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A catering Theory of Dividends

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Table 8. Dividend policy and the dividend premium: Firm characteristics controls, 1963-2000. Two-stage regressions of dividend policy on firm characteristics and the dividend premium. The first stage performs Fama-MacBeth logit regressions of dividend policy on firm characteristics.

The second stage regresses the average annual prediction errors (actual policy minus predicted policy) from the logit regressions on the dividend premium.

, where .

We perform this analysis on three subsamples. The first two rows examine the propensity to initiate dividends PTP New and so restrict the sample to surviving nonpayers. The next two rows examine the propensity to continue paying dividends PTP Old and so restrict the sample to surviving payers. The last two rows examine the propensity to list as a payer PTP List and so restrict the sample to new lists. The firm characteristics are the NYSE percentile NYP, the market-to-book ratio M/B, asset growth dA/A, and profitability E/A. The NYSE percentile is the percentage of firms listed on the NYSE that are equal to or smaller in terms of market capitalization (PRC*SHROUT). The market-to-book ratio is the ratio of the market value of the firm to its book value. Market value is equal to market equity at calendar year end (Item 24 times Item 25) plus book debt (Item 6 minus book equity). Book equity is defined as stockholders’ equity (generally Item 216) minus preferred stock (generally Item 10) plus deferred taxes and investment tax credits (Item 35) and post retirement assets (Item 330). Asset growth is the change in assets (Item 6) over assets. Profitability is earnings before extraordinary items (Item 18) plus interest expense (Item 15) plus income statement deferred taxes (50) over assets. The dividend premium PD-ND is the difference between the logs of the VW market-to-book ratios for dividend payers and nonpayers. These data are shown in Table 1. T-statistics in the second stage regression use standard errors that are robust to heteroskedasticity and serial correlation up to four lags.
























































PTP List











PTP List









 We would like to thank Viral Acharya, Raj Aggarwal, Katharine Baker, Randy Cohen, Gene D'Avolio, Xavier Gabaix, Paul Gompers, Dirk Jenter, Kose John, John Long, Asis Martinez-Jerez, Colin Mayer, Holger Mueller, Eli Ofek, Lasse Pedersen, Gordon Phillips, Rick Ruback, David Scharfstein, Hersh Shefrin, Andrei Shleifer, Erik Stafford, Jeremy Stein, Ryan Taliaferro, Jerold Warner, and seminar participants at Harvard Business School, London Business School, LSE, MIT, Oxford, and the University of Rochester for helpful comments; John Long and Simon Wheatley for data; and Ryan Taliaferro for research assistance. Baker gratefully acknowledges financial support from the Division of Research of the Harvard Business School.

1 Allen and Michaely (2002) provide a comprehensive survey of payout policy research.

2 Hyman (1988) describes investor reaction to Consolidated Edison’s 1974 dividend omission. “[It] hit the industry with the impact of a wrecking ball. It smashed the keystone of faith for investment in utilities: that the dividend is safe and will be paid.” (p. 109).

3 Graham and Dodd (1951) and Gordon (1959) are recognized for this idea. Miller and Modigliani (1961) cite a number of other papers of this vintage that make the same argument.

4 Building on ideas in Thaler and Shefrin (1981), Shefrin and Statman (1984) propose that some investors prefer dividend-paying stocks (over homemade dividends) because of self-control problems. If self-control problems vary over the business cycle, for example, they could also generate time varying sentiment for dividends.

5 Limited arbitrage explanations have been developed for closed-end fund discounts (Lee, Shleifer, and Thaler (1991) and Pontiff (1996)), risk arbitrage returns (Mitchell and Pulvino (2001) and Baker and Savasoglu (2002)), post-earnings-announcement drift (Mendenhall (2001)), the Internet bubble (Ofek and Richardson (2001, 2002)), seasoned equity issue returns (Pontiff and Schill (2001)), negative stub values (Lamont and Thaler (2000) and Mitchell, Pulvino, and Stafford (2001)), IPO underpricing (Duffie, Garleanu, and Pedersen (2002)), the predictive power of breadth of ownership (Chen, Hong, and Stein (2002)), the predictive power of market liquidity (Baker and Stein (2002)), and index inclusion effects (Greenwood (2001) and various papers on S&P 500 additions).

