r. david mclean, jeffrey pontiff and akiko watanabe - Center for ...

Share Issuance and Cross-Sectional Returns: 

R. David McLean 

University of Alberta 

rdmclean@ualberta.ca 

(780) 492-8005 

International Evidence Ψ 

Jeffrey Pontiff 

Boston College 

pontiff@bc.edu 

(617) 552-6786 

April 4, 2008 

Abstract 

Akiko Watanabe 

University of Alberta 

akiko.watanabe@ualberta.ca 

(780) 492-0385 

Share issuance predicts cross-sectional returns in a non-U.S. sample of stocks from 41 

different countries. The issuance effect is more statistically significant than either the size or 

momentum effects, and is similar to the book-to-market effect. As in the U.S., the 

international issuance effect is robust across both small and large firms. Compared to the 

U.S., the effect is driven more by low returns after share creation rather than positive returns 

following share repurchases. The share issuance effect is stronger in countries in which there 

is greater share issuance activity, greater stock market development, and stronger investor 

protection. The results suggest that the return-predictive ability of share issuance is related to 

the ease with which firms can issue and repurchase their shares. 

Ψ We thank Brad Barber, David Chapman, Wayne Ferson, Mark Huson, Masahiro Watanabe, Seminar 

Participants at Michigan State University, and an anonymous referee for helpful discussions. McLean is grateful 

to the Southam/Edmonton Journal Fellowship Award for financial support.

Recent studies by Daniel and Titman (2006), Pontiff and Woodgate (2006), and 

Fama and French (2007) show that there is a significant negative relationship between share 

issuance and average returns in the cross section of U.S. firms. In this paper, we take a first 

look at the return predictive ability of firm-level share issuance in international markets. Our 

analysis is divided into two parts. In the first part we test whether the issuance effect is 

present among non-U.S. firms, and compare our results to those reported in U.S. studies. In 

the second part of our analysis we test whether the issuance effect differs across countries, 

and if so whether proxies for equity market development, investor protection, and other 

country characteristics can explain any cross-country differences. 

With respect to the first part of our analysis, the use of international data enables a 

better understanding of whether sources of return predictability identified in the U.S. pose 

challenges to asset pricing, or whether they are statistical artefacts from data-mining. 

Previous research in this vein includes Rouwenhorst (1998) who studies momentum effects 

in twelve European markets, and Fama and French (1998) who examine value effects in 

twelve developed countries. These papers find that momentum and value display similar 

predictability in international markets as in the U.S. Such an investigation is particularly 

important for share issuance, since Pontiff and Woodgate (2006) find that the relationship 

between issuance and returns is insignificant in their pre-1970 sample, suggesting that the 

issuance effect may be sample specific. Our analysis based on non-U.S. firms hence provides 

a useful out-of-sample test of the issuance effect. 

We use a large sample of firms drawn from 41 non-U.S. countries and examine the 

existence of an international issuance effect over a 25-year period between 1981 and 2006. 

Using net issuance measures that reflect both share issuance and repurchases, we find that 

1

there is a significant issuance effect in international markets. Similar to the recent U.S. 

evidence, international share issuance has strong return-predictive ability. A one standard 

deviation difference in annual share issuance is associated with a 0.16% difference in 

subsequent monthly returns in the non-U.S. markets, which is half of the magnitude in the 

post-1970 U.S. findings reported in Pontiff and Woodgate (2006). The predictive ability of 

annual issuance is more statistically significant than that of size and momentum, and is of the 

same magnitude as book-to-market. We also find that the issuance effect is robust across 

both small and large firms, which is consistent with the findings in Fama and French (2007). 

The evidence in Loughran and Ritter (1995), Loughran and Vijh (1997), and Fama 

and French (2007) shows that in the U.S. abnormal returns are associated with both positive 

share issuance and share repurchase. Our sample of non-U.S. firms allows for out-of-sample 

tests of both effects. We find that non-U.S. firms that issue stock tend to experience larger 

negative abnormal returns than do U.S. issuers. 1 There is a buyback effect across non-U.S. 

firms, but it is weaker than that found in the U.S., and unlike the U.S. effect it is limited to 

small firms. 

In the second part of our analysis we examine cross-country differences in the 

issuance effect. The U.S. evidence suggests that the ease with which firms can issue and 

buyback their shares is an important factor in explaining the issuance effect. Pontiff and 

Woodgate (2006) show that pre-1970 only 37.4% of U.S. firms had nonzero values of share 

issuance, and that during this period there was no share issuance effect. Post-1970, 75.8% of 

U.S. firms had nonzero values of share issuance, and during this period the return-predictive 

ability of share issuance is strong. 

1 Ikenberry, Lakonishok, and Vermaelen (2000) find evidence of low abnormal returns following both seasoned 

equity offerings and stock-financed mergers in Canada. Their sample includes 161 share issuance events over 

the period 1989-1995. 

2

Across the 41 countries in our sample there is a good deal of variation in share 

issuance activity. As an example, in Chile only 11% of our observations have nonzero 

issuance values; while in the U.K. 55% of the observations have nonzero issuance values, 

suggesting that it is less costly for firms to issue and repurchase shares in the U.K. than in 

Chile. Share issuance should also be less costly in more developed stock markets, so we use 

stock market development variables as proxies for the cost of share issuance activity as well. 

We also test whether the issuance effect is related to investor protection laws. Morck, 

Yeung, and Yeu (2000) contend that less developed stock markets, which offer fewer 

investor protections, have less efficient markets. Morck et al. reason that arbitrageurs are 

more willing to trade in developed markets which protect their property rights. If this 

reasoning is correct, then we might expect the issuance effect to be stronger in less developed 

markets, as the firms in these markets should contain larger mispricing. 

We find that the issuance effect is stronger in countries with more issuance activity, 

in countries with more developed stock markets, and in countries with better investor 

protection laws. One interpretation of these results is that market timing is more prevalent in 

countries in which it is less costly for firms to issue and buyback shares. La Porta et al. 

(2006) show that countries that have better investor protection laws have more developed 

stock markets, and offer firms greater access to equity capital. This might explain why the 

issuance effect is stronger in countries with better investor protection 

Our findings may also be consistent with an efficient markets explanation. A Firm 

may attempt to maintain its optimal capital structure by issuing and repurchasing shares in 

response to changes in its investment opportunities. If changes in investment opportunities 

are correlated to changes in risk exposure, then share issuance is likely to have a stronger 

3

correlation to stock returns in an environment where it is less costly to issue shares, so firms 

rebalance their capital structure frequently, than in an environment in which the costs of 

share issuance exceed the benefits of maintaining a target capital structure. 

The remainder of the paper is organized as follows. Section 1 discusses data and 

estimation procedures. Section 2 presents regression results using continuous measures of 

share issuances, and Section 3 provides results based on issuance portfolios that allow us to 

study positive and negative share issuance effects separately. Section 4 studies the issuance 

effect across countries. Section 5 concludes. 

1. Data, Variables, and Estimation 

1.1. Data 

Our sample consists of 41 non-U.S. countries, which are listed in Table 1. The data 

used in this study are obtained from Thomson Datastream. We use data from monthly stock 

price indices to calculate returns. We also use market capitalizations, market-to-book values, 

shares outstanding, and the capital adjustment index to compute our share issuance measures. 

Returns and market capitalizations are converted to U.S. dollars. We select common stocks 

listed on each country’s major stock exchange(s) from both active and defunct research files 

of Datastream in order to avoid survivorship bias. We screen the data for coding errors via 

the methods of Ince and Porter (2006) and winsorize each variable within country at the top 

and bottom 1% to eliminate the affects of outliers. 

Due to the availability of firm book values in Datastream, our regression analysis 

begins in July of 1981 and ends in June of 2006. The start and end dates vary across 

countries based on each country’s data availability (see columns 2 and 3 of Table 1). We use 

4

data prior to the listed start dates to construct some of the variables that are described in the 

following subsection. To be included in our sample, a stock must have sufficient information 

to generate the annual issuance measure (explained below), market value of equity, lagged 

six-month holding period return, and current month’s return. Each month we limit our 

sample to countries that have at least 50 firm observations in that month. 

Our final sample consists of 2,819,906 total firm-month observations (see column 4 

of Table 1). Japan represents the largest part of our sample, accounting for 14.72% of the 

total observations (column 5) and 29.56% of the total market value per month (column 9). 

The United Kingdom is the second largest and accounts for 13.27% of the total observations 

and 11.68% of the total market value. The rest of the countries typically accounts for less 

than 5% of the total observations and market value. 

1.2. Variables 

Share issuance. The main variable of our interest is the real change in shares 

outstanding, or the change in the number of shares outstanding adjusted for distribution 

events such as stock splits and stock dividends. We use the capital adjustment index from 

Datastream recorded at the end of month t (CAIt) to calculate the number of real shares 

outstanding for that month (Adjusted Sharest). The CAI is the cumulative product of the 

inverse of the individual-period capital adjustment factor (AX) and is analogous to the Total 

Factor of Pontiff and Woodgate (2006): 

CAIt = ∏ 

i= 

t 

1 

1 /AXi 

. 

Adjusted Sharest is then given by: 

Adjusted Sharest = Shares Outstandingt / CAIt. 

5

We use Adjusted Shares to construct two continuous measures of share issuance. 

First, we compute a one-year issuance measure (ISSUE) used in Pontiff and Woodgate 

(2006) and Fama and French (2007) as: 

ISSUEt,t-12 = Ln(Adjusted Sharest) – Ln(Adjusted Sharest-12). 

Size. We calculate the natural logarithm of the June-end U.S.-dollar converted market 

value of equity from Datastream. This variable, ME, is used to forecast returns from July of 

this year through June of the following year. 

Book-to-market. We use the Fama and French (1992) procedure and construct the 

natural logarithm of the previous fiscal year-end book-to-market ratio, BM. 2 The book-to- 

market ratio is the inverse of the market-to-book value provided by Datastream. To ensure 

the availability of accounting information, BM is used to forecast returns from July of the 

current year through June of the following year. 

We follow Pontiff and Woodgate (2006) and create a book-to-market dummy 

variable, BM-Dum. If the book value of equity is either missing or negative, we assign both 

BM and BM-Dum values of zero. Otherwise, BM-Dum is set to one. The use of BM-Dum 

allows us to include firms with either missing or negative book values of equity without 

influencing inference of the slope coefficient on BM. 

Momentum. Our momentum measure, MOM, is given by the U.S.-dollar returns over 

the previous six months. A one month lag of this variable, MOMt-7,t-1, is used to forecast 

holding period returns from month t+1 in order to avoid the effect of bid-ask bounce. 

