Why do only some Nasdaq firms switch to the NYSE? Evidence from corporate transactions

Journal of Financial Markets 14 (2011) 109–126 www.elsevier.com/locate/finmar

Why do only some Nasdaq firms switch to the NYSE? Evidence from corporate transactions Simi Kediaa,n, Venkatesh Panchapagesanb a

Rutgers Business School, 94 Rockafeller Road, Levin 117, Piscataway, NJ 08854, USA b Goldman Sachs Asset Management, 32 Old Slip, New York, NY 10005, USA Available online 14 July 2010

Abstract Every year only a small fraction of Nasdaq firms that are eligible to move to the NYSE actually choose to move. This is surprising as prior literature documents significant gains to listing on NYSE. Gains in visibility and liquidity associated with a move to NYSE reduce the firm’s cost of capital. Consequently, firms are more likely to move to NYSE when they are raising external financing or engaging in acquisition activity. We study a set of corporate transactions – issue of debt, equity and involvement in acquisitions – for a group of Nasdaq firms that chose to move to the NYSE and a size and industry-matched control group over the period 1986–1998. We find that firms that move to the NYSE issue more debt and equity, and engage in more asset transactions following their move relative to control firms. Our results suggest that the listing decision of a firm is often not isolated, but rather related, to other important corporate objectives of the firms. & 2010 Elsevier B.V. All rights reserved. JEL classification: G10; G14 Keywords: Exchange listing; Debt issues; Acquisitions; Cost of capital

1. Introduction The Nasdaq stock market emerged in the 1970s to provide small firms with access to capital markets. Most of these firms eventually moved on to the New York Stock Exchange (NYSE) following years of growth. This is not surprising given that many

n

Corresponding author. Tel.: 1 732 445 4195; fax: 1 732 445 2333. E-mail address: [email protected] (S. Kedia).

1386-4181/$ - see front matter & 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.finmar.2010.07.002

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researchers in the past have documented tangible gains from a NYSE listing (see, for example, Kadlec and McConnell, 1994; Baker, Powell and Weaver, 1999a, b). These gains to a NYSE listing involve gains in visibility and ‘‘prestige’’ leading to increases in market values of these firms’ shares. The gains to a NYSE listing also arise from increases in liquidity and potentially lower transaction costs. Despite these varied benefits that Nasdaq firms potentially derive from a NYSE listing, not all firms that are eligible to move choose to move. Based on the NYSE listing criteria, there were approximately 2,654 non-financial Nasdaq firms that satisfied the eligibility criteria of listing on NYSE from 1986 to 1998 but only 460 firms, or about one in six eligible firms, chose to actually move to the NYSE.1 Further, firms that move wait for a few years after their first eligibility before they list at the NYSE. Why do some Nasdaq firms move to the NYSE when others who are eligible to move choose not to? One possibility could be that firms where such benefits are not apparent are more likely to stay in Nasdaq. Amihud and Mendelson (1986) argue that highly liquid firms in Nasdaq realize little gain in liquidity by moving to the NYSE. In similar vein, Reinganum (1990) shows that small firms have a liquidity advantage on the Nasdaq as compared to the NYSE. Aggarwal and Angel (1997) argue that higher spreads in Nasdaq give incentives to broker-dealers to market the stock that may be missing in a market like the NYSE where the nexus between brokers and dealers is weaker. Firms that depend on broker network for secondary market liquidity, therefore, choose not to list on the NYSE to exploit this marketing advantage. While these studies view differences in firm characteristics as the primary drivers in the listing decision, we present, in this paper, an alternative hypothesis that is based on the ability of a firm to exploit the visibility and liquidity gains from a NYSE listing as an important factor in the decision to move to the NYSE. Merton (1987) shows that firms benefit from a widening of their investor base through a lower cost of capital since investors prefer to invest only in securities that they are aware of. Similarly, Amihud and Mendelson (1986, 1988) show that investors are willing to accept a lower return for stocks with higher liquidity. Since NYSE stocks are usually more widely followed and are more liquid it is likely that Nasdaq firms moving to the NYSE experience a reduction in their cost of capital. Though a lower cost of capital is attractive, it is especially so when the firm is issuing new equity or debt. Consequently, firms are more likely to move to NYSE when they anticipate raising significant capital in the years ahead. A reduction in the cost of capital also reduces the cost of financing acquisition activity facilitating a firm’s acquisition program. In summary, firms are more likely to move to NYSE when their interactions with capital markets are high. Just like people are more likely to undertake home improvement projects to enhance the value of their house prior to putting the house for sale, firms might be more likely to capture the gains from a NYSE listing that reduce its cost of capital prior to major interactions with the capital markets. To examine this we choose Nasdaq firms that move to NYSE over the period 1986–1998 and a size and industry-matched control group of firms that were eligible to move in the 1

Because there were many firms that were eligible to move in more than one year, there were only 2,654 distinct firms among the 10,119 firms eligible to move from Nasdaq to the NYSE between 1986 and 1998. Among the firms that moved, there were 80 Nasdaq firms that did not satisfy the eligibility criteria that we use in our study (see Table 1).

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same year but chose to stay in Nasdaq. We study a set of corporate transactions – issue of debt, equity and involvement in acquisition activities – for both the sample and control firms. We find strong evidence that sample firms raise more debt than their control firms in the two years after the move to the NYSE. The evidence from equity issues is mixed—though sample firms have a larger number of equity issues they do not differ in the total proceeds raised from these equity issues from their control firms. Our evidence on acquisition activities present greater contrast between firms that move to the NYSE and firms that chose to remain in Nasdaq. The increase in acquisition activities for sample firms is twice as much as the increase for the control firms, and 50% more than when they were in Nasdaq. Our results suggest that firms choose to move to the NYSE when their interactions with capital markets are likely to be high. As far as we know, this paper is the first to show that firms’ involvement in capital raising and acquisition activities is an important factor impacting their decision to move to NYSE. The rest of the paper is organized as follows. Section 2 describes the empirical design and our data. Section 3 examines changes in corporate transactions for sample and control firms around the time they decide to leave Nasdaq and Section 4 concludes. 2. Empirical design and data 2.1. Hypotheses The premise of our analysis in this paper is that the decision to list on the NYSE, as well as, when to list is influenced by the ability of firms to exploit potential gains that are associated with a move from Nasdaq to the NYSE. One of the gains from a NYSE listing is the increase in the firm’s visibility (see Kadlec and McConnell, 1994; Baker, Powell and Weaver, 1999a, b; Baker and Johnson, 1990). This increased visibility from a NYSE listing will be associated with a widening of the firm’s investor base, and also an increase in ownership by institutional investors. As investors and institutions are not equally informed about all firms and only hold securities they are informed about, stocks that have a wide investor base and higher institutional ownership have lower expected returns as shown by Merton (1987). In short, increased visibility from a move to NYSE is likely to lead to a lower cost of capital for the firm. Another gain from a move to NYSE is an increase in liquidity (see Kadlec and McConnell, 1994; Christie and Huang, 1993). As investors are willing to accept lower rate of return for liquid stocks (see Amihud and Mendelson, 1986, 1988), increased liquidity is also likely to lead to a lower cost of capital. This reduction in the cost of capital, arising from an increase in visibility and liquidity, will be most valuable when the firm is planning capital raising activities. A lower cost of capital implies that the firm will be able to raise capital, both debt and equity, at a lower rate of return after it lists on the NYSE. Therefore, firms are more likely to move to NYSE when they anticipate raising debt and equity soon after they move. This leads to Hypothesis 1. Firms will engage in more capital raising activities, both debt and equity issuance, soon after they move to NYSE. A lower cost of capital also implies that it is cheaper to finance an acquisition program. Further, as merger and acquisition talks can be lengthy and time consuming the increased visibility from a NYSE listing may make for a more attractive and credible counter party.

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Therefore, firms are more likely to move to NYSE when they plan on major asset acquisitions in the years ahead. This leads to, Hypothesis 2. Firms will engage in more asset acquisitions after they move to NYSE. While some firms may choose to issue debt others may issue equity or acquire assets to exploit the lower cost of capital from the NYSE move. Therefore, a joint implication of Hypotheses 1 and 2 is that firms will engage in more overall corporate transactions, be it debt issues, equity issues or asset transactions after they move to NYSE. Though firms could be involved in a variety of transactions such as equity carve-outs and restructurings, in this paper we do not consider these and limit our focus to transactions that are central to a typical corporate strategy. 2.2. NYSE listing eligibility Panel A of Table 1 presents the objective listing criteria that the NYSE adopts towards domestic companies. During our sample period 1986–1998, the eligibility requirements were changed only once. We use a subset of these criteria based on firms’ earnings, total assets and market value to determine eligibility for listing (see Panel B). It is important to Table 1 NYSE listing requirements for domestic firms. This table lists the requirements for listing on the NYSE. Panel A displays the NYSE listing requirements for the period 1986–1998. The listing requirements are from the NYSE fact book. Panel B lists the implementation of the requirement for the determination of eligibility to move to the NYSE for this study. The NYSE listing criteria also include requirements regarding corporate governance practices of firms, which have not been taken into account here. Also the NYSE over recent years has been seen to relax some of these criteria for some firms. As a result eligibility as estimated by the criteria here is only indicative and does not predict with certainty that the firms would be listed on the NYSE if they want to. 1986–1994

1995–1998

Panel A: NYSE listing requirements Pre-tax income latest year Pre-tax income in the preceding two years Net tangible assets Aggregate market value of publicly held shares Shares publicly held Number of holders of round lots (greater than 100 shares)

$2.5 milliona $2.0 milliona $40.0 million $18.0 million 1.1 million 2,000

$2.5 milliona $2.0 milliona $40.0 million $40.0 millionb 1.1 million 2,000

Panel B: Implementation of the requirements for this study EBIT in the year prior to the year of change EBIT in the preceding two years Total assets Aggregate market value of firm Number of shares outstanding

$2.5 milliona $2.0 milliona $40.0 millionc $18.0 million 1.1 million

$2.5 milliona $2.0 milliona $40.0 millionc $40.0 millionb 1.1 million

a

Or $6.5 million for prior three years and $ 4.5 million in the most recent year. Was $18 million prior to January 2, 1996. c As many firms which moved to the NYSE had Net PPE less than 40 million we decided to interpret the requirement of net tangible assets being greater than 40 million as being that of total assets being greater than or equal to $40 million. b

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Table 2 Summary information on eligible and sample firms. This table presents summary information on Nasdaq firms that are eligible to move to the NYSE and Nasdaq firms that did move to the NYSE between 1986 and 1998. We identify eligible firms based on the eligibility criteria listed in Table 1 but exclude financial and foreign incorporated firms. Firms may be eligible to move in more than one year. We report average years of eligibility before moving for sample firms only for the years 1988–1998 as the statistic would be more likely to be biased for years 1986 and 1987 for lack of eligibility information prior to the sample period. Year Eligible firms (Nasdaq firms that are eligible to list at the NYSE) Total assets (in million dollars) N Mean Median 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Sample firms (Nasdaq Firms that move to the NYSE)

% of eligible Average years of eligibility firms that move to NYSE before moving

Total assets (in million dollars) N Mean Median

362 577 627 571 646 645 730 854 1,017 949 1,039 1,081 1,021

215.88 240.16 276.16 259.94 324.96 329.23 344.91 342.28 318.90 389.47 551.00 550.46 521.73

106.65 119.86 123.37 129.57 132.79 133.60 128.85 132.11 138.42 163.91 172.58 175.34 201.71

21 30 37 26 24 28 26 28 26 45 48 64 57

179.62 248.35 480.82 566.39 579.03 380.04 321.41 1,227.57 663.04 515.07 732.49 981.02 1,051.64

130.80 128.42 244.61 296.40 215.53 350.94 236.54 180.56 401.54 342.11 421.46 593.62 475.68

5.8% 5.2 5.9 4.6 3.7 4.3 3.6 3.3 2.6 4.7 4.6 5.9 5.6

Total 10,119

385.30

146.24

460

672.41

312.11

4.5

NA NA 2.40 2.93 3.50 3.95 5.24 5.05 5.57 6.46 5.68 6.02 6.74 5.20

note that a NYSE listing is not guaranteed for firms that satisfy our criteria as the exchange often uses other subjective criteria as well. Similarly, there could be special circumstances under which Nasdaq firms could move to the NYSE without satisfying these objective criteria. Given that such exceptions are rare, we limit our study to those Nasdaq firms that meet our objective NYSE listing criteria only. Based on our criteria, there were 2,654 Nasdaq firms that were eligible to be listed on the NYSE over the period 1986–1998. We do not consider financial firms and firms that were deemed foreign by CRSP for this study. There were more Nasdaq firms that were eligible to move to the NYSE in the latter part of our sample (see Table 2). This is not surprising and reflects the rapid increase in the valuation of Nasdaq firms during that period. There were more than 1,000 Nasdaq firms that were eligible from the mid 1990s, which is twice the number of firms that were eligible in the mid 1980s. The average (median) size of eligible firms also more than doubled over our sample period from $215 million dollars ($107 million) in 1986 to $520 million dollars ($201 million) of total assets in 1998. 2.3. Sample and control firms From our eligible firms, we identify firms that moved from Nasdaq to the NYSE in each of the years 1986–1998. There were 460 Nasdaq firms that moved to the NYSE during this period. Firms that move are, on average, larger in size compared to firms that stay back.

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Table 3a Industry distribution of sample and eligible firms. This table displays the frequency distribution of Nasdaq firms that moved to the NYSE and eligible Nasdaq firms that chose not to move during the period 1986–1998 across industries using a 2-digit SIC code. We identify eligible firms based on the eligibility criteria listed in Table 1 but exclude financial firms. We report the top fifteen industry codes in which the sample firms operate. We also report the percentage of unique eligible firms – firms that were eligible to move to the NYSE at least once during the sample period – that operate in the same industry code. Two-digit SIC code

% of sample firms

% of unique eligible firms

35 49 73 13 80 28 36 34 38 27 51 50 59 58 37 Others

8.70 7.39 7.17 5.87 5.87 5.43 5.00 3.26 3.26 3.04 3.04 2.61 2.61 2.39 2.17 32.17

9.04 2.52 12.58 2.15 3.77 3.13 10.85 2.19 5.99 1.32 2.37 4.33 3.13 2.83 2.03 31.77

In recent years, firms that move are twice as large as firms that choose not to move to the NYSE. Moreover, firms wait twice as long to move after becoming eligible to move in comparison to earlier periods. Since we do not consider eligibility prior to our sample period, our estimate on the average years of eligibility before moving is likely to be conservative, especially in the earlier part of the sample. The proportion of eligible firms that move dropped from the mid 1980s to early 1990s, indicating the growing importance of the Nasdaq stock market. However, we find evidence of more firms opting to move to the NYSE in the latter part of our sample. It is possible that more firms moved following government investigations on Nasdaq market practices or following enhanced marketing efforts by the NYSE. We find that firms that choose to move to the NYSE are likely to operate in industries that are quite different from industries where most eligible firms operate (see Table 3a). Further, extant research has shown that firms with imminent gains in visibility and liquidity are likely to move to the NYSE. To ensure that the firm behavior we study is not driven by these factors, we create a control group that is matched on these criteria. We use size as a proxy for visibility and liquidity, in line with prior research, and therefore match on size in lieu of a match on visibility and liquidity.2 The control group consists of Nasdaq firms that were eligible to move but choose not do so. Given that we study firm behavior around the time of their move, we require that the control firm should not have moved to the NYSE not only in the year in which the sample firm moved but also in the two years after. The control firm should have total assets within 2

Arbel and Strebel (1982, 1983) and Baker, Powell and Weaver (1999) document a positive correlation between firm size and visibility. Christie and Schultz (1994) provide evidence of the relationship between size and liquidity.

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Table 3b Market reaction to listing change. This table displays cumulative abnormal returns around the announcement of a move to NYSE for sample firms. The abnormal returns were computed using a value-weighted CRSP market model after adjusting for market movements. The t-statistic is reported in parenthesis below. *** represents significance at the 1% level. Time interval around listing change announcement

Mean cumulative abnormal return (t-statistic) (%)

30 to 3 2 to þ2 þ2 to þ30

1.90 (1.66) 2.74 (5.65***) 1.26 (1.10)

