From models 1 and 2 the coefficients of FINST is not statistically different from zero, suggesting that industry effects seem to have no influence on the probability to pay dividends.
Table 1 Summary of research hypotheses and proxy variables Hypothesis Proxy(s) Expected Sign [H.sub.1]: Agency NOSH: the ratio of the number of Positive costs common shareholders to total shares outstanding INSD: percentage held Negative by insiders [H.sub.2]: Size SIZE: natural log of market Positive capitalisation [H.sub.3]: Profita- PROF: earnings per share Positive bility [H.sub.4]: Financial FLEVER: total debt-to-equity ratio Negative leverage [H.sub.5]: Growth and PER: price earnings ratio Negative Investment AGE: age of the firm Positive opportunities AGESQ: the square of AGE Negative Control variable FINST: is a dummy variable to Negative/ control for industry effects Positive equals one if a firm belongs to financial sectors, and zero otherwise.
Table 3: Step-wise Selection Summary Group P Group N P-value Mean Mean FINST
.003 8.16 21.76 EARNVOL .009 0.26 0.13 SIZE .010 1.57(billion) 3.49 PEARN .017 0.74 0.47
'It was then that I looked down to see that the entries in the visitor book all ended in Finst
. There I was: Richard D Brennan Finst
Pylyshyn, Z.W., 2009, "Perception, Representation and the World: the FINST
that Binds", en D.