Holding Period Returns. The dependent variables in our regressions are subsequent 

holding period U.S.-dollar returns. We measure returns over the first month and first year. 

2 The fiscal year end for Japan is March, whereas it is December for all other countries. 

6

1.3. Estimation 

We estimate a set of Fama and MacBeth (1973) regressions each month to calculate 

linear relations between holding period returns and our independent variables. We then report 

time-series averages of intercepts, slope coefficients, and adjusted R 2 s obtained from the 

cross-sectional regressions. We use the procedure of Pontiff (1996) to calculate t-statistics for 

the regression coefficients with autocorrelation-consistent standard errors that correct for the 

holding period overlap. 

Our goal in this paper is to study the pervasiveness of the issuance effect in 

international markets. Therefore, we pool firm observations from the 41 countries into one 

sample and conduct all of our analyses using this pooled data. We estimate every regression 

both with and without country dummy variables. When the country dummies are included, 

the regression coefficients provide estimates of the within-country effects. When the 

dummies are excluded, the coefficients measure the effects across the entire sample. 

Henderson, Jegadeesh, and Weisbach (2006) show that countries with large positive 

share issuances have low subsequent returns. Their results suggest that there is an aggregate 

issuance effect across countries, but do not tell us whether there is an issuance effect across 

stocks within each country. The cross-stock issuance effect in the U.S. is documented by 

Daniel and Titman (2006), Pontiff and Woodgate (2006), and Fama and French (2007). The 

use of country dummies in our regression analyses allows us to test whether such a cross- 

stock effect exists in international markets. 

In addition, we also estimate all of our regressions by both equal-weighting and 

value-weighting each observation. If the results from the two regressions are comparable, 

then we infer that the issuance effect is similar across both small and large firms in our 

7

sample. This investigation is motivated by Fama and French (2007), who find that the 

issuance effect is pervasive across different size groups in the U.S. 

Firms are on average larger in more developed markets than in less developed ones, 

so value-weighting in our sample might just be measuring a developed market effect. To 

address this issue we use a third weighting scheme, in which we scale each value-weight by 

the average market value in the firm’s country (scaled-weight). The scaled-weight is a 

within-country value-weight; it allows us to test whether the issuance effect is present in 

stocks that are large relative to other stocks in the same country. 

2. Return Predictive Ability of Continuous Issuance Measures 

2.1. Summary Statistics for Continuous Issuance Measures 

Table 2 presents summary statistics for the variables used in our study. We focus on 

the continuous issuance measures, ISSUE. We observe that ISSUE has a pronounced right 

skew; it has a mean value of 0.048, which is greater than its 75th percentile value of 0.007. 

Pontiff and Woodgate (2006) report similar findings for the U.S.; their ISSUE measure has a 

mean of 0.04 and a 75th percentile value of 0.03. 3 These numbers also indicate that the 

average level of ISSUE is similar between U.S. and non-U.S. firms. 

2.2. Determinants of International Share Issuance 

We study the characteristics of international share issuances further by examining 

how they are related to firm characteristics. Table 3 reports the results from Fama-MacBeth 

regressions in which ISSUE is regressed on the values of size, book-to-market, and 

3 Unless otherwise noted, our comparisons of summary statistics and regression results to those of Pontiff and 

Woodgate (2006) use their post-1970 study since our sample begins in 1981. 

8

momentum that are available immediately before the ISSUE-construction months, as well as 

on the twelve-month lag of ISSUE (LAG-ISSUE). We estimate six different regression 

specifications; first using equal-weights, value-weights, and scaled-weights with country 

dummies and then without country dummies. 

In all six regressions, the coefficients on size are both negative and significant, 

suggesting that large firms issue fewer shares than do small firms. The coefficients on the 

momentum and lagged issuance measures are both positive and significant in all six 

regressions. This implies that firms with high past returns and firms that have recently issued 

shares are likely to issue more shares. These findings are consistent with Pontiff and 

Woodgate’s (2006) U.S. findings. 

The book-to-market coefficients are positive in all six regressions, but are significant 

only in the equal-weighted regressions. This suggests that high book-to-market firms issue 

more shares and low book-to-market firms buyback more shares, and that this pattern is more 

strongly observed among large firms. The result is in stark contrast to the findings for U.S. 

firms, in which low book-to-market firms tend to issue more shares (see Loughran and Ritter 

(1995), Baker and Wurgler (2002) and Pontiff and Woodgate (2006)). 

The use of country dummies does not have a strong effect on the regression 

coefficients; economic and statistical significances of the coefficients are mostly similar in 

the regressions with country dummies and those without. However, the average R 2 statistics 

from the regressions with country dummies are more than twice as large as those from the 

regressions without the dummies. Thus, country of origin explains as much of the variation in 

share issuances as do the individual firm characteristics that are included in the regressions. 

9

2.3. Share Issuance and Future Returns 

We now turn to one of the main focuses of our paper, and test whether international 

share issuance can predict the cross section of stock returns. We conduct our analyses using 

holding period returns measured over the first month and first year, and with equal-weighted, 

value-weighted, and scaled-weighted returns. 4 

Panels A and B of Table 4 summarize the results of the regressions in which ISSUE is 

the only explanatory variable along with country dummies (Panel A) and without the 

dummies (Panel B). The ISSUE coefficients are negative and significant in all twelve of the 

regressions reported in Panels A and B. This indicates that annual issuance has a significant 

and persistent ability to predict cross-sectional returns both within country (Panel A) and 

across countries (Panel B). 

The issuance effect is robust to all three weighting schemes, suggesting that the effect 

is strong in both large and small stocks. Looking across the columns in Panel A and B we see 

that, for a given holding period the, coefficients and t-statistics are similar for each of the 

three weighting schemes. This is consistent with Fama and French (2007), who find that the 

issuance effect is present across both large and small stocks in U.S. markets. 

A comparison of our results in to those of Pontiff and Woodgate (2006) reveals that 

when estimated with a continuous issuance measure the economic magnitude of the annual 

issuance effect is stronger in the U.S. than in international markets. For example, In Panel A 

our equal-weighted one-month holding period regression yields an ISSUE coefficient 

estimate of -0.79, implying that a one standard deviation increase (0.21) in annual issuance 

leads to a 0.16% decline in the cross section of monthly international returns. From the same 

4 In an earlier version of this paper we also used returns measured over six months, second year, and third year. 

The results over these horizons are similar to the results for the one month and one year horizons, so for the 

sake of brevity we do not report them. 

10

egression that includes only the ISSUE variable, Pontiff and Woodgate (2006) find its slope 

to be -2.23; this indicates that a standard deviation increase (0.15) in annual issuance is 

associated with a 0.33% decline in the subsequent month’s cross-sectional returns in the U.S. 

A similar comparison made for the 1-year holding period also shows that the continuous 

annual issuance measure exhibits a stronger economic effect on future returns in the U.S. 

than in non-U.S. countries. 

2.4. The Impact of Size, Book-to-Market, and Momentum on the Share Issuance Effect 

To test the robustness of the international issuance effect, we include size (ME), 

book-to-market (BM), and momentum (MOM) as control variables in the regressions. We 

report these results in Panels C and D of Table 4. Controlling for these effects is important 

since they exist in international markets (see Fama and French (1998), Rouwenhorst (1998, 

1999), and Griffin, Ji, and Martin (2003)). 

Overall, we observe that the effects of ISSUE are robust to the inclusion of other firm- 

specific variables. The issuance measure has significant negative coefficients in all twelve 

regressions reported in Panels C and D, and the effect remains similar in both economic 

magnitude and statistical significance as compared to the results in Panels A and B. These 

results are similar to those reported in Pontiff and Woodgate (2006) and Fama and French 

(2007), who find that the U.S. issuance effect remains pervasive after controlling for other 

firm characteristics known to affect future returns. 

The results in Panels C and D show that the statistical significance of issuance 

compares favourably to those of other firm-specific variables. The t-statistics for the ISSUE 

slopes are considerably larger than those for ME and comparable to those for BM throughout 

11

the regressions. They are also greater than those for MOM in both the value- and scaled- 

weighted regressions. 

2.6. Discussion 

Based on our analysis, we offer several additional observations and interpretations of 

our results. First, we observe large differences in average R 2 statistics resulting from the same 

regression specification estimated with and without country dummies. For example, the 

average R 2 statistics are mostly 20% and above in Panel A of Table 4 (with country 

dummies), whereas they are at most 0.30% in Panel B of the same table (without country 

dummies). The R 2 statistic tells us how much stock-return variation is associated with the 

variation in the explanatory variables. Therefore, this difference in average R 2 suggests that 

country effects alone can explain about 20% of the cross-sectional variation in international 

stock returns. 

A comparison of the results from the same regression that differs only in terms of 

country-dummy usage also shows that the t-statistics on the ISSUE coefficients are larger 

when the dummies are used. This finding indicates that the return predictive ability of share 

issuance tends to be more robust within a country than across countries. 

Annual share issuance alone explains very little of the cross-sectional variation in 

international stock returns. Across all holding periods, the highest average R 2 is only 0.30%, 

and is lower in four out of the five holding periods examined by Pontiff and Woodgate 

(2006). Pontiff and Woodgate show that in the U.S., size, book-to-market, and momentum 

explain 2-8 times the cross-sectional return variation explained by share issuance. Since the 

ability of annual issuance to explain cross-sectional return variation is even smaller in 

12

international markets than in the U.S., it is doubtful that share issuance proxies for a risk 

factor in the same vein as book-to-market and size in the U.S. Share issuance may still reflect 

rational asset pricing, although its contribution to expected returns is likely to be through a 

non-risk based avenue, such as providing compensation for taxes or transaction costs. 

The relation between book-to-market and issuance runs counter to market-timing 

literature that uses book-to-market as a proxy for mispricing (Lakonishok, Shleifer, and 

Vishny (1994)). Counter to this literature, Table 2 shows that high book-to-market firms 

tend to issue more stock. 

We find that firms are more likely to issue shares after having had high past returns, 

and that this result is stronger for small firms. This finding is consistent with both the U.S. 

evidence and with market timing theories. However, high past returns could be the result of 

improved investment opportunities, and smaller firms may be more dependent on equity 

financing than large firms. Therefore, capital raising for legitimate investment opportunities 

could also explain the observed relation between past returns and share issuance. 

3. Effects of Positive and Negative Share Issuances 

Previous studies have investigated long-run returns following specific events that 

affect shares outstanding, such as seasoned-equity offerings (Loughran and Ritter (1995)) 

and stock-financed mergers (Loughran and Vigh (1997)). Fama and French (2007) compare 

issuance-return predictability based on the whether the firm is an issuer or repurchaser, and 

the magnitude of the respective activity. Motivated by the results in these studies, we test 

whether positive and negative issuances can separately predict returns across non-U.S. firms. 

