciated!