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Managers’ Trading Intention and the Performance of Newly Listed Firms

Balasingham Balachandran, Peter Kien Pham† and Michael Skully

Abstract

We examine a sample of IPOs in which pre-IPO owners/managers’ shares are restricted from selling to highlight the impact of their trading intention on firm performance. Share price, accounting and relative performance measures are all significantly stronger during the restricted than the unrestricted period. These performance changes coincide with an increase in information asymmetries and an accelerated disposal of pre-IPO owners’ shares. They are also related to the proportion and duration of restricted shares, and cannot be simply explained by the IPO under-performance phenomenon, as well as the size and book-to-market effects. Our results suggest that agency problems are exacerbated when managers have the ability and intention to relinquish their ownership and support a wider and stricter application of trading restrictions in IPOs.

† Peter Pham is from the School of Banking and Finance, University of New South Wales. Balasingham Balachandran and Michael Skully are both from the Department of Accounting and Finance, Monash University. We would like to thank from comments by Mohamed Ariff, Rob Brown, Beverly Marshall, Kim Sawyer, Sheridan Titman, Terry Walter, conference participants at the Financial Management Association Meeting, and seminar participants at the University of Melbourne and Monash University. We are solely responsible for any remaining errors. Corresponding author and address: Peter Kien Pham, School of Banking and Finance, UNSW, NSW 2052, Australia. Email: [email protected].

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1. INTRODUCTION

Since the seminal work of Jensen and Meckling (1976), managerial equity ownership

has become well recognized as an important mechanism to address agency problems. With

today business environment marred by corporate governance scandals, the shareholding

levels of executives receive even greater scrutiny. Financial commentators are eager to laud

managers that invest heavily in their firms and lament those that do not. However, this

focus on the managerial immediate shareholdings overlooks the fact that such holdings are

unlikely to persist, and hence, may not reflect the true incentive of managers if they intend

to trade their shares. So far, empirical research has also concentrated on managerial

ownership and its impact on firm performance, while neglecting the important issue of

whether managers commit to their shareholdings and what happens if they do not.

Numerous explanations exist about why managers may possess a strong intention to

dispose their equity stakes. For instance, one of the main motives of pre-IPO (original)

owners is to realize their initial investments through selling shares in the aftermarket.

Brennan and Franks (1997), Mikkelson et al. (1997), Pagano, Panetta and Zingales (1998)

documents a steady decline of pre-IPO owners’ stakes for up to 10 years post-IPO. Even in

seasoned companies, the optimal ownership of large shareholders and managers can vary

with their personal diversification preferences (Admati, Pfeiderer and Zechner, 1994).

Therefore, when their shareholdings change due to new issues, buy-backs, expiry of

executive options and stock-based compensation, managers are likely to trade shares to

re-establish their perceived optimal level of ownership (Ofek and Yermack, 2000).

Does this management intention to trade shares influence agency problems and

ultimately firm performance? In this study, we argue that there may be a substantial shift in

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the relation between ownership structure and firm value if the existing theory is extended to

consider secondary market trading by managers. When a company goes public, for

example, Zingales (1995) and Mello and Parsons (1998) show that it may be optimal for

pre-IPO managers to dispose of their shares over an extended period post-listing to reach

their desired risk-sharing ownership levels. As subscribers to the IPO may face lower share

prices when the managers actually sell these holdings, they are likely to lower their initial

valuation of the firm to account for the potential post-listing reduction in managerial

incentive.2 In order to compensate for this price reduction, the managers would also

consume more perquisites, and the equilibrium achieved under the condition in which

future selling by the managers is expected would imply a lower firm value and higher

agency costs than the one described in Jensen and Meckling’s (1976) static setting. In a

theoretical model, DeMarzo and Urosevic (2002) also argue that the current firm value

should reflect among other things expected future holdings of managers and large

shareholders. Maug (1997) and Kahn and Winton (1998) similarly suggest that future

trading is an important consideration of large shareholders when deciding their current

monitoring efforts.

However, the idea that managers’ intention to trade shares can affect the relation

between their shareholdings and firm value has not yet been empirically investigated. The

difficulty of such a research is to distinguish between the effect of managers’ current

holdings and the impact of their intention to trade. This study considers a situation where

such separation occurs, that is, when the owner/manager of a firm hold restricted shares

that cannot be traded in the market for a certain time. Holding other aspects of the firm

2 This may explain why post-listing performance and ownership structure of IPO firms are not strongly

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constant, when the shares remain restricted, then its agency costs should be proportional to

the fraction of shares held by the manager according to the classic argument of Jensen and

Meckling (1976). However, after the restriction expires, firm value and performance

should change to reflect potential management trading on their future incentives.

We select a sample of Australian IPOs that issue restricted shares to test the above

prediction, for several important reasons. First, IPOs provide a suitable setting as there is on

average a strong intention of pre-IPO owners to sell shares after listing. While issues of

restricted shares are not exclusive to newly listed firms, we cannot positively infer the same

intention to trade by managers of seasoned firms because their equity holdings are more

likely to have reached the desired risk sharing level. Second, using Australian data also

confers an additional advantage of a long event window. Most Australian IPOs have

escrow periods of one to three years. In comparison, the equivalent in the US (the lock-up

agreement) typically lasts for only 180 days. This is too short to examine both

market-based and operating performance before and after the trading restriction expires.3

More importantly, the US lock-up agreements are set by underwriters, who sometimes

allow for an early release from such contracts. In contrast, Australian data do not face the

same problem as restricted shares are subject to listing rules with much stricter compliance

requirements. In fact, our sample contains no IPOs that have early releases.

By comparing sample firms’ share price, operating returns, and Tobin’s Q before and

after the escrow expiration, we document a substantial decline in firm value and

correlated (Mikkelson et al., 1997), unlike some significant correlation observed for more mature companies. 3 There are a number of US studies on lock-up shares, which focus on the short-term price-pressure effect of releasing a large volume of shares and its implication on market efficiency (Osborne, 1982; Field and Hanka, 2001; Brav and Gompers, 2003). Our study, in contrast, examines long-term consequences of trading restriction upon firm performance due to the impact of shareholders’ trading intention.

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performance once pre-IPO managers are free from trading restriction. For example,

annualized buy-and-hold returns during the three years after the escrow expiration date is

about 9.3 to 11.0 percentage points lower than the same measure in the pre-expiration year.

Similarly, net operating profits after tax scaled by total assets decline (in median terms) by

a range of 4.6 to 6.0 percentage points from the reporting period before the expiration date

to the reporting period immediately after that date (and three following financial years).

The relative performance measure of Tobin’s Q also follows the same trend. During the

post-restriction periods, we also observe an accelerated pace of ownership liquidation by

pre-IPO owners and an increase in the level of information asymmetries.

Although such performance declines are both economically and statistically

significant, they may result from patterns inherent to all IPOs. It has been well documented

that, in the long run, IPOs under-perform in both share price (Ritter, 1991) and operating

performances (Jain and Kini, 1994). So it is also possible that these differences may merely

reflect the possibility of worse results arriving in the later years (this however has not been

documented by previous empirical studies on long-run IPO underperformance), or that they

are driven by the well-documented size and book-to-market effects. To address these

issues, we adjust performance measures of the sample firms against those of corresponding

matched firms (i.e. non-escrowed IPOs in the same industry, with similar size and

book-to-market ratio). We also employ a Fama-French calendar-time regression to

incorporate the size and book-to-market ratio effects as another way to detect abnormal

returns. The application of both methods does not change our initial findings. Therefore, it

is unlikely that the observed performance differences between before and after escrow

expiration is a result of a potential inter-temporal or cross-sectional pattern in IPO

underperformance. Further, our cross-sectional analysis also documents statistically

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significant evidence that these differences are positively related to the percentage of

escrowed shares. This result holds even after correcting for potential selection bias (using

Heckman’s (1979) procedures), which could arise because the escrow decision may be

determined by firm characteristics that also influence IPOs’ aftermarket performance.

Given that pre-IPO owners/managers on average are likely to relinquish further

shares after listing, our results demonstrate that the equilibrium that determines managerial

effort and corresponding firm value could shift depending on their trading intention. This

finding raises some important implications. First, the relation between ownership structure

and firm value may be difficult to be established under the situation which managers intent

to trade further to reach their desired positions. Second, it highlights the benefits of

restricted shares as a component of corporate governance. For newly listed firms, this

arrangement could force pre-IPO owners to exert themselves for a certain period to allow

investors sufficient time to assess the company after listing. For seasoned companies,

restricted shares are best used in a rolling-over type of compensation mechanism to reduce

“cut and run” behaviour of managers. In this regard, our study makes an important

contribution by showing that the presence of restricted shares has positive influence on

performance. While these shares are widely used in corporate finance practices,

insufficient research attention has been paid to measuring their effectiveness.

The remainder of the paper is structured as follows. Section 2 describes the sample

and main statistics. Section 3 documents a pattern of declining performance from before to

after the escrow expiration date. Section 4 compares the agency-cost and information-

asymmetry conditions between pre- and post-restriction periods. Section 5 examines the

impact of trading restriction conditions on various measures of performance changes in a

regression framework. Section 5 concludes and highlights the implications of our results.

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2. DATA

2.1. Sample Selection

Although trading intention is inherently unobservable, its impact on firm value and

performance can be detected by comparing periods in which trading ability of managerial

shareholdings differs. For this purpose, we focus on a sample of Australian IPOs, as many

of them have escrowed shares (held by their pre-IPO owners/managers) that cannot be sold

for periods of one to three years. In contrast, IPOs in the United States are often subject to a

much shorter restriction (lock-up) period of six months, which makes comparison of

long-term performance between periods with and without restriction difficult. Further, the

escrow requirement in Australia in most cases is strictly enforced by the Australian Stock

Exchange, where as in the US, early termination of the lock-up contract is possible at the

discretion of the underwriter.

Another important reason for examining IPOs is that there is on average a strong

intention of IPO owners/managers to sell more shares after listing (Brennan and Franks,

1997; Mikkelson et al., 1997; Mello and Parsons, 1998). In contrast, one cannot positively

infer the same trading intention by managers of seasoned firms because it is more likely

that their equity ownership has reached their desired risk-sharing levels. In the U.S., mature

companies issue restricted shares as well, either as executive compensation or as privately

placed equity (under Rule 144). However, in the former, executives receiving restricted

shares often immediately sell their unrestricted ones immediately for diversification

reasons (Ofek and Yermack, 2000). In the latter case, shares issued after the holding period

are not exactly tradable but still limited by some certain ceilings on selling amounts and

strict disclosure rules. These tangential aspects therefore make it difficult to determine a

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cut-off date so that performance during the periods with and without trading restriction can

be measured and compared. In summary, the above reasons highlight that newly listed

firms, and Australian IPOs in particular, provide the most suitable setting to examine the

impact of managerial trading intention.