Our investigation varies from the repurchase literature in that our issuance variable measures 

13

actual issuance activity, whereas the repurchase literature uses announcements [for example, 

Ikenberry, Lakonishok, and Vermaelen (1995), Ikenberry, Lakonishok, and Vermaelen 

(2000), and Rau and Vermaelen (2002)]. 

3.1. Methodology 

In order to compare the U.S. and non-U.S. evidence, we follow Fama and French 

(2007) and sort stocks every month into eight groups based on the level of issuance. Like 

Fama and French (2007), we use all but the smallest quintile stocks in our sample to 

determine the portfolio breakpoints, although the smallest stocks are also included in the 

portfolios. POS1 through POS5 are the quintiles of firms with positive share issuances, with 

POS5 consisting of the largest issuers. NEG1 and NEG2 are the portfolios of firms with 

negative issuance, with NEG1 containing the largest net share repurchasers, with ISSUE 

values below that month’s median negative value. Firms with zero issuance are included in 

the portfolio, ZERO. 

There is some variation in the laws concerning buybacks across the countries in our 

sample (see Table 7), and many of the countries in our sample had changes in their laws 

regarding buybacks during our sample period. The law changes either made buybacks legal 

for the first time, or made buybacks more feasible from either a tax or regulatory perspective. 

To test whether buyback restrictions affect the issuance and repurchase effects, we exclude 

firm-month observations for which buybacks were either illegal or infeasible, and repeat our 

analysis. 

3.2. Summary Statistics for Positive and Negative Issuance Portfolios 

14

Summary statistics for the portfolios are presented in Table 8. Panel A reports the 

statistics for the entire sample. The table shows that in an average month 58.05% of the firms 

in our sample have ISSUE values of zero, while about 6% have negative share issuances and 

the remaining 36% have positive share issuances. The smallest three positive-issuance 

portfolios have negligible values of ISSUE; they are 0.1%, 0.9%, and 3.8%. This is similar to 

the findings in Fama and French (2007) who report values of 0.14%, 0.57%, and 1.48% for 

the same quintiles with U.S. stocks. 5 

Compared to the U.S., the biggest issuers and the biggest net repurchasers in the 

world tend to have more extreme changes in their shares outstanding. For the highest quintile 

of positive issuers we find a mean issuance of 46.2%, compared to Fama and French’s (2007) 

finding in the U.S. of 24.04%. For the lower half of repurchasers we find a mean value of 

issuance of -13.3%, compared with -5.73% from Fama and French’s (2007) study. 

Panel B displays the results for the sample that excludes firm-month observations that 

have buyback restrictions. We expect the absolute values of the NEG portfolios to increase 

when buybacks become either legal or more attractive, and the results in Panel B relative to 

those in Panel A show this. The results in Panel B also show that the value of POS increases 

when buybacks are allowed. The POS4 and POS5 portfolios increase from 12.00 and 46.20 

in Panel A, to 13.98 and 50.23 in Panel B. One reason for this increase could be market 

timing, in that firms are more willing to issue overvalued shares if they can buy the shares 

back if their equity becomes undervalued. 

5 Buybacks in the U.S. were restricted prior to 1982, so Fama and French’s sample, which begins in 1963, also 

includes observations for which buybacks were restricted. 

15

3.3. Positive and Negative Share Issuances and Subsequent Returns 

In Table 9 we again test whether share issuance can predict returns, only now we 

replace the ISSUE measure with dummy variables that indicate which of the seven share 

issuance portfolios that a firm belongs to. Panel A reports the results for the full sample. 

NEG1 is significant only with equal-weightings, and NEG2 is not significant with any of the 

weightings. This shows that the international issuance effect is weak, and limited to smaller 

firms. This is different than the results that Fama and French (2007) obtain with U.S. stocks; 

they find that negative issuance portfolios have positive and statistically significant abnormal 

returns in both large and small stocks, showing that the buyback effect is weaker 

internationally than it is in the U.S. 

At the one-month horizon the POS4, and POS5 coefficients are negative and 

statistically significant under each of the three weighting schemes. This result is stronger than 

that reported by Fama and French (2007) for U.S. stocks; they find that only the fifth quintile 

of issuers has negative abnormal returns. The POS5 slope is -0.44% and its t-statistic is -6.00, 

suggesting that if a firm is in POS5 its expected returns over the subsequent month are lower 

by 0.44%. Fama and French (2007) find that this group of firms in the U.S. underperforms by 

0.27% per month. The POS4 slope is -0.28% and its t-statistic is -4.57. Fama and French 

(2007) find that this group of firms in the U.S. has a positive abnormal return of 0.07%. 

Taken together, these results show that the impact of positive issuances on future returns is 

both more pervasive and of greater economic magnitude internationally than in the U.S. 

Overall the results in Panel A show that the positive issuance effect found in the U.S. 

is not sample specific, and exists in a similar fashion across non-U.S. firms. The results also 

show that there are both similarities and differences between the U.S. and non-U.S. buyback 

16

effects. In the U.S., the buyback effect exists in both small and large firms, whereas 

internationally the effect is found primarily among small firms. 

Panel B restricts the sample to observations for which buybacks were feasible. 

Surprisingly, the NEG coefficients are not positive and significant in any of the regressions. 

However the POS4 and POS5 coefficients in Panel B are noticeable larger, as are their t- 

statistics, when compared to those in Panel A. This shows that when firms can buy their 

shares back, the post-issuance returns are worse following positive issuances. This again 

could be consistent with market timing, as firms may be more willing to issue overvalued 

shares if they know that they can buy those shares back if their equity becomes undervalued 

in the future. 

4. Determinants of Cross-Country Differences in the Share Issuance Effect 

In this Section we test whether the share issuance effect varies across countries, and if 

so what type of factors can explain cross-country differences in the effect. 

4.1. Hypothesis Development 

The issuance effect might be stronger in countries in which it is easier for firms to 

issue and buyback their own shares. To understand why, assume that the benefits from share 

issuance and repurchase activities include both taking advantage of mispricing and target 

capital structure adjustments. However there are costs involved with issuing and 

repurchasing shares and rational managers will only engage in capital structure changes if the 

total benefit is larger than the cost. In this framework if the cost of transacting in one’s own 

stock decreases, then we would expect firms to transact in their own stock more frequently, 

17

and we would also expect these transactions to convey more information about cross- 

sectional mispricing. 

The findings in Pontiff and Woodgate (2006) support this hypothesis. Pontiff and 

Woodgate (2006) find that in the U.S. pre-1970, 37.4% of firms have nonzero annual 

issuance, and that during this time period the relation between issuance and future stock 

returns is insignificant and often positive. Post-1970, Pontiff and Woodgate (2006) find a 

negative and statistically significant relation between issuance and future returns. During this 

period issuance and repurchase activity are more frequent, with 75.8% of firms having 

nonzero annual issuance. 

Like Pontiff and Woodgate, we use the percentage of firm-month observations with 

nonzero ISSUE values as a proxy for the ease with which firms can issue and repurchase their 

shares. There is significant variation in the issuance activity among the countries in our 

sample (see Table 7), and we test whether the issuance effect is greater in countries where 

issuance activity is greater. 

Share issuance should be less costly in countries with more developed stock markets, 

so we also use several stock market development measures as proxies for the cost of issuing 

shares. La Porta et al. (2006) introduce several measures of stock market development and 

we use their measures. 

We also test whether the issuance effect is related to investor protection laws. One 

might expect that the issuance effect will be weaker in countries with stronger investor 

protection laws. To see why, consider an environment in which some investors are irrational, 

so mispricing can arise. However there are arbitragers that can profit from this mispricing, 

thereby keeping markets efficient. Further assume that investor protection laws are effective. 

18

These laws reduce information asymmetries between issuers and investors, and prevent 

managers from expropriating the firm’s resources. In a state with strong protection, 

arbitrageurs will have similar information as managers. Because they do not fear 

expropriation, arbitrageurs will trade on their information keep prices close to fundamental 

values [see Morck, Yeung, and Yeu (2000)]. In states with weak investor protection, the 

information asymmetries between managers and arbitrageurs will be greater, and arbitrageurs 

are less willing to trade due to a lack of protection. This should result in larger mispricing in 

low protection countries, and stronger share issuance effects. 

4.2. Variable Descriptions 

To test these hypotheses we use several different measures of stock market 

development and investor protection that have been used in previous studies. Each of the 

variables is displayed in Table 7. We include U.S. firms in this part of our analysis. 

4.2.1. Measures of Firm-Level Issuance, Issuance Activity, and Stock Market Development 

Country-Level Issuance Coefficients. We estimate monthly and yearly issuance 

coefficients for each country, using monthly returns, equal weights, and controls for size, 

book-to-market, and momentum. Share issuance activity is infrequent in many smaller 

countries, with many firms having values of zero for ISSUE. Therefore we only estimate the 

coefficient in countries which have at least 100 firms in each cross-section. We display the 

monthly coefficients in Panel A of Table 7 and the yearly coefficient in Panel B of Table 7. 

Percentage with Nonzero Issuance. Each month we measure the percentage of firms 

in each country with nonzero values of ISSUE. Countries with a higher value of this measure 

19

contain firms that more actively issue and repurchase their own shares, suggesting that share 

issuance activity is not costly. 

Liquidity is the total dollar value of stocks traded scaled by GDP, for the period 1996- 

2000. This measure is used by La Porta et al. (2006) as a proxy for the level of stock market 

development. 6 

Turnover is the total dollar value of stocks traded, scaled by the value of shares 

outstanding, for the period 1996-2000. This measure is used by La Porta et al. (2006) as a 

measure of stock market development. 

Log GDP per capita is per capita GDP in U.S. dollars in 2000. La Porta et al. (2006) 

show that countries with higher per capita GDP have more developed stock markets. 

Buybacks. We create a dummy variable which is equal to 1 if buybacks are feasible, 

and zero if they are not feasible. We define buybacks as not feasible if they are illegal, or if 

tax or other regulatory issues make them highly unattractive. As an example, we define 

Australia as feasible post-1995. Buybacks became legal in Australia in 1989, but regulatory 

issues made them infeasible (and highly infrequent) until rule changes in 1995. We obtained 

our buyback data from various sources, with Kim, Schremper, and Varaiya (2004) providing 

data for the ten largest stock markets. 

