coefficient on franking credits that arises from these studies as however, this is not correct, U; and the result is to underestimate both and its standard error. To demonstrate this, suppose U that a dividend drop-off study involves the following regression: (4) where is the cum-dividend price, is the ex-dividend price corrected for the market Pit-1 movement, is the cash dividend, is the franking credit, and is the regression Di FCi ui residual. Furthermore, there is no distinction between a cash dividend and a franking credit to the extent that the latter can be used. For example, if a franking credit can be fully used, a cash dividend of $10 plus a franking credit of $2 is as good as a cash dividend of $12; in both cases, the gross dividend is $12 and the post-tax dividend is $12(1 where is t) t investor’s – their marginal ordinary tax rate. If all investors could fully utilise the credits, the regression model should then be framed as (5) where would recognise that the expected price change might differ from the gross dividend δ (because the tax rate on gross dividends differs from that on capital gains for many investors). However some investors cannot use the credits at all and this should be dealt with by multiplying by a coefficient that represented some kind of average utilisation rate. FC U Equation (5) would then become (6) Comparison of equation (6) with equation (4) above then reveals that rather than = This U. θ distinction is also recognised by Handley (2008, page 11). To illustrate the effect here, SFG (2013a, para 85) conclude with an estimate of 0.85-0.90 for and 0.35 for and they equate δ θ, the latter with However, since , the implied estimate for is 0.35/0.875 = 0.40 rather than U. U 0.35. Even more significantly, Beggs and Skeels (2006, Table 5) estimate at 0.80 and at δ θ 0.57 for 2000-2004, which implies that is 0.57/0.80 = 0.72 rather than 0.57. U
coefficient on franking credits that arises from these studies as U; however, this is not correct, and the result is to underestimate both U and its standard error. To demonstrate this, suppose that a dividend drop-off study involves the following regression: (4) where Pit-1 is the cum-dividend price, is the ex-dividend price corrected for the market movement, Di is the cash dividend, FCi is the franking credit, and ui is the regression residual. Furthermore, there is no distinction between a cash dividend and a franking credit to the extent that the latter can be used. For example, if a franking credit can be fully used, a cash dividend of $10 plus a franking credit of $2 is as good as a cash dividend of $12; in both cases, the gross dividend is $12 and the investor’s post-tax dividend is $12(1 – t) where t is their marginal ordinary tax rate. If all investors could fully utilise the credits, the regression model should then be framed as (5) where δ would recognise that the expected price change might differ from the gross dividend (because the tax rate on gross dividends differs from that on capital gains for many investors). However some investors cannot use the credits at all and this should be dealt with by multiplying FC by a coefficient U that represented some kind of average utilisation rate. Equation (5) would then become (6) Comparison of equation (6) with equation (4) above then reveals that rather than θ = U. This distinction is also recognised by Handley (2008, page 11). To illustrate the effect here, SFG (2013a, para 85) conclude with an estimate of 0.85-0.90 for δ and 0.35 for θ, and they equate the latter with U. However, since , the implied estimate for U is 0.35/0.875 = 0.40 rather than 0.35. Even more significantly, Beggs and Skeels (2006, Table 5) estimate δ at 0.80 and θ at 0.57 for 2000-2004, which implies that U is 0.57/0.80 = 0.72 rather than 0.57.