Our sample comprises 585 industrial IPOs listed on the ASX from July 1986 to June

2000, for which prospectuses can be obtained. As the most common escrow period is two

years from the listing date, setting the year 2000 as the final year for the IPO sample is

necessary in order to measure performance for up to five years, two years before and three

years after the escrow expiration date of each firm. The last accounting performance

figures included in our analysis are thus those reported in December 2005. Following Ritter

(1984), IPOs of trusts, and convertible notes are not included in the sample. Mining

companies are also excluded as they often issue no-liability shares and feature unique

ownership structures for the purpose of dealing with risky mineral exploration (Pham et al.,

2003). We also remove IPOs of privatized government-owned companies because their

motives for going public and number of shares sold may be influenced by public policies

and political aims.

There are in total 250 firms having escrowed shares in the sample. Most agreements

restrict the sale by pre-IPO owners over a fixed period of time, often measured in years

(only 9 firms have escrow release dates other than the exact anniversaries of their listing

dates). We then exclude: (a) 8 firms being delisted prior to their escrow releases due to

take-over or bankruptcy, (b) 8 firms being suspended from trading around the time of

escrow expiration, (c) 10 firms with escrow releases conditional upon certain profit targets,

and (3) firms with missing ownership information. The final sub-sample of firms with

escrowed shares stands at 221. Among these, 75 firms have a single one-year escrow period

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and 146 firms have at least one escrow period longer than one year (i.e., the typical length is

two years, with only six firms have shares escrowed for more than two years). There are 47

firms with multiple escrow periods for different portions of shares.

Escrow arrangements differ across types of pre-IPO shareholders. Executives,

founders, seed capitalists and other controlling shareholders, who presumably can be

viewed as “insiders”, often have long restriction periods with expiration dates being some

yearly anniversaries of the listing date. In contrast, shares held by non-seed capitalists (e.g.

later-stage venture capitalists, employees, small private investors, etc.) are often restricted

for one year (or less) from the time of their pre-IPO investments before the IPO. Since our

study focuses on the trading intention of managers, we do not consider the latter escrow

type, which is also less important in terms of number and volume. After this exclusion,

there are in total 258 escrow periods, the expiration of which constitutes the set of events

examined in our study.

The information on the escrow periods and the shares covered is extracted using the

following procedures. First, for post-1994 IPOs, announcements of escrow expiration are

checked using the ASX’s Signal G database provided by DatAnalysis. These

announcements state the number of escrowed shares released and the total shares

outstanding at that time but may not contain the exact escrow release dates. Therefore, once

an IPO with escrowed shares is identified, the exact release date can be determined from

either the prospectus or the pre-quotation disclosure statement lodged with the ASX. For

pre-1994 IPOs, escrow information is obtained from the ASX Research Services’

Company Review books.

Table 1 describes the extent of escrowed shares in IPO firms across time and

industry. The use of the escrow condition varies substantially from year to year, but appears

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to be more prevalent in known hot IPO periods in Australia, such as the 1986-1897 and

1999-2000 periods, during which the number of escrowed IPOs are similar to the number

of non-escrowed IPOs and the value of escrowed shares are much higher than the gross

proceeds from shares issued to the public (see Panel A). This reflects the fact that IPOs with

a lack of profitability track records often attempt to exploit favorable IPO-market

conditions. The ASX does not seem to restrict their numbers, but instead impose strict exit

conditions to protect market integrity. Escrowed IPOs are also fairly well represented

across industries, but are concentrated in those with high growth potentials and unstable

cash flows, such as Health and Biotechnology and Miscellaneous Industrials (which is a

mixed bag of small industrial and high-tech companies).

2.2. Descriptive Statistics

Table 2 reports the summary statistics for key firm characteristics of the final sample

at the time of listing. On average, an escrow agreement covers about 45% of the total issued

capital at listing. This figure is less than the average retained ownership of all escrowed

firms (58.79%) because there may be multiple pre-IPO owners and some owners may not

wish to or be required by the ASX to escrow their shares.

Table 2 also provides evidence that there are systematic differences in the firm

characteristics of escrowed versus non-escrowed IPOs. In particular, the median pro-forma

market capitalisation is $20.75 million for the former group and $35.66 million for the

latter group. This difference is statistically significant and is also observed for other key

pre-listing firm characteristics such as asset tangibility, retained ownership, firm age,

book-to-market ratio as well as post-listing indicators such as underpricing and

first-listing-year return volatility. These results show that escrowed IPOs have less track

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records, higher risk, and high growth potential than non-escrowed firms. They also justify

the need to benchmark the performance of escrowed IPOs against a close-match sample of

non-escrowed counterparts before reaching any conclusion regarding their performance

patterns.

3. FIRM PERFORMANCE BEFORE AND AFTER ESCROW EXPIRATION

3.1. Selection of Performance Measures

To observe the effect of trading intention on firm performance, we study the set of

events of escrow expiration dates and then compare performance between before and after

the event date. Because the shortest escrow period in the sample is one year, the window of

investigation is from one year before the escrow expiration date to three years after. To

examine long-run share price return performance, we employ buy-and-hold abnormal

returns (BHARs) instead of cumulative abnormal returns (CARs). Barber and Lyon (1997)

and Barber, Lyon and Tsai (2001) argue that that due to the effect of monthly

compounding, CARs are a biased predictor of BHARs and so yield less reliable test

statistics.

We also examine operating performance indicators, such as net operating cash flows

(NOCF), earnings before interest, tax, depreciation and amortisation (EBITDA), net profits

after tax (NPAT). All of these are scaled by the average of beginning and closing total

assets of the relevant financial year. The use of operating returns helps to strengthen the

aforementioned argument that trading restrictions influence not only the market perception

of future earnings of a firm but also its ongoing profitability. In addition, by comparing

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accounting and cash-flow-based returns, this study may be able to distinguish differences

in real economic performance against those potentially created by accrual-based earnings

management techniques (Teoh, Welch and Wong, 1998). To observe the change in

performance when shares are and are not restricted, the reporting year in which the escrow

agreement expires is defined as year 0, and both the median levels and the median changes

in performance from year –1 to years 0, +1, +2, and +3 are examined.4 Finally, we also use

Tobin’s Q as a performance measure. This relative measure provides a different

perspective of a firm’s value compared to share price and operating returns, and therefore

its inclusion is important to ensure the robustness of our results.

3.2. Selection of Benchmarks and Matched Sample

In previous IPO long-term performance studies, raw returns are often adjusted by

those of the market index or a reference portfolio (Ritter, 1991). In this study, we employ

the All Ordinary index and a set of size-deciles reference portfolios as alternative

benchmarks. The size deciles are constructed by ranking the market capitalization of all

ASX firms available in the Australian Graduate School of Management’s CRIF database at

the end of June from 1986 to 2005.

Our measure of long-term share price returns can be expressed as follows:

tMtiti RRAR ,,, −=

in which tiAR , is the buy-and-hold abnormal return (abbreviated to BHAR hereafter)

of firm i (an escrowed IPO) at period t relative to the escrow expiration date. tiR , and tMR ,

are the raw buy-and-hold return of firm i and the contemporaneous buy-and-hold return of

4 The median is used to reduce the effects of outliers and high level of skewness in operating returns.

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the benchmark during the same period.

As IPO returns tend to decline in the long run (Ritter, 1991), any evidence of

performance changes may not be unique to those with escrow agreements, but actually

inherent to all IPOs. To control for this potential downward bias, a number of IPO-specific

benchmarks are created to reflect how an IPO without escrowed shares would perform in

the aftermarket. To evaluate abnormal share price return at period t for each escrowed firm

i, we match this firm with a non-escrowed IPO firm j. We then compute for j its

buy-and-hold return over the equivalent listing period t, which begins and ends with the

same number of months after the initial listing date of j as in the case of period t of firm i.

This allows us to construct the measure of matched-firm adjusted BHAR measure for each

firm i as follows:

τ,,, jtiti RRAAR −=

For example, if an IPO has shares escrowed for one year, its one-year pre-release BH

returns are adjusted against the first-listing-year BH return of the matched non-escrowed

IPO. Its annualized two-year post-expiration returns are adjusted by the annualized return

of the matched non-escrowed IPO over the period from the beginning of the second to the

end of the third year after listing.

Our use of a matched non-escrowed IPO also serves to address a potential concern

that any long-run performance may simply reflect the size and book-to-market effects

(Brav and Gompers, 1997). This problem may be even greater in the sample as the IPOs

with escrowed IPOs tend to be smaller firms and have greater growth potential than those

without escrowed shares. There are different matching algorithms for different

performance measures proposed in the literature. According to Barber and Lyon (1997), for

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share price returns, the matching process should be based on the criteria of size and

market-to-book ratio. For accounting-based performance measures, however, Barber and

Lyon (1996) suggest that the control firms be selected according to industry, size and

pre-event-window operating returns. However, for IPOs with only a one-year escrow

period, the Barber and Lyon’s procedure requires one of the matching criteria to be

operating returns before going public. Unfortunately, this is difficult to apply because some

IPOs have no reporting history. In addition, it is quite obvious that new companies and their

profitability change quite radically from the pre- to post-listing periods, depending on the

size and purposes of their issues, and hence create potential unknown biases in the

matching process.

As a result, this study employs industry grouping, size and market-to-book to detect

similarity in pre-event-window firm characteristics, regardless of the performance

measures (share price or operating returns) being compared. Although controlling for

industry specific effects when evaluating share price returns is not mentioned in Barber and

Lyon (1997), its inclusion is unlikely to create a less closely matched control group.5

The details of this algorithm are quite similar to those described in Barber and Lyon

(1996, 1997). First, matching firms must be non-escrowed IPOs listed during the same

sampling period and matching criteria are measured at the time of listing.6 Second, for each

5 During our sample period, the ASX used two-digit codes to categorize industries and three-digit codes for more specific subgroups. We classify the sample firms according to their two-digit codes. The only exception is the Miscellaneous Industrials category (code 22), which consists of many subgroups of completely unrelated activities, such as High Technology (code 228) and Automotive and Related Services (code 225). As each of this subgroup often has as many firms as other industry group, this study classifies the IPOs within this broad category according to their three digit codes. 6 Size is calculated as the average market capitalisation during the first 10 trading days and then adjusted for inflation. Market-to-book ratio is obtained by dividing this market capitalisation by book value of equity reported in the prospectus. Book value of assets is also used as an alternative proxy for size but this does not materially change either the control group or any of the results to be reported later in section 3.