Short Selling. We create a dummy variable which is equal to 1 if short selling is not 

allowed and zero if it is allowed. We obtained this measure from Bris et al. (2007). If short 

selling was legal prior to 1990, then Bris et al. report “Before 1990” as the effective date. For 

these countries, we assume that short selling was allowed in each of the years prior to 1990. 

6 

The measures from La Porta et al. (1999 and 2006) were obtained from Andrei Shleifer’s website. We thank 

Andrei Shleifer for making the data available. 

20

4.2.2. Measures of Investor Protection 

Law. We create a dummy variable which is is equal 1 if a country is of common law 

origin and zero if the country is of civil law origin. This measure is from La Porta et al. 

(1997). La Porta et al. show that common law countries tend to have stronger investor 

protection laws than civil law countries. 

Accounting is an index of accounting standards; a higher value represents better 

accounting standards. The index is based on the reporting or omission of 90 items from 

annual reports. A higher value signals better accounting standards. This measure is from La 

Porta et al. (1997). 

Criminal is an index which measures the ease with which accountants, directors, and 

distributors can be pursued in criminal courts for not fully disclosing information in 

prospectuses. A higher value signals greater investor protection. This variable is from La 

Porta et al. (2006). 

Liability is an index which measures the ease with which accountants, directors, and 

distributors can be pursued in civil courts for not fully disclosing information in 

prospectuses. A higher value signals greater investor protection. This variable is from La 

Porta et al. (2006). La Porta et al. show that countries with higher values of Liability have 

more developed equity markets. 

Protect is the principle component of three different investor protection indices. The 

indices are Liability, an index of disclosure requirements, and an index of anti-director rights. 

A higher value of Protect signals greater investor protection. This variable is from La Porta 

21

et al. (2006), who show that countries with higher values of Protect have more developed 

equity markets. 

Earnings Management Score (EMS) is from Leuz et al. (2003). EMS is the average 

rank of four different earnings management measures. A higher value of the EMS suggests 

poorer earnings quality. 

4.2.3 Correlations Among Variables 

Panel C of Table 7 reports the correlations among the variables. We focus our 

discussion on the correlations between the 1-month ISSUE coefficient and the other 

variables; the 1-year ISSUE coefficient’s correlations are similar. The 1-month ISSUE 

coefficient is negatively correlated to the frequency of nonzero issuance; hence countries 

with more issuance activity have stronger issuance effects. The market development 

indicators Liquidity, Turnover, and Log GDP are each negatively correlated to the 1-month 

ISSUE coefficient as well, suggesting that the issuance effect is stronger in more developed 

markets. The remaining correlations suggest that the issuance effect is stronger in countries 

with stronger investor protection, and better earnings quality. Taken in their entirety, the 

results suggest that the issuance effect is stronger in countries in which it is easier for firms to 

issue and buyback their shares. We test this hypothesis more rigorously with regressions 

which are reported in Table 8. 

4.3. Interaction Regressions 

4.3.1. Methodology 

22

Our objective is to test whether country characteristics can explain differences in the 

issuance effect across countries. To maximize the power of our tests, we return to our pooled 

sample and regress monthly stock returns on ISSUE along with interaction variables which 

are the product of ISSUE and each of the country characteristics described in Table 7. The 

interaction coefficients measure to what extent the issuance effect differs across countries 

with different levels of issuance activity, stock market development, and investor protection. 

4.2.1. Issuance Activity, Market Development, Buyback, and Short Selling 

Interactions 

Panels A and B of Table 8 show that the issuance effect is stronger in countries in 

which firms more actively trade in their own shares, in countries with more developed equity 

markets, and in countries where buybacks are allowed. Panel A reports results for one-month 

holding period return regressions, while Panel B reports the one-year holding period results. 

We first describe the results in Panel A. 

In regression 1 ISSUE is interacted with the percentage of observations within the 

country that have a non-zero value of ISSUE. The interaction term is negative and highly 

significant, with a t-statistic of -5.24., showing that the issuance effect is stronger in countries 

with more issuance activity. 

Regressions two, three, and four report the market development interactions. All three 

of the interaction terms are negative; the t-statistics range from -3.70 to -5.07, showing that 

the issuance effect is stronger in markets that are more developed. 

The buyback interaction is also negative and significant. Recall that Buyback is equal 

to one if buybacks are permitted and zero otherwise. The interaction term is -0.58, while the 

23

ISSUE coefficient is -0.70. Taken together, the coefficients show that the issuance coefficient 

is -0.58 in countries that do not allow buybacks, and -1.28 in countries that do. The t-statistic 

for the buyback coefficient is -1.87, which is much smaller than the development and 

nonzero interactions, suggesting that buyback regulations are not as important as issuance 

activity and equity market development with respect to explaining the issuance effect. 

The final regression in Panel A is an interaction with a short sale prohibition dummy. 

If the low returns following share issuances are the result of overvaluation, then the effect 

might be stronger in countries that prohibit short selling. However this is not what we find, as 

the interaction term is positive and not significant. Short selling tends to be allowed in 

developed markets more than in non-developed markets; this might explain why the 

coefficient has a positive sign. 

The results in Panel B are very a similar to those in Panel A. The issuance activity 

and market development interactions are all highly significant, showing that the issuance 

effect is strongest in countries where it is easier to issue shares. The buyback dummy is 

marginally significant, showing that the effect is stronger in countries where buybacks are 

feasible, while the short selling interaction is not significant. 

Taken in their entirety the results show that issuance effect is strongest in countries 

with the greatest amount of issuance activity, and with the most developed capital markets. 

These findings suggest that the effect is greatest in places where it is easier for firms to issue 

and repurchase shares. 

4.3.2. Investor Protection and Earnings Management Interactions 

24

Panels C and D of Table 8 show that the issuance effect is stronger in countries with 

better investor protection laws, and in countries with better earnings quality. We first 

describe the results in Panel C, which reports the monthly holding period return regression 

results. In the first regression, the interaction term is a dummy variable equal to one if the 

country is a common law country. The interaction term -0.96 (t-statistic = -5.58) and the 

ISSUE coefficient is -0.43 (t-statistic = -3.56). Hence in a civil law country, the average 

ISSUE coefficient is -0.43, while in common law countries it is -1.39. 

Regressions 2, 3, and 6 reinforce the notion that the issuance effect is stronger in 

countries which offer greater investor protection. The coefficients are negative and 

significant for the Accounting, Liability, and Protect interaction terms. The t-statistics range 

from -3.96 to -4.64. In regression 2 the Criminal interaction term is positive, but not 

significant. 

Regression 6 shows that the issuance effect is stronger in countries with better 

earnings quality, and weaker in countries with poor earnings quality. Leuz et al. (2003) show 

that earnings quality is better in countries with that offer better investor protection, so the 

results here again show that the issuance effect is stronger in countries with stronger investor 

protection laws. 

Panel D of Table 8 reports the regression results with the 1-year holding period. The 

signs and significance for each of the interaction terms are the same as in Panel C, showing 

that the issuance effect is stronger in countries that offer better investor protection and in 

countries that have better earnings quality. 

The results in Table 8 are not consistent with the hypothesis that markets with greater 

investor protection are more efficient than markets that offer less protection. La Porta et al. 

25

(2006) show that better governed countries have more developed equity markets, and provide 

firms with easier access to equity capital. This would suggest that it is easier to for firms to 

issue and repurchase mispriced shares in markets that offer better investor protection, so the 

results here could be consistent with market timing. 

5. Conclusion 

In this paper we take a first look at the return predictive ability of firm-level share 

issuance in international markets. We study the issuance effect across a large sample of non- 

U.S. firms, drawn from 41 different countries over a 25 year period. We find robust evidence 

of a share issuance effect in our sample. The predictive ability of annual issuance is generally 

more statistically significant than that of either size or momentum, and is similar to that of 

book-to-market. 

The international issuance effect is especially strong for positive share issuances. A 

comparison of our results to those in Fama and French (2007) shows that positive share 

issuance events have a stronger effect on subsequent returns internationally than they do in 

the U.S. Like in the U.S., international negative issuances also predict high returns, but the 

international buyback effect is weaker than that from positive issuances, and weaker than the 

buyback effect found in the U.S. 

The predictive ability of share issuance provides challenges for rational asset pricing 

models as well as behavioural models. We find that cross-sectional average R 2 s from 

regressions of returns on issuance are very low, casting doubt on a rational risk-based link, 

although we can not rule out the possibility that issuance proxies for a rational non-risk based 

factor, such as taxes or transaction costs. 

26

The findings suggest that the share issuance effect is related to the ease with which 

firms can issue and buyback their shares. The issuance effect is stronger in countries with in 

which there is more frequent issuance activity, more developed stock markets, and stronger 

investor protection laws. 

27

References 

Baker, Malcolm, and Jeffrey Wurgler, 2002, Market timing and capital structure, Journal of 

Finance 57, 1-32. 

Bris, Arturo, William Goetzman, and Ning Zhu, 2007, Efficiency and the bear: short sales 

and markets around the world, Journal of Finance 62, 1029-1079. 

Daniel, Kent, and Sheridan Titman, 2006, Market reaction to tangible and intangible 

information, Journal of Finance 61, 1605-1643. 

Fama, Eugene F., and Kenneth R. French, 1992, The cross-section of expected stock returns, 

Journal of Finance 47, 427-465. 

Fama, Eugene F., and Kenneth R. French, 1998, Value versus growth: The international 

evidence, Journal of Finance 53, 1975-1999. 

Fama, Eugene F., and Kenneth R. French, 2007, Dissecting anomalies, forthcoming in the 

Journal of Finance. 

Fama, Eugene F., and James D. MacBeth, 1973, Risk, return, and equilibrium: Empirical 

tests, Journal of Political Economy 71, 607-636. 

Griffin, John, Xiuqing, Ji, and Spencer Martin, 2003, Momentum investing and business 

cycle risk: Evidence from pole to pole, Journal of Finance 58, 2515-5247. 

Henderson, Brian J., Narasimhan Jegadeesh, and Michael S. Weisbach, 2006, World markets 

for raising new capital, Journal of Financial Economics 82, 63-101. 

Ikenberry, David, Josef Lakonishok, and Theo Vermaelen, 1995, Market underreaction to 

open market share repurchases, Journal of Financial Economics 39, 181-208. 

Ikenberry, David, Josef Lakonishok, and Theo Vermaelen, 2000, Stock repurchases in 

Canada: Performance and strategic Liquidity, Journal of Finance 55, 181-208. 

Ince, Ozgur S., and R. Burt Porter, 2006, Individual equity return data from Thomson 

Datastream: handle with care!, Journal of Financial Research 29, 463-479. 

