Historia alrededor de Gutenberg .5 Infancia y juventud

I perform robustness checks on the definitions of the board index, firm performance, and leverage. In addition, I check for the absence of serial dependence of the firm performance, that is, whether lagged firm perfor-mance is zero. Finally, I check the Fauver and Fuerst (2006) results in two sub-samples of information industries and other industries. With simulta-neous equations, changes in one place are likely to propagate throughout the system. Thus, different coefficient values and significance from the original formulation are quite likely to appear. Fortunately, the results largely confirm those in section 3.6.

Do the co-determination results survive when the individual board mechanisms are used in place of the board index? Table 3.7 shows simul-taneous regressions results when all four board characteristics making up the board index enter the regressions individually.

Table 3.7

Former results for co-determination largely apply. The employee di-rector variable is negative to Tobin’s Q, and positive to average wage and leverage. For the board characteristics, only the relation to board size is significant. On the other hand, the hypotheses on governance variables are upheld for all board characteristics but the gender variable. It turns

out to be non-significant in the Tobin’s Q relation. The other variables are as expected, and their coefficients are close to those Bøhren and Strøm (2007) find in partial GMM estimations. They also discuss endogeneity.

Even though the estimations are not directly comparable, none of the sig-nificant results in table 3.7 conflict with the endogeneity results in Bøhren and Strøm (2007). The second endogeneity effect from lagged firm perfor-mance is significant in the leverage, but not in any of the board variables.

However, the signs on the individual board variables conform to the pos-itive sign of the board index in earlier tables.

Besides these main points, table 3.7 contains many new details, which it is beyond this paper to explore. For instance, the substitution effect between the board index and leverage in former tables now turns out to concern network, while leverage is a complement to board size and gen-der. Thus, overall the results are well in line with former findings, except for the lagged firm performance relationship to governance variables.

In the next table 3.8 I have modified the board index to include all board variables used in Bøhren and Strøm (2007) as specified in footnote 13 to check if the board index is sensitive to the selection of board charac-teristics.

Table 3.8

The overall Wald tests are strong and the significance of the coefficients are almost similar to what earlier full sample results in table 3.4 show. We note that the impact of the employee director variable is less in the new board index, and is now significant in its positive relationship to average wage. Thus, the co-determination hypothesis is supported with this new board index, although with lower coefficient values. The endogeneity ef-fect of a lagged firm performance loses significance in the board index relation. The same happens when individual board characteristics replace the board index, and also disappear in the shareholder determined sub-sample. Thus, a preliminary conclusion is that the reverse causation in the board index relation seems to be sensitive to the specification of the index and in sub-samples.

The conclusion from the discussion of the two last tables is that the results are upheld, in particular, the co-determination hypothesis is con-firmed.

Now I turn to variations on firm performance, using the stock return and ROA instead of Tobin’s Q. The stock return and ROA may be seen as two extremes in performance measurement, the one only market based,

the other only accounting based. Bhagat and Jefferis (2002) argue in favour of accounting measures, noting that market measures may contain an an-ticipation bias, since accounting numbers may be manipulated during a given year. Since our data span fourteen years, this accounting manipula-tion should be a minor concern. These two measures of firm performance should together provide an adequate framework for robustness tests.

The results for the full sample are given in table 3.9. Since the results in samples largely parallel those found for the full sample, the sub-sample results are not reported.

Table 3.9

The results in table 3.9 largely replicate those already found for To-bin’s Q in table 3.4. The co-determination and the governance hypotheses show the same confirmations. As before, leverage is negative in the firm performance equation. Again, the board index and leverage are substi-tutes. Endogeneity (or reverse causation) is evident in both firm perfor-mance specifications, although at different variables. For the stock return the lagged stock return is significant in firm performance and leverage, as before. One would expect this to happen with accounting numbers due to earnings management or conservative accounting practices (Watts, 2003), which would induce serial correlation. However, lagged perfor-mance is significant for only the board index for the accounting measure ROA. Overall, table 3.9 supports earlier findings.

The upshot is that alternative performance measures do not upset con-clusions reached with Tobin’s Q. Therefore, further robustness tests may well proceed with Tobin’s Q as the dependent variable.

Next, table 3.10 shows results when the dividend payout rate replaces the leverage, and Tobin’s Q is the firm performance in the upper part, while in the lower part the lagged firm performance is removed. Divi-dend payout rate is gauged as the annual diviDivi-dend as a fraction of the earnings before interest, taxes, depreciation, and accruals (EBITDA). Dur-ing the period of study, share buybacks were illegal in Norway.

Table 3.10

The striking results are first that the dividend payout rate is nowhere significant as an independent variable, and second, as a dependent vari-able no varivari-able in the system is related in a significant way. In fact the Wald test cannot reject the hypothesis that all coefficients in the dividend

payout rate equation are zero. An exclusion test (not reported) for the div-idend payout rate cannot confirm that the variable coefficient is different from zero. Thus, the dividend payout rate is an inferior substitute for the leverage. Second, the results for the other variables are not affected, even though changes in one part of a simultaneous system may bring about new values in other parts. Therefore, the results in table 3.10 increase the confidence in the original model.

The lower part of table 3.10 shows results when the lagged firm per-formance is left out. The reason for the removal is that lagged firm perfor-mance induces bias (Hsiao, 2003, p. 71-2), since the errors are no longer independent of the regressors. The smaller the bias, the larger is the num-ber of periods in the panel and the closer to zero is the auto-correlation coefficient on lagged firm performance. Furthermore, if the explanatory variables apart from the lagged firm performance have very persistent el-ements, the bias will not disappear. This persistence can be a concern in governance studies. For instance, the firm’s board size is likely to be fairly stable. To test for the seriousness of this bias, I include static system re-gressions, that is, with no lagged performance.

Comparing the results from the no lagged firm performance regres-sion to the original estimates in table 3.4 we see that practically all signs are maintained, and also that coefficient values are quite similar. The co-determination hypothesis is confirmed. For average wage on firm perfor-mance, the variable is significant in the static specification but not in the dynamic. But overall the results from the dynamic estimations are upheld.

Apparently, the low auto-correlation coefficient, the rather long time pe-riod and small persistence in the explanatory variables warrants the use of the dynamic specification in table 3.4.

I also run a regression (not reported) with all explanatory variables lagged one period for the entire sample. This regression shows far fewer significant results, and although the signs are the same as before, this spec-ification is far inferior to the main regression in table 3.4. Again, this points to a contemporaneity in governance mechanisms.

Finally, I run a test for the Fauver and Fuerst (2006) information hy-pothesis in sub-samples. The authors assume information significance to trade, transportation, and manufacturing industries. Using the same GICS industry classification as in table 3.3, I allocate Capital goods, Trans-port, Consumer articles, Retailing, Food and staples retailing, Health care equipment and supplies, and Telecommunications to the information in-tensive industries, while the rest is in other industries. Co-determined

firms are distributed in the two sub-samples almost as in the total popula-tion, with 61.1 per cent without employee directors in the Other industries category against 57.4 in the full sample. A test for the Fauver and Fuerst (2006) information hypothesis is that the employee director variable is pos-itive in the information intensive industries. Table 3.11 shows results.

Table 3.11

The main interest is in the employee director, that is, the co-determination hypothesis. Both sub-samples show a negative and significant coefficient on the employee director variable. The Chow test shows that the two sub-samples are different, but the main Fauver and Fuerst (2006) hypothesis is not supported.

Overall, the results for the robustness test do not invalidate the results found in table 3.4.