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IPO with escrowed shares, we select from the entire sample of all IPOs in the same industry

that have a firm size within the range of 70% to 130% of that of the target firm. Within this

subgroup, the IPO with the closest book-to-market ratio to our target firm is selected to be

the match. After this matching process, the size and book-to-market ratio of the escrowed

IPOs group and those of the control sample of matched non-escrowed firms are no longer

statistically significant, as previously reported in Table 2.

3.3. Share Price Returns Before and After Escrow Expiration

Table 3 reports BHARs of the escrowed IPOs sample for various periods up to one

year before and up to 3 years after the escrow expiration date. Across four measures of

abnormal returns: (1) unadjusted, (2) index adjusted, (3) reference-portfolio adjusted, and

(4) matched-firm adjusted returns, we find consistent evidence of long-term

underperformance, as have been widely reported in the IPO literature. Most importantly,

escrowed IPOs appear to under-perform relative to their non-escrowed matched firms,

especially in periods after the escrow expiration date. Most of the performance decline is

concentrated in the year immediately after the event date. During the subsequent year,

BHARs do not seem to decline much further.

It is evident that regardless of the benchmark, share prices decline more substantially

after escrowed shares are freely tradable than during the escrow period. During month -11

to the event month, the average buy-and-hold return is about -8.5%, but for three years after

the escrow expiration date, this figure drops to about 19.1% to 21.8% per year. We formally

test whether this difference is significant by using the buy-and-hold return in the year

before the event date as the abnormal return benchmark. The statistics in the last column of

Table 3 show that post-expiration returns consistently under-perform the returns observed

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during the escrow period. In an unreported robustness check, we also compare BHAR in

periods before and after the escrow expiration date using paired t-test. Again, regardless of

the benchmarks, post-event return performance measures are always lower than their

pre-event counterparts. In most cases, this difference in share price performance is

statistically significant. In addition, all of these above-mentioned results remain robust

when we split the sample into events with one-year escrow duration and those with greater

than one year escrow duration (see Panel B and C of Table 3).

This finding also does not seem to be generated by the well-documented size and

book-to-market ratio effects. In Table 4, we report the results of the Fama-French

calendar-time regression, in which the dependent variable is monthly calendar-time returns

of four alternative escrowed IPO portfolios formed using one-year pre-expiration returns or

up to three years of post-expiration returns. The explanatory variables are the three

Fama-French factors. This method allows the detection of abnormal returns, controlling for

the size and book-to-market ratio effects and also reducing the problem of event clustering.

We find no evidence of abnormal returns for the one-year period before the event date.

However, during the periods of up to three years after the event date, abnormal returns are

significantly negative.

3.4. Operating Performance Before and After Escrow Expiration

This study also examines the decline in operating performance from before to after

escrow expiration. The advantage of operating returns is that they do not incorporate

information asymmetries or share market sentiments, and therefore may be more accurate

in reflecting management incentives and perhaps agency costs. To separate the impact of

potential earnings management from reported accounting performance, both operating cash

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flows and accounting earnings are investigated.

Table 5 reports both the median levels and median changes in (1) net operating cash

flows (NOCF), (2) earnings before interest, tax, depreciation and amortisation (EBITDA),

(3) earnings before tax (EBT), (4) net profits after tax and inclusive of extraordinary items

(NPAT), and (5) the use of accruals (earnings before interest and tax minus net operating

cash flows). Similar to Jain and Kini (1994) and Mikkelson, et al. (1997), we document a

long-run underperformance pattern with respect to operating returns, with the median

levels of most measures in Panel A being significantly negative. In contrast, the same

statistics for non-escrowed IPOs are all significantly positive (see Panel B).

We also report the median of changes in operating performance from year -1 before

to year t after the escrow expiration date, which are all significantly less than zero. This

finding indicates that the managerial incentive to maximize performance only extends to

the year before trading restriction ends. In year 0 (the year during which escrowed shares

expire), the operating results at the balance date are released after the escrow expiration

date, and they are substantially worse than pre-escrow-expiration levels. We also observe a

similar trend of declining operating performance for the control sample of non-escrowed

IPOs. However, the comparison of median changes in operating performance between

escrowed IPOs and their matches (see Panel C) shows that the declining performance of the

former is significantly more pronounced than the latter group.

Similar findings are also obtained when we examine changes in Tobin’s Q. Before

the escrow expiration date, the median Q of escrowed IPOs is about 1.40, which is

significantly higher the same measure for non-escrowed IPOs of about 1.18. When shares

are freely tradable, this difference is substantially reduced. The median changes in Q from

year -1 to year 0 and year +1 are also significantly negative. In contrast, the Q levels of

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non-escrowed IPOs do not differ significantly from before to after the escrow expiration

date. Overall, our findings with respect to share price returns, operating returns, and

Tobin’s Q all show a clear pattern of declining firm performance and value when shares are

freely tradable compared to when they are restricted.

3.5. Potential Explanations

The above analysis shows a substantial performance decline after escrow expiration.

We argue that this phenomenon reflects increased agency costs or higher information

asymmetries as pre-IPO owners (managers) are allowed to trade. Table 7 first documents

the declining level of managerial incentives after the event date. The percentage ownership

levels of pre-IPO managers and all executives (old and new) in years 0 to +3 are all

significantly lower than those in year -1. This indicates that as pre-IPO managers

aggressively sell their shares after the expiration of their escrow conditions, and while in

some cases they may be replaced by new professional managers, the latter lacks the same

ownership interests.

The ownership of pre-IPO non-managerial capitalists also declines substantially, to

the extent that they effectively own no shares (in median terms) in year +3. They appear to

be replaced by new large block shareholders, so that the ownership concentration of outside

monitors remains stable. However, the declining performance of escrowed IPOs suggests

that new large block shareholders are not as effective in their monitoring roles as pre-IPO

capitalists and appear to suffer substantial losses. This declining ownership pattern is also

observed for non-escrowed IPOs (see Panel B). However, the extent of the ownership

decline is more observable for escrowed IPOs. Panel C compares post-expiration

ownership changes (relative to year -1) and the differences are mostly statistically

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significant. Overall, the pattern of declining performance in escrowed IPOs appears to

coincide with the accelerated selling of pre-IPO owners’ shares, which exacerbate their

agency problems.

A manifestation of higher agency costs can be observed through evidence of potential

earnings management. We investigate the possibility that the difference in accounting

earnings may be further attributed to earnings management techniques. According to Teoh,

Welch and Wong (1998), managers can inflate earnings (or deflate losses) before a

seasoned equity offering by altering the extent of accounting accruals, defined as the

difference between accounting earnings and operating cash flows, divided by total assets. If

this possibility also applies to the escrow expiration event, then the extent of accounting

accruals usage would be higher before rather than after the event date. As reported in Table

5, there is indeed a negative change in the accrual figures from year –1 to year 0 and from

year -1 to year +1 (see Panel A). . Furthermore, when comparing against corresponding

matched firms, the usage of accounting accruals is also significantly more pronounced for

escrowed IPOs. Therefore, there is evidence that firms with escrowed shares are quite

aggressive in earnings management and they use this to improve accounting profits (or

lower losses) in the year before the escrowed shares are released, making it easier for them

to relinquish their ownership when their shares are freely tradable.

The fact that pre-IPO owners can start trading after the escrow expiration date can

also increase a firm’s level of information asymmetries. We explore this possibility by

comparing secondary market trading before and after the event. If liquidity in the latter

period is higher than the former, then investors may be more hesitant to trade against

pre-IPO owners, who possess superior information about their companies. According to

Amihud and Mendelson (1986), lower liquidity due to higher information asymmetries

20

would lead to higher costs of capital and therefore lower market valuation.

Two proxies for liquidity are the average trading turnover and percentage bid-ask

spread. The former is calculated as the average of monthly trading turnover (volume

divided by the total issued shares) in a particular year relative to the event date. The latter is

computed as the average of weekly percentage bid-ask spread (the difference in weekly

closing bid and ask quotes, divided by their mid-point) for the same period. As recorded

bid-ask data are only available from 1992 onwards, we can only include firms with the

escrow expiration date after 1993, and hence, the sample drops to 189 observations.

The results in Table 8 show a substantial decrease in liquidity after pre-IPO owners

are no longer restricted from trading. The average turnover decreases from 2.81% in the

year before the event date to about 2.05% to 2.16% in the three years after that date. The

average bid-ask spread increases from 7.56% to about 9.92% to 10.88% during the same

event window. These differences are all statistically significant. They also have a high

degree of economic significance as higher bid-ask spreads increase the cost of capital. To

illustrate this effect with a simple example, assume that a company has constant future cash

flows and an expected return of 20 percent, then the 2.40 percentage point increase in

bid-ask spreads (the difference between the year before and the year after the event date)

actually translates to a 10.12 percent decline in the share price. In addition, we also

compare the trading turnover and bid-ask spreads of the control sample during their

comparable listing periods, and find no significant changes in either measure. Overall,

these results show that information asymmetries increase substantially after escrow

expiration as investors now expect potential losses when trading against pre-IPO owners

with superior information. This is a factor that may partly contribute to the observed pattern

of declining share price returns and firm value.

21

4. REGRESSION ANALYSIS

4.1. Regression Variables

Not all IPO owners place all of their shares into escrow agreements. Even before the

expiration of trading restriction, pre-IPO owners can still trade unrestricted shares. At the

time of escrow expiration, the trading intention changes to include only the just-released

shares. In addition, in some IPOs, pre-IPO managers only retain a small proportion of

equity, and hence, the effect of their future trading after escrow expiration on performance

is less important. Thus, the change in performance from before to after escrow expiration

should differ from one firm to another, depending upon the relative scope of potential

future selling by managers. Assuming that pre-IPO owners continually relinquish their

shareholdings in the aftermarket as documented in Brennan and Franks (1997) and

Mikkelson et al. (1997), the proportion of escrowed shares can be used to reflect a the

scope for future selling. When the number of escrow shares are proportionally large,

escrow expiration should bring a substantial change in the scope of owners’ trading

intention, and hence, performance difference should be correspondingly high. As a result,

we propose that the impact of trading intention on performance can be further observed by

testing whether changes in firm performance from before to after trading restrictions expire

are positively related to the proportion of restricted shares. To do this, we employ a

cross-sectional regression analysis of the change in performance between pre- and

post-event periods (dependent variable) and the number of escrowed shares as a proportion

of issued shares immediately before the expiration date (explanatory variable), labelled

ESCROWPROP hereafter. We also examine the role of escrow period length under the

expectation that IPOs may signal their quality by adopting a long escrow period and that it

22

may be difficult for pre-IPO owners to delay bad news and manage earnings over a long

period when their shares are still restricted. This suggests that IPOs with a longer escrow

period may experience less substantially performance decline.