Jegadeesh, Narasimhan, and Sheridan Titman, 1993, Returns to buying winners and selling 

losers: Implications for stock market efficiency, Journal of Finance 48, 65–91. 

Jegadeesh, Narasimhan, and Sheridan Titman, 2001, Profitability of momentum strategies: 

An evaluation of alternative explanations, Journal of Finance 56, 699-720. 

Lakonishok, Josef, Andrei Shleifer, and Robert W. Vishny, 1994, Contrarian investment, 

extrapolation, and risk, Journal of Finance 49, 1541-1578. 

28

La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert Vishny, 1997, 

Law and Finance, Journal of Political Economy 103, 1113-1155. 

La Porta, Rafael, Florencio Lopez-de-Silanes, and Andrei Shleifer, 2006, What works in 

securities laws?, Journal of Finance 61, 1-32. 

Leuz, Christian, Dhananjay Nanda, and Peter D. Wysocki, Earnings and investor protection: 

an international comparison, Journal of Financial Economics, 69, 505-527. 

Loughran, Tim, and Jay Ritter, 1995, The new issues puzzle, Journal of Finance 50, 23-51. 

Loughran, Tim, and Arnand Vijh 1997, Do long-term shareholders benefit from corporate 

acquisitions? Journal of Finance 52, 1765-1790. 

Morck, Randall, Bernard Yeung, and Wayne Yu, 2000, The information content of stock 

markets: Why do emerging markets have synchronous stock price movements? Journal of 

Financial Economics 58, 215-260. 

Pontiff, Jeffrey, 1996, Costly arbitrage and closed-end fund discounts, Quarterly Journal of 

Economics 111, 1135-1151. 

Pontiff, Jeffrey, and Artemiza Woodgate, 2006, Share issuance and cross-sectional returns, 

forthcoming in the Journal of Finance. 

Rau, Raghavendra P., and Theo Vermaelen, 2002, Regulation, taxes, and share repurchases 

in the United Kingdom, Journal of Business 75, 245-282. 

Rouwenhorst, K. Geert, 1998, International momentum strategies, Journal of Finance 53, 

267-284. 

Rouwenhorst, K. Geert, 1999, Local return factors and turnover in emerging markets, 

Journal of Finance 54, 1439-1464. 

29

Table 1: Summary Statistics for Sample Countries 

This table provides summary statistics for the 41 countries included in our sample. Columns 2 and 3 

list the beginning and ending dates during which each country is included in our regression analysis. 

The table additionally reports the total number of firm-month observations (column 4) and the average 

number of firm observations per month (column 6). The values of these statistics represented as 

percentages of the corresponding total across countries are given in the remaining columns 5, and 7. 

The average monthly total market capitalization in millions of U.S. dollars is given in column 8. The 

percentage of firms with non-zero one-year change in the number of shares outstanding adjusted for 

distribution events such as stock splits and stock dividends (ISSUE) is displayed in column 9. ISSUE 

is computed over month t-12 to t: ISSUEt,t-12 = Ln(Adjusted Sharest) – Ln(Adjusted Sharest-12). 

30

Country Start Date End Date 

Total Number 

of Firm- 

Month 

Observations 

Percentage 

of Total 

Sample (%) 

31 

Average 

Number of 

Firm 

Observations 

per Month 

Monthly 

Average 

Percentage of 

Sample (%) 

Average 

Monthly Total 

Market Value 

Average 

Monthly 

Percentage of 

Total Market 

Value (%) 

Argentina 03/1995 06/2006 8,511 0.30 63 0.53 24,942 0.45 

Australia 07/1981 06/2006 138,645 4.92 462 3.89 96,456 1.75 

Austria 01/1991 06/2006 9,613 0.34 75 0.63 22,865 0.42 

Belgium 10/1985 06/2006 28,052 0.99 128 1.07 55,312 1.01 

Brazil 03/1995 06/2006 58,402 2.07 429 3.62 137,145 2.49 

Canada 07/1981 06/2006 218,867 7.76 730 6.14 223,245 4.06 

Chile 02/1991 06/2006 24,855 0.88 153 1.29 44,459 0.81 

China 08/1994 06/2006 90,180 3.20 631 5.31 212,619 3.87 

Czech Republic 07/1996 11/2001 3,768 0.13 77 0.65 6,151 0.11 

Denmark 01/1989 06/2006 36,657 1.30 183 1.54 49,618 0.90 

Egypt 01/2001 06/2006 4,479 0.16 76 0.64 9,233 0.17 

Finland 07/1990 06/2006 16,719 0.59 96 0.80 41,519 0.75 

France 07/1981 06/2006 132,542 4.70 443 3.73 331,623 6.03 

Germany 07/1981 06/2006 112,621 3.99 377 3.17 300,368 5.46 

Greece 08/1989 06/2006 36,381 1.29 179 1.51 30,446 0.55 

Hong Kong 09/1981 06/2006 94,629 3.36 325 2.74 123,696 2.25 

India 08/1991 06/2006 124,086 4.40 693 5.84 73,522 1.34 

Indonesia 04/1992 05/2006 12,551 0.45 113 0.95 22,908 0.42 

Ireland 10/1996 12/2001 864 0.03 51 0.43 39,212 0.71 

Italy 07/1981 06/2006 60,813 2.16 203 1.71 165,867 3.02 

Japan 07/1981 06/2006 415,165 14.72 1,384 11.65 1,625,890 29.56 

Malaysia 08/1987 06/2006 88,985 3.16 392 3.30 73,995 1.35 

Mexico 01/1990 06/2006 22,699 0.80 117 0.99 72,992 1.33 

Netherlands 07/1981 06/2006 44,442 1.58 149 1.25 167,715 3.05 

New Zealand 08/1989 06/2006 14,765 0.52 73 0.61 11,541 0.21 

Norway 08/1983 06/2006 26,847 0.95 104 0.87 25,239 0.46 

Pakistan 02/1994 06/2006 27,574 0.98 185 1.56 6,459 0.12 

Peru 10/1993 06/2006 16,670 0.59 109 0.92 7,772 0.14 

Philippines 07/1991 06/2006 28,023 0.99 156 1.31 20,857 0.38 

Poland 02/1999 06/2006 11,528 0.41 133 1.12 18,976 0.35 

Portugal 12/1989 06/2006 11,862 0.42 77 0.65 22,344 0.41 

Singapore 08/1984 06/2006 40,403 1.43 157 1.32 65,385 1.19 

South Africa 05/1982 06/2006 66,391 2.35 253 2.13 88,217 1.60 

South Korea 08/1987 06/2006 148,122 5.25 653 5.49 82,878 1.51 

Spain 10/1988 06/2006 20,815 0.74 98 0.82 160,075 2.91 

Sweden 08/1983 06/2006 54,317 1.93 198 1.66 97,062 1.76 

Switzerland 07/1981 06/2006 58,621 2.08 197 1.66 63,230 1.15 

Taiwan 02/1991 06/2006 63,985 2.27 346 2.91 173,789 3.16 

Thailand 08/1988 06/2006 41,520 1.47 209 1.76 35,353 0.64 

Turkey 07/1990 06/2006 29,810 1.06 157 1.32 26,860 0.49 

U.K. 07/1981 06/2006 374,127 13.27 1,247 10.50 642,183 11.68 

Total 2,819,906 100.00 11,878 100.00 5,500,018 100.00

Table 2: Aggregate Summary Statistics 

This table reports aggregate summary statistics for one-month and one-year holding period returns, the 

natural logarithm of the June-end market value (ME), the natural logarithm of the previous year’s 

fiscal year-end book-to-market ratio (BM), the past six-month stock return (MOM), and one-year 

(ISSUE) changes in the number of shares outstanding adjusted for distribution events such as stock 

splits and stock dividends. ISSUE is computed over month t-12 to t: ISSUEt,t-12 = Ln(Adjusted Sharest) 

– Ln(Adjusted Sharest-12). The sample is drawn from 41 countries, covers a period between July 1981 

and June 2006, and consists of 2,819,906 total firm-month observations. 

Total Number of 

Standard 25 

Variable Observations Mean Deviation 

th 

75 

Percentile Median 

th 

Percentile 

1-Month Return 2,819,906 0.011 0.141 -0.057 0.000 0.063 

1 st -Year Return 2,338,097 0.162 0.642 -0.179 0.054 0.353 

ME 2,819,906 4.382 2.037 3.004 4.419 5.777 

BM 1,901,598 -0.390 0.850 -0.908 -0.372 0.139 

MOM 2,819,906 0.068 0.409 -0.146 0.012 0.204 

ISSUE 2,819,906 0.048 0.206 0.000 0.000 0.008 

32

Table 3: Fama-MacBeth Cross-Sectional Regressions of Annual Share Issuance on Firm 

Characteristics 

This table reports the results of Fama-MacBeth cross-sectional regressions. The annual share issuance 

measure (ISSUE) is regressed on the following firm-specific variables available immediately before 

the ISSUE-construction months: the natural logarithm of the June-end market value (ME), the natural 

logarithm of the previous year’s fiscal year-end book-to-market ratio (BM), the past six-month stock 

return (MOM), and the annual share-issuance measure lagged by 12 months (LAG-ISSUE). If the book 

value of equity is either missing or negative, then we assign both BM and BM-Dum values of zero. 

Otherwise, BM-Dum receives a value of one. ISSUE is the real change in the number of shares 

outstanding adjusted, computed over month t-12 to t: ISSUEt,t-12 = Ln(Adjusted Sharest) – Ln(Adjusted 

Sharest-12). We estimate six different regression specifications using either equal-weighting, or valueweighting, 

or scaled weighting each observation, and by either including or excluding country 

dummies. The scaled-weights are computed by dividing each value-weight by the average market of 

the firm’s home country. The coefficients and adjusted R 2 s are in percentages and are given by the 

time-series averages of the corresponding statistics obtained from the monthly cross-sectional 

regressions. T-statistics, corrected for overlapping ISSUE-construction periods, are reported in 

parentheses. Coefficients with a 10% significance level or higher are bolded. The sample is drawn 

from 41 countries, covers a period between January 1983 and June 2006, and consists of 1,944,531 

firm-month observations. 