6 Barberis, Shleifer, and Wurgler (2001) and Greenwood and Sosner (2001) find evidence that relates to this hypothesis. They find that when a stock is added to a prominent index, its returns suddenly comove significantly more with stocks already in the index, and less with stocks that remain outside the index. These results indicate that institutional categorization affects stock prices.

7 In 1955 CU obtained a special IRS exemption making the stock dividends not taxable as ordinary income. In general, regular stock dividends have been taxable since the 1969 Tax Reform Act, but CU received a grandfather clause in that Act.

8 Conditions under which managers will pursue short-run over long-run value are also discussed by Miller and Rock (1985), Stein (1989), Shleifer and Vishny (1990), Blanchard, Rhee and Summers (1993) and Stein (1996).

9 An example of a setting in which no tradeoff exists is firm names. Cooper, Dimitrov, and Rau (2001) and Rau, Patel, Osobov, Khorana, and Cooper (2001) document that when investor sentiment favored the Internet (before March 2000), a number of firms added “dot com” to their names, but when sentiment turned away (after March 2000), firms were changing back. While many of these name changes surely coincided with changes in investment policy, Rau et al. provide anecdotal evidence that at least some of them were simply catering to sentiment for the Internet.

10 A firm-level analysis is necessary to evaluate certain non-catering explanations for our results, as discussed in the following section.

11 Market-to-book ratios are approximately lognormally distributed. As a result, levels of the market-to-book ratio, unlike logs, have the property that the cross-sectional variance increases with the mean. In our context, this means that the absolute size of a premium measured in levels could proxy for a market-wide valuation ratio.

12 Our goal here is to calculate an aggregate market-to-book measure for a precise point in time, the end of the calendar year. Later in the paper, when we use market-to-book as a firm characteristic, we use the end of fiscal year stock price.

13 There are two further adjustments made throughout the 1962 through 1989 series. The annual value that we consider is the log of the average of the monthly price ratios, because the relative prices fluctuate dramatically even within a year. And to control for the fact that cash dividends were quarterly, in practice, while the stock dividends were semiannual, the cash dividends are assumed to be reinvested until the corresponding stock dividend is paid.

14 In closer analogy with the other dividend premium variables, one could define an announcement effect variable that combines the reactions to initiations and omissions. That is, when investor demand for dividends is high, initiation effects may be particularly positive and omission effects particularly negative. Unfortunately, CRSP data do not provide precise omission announcement dates.

15 If nonpayers are trading at a discount to payers, a large number of initiations may mechanically dilute the price of payers and hence lower the premium. This can create the sort of Stambaugh (1999) bias that is described in the Appendix in connection with return predictability. This bias is increasing in the correlation between the errors of the prediction regression in Table 5 and the errors in an autogression of the dividend premium on the lagged dividend premium. In the case of PTP New, these errors have a correlation of less than 0.01, so the bias is inconsequential. In the case of PTP Old and PTP List, the correlation is also not statistically significant.

16 The dependent variable is implicitly an equal-weighted measure, so an equal-weighted independent variable may seem appropriate. On the other hand, the value-weighted premium, which emphasizes larger firms, may be more visible to potential initiators.

17 Including the dividend premium directly in equation (13) and estimating the coefficients in a panel regression gives qualitatively similar results to our two-stage procedure (unreported). A panel regression is necessary in that specification because the dividend premium does not vary within a year, as the Fama-MacBeth procedure requires.

18 Miller and Scholes (1978) propose that tax code changes could have no influence, because taxes on dividends can be postponed indefinitely. However, Peterson, Peterson, and Ang (1985) find empirically that most investors do not avoid taxation.

19 Poterba (1987) calculates a tax preference for dividends for a given shareholder class as the ratio of the after-tax income to cash dividends to the after-tax income of retained earnings. He then computes an overall tax preference for dividends parameter by weighting this ratio across shareholder classes. Bernheim and Wantz (1995) use the same parameter. In the 1962-1986 period over which our series overlap, the Poterba tax preference parameter has a correlation of –0.85 with our tax disadvantage measure.

20 The rise of mutual funds roughly coincides with these falling transaction costs, potentially lowering an individual investor’s cost of monetizing capital gains further still.

21 For recent treatments of investor sentiment, see for example Barberis, Shleifer, and Vishny (1998), Daniel, Hirshleifer, and Subrahmanyam (1998) and Hong and Stein (1999).
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