The proportion of escrowed shares is the most observable but not the only indicator

of future trading intention. Managers are likely to trade in order to achieve their optimal

risk-sharing ownership positions, which can be influenced by other firm characteristics

related to the costs of holding and trading shares. In particular, large shareholdings in large

and risky firms can impose more diversification constraints on managers’ investment

portfolios than others. A liquid secondary market on the other hand encourages more

frequent trading. Therefore, we also include the following as control variables in the

regression: LogSIZE (log of market capitalisation measured at the end of year -1),

TURNOVER and VOLATILITY (the monthly average trading turnover and the standard

deviation of daily returns during the year before the escrow expiration date).

Further, we also consider the possibility that relinquishing ownership by managers

may take the form of additional equity issues. These are more likely to happen for firms

with high leverage and growth opportunities. Therefore, we also include the ratios of

interest-bearing debt to assets (labelled DEBT) at the end of year -1. Finally, we control for

the fact that some firms have a greater degree of information asymmetries and inferior

outside monitoring incentives than others, leading to more substantial decline in

managerial incentive and performance in the post-expiration periods. To do this, we

include: (1) the ratio of intangible assets to total assets at the end of year -1 (labelled

INTANGIBLE), (2) a dummy indicator for whether a firm pays dividends in year -1

(labelled DIVIDEND), (3) the percentage ownership of new large block shareholders, who

own at least five percent of issued shares, excluding pre-IPO owners (labelled

23

NEWBLOCKOWN), and (4) the percentage ownership of non-executive directors,

excluding company founders (labelled NONEXECOWN). Overall, these additional control

variables potentially reflect the extent of managerial trading intention and changes in the

information asymmetry environment, and ultimately may further explain the observed

performance differences from before to after escrow expiration.

4.2. Correction for Selection Bias

Another problem when investigating this relation is the possibility that it may be

spurious due to the intervening effects of various factors that may influence both

aftermarket performance and the decision of whether to escrow shares. In fact, the ASX’s

procedures in deciding which IPOs should have escrowed shares depend on factors such as

size, track record of profit history and tangibility of assets.7 As these variables may

influence both the decision to escrow shares and post-listing performance, the classic

selection bias problem (Heckman, 1979) emerges in the regression between change in

performance and the proportion of escrowed shares. As a result, all cross-sectional

regression analyses need to utilise Heckman’s (1979) two-step correction for selection bias.

First, the predicted probability of an IPO featuring escrowed shares is estimated using the

following probit regression on the entire sample of IPOs (with and without escrowed

shares). The explanatory variables are the above-mentioned pre-listing factors that may

affect the decision of whether an IPO should have an escrow agreement:

εαααα ++++= PFINTANGIBLEINGLogAGELISTLogSIZEPFESCPROB 3210

in which ESCPROB takes value of 1 if an IPO has escrowed shares and 0 otherwise,

7 This is elaborated in appendix 9B accompanying Chapter 9 of the ASX Listing Rules.

24

LogSIZEPF is the natural logarithm of pro-forma firm size (issue price multiplied by the

total number of issued shares), LogAGELISTING is the natural logarithm of firm age at

listing, which is included as a proxy for profit history, and INTANGIBLEPF is the

proportion of intangible assets over total assets (based on pro-forma balance sheet figures).

This probit regression is estimated using maximum likelihood. The coefficients 1α̂ ,

2α̂ and 3α̂ are all significant at the 0.01 level and take values of -0.272, -0.096 and 1.159,

respectively. Thus, the above variables are indeed important determinants of the

probability of whether a firm has escrowed shares. The pseudo R-square for the model is

7.92 percent.8 The log likelihood ratio statistic is extremely high at 56.94 and significant at

the 0.01 level. This suggests that selection bias may indeed exist between escrowed and

non-escrowed IPOs. Based on the output of this probit regression, the next step (the

correction) involves the calculation of the inverse of Mill’s ratio (hereafter denoted as

INVMILLS), which is a monotone decreasing function of the probability of a firm having

escrowed shares. The estimated values of this variable are then used as a regressor in all

equations that model the relation between change in performance and the proportion of

escrowed shares. Consistent estimates of these regressions can be obtained using OLS.

However, the asymptotic variance-covariance matrix of the estimates used for the purpose

of hypothesis testing is calculated following procedures outlined in Heckman (1979). If the

coefficient of INVMILLS in the regression is significant and coefficients of other variables

do change substantially, then it is possible that the relation between the change in

8 It should be noted that R2 values are normally much lower in probit than in OLS regressions. As a robustness check , we also include in this probit regression other pre-listing factors not stated in the ASX listing rules that differ significantly between escrowed and non-escrowed IPOs, such as debt ratio, ownership retention and pro-forma book-to-market ratio. While the pseudo R-squared increases with these additional variables, the results in the second-stage regressions remain the same.

25

performance and the proportion of escrowed shares across observations is driven by

selection bias. In summary, the regression analysis employed to test Hypothesis 2 can be

represented by the following equation:

+++++=Δ iiiii TURNOVERLogAGELogSIZEESCROWP 43210 ααααα

++++ iiii DIVIDENDINTANGIBLEDEBTVOLATILITY 8765 αααα

εααα +++ iINVMILLSNONEXECOWNNNEWBLOCKOW 11109

in which iPΔ denotes changes in performance measures (share price returns,

operating returns, and Tobin’s Q) for observation i from one year before to one year after

the event date. In addition to the explanatory variables listed above, we also include the

extent of accruals usage in year -1 as an additional control in the regression models

involving changes in EBITDA and NPAT to account for the fact that excessive use of

accounting accruals is likely lead to earnings reversal in subsequent years.

4.3. Regression Results

Before the regression results can be discussed, it is important to examine the potential

selection bias due to the fact that the ASX decides whether an IPO’s shares should be

escrowed based upon the firm’s size, profit history and asset tangibility (see Table 2 for

differences between non-escrowed and escrowed IPOs). Using Heckman’s (1979)

procedures, the variable INVMILLS represents a monotone decreasing function of the

probability of a firm having escrowed shares and is included in the regressions in Tables 9,

10, and 11 to account for potential selection bias. In all of these tables, the coefficients of

INVMILLS are mostly significant for measures of performance changes between the first

two years after and the year before the escrow expiration date. While we do not report the

26

results of the regression in which INVMILLS is excluded, the inclusion of this variable does

not alter the significance of other variables in most cases and the coefficients of other

variables do not change substantially (none by more than one standard deviation).

Therefore, although some pre-listing firm characteristics appear to influence whether a firm

would have escrowed shares or not, the relation between change in performance and the

proportion of escrow shares cannot be entirely attributed to this selection bias.

Table 9 reports the regression results on this relation when performance difference is

calculated using unadjusted buy-and-hold returns periods before and after escrow

expiration. The first column shows that the proportion of escrowed shares is positively (but

not significantly) related the buy-and-hold return in the pre-event period, but this relation

becomes negative and significant after escrow agreements expire (in the next three

columns). Further, the difference in buy-and-hold returns between the pre- and post-event

periods and the proportion of escrowed shares are also significantly related. A longer

escrow period also appear to positively and significantly influence both pre- and

post-expiration returns, but

Similar results are reported on Table 10 for Tobin’s Q. Due to the fact that the Q

measure are of highly leptokurtic, the estimation for each year excludes observations for

which the Q measure is outside the range of two standard deviations from the mean Q (of

that year). We find that the proportion of escrowed shares significantly influences the

change in Q from year -1 to years 0 and +1, but not for the years after. The escrow length

variable is also significantly related to the change in Q from year -1 to year 0.

Table 11 reports the relation between escrow conditions and changes various

operating return measures (i.e. NOCF, EBITDA, and NPAT). We do not find any evidence

that the proportion of escrowed shares influences changes net operating cash flows, but this

27

variable does significantly influence changes in accounting earnings in the first year. This

indicates that the potential decline in managerial incentive after the escrow expiration date

may have a more observable impact on accounting earnings, which can be manipulated

than operating cash flows, which are relatively beyond managerial control.

Overall, the above results provide a robust support for the suggestion that the extent

of performance decline after escrow expiration is determined by the proportion of

escrowed shares, which reflects the potential change in trading intention of pre-IPO

owners, and to some extent the length of escrow periods, which may reflect the quality of a

firm and the initial commitment of pre-IPO owners. This relation does not appear to be

driven by firm characteristics that may predict changes in managerial incentives, agency

costs and the information asymmetry environment.

5. CONCLUSION

We investigate the restriction on the ability to sell shares of managers and its impact

on firm performance by analysing a sample of IPOs with escrow agreements. The results

indicate that there are substantial differences in performance in the periods before and after

such an agreement expires. This is consistently observed over various measures of

performance (i.e. abnormal share price returns, operating cash flows, accounting earnings,

and Tobin’s Q). These measures are also adjusted for their corresponding figures from a

control group of non-escrowed IPOs with similar firm characteristics (i.e. industry, size and

book-to-market ratio). Even with the adjusted measures, the same pattern of performance

change is still observed. Therefore, this finding does not appear to be driven by the

well-known IPO long-term under-performance phenomenon or the effects of firm size and

28

book-to-market ratio. More importantly, the observed performance difference is directly

related to the proportion of escrowed shares and (for some performance measures) to the

length of escrow periods, after controlling for firm characteristics that may influence the

levels of agency costs and information asymmetries.

This result is particularly important to the on-going debate on the role and impact of

ownership structure. Previous theoretical studies often analysed ownership structure in a

static framework, which does not account for differences in future trading direction of key

shareholders. This may be one of the reasons why prior empirical research on the

ownership–performance relation has often produced mixed and inconclusive results. In this

study, it is argued that firm value is also dependent on the trading intention of pre-IPO

owners/managers in the secondary market. When their trading ability is restricted,

managerial commitment to the firm is higher and agency costs are reduced to the extent that

reflects their shareholdings. However, when this restriction expires, the equilibrium that

determines management efforts and firm performance would also account for their future

trading intention. In the case of IPO firms, since pre-IPO owners on average intend to sell

rather than buy further shares, this study observes significantly inferior performance after

escrow expiration. At the same time, the level of information asymmetries also increases

and this contributes to further declines in market valuation.

Although trading restriction is frequently used in and applied to today corporations,

for example, as a part of remuneration packages, compliance with Rule 144 and in lock-up

(or escrow) agreements, its effectiveness has rarely been evaluated in the past literature. By

documenting evidence that companies on average perform better during the period of

trading restriction, our analysis provides a justification for the use of trading restriction to

improve management incentive and commitment to the firm. However, judging from our

29

sample firms, it seems that the average length of restriction periods may still be too short as

there is still evidence of earnings being managed in order to inflate profits and deflate

losses before escrowed shares are released. It is believed that longer and more frequent

usage of trading restriction may be more beneficial for investors buying into newly listed

firms. For seasoned firms, a voluntary introduction and enforcement of similar mechanisms

may act to signal the commitment of managers and may improve their market valuation.