Regression (1) (2) (3) (4) (5) (6) 

Weighting Equal Value Scaled Equal Value Scaled 

Intercept 6.71 5.42 6.32 6.55 5.15 6.05 

(9.67) (10.03) (11.85) (8.49) (10.01) (10.97) 

ME -0.50 -0.37 -0.52 -0.68 -0.42 -0.56 

(-4.87) (-10.21) (-10.48) (-5.70) (-7.39) (-8.76) 

BM 0.25 0.45 0.50 0.41 0.46 0.60 

(1.17) (3.89) (3.81) (1.13) (2.04) (3.86) 

BM-Dum -0.07 0.35 0.59 0.09 0.13 0.61 

(-0.28) (1.07) (1.83) (0.36) (0.39) (1.92) 

MOM 1.61 0.96 1.02 1.41 0.95 0.85 

(4.45) (2.24) (2.54) (4.23) (2.95) (3.11) 

LAG-ISSUE 7.69 3.65 4.13 10.83 6.74 6.71 

(3.60) (1.83) (2.37) (5.58) (5.49) (5.48) 

Average Adj. R 2 8.48 8.24 8.20 3.23 2.69 2.50 

Country Dummies Yes Yes Yes No No No 

33

Table 4: Fama-MacBeth Regressions of Holding Period Returns on Share Issuance and 

Share Issuance with Controls 

This table reports the results of Fama-MacBeth regressions both with and without country dummies. 

The regressions are estimated with equal-weights, value-weights, and value-weights scaled by the 

average market value within the firm’s country. In Panels A and B holding period returns, measured 

over the first month and first year, are regressed on one-year (ISSUE) real changes in the number of 

shares outstanding. ISSUE is computed over month t-12 to t: ISSUEt,t-12 = Ln(Adjusted Sharest) – 

Ln(Adjusted Sharest-12). In Panels C and D holding period returns, measured over the first month and 

first year, are regressed on the natural logarithm of the June-end market value (ME), the natural 

logarithm of the previous year’s fiscal year-end book-to-market ratio (BM), the past six-month stock 

return (MOM), and one-year (ISSUE) real changes in the number of shares outstanding. If book value 

of equity is either missing or negative, then we assign both BM and BM-Dum values of zero. 

Otherwise, BM-Dum receives a value of one. T-statistics, corrected for overlapping holding periods, 

are reported in parentheses. Coefficients with a 10% significance level or higher are bolded. The 

sample is drawn from 41 countries, covers a period between July 1981 and June 2006, and consists of 

2,819,906 total firm-month observations. 

Panel A 

Regression (1) (2) (3) (4) (5) (6) 

Return Horizon 1-Month 1-Month 1-Month 1 st -Year 1 st -Year 1 st -Year 


Intercept 1.15 1.3 1.30 18.24 16.82 16.83 

(3.91) (4.19) (4.20) (4.37) (5.22) (5.23) 

ISSUE -0.79 -0.59 -0.66 -7.10 -6.58 -6.39 

(-7.12) (-3.78) (-5.07) (-6.25) (-3.63) (-3.96) 

Average Adj. R 2 19.82 23.57 27.46 22.15 25.34 28.13 

Country Dummies Yes Yes Yes Yes Yes Yes 

Panel B 

Regression (1) (2) (3) (4) (5) (6) 



Intercept 1.24 1.07 1.23 17.63 13.78 16.38 

(5.23) (3.94) (4.90) (0.45) (3.27) (4.83) 

ISSUE -0.96 -0.73 -0.82 -7.05 -7.25 -7.00 

(-5.28) (-2.60) (-3.93) (-3.55) (-2.33) (-3.39) 

Average Adj. R 2 0.18 0.29 0.22 0.26 0.27 0.28 

Country Dummies No No No No No No 

34

Table 4: Continued 

Panel C 

Regression (1) (2) (3) (4) (5) (6) 



Intercept 1.17 0.95 0.84 7.70 15.25 15.47 

(4.05) (2.38) (2.52) (3.57) (3.09) (3.43) 

ME -0.04 0.02 0.04 -0.21 -0.04 -0.08 

(-1.63) (0.54) (1.23) (-1.20) (-0.08) (-0.29) 

BM 0.34 0.36 0.36 2.13 4.21 4.24 

(7.27) (4.84) (5.99) (4.33) (3.78) (3.60) 

BM-Dum 0.33 0.36 0.36 2.15 3.75 4.08 

(6.59) (3.77) (4.74) (5.32) (3.44) (3.30) 

MOM 0.85 0.36 0.63 6.29 5.18 6.39 

(5.19) (1.04) (2.44) (7.58) (1.79) (2.49) 

ISSUE -0.71 -0.65 -0.68 -3.30 -6.77 -6.59 

(-6.84) (-4.41) (-5.53) (-5.47) (-3.77) (-4.08) 

Average Adj. R 2 20.73 26.71 29.11 24.58 28.79 30.26 


Panel D 

Regression (1) (2) (3) (4) (5) (6) 



Intercept 1.58 0.85 1.27 24.17 15.91 21.75 

(6.07) (2.37) (3.50) (5.27) (3.87) (5.22) 

ME -0.10 0.01 -0.03 -1.55 -0.29 -0.85 

(-3.10) (0.26) (-0.64) (-4.67) (-0.74) (-2.28) 

BM 0.34 0.34 0.38 4.69 4.25 4.90 

(3.90) (3.25) (4.01) (6.77) (4.83) (7.12) 

BM-Dum 0.26 0.39 0.32 3.28 4.18 3.85 

(2.27) (3.14) (2.76) (2.04) (3.72) (5.16) 

MOM 0.94 0.31 0.62 8.04 3.58 5.31 

(3.42) (0.71) (1.70) (2.50) (0.78) (1.35) 

ISSUE -0.91 -0.78 -0.92 -6.87 -8.66 -8.71 

(-5.37) (-3.22) (-4.77) (-4.16) (-2.56) (-3.69) 

Average Adj. R 2 3.26 6.64 4.90 3.89 7.03 5.50 

Country Dummies No No No No No No 

35

Table 5: Summary Statistics for Portfolios Sorted on Annual Share Issuance 

This table provides summary statistics for portfolios sorted on annual share issuance (ISSUE). ISSUE 

is the real change in the number of shares outstanding computed over month t-12 to t: ISSUEt,t-12 = 

Ln(Adjusted Sharest) – Ln(Adjusted Sharest-12). Each month, we follow Fama and French (2007) and 

use all but the smallest quintile stocks to determine our portfolio breakpoints. The smallest stocks are 

included in the portfolios. We sort stocks with negative issuance into two portfolios; NEG1 is a 

portfolio for stocks below the negative issuance median and NEG2 is for stocks above the negative 

issuance median. We sort stocks with positive issuance into five quintiles (POS1-POS5); POS1 is for 

stocks in the lowest positive issuance quintile and POS5 is for stocks in the highest issuance quintile. 

ZERO is a portfolio that includes stocks with zero net annual issuance. The sample is drawn from 41 

countries, consists of 2,819,906 total firm-month observations, and is from July of 1981 to June of 

2006. Panel A reports results for the entire sample, while Panel B excludes observations for which 

buybacks were either illegal or unattractive from either a tax or other regulatory perspective. 

Panel A 

Average Monthly Average Number 

Average Cross-Sectional of Firm Average Monthly 

ISSUE Rank Monthly Value Standard Deviation of Observations per Percentage of 

Portfolio 

of ISSUE 

ISSUE 

Month 

Sample (%) 

NEG1 -0.133 0.298 306 3.26 

NEG2 -0.002 0.002 288 3.06 

ZERO 0.000 0.000 5,457 58.05 

POS1 0.001 0.001 623 6.63 

POS2 0.009 0.004 628 6.68 

POS3 0.038 0.014 651 6.93 

POS4 0.120 0.034 681 7.25 

POS5 0.462 0.359 766 8.15 

Panel B 

Average Monthly Average Number 

Average Cross-Sectional of Firm Average Monthly 

ISSUE Rank Monthly Value Standard Deviation of Observations per Percentage of 

Portfolio 

of ISSUE 

ISSUE 

Month 

Sample (%) 

NEG1 -18.41 34.88 220 3.53 

NEG2 -0.27 0.26 208 3.34 

ZERO 0.00 0.00 3,450 55.43 

POS1 0.15 0.12 432 6.94 

POS2 1.01 0.46 435 6.99 

POS3 4.43 1.73 458 7.36 

POS4 13.98 3.86 483 7.76 

POS5 50.23 36.61 538 8.65 

36

Table 6: Equal-Weighted Fama-MacBeth Regressions of Holding Period Returns on 

Annual Share Issuance Rankings and Other Firm Characteristics 

This table reports the results of Fama-MacBeth regressions with country dummies. The regressions 

are estimated with equal-weights, value-weights, and value-weights scaled by the average market 

value within the firm’s country. Holding period returns, measured over the first month and first year, 

are regressed on the natural logarithm of the June-end market value (ME), the natural logarithm of the 

previous year’s fiscal year-end book-to-market ratio (BM), the past six-month stock return (MOM), 

and annual-issuance (ISSUE) rank dummies. If book value of equity is either missing or negative, then 

we assign both BM and BM-Dum values of zero. Otherwise, BM-Dum receives a value of one. ISSUE 

is the real change in the number of shares outstanding adjusted computed over month t-12 to t: 

ISSUEt,t-12 = Ln(Adjusted Sharest) – Ln(Adjusted Sharest-12). Each month, we follow Fama and French 

(2007) and use all but the smallest quintile stocks to determine our portfolio breakpoints. The smallest 

stocks are included in the portfolios. We sort stocks with negative issuance into two portfolios; NEG1 

is a portfolio for stocks below the negative issuance median and NEG2 is for stocks above the 

negative issuance median. We sort stocks with positive issuance into five quintiles (POS1-POS5); 

POS1 is for stocks in the lowest positive issuance quintile and POS5 is for stocks in the highest 

issuance quintile. An ISSUE rank dummy variable is assigned a value of one if the firm is in the 

portfolio, and zero otherwise. The coefficients and adjusted R 2 s are in percentages and are given by 

the time-series averages of the corresponding statistics obtained from the monthly cross-sectional 

regressions. t-statistics, corrected for overlapping holding periods, are reported in parentheses. 

Coefficients with a 10% significance level or higher are bolded. The sample is drawn from 41 

countries, covers a period between July 1981 and June 2006, and consists of 2,819,906 total firmmonth 

observations. Panel A reports results for the entire sample, while Panel B excludes 

observations for which buybacks were either illegal or unattractive from either a tax or other 

regulatory perspective. 