75% and 125% of the total assets of the sample firm and be in the same two-digit SIC. After removing financial firms, our matching procedure, without replacement, yielded 237 distinct pairs of sample and control firms.3 To examine whether there is any significant gains associated with a NYSE move we estimate the market reaction to the announcement of the listing on NYSE for sample firms.4 Abnormal returns were computed using a value-weighted CRSP market model. Consistent with prior literature, we find that the move to NYSE is associated with significant gains. As can be seen from Table 3b, the mean cumulative abnormal return (CAR) for the five day period from (2, 2) days is 2.74% and significant at the 1% level. Table 4 reports characteristics for sample and control firms. We use three different proxies for size – total assets, sales and market value in the year prior to the move – and find no difference between sample and control firms. This indicates that our matching procedure has worked well to control for this important attribute. We also find little difference between the sample and control firms in age, i.e., the number of years for which the firm has been covered by CRSP database and leverage, the ratio of long term debt to total assets. Both sample firms and their control firms grew in the years before the move. There was however, a difference in the rate of growth of these two groups. The median sample firm experienced an average growth rate in cash, sales and assets that was almost twice that of the median control firm over the two years prior to the move. Sample firms also had a higher Tobin’s Q than their control firms.5 We also use the market-to-book value of equity to capture growth opportunities (see Goyal, Lehn and Racic, 2004; Jacquier, Titman and Yalcin, 2001). Consistent with the other measures of growth, we find that sample firms had higher market-to-book value of equity with the difference in medians being significant. This difference in growth rates in the years prior to moving is consistent with evidence 3

Since only 460 of the 2,654 firms that were eligible to move actually moved, there are potentially several control firms for each firm that moved. We find that 70% of sample had on average two matched firms. Further, we were able to find at least one match for only 237 of the 460 firms that moved. The firms that moved for which we were not able to get a matched control firm were significantly larger. We examined the corporate transactions of these firms that moved to NYSE but are not included in our sample, and find that it is similar to the sample firms. Therefore, we believe that our inability to include them in the study does not bias the findings. 4 The listing dates were obtained through a search in Factiva (www.factiva.com), a search engine that scans trade and mainstream publications. Only sample firms for which we have clear announcements dates were included in this estimation. 5 We measure Tobin’s Q as (Total AssetsþMarket Value of EquityBook Value of EquityþDeferred Taxes)/ Total Assets. Extreme observations for cash, sales and asset growth rates as well as share volume have been removed for the purpose of Table 4.

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Table 4 Cross-sectional statistics of control and sample firms. This table presents summary cross-sectional statistics of our sample firms and control firms. Sample firms are Nasdaq firms that move to the NYSE between 1986 and 1998. Control firms are size and industry matched Nasdaq firms that were eligible to move to NYSE. Market capitalization, total assets, and sales are the respective values prior to the year of moving, in millions of dollars. Age is the number of years at time of moving since the firm was first covered by CRSP database. Leverage is the percentage of long-term debt to total assets in the year prior to moving to the NYSE. Growth rate in cash, total assets and sales is the average percentage growth rate for the two years prior to moving. Extreme observations for these have been removed. Share volume, expressed in million of shares, closing share price, number of analysts, the number of institutional shareholders and the percentage of the firm held by institutions pertain to the year prior to moving. The ‘‘Difference’’ column displays difference in means and medians. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively for the t-statistics testing difference in means and the Mann–Whitney Z-statistics testing difference in medians. Mean

Median

Sample

Control

Difference

Sample

Control

Difference

Total assets Sales Market Value Age Leverage

304 358 433 7.9 18.9

315 369 556 8.1 17.3

10 11 123 0.19 1.6

160 214 220 4 14.7

179 208 200 6 11.1

19 6 19 2 3.6*

Cash growth Sales growth Assets growth Tobin’s Q Market-to-book for equity

231 44.9 48.9 2.36 2.84

178 28.6 34.8 2.07 2.80

53 16nnn 14nnn 0.28nn 0.04

56 28.8 31.2 1.89 2.76

33 17.5 18.2 1.58 2.12

23nn 11nnn 12.9nnn 0.31nnn 0.63nnn

Share Volume Closing price

32,972 22.1

25,163 20.7

7,808 1.37

12,565 19.75

8,535 18.25

4,030nnn 1.5

Number of Analysts % of firm owned by institutional investors Number of institutional investors