These and many other related issues are also promising avenues that await future research.

30

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33

Table 1. Sample Descriptions The sample excludes listings of mining firms, unit trusts and government privatisations. Gross issue proceeds and value of escrow shares are calculated on the pro-forma basis using the issue price and then adjusted for inflation. The industries in Panel B follow the pre-2002 Australian Stock Exchange’s sectoral classification.

Escrowed IPOs Non-escrowed IPOs

N Gross proceeds

($m)

Value of escrow shares

($m)

N Gross proceeds

($m)

PANEL A: Sample classification according to time period July 86 – Jun 88 60 878.831 1201.024 75 2303.203 July 88 – Jun 90 9 77.757 83.684 12 280.735 July 90 – Jun 92 1 9.448 2.364 12 2261.158 July 92 – Jun 94 31 520.266 532.481 76 3978.218 July 94 – Jun 96 23 327.520 347.803 33 1892.979 July 96 – Jun 98 14 168.212 236.819 44 2955.625 July 98 – Jun 00 83 1193.770 3179.099 81 5214.166 Total 221 3175.804 5583.274 333 18886.084

Panel B: Sample classification according to industry Infrastructure & Utilities 3 76.680 126.964 4 600.141 Developers & Contractors 13 292.492 304.966 14 611.618 Building Materials 4 26.523 30.565 10 344.023 Alcohol & Tobacco 8 120.637 62.951 9 196.733 Food & Household 5 142.175 148.857 14 398.356 Chemicals 1 2.544 4.173 2 105.636 Engineering 11 120.067 200.673 16 281.415 Paper & Packaging 0 0.000 0.000 5 181.670 Retail 16 218.212 433.121 23 1714.850 Transport 1 3.352 3.465 10 388.045 Media 18 508.195 1052.813 17 2830.061 Banks 0 0.000 0.000 6 703.667 Insurance 0 0.000 0.000 8 1941.925 Telecommunication 18 230.539 799.784 19 2748.753 Financial Services 10 51.347 102.537 63 1934.810 Health & Biotechnology 32 431.400 412.712 15 557.132 Misc Industrials 66 643.433 1488.863 80 2227.564 Diversified Industrials 4 24.867 20.667 7 655.752 Tourism & Leisure 11 283.339 389.993 11 463.884

34

Table 2. Descriptive Statistics of Sample Firms at Listing Date and at Escrow Expiration Date. Panel A reports the main firm characteristics of each IPO in the sample, split into IPOs with and without escrowed shares. The former group is further split into IPOs with the weighted-average escrow period (calculated for each IPO with multiple escrow periods as sum of the product of the length of each period and the number of shares escrowed for such a period, divided by the total number of escrowed shares) of one year or less and those with weighted-average escrow period of more than one year. Panel B reports various measures of the relative size of each portion of escrowed shares (note that each escrowed IPOs can have multiple escrow periods). The test statistics are based on Wilcoxon test for equal medians of two samples.

Variable Non- escrowed

IPOs (A)

Escrowed IPOs (B)

(A) vs (B) test

statistic

IPOs with escrow

length ≤1 (C)

IPOs with escrow

length >1 (D)

(C) vs (D) test

statistic

PANEL A: Firm characteristics of the IPOs in the sample Pro-forma market cap ($m)

Mean Median Std. Dev.

126.808 35.661

439.179

38.279 20.750 50.825

5.231*** 47.140 17.539 68.932

33.727 22.456 37.853

0.334

Market cap at listing ($m)


158.268 38.136

624.145

52.182 25.512 76.589

4.065*** 65.775 21.497

105.432

45.199 22.999 55.460

0.645

Intangible assets (%)


12.575 2.533

18.720

19.215 8.132

22.769 13.209***

18.243 6.971

21.207

19.715 9.243

23.586 0.283

Retained ownership (%)


47.455 53.853 29.443

58.794 61.166 18.574

3.815*** 56.735 59.669 18.219

59.852 62.255 18.722

1.390

Firm age (in years)


13.782 7.357

18.529

7.315 3.912

11.415 4.187***

7.586 4.359

11.934

7.176 3.435

11.177 0.404

Book-to-market ratio


0.679 0.696 0.375

0.608 0.518 0.373

2.327** 0.705 0.745 0.349

0.558 0.476 0.377

3.154***

Underpricing (%)


18.639 7.000

57.351

41.695 12.500

104.142 2.417**

29.896 12.600 67.656

47.757 12.001

118.365 0.158

First-listing- year volatility


0.034 0.028 0.021

0.049 0.046 0.023

8.178*** 0.038 0.035 0.020

0.054 0.054 0.022

5.397***

% of escrowed shares


45.229 47.696 20.061

45.100 45.945 20.442

45.296 48.753 19.934

0.904

Weighted ave. escrow period (in years)


1.649 1.937 0.524

No. of obs 333 221 75 146 (see next page)

35

Panel A reports the main firm characteristics of each IPO in the sample, split into IPOs with and without escrowed shares. The former group is further split into IPOs with the weighted-average escrow period (calculated for each IPO with multiple escrow periods as sum of the product of the length of each period and the number of shares escrowed for such a period, divided by the total number of escrowed shares) of one year or less and those with weighted-average escrow period of more than one year. Panel B reports various measures of the relative size of each portion of escrowed shares (note that each escrowed IPOs can have multiple escrow periods). The test statistics are based on Wilcoxon test for equal medians of two samples.

Variable Non- escrowed

IPOs (A)

Escrowed IPOs (B)

(A) vs (B) test

statistic

IPOs with escrow

length ≤1 (C)

IPOs with escrow

length >1 (D)

(C) vs (D) test

statistic

PANEL B: Relative size of individual portions of escrowed shares Escrowed shares as % of total issued shares at listing date


37.326 39.140 22.175

34.573 31.648 23.549

39.340 42.042 20.965

1.824*

Escrowed shares as % pre-IPO owners’ shares at listing date


65.417 73.167 34.509

61.598 69.444 38.254

68.211 76.095 31.329

0.774

Escrowed shares as % of total issued shares at expiration date


30.912 27.737 20.973

31.356 25.700 23.269

30.733 29.780 19.200

0.245

No. of obs 258 109 149 ***, **, and * denote significance at the 1, 5, and 10 percent levels.

36

Table 3. Long-run Abnormal Returns for Escrowed IPOs before and after the Escrow Expiration Date. The sample covers 258 escrow expiration events of 221 escrowed IPOs. For each observation period (in months relative to the escrow expiration date), abnormal returns (in percentage) are calculated by subtracting from the raw buy-and-hold (BH) returns one of the benchmark BH returns. These benchmarks include the BH returns of (1) the All Ordinaries index in the same calendar period, (2) the reference size-deciles portfolio in the same calendar period (with the reference portfolios reconstructed at the end of June), (3) the matched non-escrowed IPO (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent post-listing year, and (4) the same firm during the year before the escrow expiration date. Following Barber, Lyon, and Tsai (2001), bootstrapped skewness-adjusted t-statistics are used to test whether mean BHAR in a particular period is significantly different from zero.

No benchmark (raw BH returns)

Benchmark = Index

BH return

Benchmark = Reference

size-deciles portfolio BH returns

Benchmark = Matched

non-escrowed IPOs BH returns

Benchmark = One-year

pre-expiration BH returns

Period (in months relative to escrow expiration date)

Mean t-stat Mean t-stat Mean t-stat Mean t-stat Mean t-stat

Panel A: BHARs of the full sample of escrow expiration events (N = 258) -11 to -6 -7.353 -2.178* -9.287 -2.742** -14.599 -3.869*** -5.789 -1.527 -5 to 0 -3.502 -0.988 -3.846 -1.642 -11.217 -2.987** -6.701 -1.336 -1 to 0 -2.157 -1.634 -2.114 -1.656 -3.205 -2.385** 0.417 0.296 -11 to 0 -8.488 -2.133* -12.302 -2.390** -27.343 -6.027*** -13.602 -2.524** 1 to 6 -13.272 -3.715*** -13.432 -3.779*** -18.858 -5.015*** -10.623 -2.039** -9.770 -2.690** 7 to 12 -9.693 -3.402*** -11.467 -3.922*** -15.089 -4.906*** -8.486 -2.260** -5.276 -1.735* 1 to 12 -19.132 -4.097*** -20.698 -4.393*** -32.991 -7.623*** -21.200 -3.029** -10.988 -2.331** 13 to 24 2.200 0.468 -4.742 -1.110 -38.363 -6.615*** 4.886 0.756 8.493 1.311 25 to 36 5.021 0.914 -3.597 -0.484 -46.277 -5.887*** -11.725 -1.307 11.714 1.745* 1 to 24 (annualized) -19.719 -7.236*** -21.880 -8.309*** -44.743 -15.410*** -15.551 -4.441*** -10.751 -2.516** 1 to 36 (annualized) -21.848 -7.550*** -25.173 -8.662*** -49.775 -21.565*** -17.459 -4.861*** -9.310 -2.344**

PANEL B: BHARs of the sub-sample of events with an escrow period of one year (N=109) -11 to -6 -4.411 -0.959 -5.358 -1.657 -5.732 -1.125 -4.858 -0.891 -5 to 0 -10.112 -1.335 -6.111 -1.591 -12.536 -1.721* -10.677 -1.520 -1 to 0 -3.701 -1.673* -2.923 -1.448 -4.697 -1.972* -2.433 -1.080 -11 to 0 -14.763 -2.670** -11.216 -1.934* -18.764 -2.769** -16.467 -2.551** (see next page)

37

The sample covers 258 escrow expiration events of 221 escrowed IPOs. For each observation period (in months relative to the escrow expiration date), abnormal returns (in percentage) are calculated by subtracting from the raw buy-and-hold (BH) returns one of the benchmark BH returns. These benchmarks include the BH returns of (1) the All Ordinaries index in the same calendar period, (2) the reference size-deciles portfolio in the same calendar period (with the reference portfolios reconstructed at the end of June), (3) the matched non-escrowed IPO (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent post-listing year, and (4) the same firm during the year before the escrow expiration date. Following Barber, Lyon, and Tsai (2001), bootstrapped skewness-adjusted t-statistics are used to test whether mean BHAR in a particular period is significantly different from zero.