37

Panel A 

Regression (1) (2) (3) (4) (5) (6) 

Return Horizon 1-Month 1-Month 1-Month 1st-Year 1st-Year 1st-Year 


Intercept 1.18 0.85 15.45 0.98 18.70 15.42 

(4.12) (2.55) (3.15) (2.48) (3.55) (3.36) 

ME -0.040 0.03 -0.04 0.02 -0.72 -0.10 

(-1.58) (1.16) (-0.09) (0.44) (-2.42) -(-0.37) 

BM 0.33 0.35 4.16 0.34 4.42 4.23 

(7.26) (5.98) (3.79) (4.76) (3.81) (3.61) 

BM-Dum 0.33 0.36 3.88 0.36 4.19 4.14 

(6.63) (4.82) (3.47) (3.83) (4.87) (3.38) 

MOM 0.85 0.63 5.21 0.36 9.10 6.41 

(5.22) (2.46) (1.81) (1.04) (4.04) (2.51) 

NEG1 0.12 0.06 -0.21 0.06 1.14 -0.02 

(2.08) (0.82) (-0.29) (0.79) (1.94) (-0.02) 

NEG2 0.01 -0.07 -0.59 -0.11 0.30 -0.15 

(0.18) (-0.87) (-0.78) (-1.10) (0.68) (-0.17) 

POS1 0.011 -0.03 -0.20 -0.06 0.76 0.47 

(0.28) (-0.51) (-0.29) (-0.90) (2.76) (-0.80) 

POS2 0.00 0.02 -0.39 0.00 0.10 0.33 

(0.01) (-0.43) -(0.47) (-0.04) (0.22) (0.48) 

POS3 -0.08 -0.01 -0.69 -0.01 -0.03 -0.53 

(-1.89) (-0.15) (-0.79) (-0.10) (-0.05) (-0.79) 

POS4 -0.28 -0.19 -2.39 -0.18 -2.10 -2.19 

(-4.57) (-2.71) (-2.38) (-2.28) (-2.73) (-2.36) 

POS5 -0.44 -0.33 -3.81 -0.35 -4.08 -3.67 

(-6.00) (-4.45) (-6.11) (-4.35) (-5.71) (-4.69) 

Average Adj. R 2 20.78 29.40 29.41 27.25 23.84 30.62 


38

Panel B 

Regression (1) (2) (3) (4) (5) (6) 

Return Horizon 1-Month 1-Month 1-Month 1st-Year 1st-Year 1st-Year 


Intercept 1.19 0.77 15.05 0.67 19.63 16.14 

(4.09) (2.25) (2.61) (1.81) (3.25) (2.97) 

ME -0.05 0.04 0.06 0.06 -0.99 -0.10 

(-1.84) (-1.36) (-0.14) (-1.66) (-2.10) (-0.28) 

BM 0.29 0.35 3.20 0.31 3.56 3.89 

(5.63) (5.03) (2.70) (4.34) (2.87) (3.26) 

BM-Dum 0.40 0.31 2.55 0.27 4.57 3.49 

(6.99) (3.45) (1.76) (2.65) (4.57) (2.61) 

MOM 1.06 0.81 8.24 0.84 9.72 6.47 

(5.97) (2.98) (2.76) (2.70) (3.31) (2.19) 

NEG1 0.09 -0.04 -2.77 -0.10 0.37 -2.31 

(1.10) (-0.34) (-1.76) (-0.89) (-0.39) (-1.45) 

NEG2 0.03 -0.06 -0.45 -0.12 0.61 0.41 

(0.36) (-0.47) (-0.24) (-0.94) (0.91) (0.24) 

POS1 0.08 -0.05 -0.31 -0.08 1.10 0.06 

(1.53) (-0.81) (-0.55) (-1.18) (2.33) (0.10) 

POS2 -0.01 0.08 -0.31 0.05 -0.31 0.28 

(-0.14) (1.14) (-0.35) (0.69) (-0.42) (0.37) 

POS3 -0.17 -0.01 -0.54 -0.04 -0.56 -0.26 

(-2.89) (-0.09) (-0.51) (-0.52) (-0.82) (-0.37) 

POS4 -0.35 -0.27 -3.24 -0.30 -2.98 -3.32 

(-4.71) (-3.18) (-2.80) (-3.46) (-3.87) (-3.53) 

POS5 -0.55 -0.43 -5.52 -0.48 -5.03 -5.11 

(-6.30) (-4.48) (-6.45) (-5.00) (-5.84) (-6.13) 

Average Adj. R 2 16.02 24.93 25.43 23.26 19.78 27.00 


39

Table 7: Country-Level Issuance, Issuance Activity, Market Development, and 

Governance Variables 

This Table displays country level data. The first column in Panel A is the share issuance coefficient 

from a within-country equal-weighted regression of monthly returns on ISSUE along with controls for 

size, book-to-market, and momentum. The second column reports the percentage of firm-month 

observations with nonzero values of ISSUE. The items in columns 3, 4, and 5 in were obtained from 

La Porta et al. (2006). Liquidity is the total dollar value of stocks traded scaled by GDP, for the period 

1996-2000. Turnover is the total dollar value of stocks traded, scaled by the value of shares 

outstanding, for the period 1996-2000. Log GDP is per capita GDP in U.S. dollars in 2000. Buybacks 

Allowed? is the year in which buybacks first became feasible; we collected this data from various 

sources. Short Selling Allowed? is the year in which a country first allowed short selling; it is from 

Bris et a. (2007). The first two columns in Panel B are from La Porta et al (1997). Law reports 

whether the country has either a common or civil law legal origin. Accounting is an index of 

accounting standards, a higher value suggests better accounting standards. The next three columns are 

from La Porta et al. (2006). With each measure a higher value signals greater investor protection. 

Criminal and Liability are indices which measure the ease with which accountants, directors, and 

distributors can be pursued in criminal and civil courts for not fully disclosing information in 

prospectuses. Protect is the principle component of Liability and two other investor protection indices. 

Earnings Management is from Leutz et al. (2003). A higher value of the Earnings Management 

suggests poorer earnings quality. Panel C reports the correlations between the variables. 

40

Panel A: Issuance Activity and Market Development Variables 

1-Month 

Issue 

Coefficient 

% 

Nonzero 

Issuance Liquidity Turnover 

41 

Short 

Selling 

Allowed? 

Log GDP Buybacks 

Country 

per capita Allowed? 