No benchmark (raw BH returns)

Benchmark = Index

BH return

Benchmark = Reference

size-deciles portfolio BH returns

Benchmark = Matched

non-escrowed IPOs BH returns

Benchmark = One-year

pre-expiration BH returns

Period (in months relative to escrow expiration date)

Mean t-stat Mean t-stat Mean t-stat Mean t-stat Mean t-stat

1 to 6 -20.151 -3.890*** -17.699 -2.874** -21.154 -4.074*** -16.327 -2.800** -8.056 -1.460 7 to 12 -1.401 -0.293 -8.005 -1.602 -4.307 -0.882 -1.242 -0.183 6.863 1.427 1 to 12 -18.706 -2.503** -22.219 -2.864** -26.471 -3.592*** -19.404 -2.110** -6.903 -0.865 13 to 24 -13.275 -1.813* -12.621 -1.872* -34.139 -4.803*** -16.085 -1.877* -5.371 -0.654 25 to 36 8.325 1.110 -0.431 0.007 -46.724 -4.308*** 0.468 0.075 14.443 1.588 1 to 24 (annualized) -25.605 -7.446*** -27.027 -9.453*** -39.701 -8.591*** -21.927 -4.907*** -15.918 -2.704** 1 to 36 (annualized) -27.742 -7.859*** -30.052 -10.059*** -46.892 -12.368*** -23.176 -5.080*** -13.263 -2.401**

PANEL C: BHARs of the sub-sample of events with an escrow period greater than one year (N=149) -11 to -6 -8.985 -1.845* -10.967 -2.208** -20.200 -3.538*** -6.453 -1.527 -5 to 0 1.384 0.343 -1.629 -0.348 -10.405 -2.267** -3.813 -1.336 -1 to 0 -1.021 -0.594 -1.486 -0.866 -2.255 -1.324 2.486 0.296 -11 to 0 -7.913 -1.308 -12.365 -1.968* -32.793 -5.373*** -11.559 -2.122** 1 to 6 -8.279 -1.791* -10.397 -2.450*** -17.357 -3.427*** -6.481 -2.039** -10.861 -2.224** 7 to 12 -15.630 -4.632*** -14.525 -4.432*** -22.408 -6.097*** -13.848 -2.289** -13.499 -4.184*** 1 to 12 -19.229 -3.223*** -19.810 -3.382*** -37.087 -6.834*** -22.504 -3.028*** -13.587 -2.352** 13 to 24 6.079 1.114 1.296 0.262 -41.620 -4.648*** 20.843 0.756 19.197 2.077* 25 to 36 3.140 0.443 -6.781 -0.560 -45.918 -4.104*** -21.087 -1.307 9.542 1.009 1 to 24 (annualized) -16.544 -4.419*** -18.181 -4.667*** -47.925 -12.207*** -10.921 -1.744* -7.463 -1.270 1 to 36 (annualized) -18.489 -4.586*** -21.744 -5.009*** -51.634 -16.592*** -13.308 -1.827* -6.795 -1.243

***, **, and * denote significance at the 1, 5, and 10 percent levels.

38

Table 4. Long-run Abnormal Returns for Escrowed IPOs before and after the Escrow Expiration Date – Evidence from Fama-French Calendar Time Regression The dependent is the monthly calendar-time returns of the escrow-IPO portfolio. The portfolio is formed alternatively using return observations during one year before the escrow expiration date, and during one, two, and three years after the escrow expiration date. Excess market return is the difference between the All Ordinary index return and the risk free rate in the same calendar month. SMB is the difference in returns between the smallest and the largest size quintile portfolios. HML is the difference in returns between the high and low book-to-market ratio portfolios. As book-to-market ratio data are only available from 1989 onwards, returns observations before 1989 are discarded. The first three regressions also exclude the period of September 1992 to August 1993 as there are no returns observations (due to the absence of escrowed IPOs in the two earlier years) in the corresponding portfolio.

Event Period (in months relative to escrow expiration date)

- 11 to 0 1 to 12 1 to 24 1 to 36

Excess market return 0.245

(0.195) 0.092

(0.171) 0.170

(0.162) 0.322

(0.132)** SMB 0.164

(0.153) 0.107

(0.161) 0.185

(0.146) 0.150

(0.102) HML 0.065

(0.139) 0.230

(0.126)* 0.207

(0.122)* 0.168

(0.094)* Constant -0.004

(0.008) -0.019 (0.006)***

-0.010 (0.006)*

-0.009 (0.005)*

R-squared 0.017 0.024 0.027 0.047 No. of observations 148 155 166 191


39

Table 5. Differences in Operating Performance before and after the Escrow Expiration Date. The sample covers 258 escrow expiration events of 221 escrowed IPOs. The table reports the level of operating performance in a particular financial year relative to the escrow expiration date and the corresponding change relative to the performance for the financial year before this date. The operating performance measures include (1) net operating cash flows (NOCF), (2) earnings before interest, tax, depreciation and amortisation (EBITDA), (3) earnings before tax (EBT), (4) net profits (after tax and inclusive of extraordinary items), and (5) the use of accruals (earnings before interest and tax minus net operating cash flows before tax). All of these measures are scaled by the average of the opening and closing assets, and expressed in percentage. For each performance measure, the median levels and changes are reported for the escrowed IPOs sample and the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent listing year. The test statistic reported below the median is based on the Wilcoxon signed rank test for zero median.

Median level Median change Operating performance measures

Year -1 Year 0 Year +1 Year +2 Year +3 -1 to 0 -1 to 1 -1 to 2 -1 to 3

PANEL A: Operating performance levels and changes of escrowed IPOs NOCF -4.338

4.862*** -6.183 6.049***

-4.662 5.263***

-3.778 4.205***

-3.284 3.136***

-2.822 2.604**

-1.563 1.513

-1.621 0.770

0.669 0.473

EBITDA -1.682 2.068**

-2.038 3.211***

-0.232 3.482***

3.133 1.174

3.557 1.293

-1.659 3.313***

-2.483 2.850**

-1.609 0.343

-0.366 0.121

EBT -3.974 4.659***

-7.570 7.008***

-7.772 7.426***

-2.497 4.777***

-3.285 4.804***

-3.849 5.325***

-4.770 4.959***

-4.230 1.893*

-3.989 1.339

NPAT -3.594 5.077***

-6.521 7.487***

-7.182 7.532***

-4.207 5.642***

-2.668 5.016***

-3.850 5.060***

-6.043 4.949***

-4.565 2.165**

-5.096 2.078**

Use of accruals -0.393 1.354

-1.951 4.047***

-2.267 5.012***

-1.102 1.726*

-0.393 2.999***

-1.194 2.578**

-2.385 3.554***

-1.255 0.791

-0.852 1.483

PANEL B: Operating performance levels and changes of matched non-escrowed IPOs (the control sample) NOCF 3.251

5.630*** 4.451 5.485***

4.641 4.178***

3.432 3.094***

3.037 2.081**

-0.065 0.067

-0.260 0.014

-0.937 1.378

-2.341 2.857***

EBITDA 10.693 9.723***

9.898 8.293***

9.734 7.237***

9.932 6.508***

9.356 4.238***

-0.701 1.543

-1.292 2.024**

-1.595 2.149**

-3.713 3.531***

EBT 5.842 7.396***

4.232 4.759***

2.971 2.663**

2.839 2.037**

3.127 0.974

-0.986 2.937***

-2.354 3.427***

-2.841 4.073***

-4.911 4.004***

(see next page)

40

The sample covers 258 escrow expiration events of 221 escrowed IPOs. The table reports the level of operating performance in a particular financial year relative to the escrow expiration date and the corresponding change relative to the performance for the financial year before this date. The operating performance measures include (1) net operating cash flows (NOCF), (2) earnings before interest, tax, depreciation and amortisation (EBITDA), (3) earnings before tax (EBT), (4) net profits (after tax and inclusive of extraordinary items), and (5) the use of accruals (earnings before interest and tax minus net operating cash flows before tax). All of these measures are scaled by the average of the opening and closing assets, and expressed in percentage. For each performance measure, the median levels and changes are reported for the escrowed IPOs sample and the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent listing year. The test statistic reported below the median is based on the Wilcoxon signed rank test for zero median.

Median level Median change Operating performance measures

Year -1 Year 0 Year +1 Year +2 Year +3 -1 to 0 -1 to 1 -1 to 2 -1 to 3

NPAT 5.929 6.412***

4.512 1.787*

1.985 0.087

2.494 1.190

3.802 0.351

-1.834 3.293***

-2.501 3.445***

-3.458 3.062***

-4.962 3.021***

Use of accruals 2.411 4.137***

0.998 2.404***

1.182 2.178***

0.684 1.324***

1.706 1.848***

-0.574 1.141

-0.703 1.110

-0.741 1.029

0.176 0.730

PANEL C: Differences in median changes of operating performance between the escrowed IPOs sample and the control sample NOCF -4.167

2.322** -1.400 1.153

1.247 0.497

1.156 1.502

EBITDA -1.584 1.842*

-2.419 1.678*

-0.088 0.698

1.757 0.756

EBT -2.424 2.706**

-3.568 2.509**

-1.102 0.596

0.936 0.615

NPAT -1.501 1.714*

-4.664 1.961**

-1.585 0.140

-1.768 0.041

Use of accruals -0.944 1.710*

-1.769 2.228**

0.787 0.358

-2.395 0.672

Number of observations 257 257 245 217 189 257 245 217 189


41

Table 6. Differences in Relative Performance Measures (Tobin’s Q) before and after Escrow Expiration. The sample comprises 258 escrow expiration events of 221 escrowed IPOs. Panel A reports the median Tobin’s Q of the escrowed IPOs sample. Q is proxied by the market value of assets divided by book value of assets, calculated at the end of the financial year before (year -1), the year inclusive of (year 0), and the three years after (years +1, +2, and +3) the escrow expiration date. Panel B reports the median Q of the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent listing year. The test statistics reported below the median and are based on the Wilcoxon test of equal median between a post-escrow-expiration year and year -1.

Year -1 Year 0 Year +1 Year +2 Year +3

PANEL A: Tobin’s Q of the escrowed IPOs sample Median level 1.402 1.179 1.270 1.318 1.365 -vs- year -1 test statistics 2.957*** 1.826* 0.946 0.448

PANEL B: Tobin’s Q of the control sample of matched non-escrowed IPOs Median 1.183 1.135 1.132 1.156 1.213 -vs- year -1 test statistics 1.196 1.161 1.159 0.137 Escrowed IPOs vs non-escrowed IPOs test

2.973*** 0.898 1.834* 2.099** 1.132

No. of obs 258 258 245 216 188


42

Table 7. Ownership Levels and Changes before and after Escrow Expiration. The sample comprises 258 escrow expiration events of 221 escrowed IPOs. Panel A reports the ownership information of the escrowed IPOs sample at the end of the financial year before (year -1), the year inclusive of (year 0), and the three years after (years +1, +2, and +3) the escrow expiration date. Panel B reports the ownership information of the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent listing year. In Panels A and B, the reported test statistics are based on the Wilcoxon signed-rank test of whether the ownership change from year -1 is significantly different from zero. Panel C reports the test statistics of the Wilcoxon test for equal medians between ownership changes (from year -1) of the escrowed IPOs sample and that of the control sample.


PANEL A: Ownership levels and changes of escrowed IPOs %Own. of pre-IPO execs 25.298 19.690 12.090 6.452 3.730 Change from year -1 -0.541 -1.030 -0.498 -0.160 Wilcoxon test statistics 8.347*** 9.767*** 8.509*** 7.655***

%Own. of pre-IPO capitalists 14.820 10.380 5.450 1.040 0.000 Change from year -1 -0.340 -0.560 0.000 0.000 Wilcoxon test statistics 9.167*** 8.821*** 8.853*** 6.821***

%Own. of all execs 27.579 22.500 15.840 7.760 4.770 Change from year -1 -0.520 -1.000 -0.500 -0.180 Wilcoxon test statistics 7.625*** 9.241*** 8.585*** 7.153***

%Own. of all capitalists 29.890 30.460 33.111 33.375 29.902 Change from year -1 -0.000 -0.000 -0.000 -0.000 Wilcoxon test statistics 0.855 1.581 0.364 0.032

%Own. of 20 largest s/holders 75.900 76.030 73.160 71.910 71.510 Change from year -1 -0.090 -0.460 -0.120 -0.120 Wilcoxon test statistics 1.379 2.991*** 1.823* 1.324

PANEL B: Ownership levels and changes of non-escrowed IPOs %Own. of pre-IPO execs 30.520 25.631 23.000 19.860 17.000 Change from year -1 -0.338 -0.405 -0.310 -0.139 Wilcoxon test statistics 7.702*** 7.523*** 6.871*** 6.019***

%Own. of pre-IPO capitalists 6.813 3.340 0.920 0.000 0.000 Change from year -1 0.000 0.000 0.000 0.000 Wilcoxon test statistics 6.345*** 4.571*** 6.047*** 5.599***

%Own. of all execs 32.160 25.965 23.000 20.157 17.740 Change from year -1 -0.292 -0.276 -0.234 -0.139 Wilcoxon test statistics 7.720*** 7.525*** 6.871*** 6.018***

%Own. of all capitalists 23.541 26.625 24.579 23.853 24.700 Change from year -1 0.000 0.000 0.000 -0.527 Wilcoxon test statistics 3.421*** 1.915* 0.969 1.575 (see next page)

43

The sample comprises 258 escrow expiration events of 221 escrowed IPOs. Panel A reports the ownership information of the escrowed IPOs sample at the end of the financial year before (year -1), the year inclusive of (year 0), and the three years after (years +1, +2, and +3) the escrow expiration date. Panel B reports the ownership information of the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent listing year. In Panels A and B, the reported test statistics are based on the Wilcoxon signed-rank test of whether the ownership change from year -1 is significantly different from zero. Panel C reports the test statistics of the Wilcoxon test for equal medians between ownership changes (from year -1) of the escrowed IPOs sample and that of the control sample.


%Own. of 20 largest s/holders 78.275 76.800 76.180 75.200 75.085 Change from year -1 0.300 -0.000 -0.630 -0.510 Wilcoxon test statistics 0.491 1.571 3.866*** 3.482***

PANEL C: Comparing ownership changes: escrowed versus non-escrowed IPOs %Own. of pre-IPO execs 0.875 2.315** 0.752 0.539 %Own. of pre-IPO capitalists 4.261*** 5.963*** 3.214*** 0.499 %Own. of all execs 0.753 2.352** 1.651* 1.040 %Own. of all capitalists 1.932* 0.355 0.829 0.813 %Own. of 20 largest s/holders 1.116 1.057 1.123 1.771* 258 258 245 217 189


44

Table 8. Evidence of Increased Level of Information Asymmetries after Escrow Expiration. The sample comprises 258 escrow expiration events of 221 escrowed IPOs. Bid-ask spreads are calculated as the difference of weekly closing bid and ask quotes divided by their mid-point. Trading turnover is calculated as monthly trading volume divided by the beginning-of-the-month number of issued shares. For each escrow expiration event, both measures are averaged over the year before and up to three years after the event date. They are also calculated for the control sample of matched non-escrowed IPOs (i.e., an IPO in the same industry, with no escrow restriction, having a similar size and book-to-market ratio) in the same equivalent post-listing year. For each measure, paired t-test is used to detect mean differences between the escrowed IPOs and matched non-escrowed IPOs samples. The number of observations used to compute average bid-ask spreads due to the lack of recorded data on bid and ask quotes prior to 1992.

Average bid-ask spreads (%) Average trading turnover (%) Period (in months relative to escrow expiration date)

N Escrowed IPOs

Sample

Control sample of

non-escrowed IPOs

N Escrowed IPOs

Control sample of

non-escrowed IPOs

-11 to 0 (A) 189 7.556 5.488 258 2.813 2.682 1 to 12 (B) 189 9.953 6.144 258 2.137 2.248 13 to 24 (C) 181 10.877 6.309 232 2.046 2.299 25 to 36 (D) 171 9.919 6.369 202 2.167 2.565

(A) vs (B) t-stat 2.756*** 0.957 2.183** 1.440 (A) vs (C) t-stat 3.070*** 1.578 2.488** 1.213 (A) vs (D) t-stat 1.993** 1.147 2.105** 0.941


45

Table 9. Relation between Escrow Conditions and Buy-and-Hold Returns during Periods before and after Escrow Expiration Date Dependent variable is either BHRt1,t2 , which is the annualized buy-and-hold return of an escrowed IPO from month t1 to month t2 relative to the escrow expiration date, or ∆BHR t1,t2, which is the difference between BHRt1,t2 and BHR-11,0. ESCROWPROP is the ratio of escrowed shares to issued shares at the escrow expiration date. ESCROWLEN is the length of the escrow period. LogSIZE and LogAGE is log of market capitalization and firm age, respectively, at the end of year -1. TURNOVER and VOLATILITY are the monthly average trading turnover and the standard deviation of daily returns during the year before the escrow expiration date. DEBT and INTANGIBLE are the ratios of interest-bearing debt and intangible assets, respectively, to total assets at the end of year -1. DIVIDEND is a dummy indicator for whether a firm pays dividends in year -1. NEWBLOCKOWN is the percentage ownership of new large block shareholders (those holding at least five percent of issued shares, excluding pre-IPO owners). NONEXECOWN is the percentage ownership of non-executive directors, excluding company founders. INVMILLS is the inverse of the Mill’s ratio, computed following Heckman’s (1979) correction for selection bias. Figures reported in parentheses are heteroskedasticity-consistent standard errors.

BHR -11,0 BHR1,12 BHR1,24 BHR1,36 ∆BHR1,12 ∆BHR1,24 ∆BHR1,36

ESCROWPROP 0.163

(0.160) -0.328 (0.163)**

-0.250 (0.118)**

-0.287 (0.124)**

-0.491 (0.209)**

-0.413 (0.190)**

-0.450 (0.194)**

ESCROWLEN 0.137 (0.068)**

0.019 (0.065)

0.109 (0.046)**

0.120 (0.052)**

-0.118 (0.079)

-0.028 (0.071)

-0.017 (0.073)

LogSIZE 0.114 (0.035)***

-0.063 (0.029)**

-0.049 (0.020)**

-0.048 (0.023)**

-0.177 (0.045)***

-0.164 (0.043)***

-0.162 (0.043)***

LogAGE 0.030 (0.039)

0.016 (0.044)

-0.017 (0.030)

-0.017 (0.033)

-0.014 (0.051)

-0.047 (0.046)

-0.047 (0.049)

TURNOVER 0.383 (0.275)

0.326 (0.271)

0.125 (0.127)

0.147 (0.123)

-0.057 (0.352)

-0.257 (0.312)

-0.236 (0.329)

VOLATILITY -3.671 (1.938)*

-5.329 (1.869)***

-4.544 (1.277)***

-4.353 (1.294)***

-1.658 (2.521)

-0.873 (2.255)

-0.682 (2.313)

DEBT 0.322 (0.227)

-0.059 (0.229)

-0.438 (0.157)***

-0.473 (0.158)***

-0.381 (0.306)

-0.760 (0.275)***

-0.795 (0.271)***

INTANGIBLE -0.172 (0.218)

0.261 (0.246)

0.145 (0.130)

0.171 (0.141)

0.433 (0.279)

0.317 (0.240)

0.343 (0.250)

DIVIDEND 0.090 (0.093)

0.044 (0.105)

0.075 (0.060)

0.088 (0.063)

-0.046 (0.129)

-0.015 (0.111)

-0.002 (0.111)

NEWBLOCKOWN -0.362 (0.227)

-0.108 (0.291)

0.023 (0.210)

-0.083 (0.239)

0.254 (0.332)

0.385 (0.288)

0.279 (0.321)

NONEXECOWN -2.334 (4.338)

-7.784 (3.743)**

-1.143 (2.841)

-0.720 (2.579)

-5.450 (4.741)

1.191 (5.029)

1.613 (5.055)

INVMILLS 0.537 (0.201)***

-0.167 (0.214)

-0.366 (0.132)***

-0.425 (0.144)***

-0.703 (0.286)**

-0.902 (0.246)***

-0.961 (0.250)***

C -1.821 (0.544)***

0.629 (0.601)

0.949 (0.370)**

1.048 (0.402)***

2.450 (0.782)***

2.770 (0.651)***

2.869 (0.657)***

Adjusted R2 0.113 0.038 0.094 0.094 0.048 0.091 0.089 ***, **, and * denote significance at the 1, 5, and 10 percent levels.

46

Table 10. Relation between Escrow Conditions and Changes in Tobin’s Q from before to after Escrow Expiration Date Dependent variable is the difference in Tobin’s Q between year t (t = 0 to 3) and year -1 (relative to the escrow expiration date). The estimation for each year excludes observations for which the Q measure is outside the range of two standard deviations from the mean Q (of that year). ESCROWPROP is the ratio of escrowed shares to issued shares at the escrow expiration date. ESCROWLEN is the length of the escrow period. LogSIZE and LogAGE is log of market capitalization and firm age, respectively, at the end of year -1. TURNOVER and VOLATILITY are the monthly average trading turnover and the standard deviation of daily returns during the year before the escrow expiration date. DEBT, INTANGIBLE, and RESEARCH are the ratios of interest-bearing debt, intangible assets, and research and development expenditures, respectively, to total assets at the end of year -1. DIVIDEND is a dummy indicator for whether a firm pays dividends in year -1. NEWBLOCKOWN is the percentage ownership of new large block shareholders (those holding at least five percent of issued shares, excluding pre-IPO owners). NONEXECOWN is the percentage ownership of non-executive directors, excluding company founders. INVMILLS is the inverse of the Mill’s ratio, computed following Heckman’s (1979) correction for selection bias. Figures reported in parentheses are heteroskedasticity-consistent standard errors.