Argentina 0.24 5.83 14.42 8.95 Full 1999 

Australia -1.03 0.61 45.16 48.16 9.89 1996 Before 1990 

Austria 0.14 6.71 49.52 10.05 2000 Before 1990 

Belgium 1.00 0.18 16.83 24.68 10.02 2000 Before 1990 

Brazil 0.48 0.24 18.29 61.14 8.14 Full Before 1990 

Canada -0.60 0.65 57.86 65.64 10.05 Full Before 1990 

Chile 2.26 0.11 9.14 10.00 8.44 Full Before 1990 

China 0.59 0.33 9.14 10.00 8.44 Not Allowed 

Czech Republic 0.06 Before 1990 

Denmark -0.76 0.22 36.27 64.23 10.31 2001 Before 1990 

Egypt 0.08 7.76 32.81 7.28 

Finland -0.95 0.36 70.97 51.34 10.06 1998 1998 

France -0.81 0.40 44.90 63.82 9.99 1999 Before 1990 

Germany -1.23 0.20 37.80 118.46 10.03 1999 Before 1990 

Greece -0.42 0.29 60.84 78.79 9.27 Full Not Allowed 

Hong Kong -0.84 0.53 179.05 64.94 10.10 1992 1996 

India 0.22 0.26 54.65 63.72 6.16 2000 

Indonesia 0.28 0.26 13.78 65.20 6.59 Not Allowed 

Ireland 0.70 30.79 59.96 10.14 Full Before 1990 

Italy -0.57 0.38 36.58 80.08 9.84 Full Before 1990 

Japan 0.51 0.42 35.50 49.40 10.54 1996 Before 1990 

Malaysia 0.40 0.35 98.54 50.77 8.25 1998 1995 to 1997 

Mexico -0.53 0.45 9.89 34.42 8.67 Before 1990 

Netherlands -1.43 0.45 113.49 95.36 10.06 2002 Before 1990 

New Zealand 0.53 17.82 42.68 9.48 2000 1992 

Norway -0.57 0.44 30.15 79.64 10.49 2000 1992 

Pakistan -1.01 0.22 26.50 220.97 6.10 Full Not Allowed 

Peru -3.83 0.38 5.19 21.65 7.64 Not Allowed 

Philippines -0.23 0.28 21.45 39.52 6.83 1998 

Poland 0.01 0.17 1998 2000 

Portugal 0.16 30.98 68.18 9.27 Before 1990 

Singapore -0.78 0.42 79.15 49.62 10.05 1999 Not Allowed 

South Africa -1.59 0.40 41.77 27.74 7.98 2001 Before 1990 

South Korea -0.87 0.38 110.16 204.92 9.18 Full Not Allowed 

Spain 0.01 0.37 107.98 174.82 9.56 Full 1992 

Sweden -0.78 0.40 92.22 78.08 10.15 2001 1991 

Switzerland -0.31 0.25 206.27 91.22 10.41 1998 Before 1990 

Taiwan 0.06 0.72 320.69 314.74 9.54 2001 Before 1990 

Thailand 0.50 0.45 22.55 62.51 7.58 2002 1997 

Turkey -2.31 0.49 43.68 148.00 8.02 Full Before 1990 

UK -1.19 0.55 83.02 50.62 10.08 1981 Before 1990 

US -2.06 0.87 178.88 125.30 10.46 1982 Before 1990

Country 

Panel B: Governance Variables 

1-Year 

Issue 

Coefficient Law Accounting Criminal Liability Protect 

42 

Earnings 

Management 

Score 

Argentina Civil 45 0.17 0.22 0.479 

Australia -10.20 Common 75 0.83 0.66 0.784 4.8 

Austria Civil 54 0.50 0.11 0.104 28.3 

Belgium 10.48 Civil 61 0.50 0.44 0.068 19.5 

Brazil 1.55 Civil 54 0.33 0.33 0.442 

Canada -3.22 Common 74 0.83 1.00 0.959 5.3 

Chile 21.31 Civil 52 0.50 0.33 0.610 

China 34.68 Civil 

Czech Republic Civil 

Denmark -15.66 Civil 62 0.00 0.55 0.363 16.0 

Egypt Civil 24 0.42 0.22 0.202 

Finland 28.63 Civil 77 0.50 0.66 0.465 12.0 

France -7.76 Civil 69 0.33 0.22 0.473 13.5 

Germany -6.88 Civil 62 0.50 0.00 0.000 21.5 

Greece -9.23 Civil 55 0.50 0.50 0.319 28.3 

Hong Kong -11.13 Common 69 1.00 0.66 0.851 19.5 

India 0.26 Common 57 0.83 0.66 0.769 19.1 

Indonesia 4.63 Civil 0.50 0.66 0.507 18.3 

Ireland Common 0.83 0.44 0.478 5.1 

Italy -14.37 Civil 62 0.50 0.22 0.197 24.8 

Japan 7.82 Civil 65 0.00 0.66 0.420 20.5 

Malaysia 3.31 Common 76 1.00 0.66 0.730 14.8 

Mexico -6.62 Civil 60 0.50 0.11 0.100 

Netherlands -18.99 Civil 64 0.50 0.89 0.540 16.5 

New Zealand 0.00 Common 70 0.33 0.44 0.460 

Norway -3.69 Civil 74 1.00 0.39 0.440 5.8 

Pakistan -18.58 Common 0.08 0.39 0.630 17.8 

Peru -72.05 Civil 38 0.50 0.66 0.660 

Philippines -10.16 Civil 65 0.50 1.00 0.810 8.8 

Poland -2.07 Civil 

Portugal Civil 36 0.00 0.66 0.570 25.1 

Singapore -14.42 Common 78 1.00 0.66 0.770 21.6 

South Africa -7.98 Common 70 0.42 0.66 0.600 5.6 

South Korea -7.93 Civil 62 0.33 0.66 0.360 26.8 

Spain 5.64 Civil 64 0.50 0.66 0.550 18.6 

Sweden -5.08 Civil 83 0.58 0.28 0.390 6.8 

Switzerland -1.09 Civil 38 0.33 0.44 0.300 22.0 

Taiwan -7.31 Civil 65 0.83 0.66 0.550 22.5 

Thailand 11.18 Common 64 0.58 0.22 0.370 18.3 

Turkey -20.16 Civil 51 0.50 0.22 0.338 

UK -10.40 Common 78 0.42 0.78 0.770 7.0 

US -16.40 Common 71 0.50 1.00 1.000 2.0

1-Month 1-Year % 

Panel C: Correlation Matrix 

Log 

Erngs. 

Issue Issue Nonzero Liquidity Turnover GDP Law Accntg. Criminal Liability Protect Mng. 

1-Month Issue 1.00 

1-Year Issue 0.79 1.00 

% Non-Zero -0.42 -0.24 1.00 

Liquidity -0.09 -0.07 0.49 1.00 

Turnover -0.14 -0.17 0.29 0.64 1.00 

Log GDP -0.09 0.05 0.37 0.35 0.02 1.00 

Law -0.13 -0.09 0.51 0.11 -0.05 -0.08 1.00 

Accntg. 0.04 0.22 0.58 0.21 0.10 0.40 0.47 1.00 

Criminal 0.04 0.03 0.43 0.30 0.01 0.08 0.41 0.45 1.00 

Liability -0.16 -0.13 0.43 0.38 0.09 0.04 0.34 0.32 0.17 1.00 

Protect -0.16 -0.18 0.48 0.29 0.01 -0.12 0.61 0.36 0.33 0.78 1.00 

Erngs. Mng. 0.42 0.05 -0.57 0.07 0.27 -0.08 -0.45 -0.65 -0.26 -0.37 -0.54 1.00 

43

Table 8: Equal-Weighted Fama-MacBeth Regressions of Monthly Returns on Annual Share 

Issuance with Issuance Activity, Market Development, and Governance Interactions and 

Controls 

This table reports the results of equal-weighted Fama-MacBeth regressions. Holding period returns measured 

over one month and one year are regressed on the natural logarithm of June-end market value (ME), the 

natural logarithm of the previous year’s fiscal year-end book-to-market ratio (BM), the past six-month stock 

return (MOM), and one-year (ISSUE) real changes in the number of shares outstanding. If book value of 

equity is either missing or negative, then we assign both BM and BM-Dum values of zero. Otherwise, BM- 

Dum receives a value of one. ISSUE is interacted with each of the variables described in Table 7. T-statistics, 

corrected for overlapping holding periods, are reported in parentheses. Coefficients with a 10% significance 

level or higher are bolded. The sample is drawn from 41 countries, covers a period between July 1981 and 

June 2006, and consists of 2,819,906 total firm-month observations. 

44

Panel A: Issuance Activity and Market Development Interactions: 1-Month Returns 

Regression (1) (2) (3) (4) (5) (6) 

Interactive % Nonzero 

Log GDP Buybacks No Short 

Variable Issuance Liquidity Turnover per capita Allowed Selling 

Intercept 1.15 1.03 1.00 5.06 0.58 0.74 

(1.65) (2.16) (2.33) (0.72) (1.99) (2.52) 

ME 0.03 0.04 0.04 0.04 0.04 0.04 

(1.16) (1.20) (1.22) (1.19) (1.18) (1.25) 

BM 0.38 0.39 0.39 0.39 0.39 0.40 

(7.21) (7.23) (7.25) (7.23) (7.07) (7.35) 

BM-Dum 0.26 0.26 0.26 0.26 0.27 0.26 

(6.08) (6.04) (6.09) (6.08) (6.09) (6.08) 

MOM 0.99 0.99 0.99 0.99 1.02 1.00 

(5.67) (5.64) (5.63) (5.63) (5.73) (5.51) 

ISSUE 0.58 -0.27 -0.44 8.34 -0.70 -1.17 

(2.36) (-1.85) (-2.17) (4.57) (-2.90) (-8.56) 

Variable -0.42 0.00 0.00 -0.42 0.25 0.27 

(-0.47) (0.48) (0.51) (-0.61) (0.81) (0.57) 

Interaction -2.94 -0.01 -0.01 -0.95 -0.58 0.51 

(-5.24) (-5.01) (-3.70) (-5.07) (-1.87) (1.59) 

Average 

Adj. R 2 15.83 15.81 15.80 15.80 15.27 15.28 

45

Panel B: Issuance Activity and Market Development Interactions: 1-Year Returns 

Regression (1) (2) (3) (4) (5) (6) 

Interactive % Nonzero 

Log GDP Buybacks No Short 

Variable Issuance Liquidity Turnover per capita Allowed Selling 

Intercept 20.15 18.23 17.92 60.52 13.80 14.94 

(1.83) (2.38) (2.59) (0.54) (3.30) (5.37) 

ME -0.14 -0.12 -0.11 -0.12 -0.15 -0.10 

(-0.52) (-0.45) (-0.44) (-0.46) (-0.56) (-0.36) 

BM 4.35 4.37 4.41 4.40 4.39 4.44 

(3.89) (3.94) (3.98) (3.96) (3.85) (4.14) 

BM-Dum 2.78 2.89 2.92 2.91 2.77 2.91 

(3.24) (3.33) (3.37) (3.36) (3.17) (3.35) 

MOM 9.65 9.66 9.67 9.66 9.75 9.01 

(4.79) (4.76) (4.76) (4.76) (4.80) (4.22) 

ISSUE 4.30 -1.70 -5.06 53.09 -6.90 -9.95 

(1.12) (-1.06) (-1.92) (1.88) (-3.22) (-7.69) 

Variable -5.80 -0.02 -0.02 -4.17 1.84 1.91 

(-0.40) (-0.32) (-0.32) (-0.33) (0.39) (0.30) 

Interaction -23.25 -0.08 -0.05 -6.11 -4.24 -1.32 

(-3.39) (-4.61) (-1.83) (-2.15) (-1.68) (-0.28) 

Average 

Adj. R 2 20.03 19.96 19.95 19.96 19.35 19.67 

46

Panel C: Governance Interactions: 1-Month Returns 

Regression (1) (2) (3) (4) 

Interactive 

Variable Common Account Criminal Liability Protect 

47 

(5) 

(6) 

Erngs. 

Mgmt. 

Intercept 0.72 -1.17 1.81 1.20 1.46 0.71 

(2.67) (-0.38) (1.12) (1.58) (1.24) (1.97) 

ME 0.04 0.04 0.04 0.04 0.04 0.03 

(1.19) (1.20) (1.23) (1.21) (1.20) (1.09) 

BM 0.39 0.39 0.40 0.39 0.39 0.39 

(7.24) (7.15) (7.23) (7.20) (7.19) (6.85) 

BM-Dum 0.26 0.27 0.27 0.27 0.26 0.26 

(6.14) (6.06) (6.19) (6.12) (6.10) (5.69) 

MOM 0.99 1.00 1.00 1.00 0.99 1.03 

(5.65) (5.61) (5.60) (5.61) (5.61) (5.70) 

ISSUE -0.43 1.41 -1.34 -0.02 0.19 -1.66 

(-3.56) (2.42) (-5.88) (-0.11) (0.88) (-7.44) 

Variable 0.05 0.03 -2.19 -0.45 -0.72 0.03 

(0.16) (0.66) (-0.62) (-0.52) (-0.55) (0.56) 

Interaction -0.96 -0.04 0.53 -1.46 -1.72 0.06 

(-5.58) (-3.99) (1.36) (-3.96) (-4.64) (4.89) 

Average 

Adj. R 2 15.80 15.27 15.26 15.28 15.28 14.66

Panel D: Governance Interactions: 1-Year Returns 

Regression (1) (2) (3) (4) (5) (6) 

Interactive 

Variable Common Account Criminal Liability Protect 

48 

Erngs. 

Mgmt. 

Intercept 14.04 -5.92 27.40 20.66 23.39 14.61 

(3.38) (-0.14) (1.13) (1.73) (1.30) (4.14) 

ME -0.13 -0.13 -0.11 -0.11 -0.12 -0.16 

(-0.51) (-0.49) (-0.42) (-0.44) (-0.44) (-0.61) 

BM 4.40 4.39 4.43 4.38 4.37 4.34 

(3.95) (3.94) (3.98) (3.92) (3.91) (3.75) 

BM-Dum 2.79 2.85 2.93 2.90 2.89 2.72 

(3.27) (3.31) (3.38) (3.32) (3.31) (3.03) 

MOM 9.65 9.74 9.74 9.71 9.71 10.07 

(4.80) (4.73) (4.75) (4.74) (4.75) (5.11) 

ISSUE -2.18 15.09 -11.11 -0.68 2.49 -13.28 

(-1.28) (-1.75) (-3.51) (-0.18) (-0.65) (-5.98) 

Variable 1.26 0.29 -25.83 -6.05 -8.57 0.39 

(0.31) (0.41) (-0.46) (-0.46) (-0.40) (0.40) 

Interaction -9.64 -0.35 4.33 -11.44 -15.29 0.46 

(-3.94) (-2.63) (0.73) (-2.07) (-2.77) (2.46) 

Average 

Adj. R 2 20.02 19.18 19.29 19.30 19.31 18.81

r. david mclean, jeffrey pontiff and akiko watanabe - Center for ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?