∆Q0 ∆Q1 ∆Q2 ∆Q3

ESCROWPROP -0.894 (0.394)**

-0.736 (0.295)**

0.233 (0.579)

-0.570 (0.734)

ESCROWLEN 0.438 (0.119)***

0.012 (0.088)

0.057 (0.084)

-0.209 (0.181)

LogSIZE -0.552 (0.103)***

-0.205 (0.092)**

-0.056 (0.075)

-0.123 (0.212)

LogAGE -0.283 (0.079)***

-0.051 (0.072)

-0.130 (0.092)

-0.171 (0.142)

TURNOVER 0.245 (0.273)

-0.439 (0.609)

-0.077 (0.226)

0.580 (0.614)

VOLATILITY -6.442 (3.988)

-4.662 (4.252)

-1.939 (4.284)

-5.109 (7.627)

DEBT 0.764 (0.302)**

0.269 (0.301)

-0.551 (0.336)

-0.094 (0.573)

INTANGIBLE 1.949 (0.507)***

0.574 (0.424)

0.564 (0.598)

0.364 (1.059)

DIVIDEND 0.205 (0.173)

-0.118 (0.127)

0.056 (0.124)

0.223 (0.191)

NEWBLOCKOWN 0.309 (0.402)

-0.206 (0.376)

-0.173 (0.796)

0.153 (0.559)

NONEXECOWN 2.613 (6.669)

-12.921 (8.294)

10.294 (5.730)*

24.079 (11.644)**

INVMILLS -1.936 (0.482)***

-0.765 (0.459)*

-0.900 (0.572)

-0.547 (0.816)

C 5.554 (1.443)***

2.924 (1.397)**

2.135 (1.594)

2.256 (2.358)

Adjusted R2 0.330 0.032 0.002 0.001 Number of obs 240 218 189 167 ***, **, and * denote significance at the 1, 5, and 10 percent levels.

47

Table 11. Relation between Escrow Conditions and Changes in Operating Performance from before and after Escrow Expiration Date Dependent variable is the difference in net operating cash flows (∆NOCF), earnings before interest, tax, depreciation and amortisation (∆EBITDA), or net profits after tax (∆NPAT) between reporting year t (t = 0 to 3) and year -1 (relative to the escrow expiration date). The estimation for each year excludes observations for which the Q measure is outside the range of two standard deviations from the mean Q (of that year). ESCROWPROP is the ratio of escrowed shares to issued shares at the escrow expiration date. ESCROWLEN is the length of the escrow period. LogSIZE and LogAGE is log of market capitalization and firm age, respectively, at the end of year -1. TURNOVER and VOLATILITY are the monthly average trading turnover and the standard deviation of daily returns during the year before the escrow expiration date. ACCRUAL, DEBT, INTANGIBLE, and RESEARCH are the ratios of the use of accruals (EBIT-NOCF), interest-bearing debt, intangible assets, and research and development expenditures, respectively, to total assets at the end of year -1. DIVIDEND is a dummy indicator for whether a firm pays dividends in year -1. NEWBLOCKOWN is the percentage ownership of new block shareholders (those holding at least five percent of issued shares, excluding pre-IPO owners). NONEXECOWN is the percentage ownership of non-executive directors, excluding company founders. INVMILLS is the inverse of the Mill’s ratio, computed following Heckman’s (1979) correction for selection bias. Figures reported in parentheses are heteroskedasticity-consistent standard errors.

∆NOCF ∆EBITDA ∆NPAT

-1 to 0 -1 to 1 -1 to 2 -1 to 3 -1 to 0 -1 to 1 -1 to 2 -1 to 3 -1 to 0 -1 to 1 -1 to 2 -1 to 3

ESCROWPROP -0.093 (0.064)

-0.060 (0.085)

-0.073 (0.113)

-0.012 (0.127)

-0.122 (0.070)*

-0.075 (0.107)

-0.148 (0.110)

-0.031 (0.163)

-0.172 (0.084)**

-0.122 (0.121)

-0.122 (0.138)

-0.055 (0.171)

ESCROWLEN 0.018 (0.022)

0.000 (0.028)

-0.036 (0.041)

-0.042 (0.053)

-0.010 (0.026)

-0.008 (0.032)

-0.013 (0.045)

-0.110 (0.075)

-0.016 (0.034)

0.025 (0.043)

0.045 (0.054)

-0.005 (0.062)

LogSIZE -0.028 (0.011)**

-0.016 (0.021)

-0.041 (0.031)

-0.002 (0.028)

-0.029 (0.016)*

-0.033 (0.027)

-0.062 (0.023)***

0.006 0.031)

-0.022 (0.021)

-0.059 (0.030)**

-0.053 (0.033)

-0.012 (0.035)

LogAGE -0.039 (0.014)***

-0.036 (0.021)*

-0.034 (0.031)

-0.036 (0.035)

-0.024 (0.015)

-0.039 (0.023)*

-0.055 (0.027)**

-0.036 (0.038)

-0.021 (0.020)

-0.052 (0.031)*

-0.032 (0.036)

-0.048 (0.042)

TURNOVER -0.007 (0.058)

-0.110 (0.133)

-0.060 (0.146)

0.056 (0.254)

-0.007 (0.076)

-0.043 (0.134)

-0.012 (0.085)

0.117 (0.265)

0.005 (0.080)

0.022 (0.138)

-0.048 (0.174)

0.257 (0.365)

VOLATILITY -0.588 (0.582)

0.267 (0.910)

0.722 (1.365)

2.414 (1.518)

-2.391 (0.967)**

-0.878 (1.110)

-0.629 (1.351)

0.167 (2.037)

-2.059 (1.204)*

-0.724 (1.290)

-0.083 (2.008)

-0.225 (2.252)

ACCRUAL

-0.629 (0.143)***

-0.792 (0.175)***

-0.761 (0.184)***

-1.071 (0.231)***

-0.579 (0.193)***

-0.888 (0.199)***

-0.966 (0.253)***

-1.222 (0.262)***

DEBT -0.001 (0.059)

0.018 (0.079)

0.072 (0.160)

0.101 (0.217)

0.131 (0.063)**

0.045 (0.097)

0.074 (0.139)

0.244 (0.208)

0.230 (0.079)***

0.038 (0.122)

0.160 (0.179)

0.071 (0.226)

(see next page…)

48

Dependent variable is the difference in net operating cash flows (∆NOCF), earnings before interest, tax, depreciation and amortisation (∆EBITDA), or net profits after tax (∆NPAT) between reporting year t (t = 0 to 3) and year -1 (relative to the escrow expiration date). The estimation for each year excludes observations for which the Q measure is outside the range of two standard deviations from the mean Q (of that year). ESCROWPROP is the ratio of escrowed shares to issued shares at the escrow expiration date. ESCROWLEN is the length of the escrow period. LogSIZE and LogAGE is log of market capitalization and firm age, respectively, at the end of year -1. TURNOVER and VOLATILITY are the monthly average trading turnover and the standard deviation of daily returns during the year before the escrow expiration date. ACCRUAL, DEBT, INTANGIBLE, and RESEARCH are the ratios of the use of accruals (EBIT-NOCF), interest-bearing debt, intangible assets, and research and development expenditures, respectively, to total assets at the end of year -1. DIVIDEND is a dummy indicator for whether a firm pays dividends in year -1. NEWBLOCKOWN is the percentage ownership of new block shareholders (those holding at least five percent of issued shares, excluding pre-IPO owners). NONEXECOWN is the percentage ownership of non-executive directors, excluding company founders. INVMILLS is the inverse of the Mill’s ratio, computed following Heckman’s (1979) correction for selection bias. Figures reported in parentheses are heteroskedasticity-consistent standard errors.

∆NOCF ∆EBITDA ∆NPAT

-1 to 0 -1 to 1 -1 to 2 -1 to 3 -1 to 0 -1 to 1 -1 to 2 -1 to 3 -1 to 0 -1 to 1 -1 to 2 -1 to 3

INTANGIBLE 0.209 (0.078)***

0.092 (0.141)

0.100 (0.197)

-0.114 (0.226)

0.176 (0.091)*

0.053 (0.155)

0.224 (0.145)

-0.134 (0.248)

0.017 (0.148)

-0.060 (0.196)

-0.111 (0.240)

-0.176 (0.266)

DIVIDEND -0.013 (0.026)

-0.035 (0.034)

-0.052 (0.042)

-0.065 (0.056)

-0.006 (0.030)

-0.008 (0.037)

-0.080 (0.047)*

-0.151 (0.072)**

0.011 (0.043)

0.006 (0.046)

-0.095 (0.066)

-0.156 (0.074)**

NEWBLOCKOWN 0.103 (0.082)

0.066 (0.134)

0.331 (0.168)*

0.343 (0.170)**

0.084 (0.074)

0.213 (0.102)**

0.106 (0.123)

0.406 (0.175)**

0.046 (0.103)

0.245 (0.134)*

0.093 (0.180)

0.441 (0.201)**

NONEXECOWN 0.019 (1.293)

1.488 (1.968)

5.754 (2.201)***

7.230 (2.784)**

-0.549 (1.661)

1.895 (2.483)

5.598 (2.778)**

6.407 (3.671)*

-1.783 (2.195)

2.620 (3.310)

5.916 (3.428)*

7.978 (4.244)*

INVMILLS -0.185 (0.081)**

-0.274 (0.139)*

-0.295 (0.198)

-0.139 (0.269)

-0.120 (0.110)

-0.283 (0.138)**

-0.537 (0.155)***

-0.327 (0.259)

-0.096 (0.142)

-0.478 (0.192)**

-0.390 (0.253)

-0.325 (0.259)

C 0.538 (0.229)**

0.720 (0.412)*

0.829 (0.572)

0.301 (0.719)

0.480 (0.325)

0.815 (0.433)*

1.561 (0.403)***

0.910 (0.706)

0.375 (0.406)

1.263 (0.565)**

1.054 (0.709)

0.819 (0.710)

Adjusted R2 0.017 0.001 0.042 0.036 0.195 0.151 0.182 0.164 0.085 0.163 0.182 0.219 Number of obs 257 245 217 189 257 245 217 189 257 245 217 189 ***, **, and * denote significance at the 1, 5, and 10 percent levels.

49

Figure 1. Cumulative Average Raw Returns of Escrowed and Matched Non-Escrowed IPOs

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

-12 -6 0 6 12 18 24 30 36

Escrowed IPOs Matched Non-Escrowed IPOs

managers’ trading intention and the performance of newly ...€¦ · managers’ trading...

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