6.1 45.45 40.9

6.4 47.78 40.5

0.3 2.33 0.4

5 37 39.3

5 34.5 39.8

0 2.5 0.5

documented in other studies that suggest that firms move after a period of strong growth (see, for example, Dharan and Ikenberry, 1995; McConnell and Sanger, 1987; Cowan, Carter, Dark and Singh, 1992). Given that sample firms are growing faster than control firms, it is not surprising to see that they trade more actively despite being quite similar in their sales and total assets. The median sample firm has 50% more volume than the median control firm in our sample. Interestingly, these marked differences in growth and trading activity between sample and control firms are not reflected either in the analyst coverage, or in the institutional ownership of these two groups of firms prior to the year they move, or the year in which they were eligible to move but chose not to.6 The median firm in our sample, whether it be 6

Data on analyst coverage is obtained from I/B/E/S database while that on institutional ownership is obtained from Spectrum.

Mean difference between sample and control firms

Number tWilcoxon statistic signed-rank of pairs statistic

0.01 17.1

0.11 2.6nnn

7.94nnn 7.8nnn

237 237

0.33 0.5

2.48nn 0.02

237 237

0.40

1.68n

2.36nn

237

0.38

1.82n

2.71***

237

Sample firms

Control firms

2 years before

2 years Mean after change

2 years before

2 years Mean after change

Number of debt issues Gross proceeds of debt issues (millions of $)

58 3,756

52 6,894

0.025 13.2

24 2,363

16 1,450

0.034 3.9

Number of equity issues Gross proceeds of equity issues (millions of $)

116 5,804

53 4,645

82 0.27nnn 4.9 4,434

24 2,472

0.24nnn 0.02 3.4 8.3n

Number of transactions involving sale or purchase of assets/firm (including mergers)

332

502

0.72nnn

283

358

0.32

Number of transactions involving purchase of assets/firm only

288

423

0.57nn

257

303

0.19

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Table 5 Changes in corporate transactions in the years around the move to the NYSE. The table displays incidence of corporate activity for sample and control firms in the two years before and the two years after they move to the NYSE or were eligible to move but chose not to. Control firms consist of size and industry matched Nasdaq firm that was eligible to move to NYSE but chose not do so. Column 4 and 7, titled ‘Mean change’ is the difference in the cross-sectional average of the number of corporate transactions in the two years before and two years after the move or after they were eligible to move. Column 8, titled ‘Mean Differencey’ represents the difference in the mean changes between sample and control firms. All data for corporate activities are from the SDC database. The t-statistic is computed using a two-tailed paired t-test. The Wilcoxon signed-rank statistic tests for differences in the medians between sample and control firms. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively.

117

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a sample firm or a control firm, is covered by five analysts and has a little less than 40% institutional ownership during our sample period. Our descriptive results suggest that Nasdaq firms that chose to move to the NYSE grow at a faster rate prior to their move than similar sized Nasdaq firms operating in the same industry that are eligible to but choose not to move to the NYSE. While a firm’s growth prospects may not determine whether it chooses to list at the NYSE, it certainly could determine when it lists at the NYSE. Studies such as Dharan and Ikenberry (1995) have documented that Nasdaq firms move after a period of high growth before bad performance derails their chance of a NYSE listing. 3. Corporate transactions To examine whether the decision to list is part of a broader corporate agenda, we examine three types of corporate transactions – issue of debt, issue of equity and the purchase or sale of the whole or part of a firm’s assets including mergers (to be subsequently referred to as asset transactions) – surrounding the move to the NYSE for sample and control firms. Our data on corporate transactions are from Securities and Data Corporation’s database. We use the year of moving for the sample firm as the ‘‘event year’’ for both the sample firm and its control firm. For each sample and control firm, we obtain data on all debt issues, equity issues, and purchases and sales of assets including mergers for the two years prior to and for the two years subsequent to its event year. We exclude transactions in the event year for our analyses. We first examine average changes in corporate activity of sample and control firms following their decision to move from Nasdaq. We examine changes both in the level and size of debt and equity issues but examine only changes in the level of asset sales or purchases around the event year for sample and control firms. Data on the value of asset transactions are mostly incomplete, especially when such transactions involve firms that are not publicly traded. To see if there are differences in assets sales and purchases, we also examine changes in the number of asset transactions where the firm was an acquirer. 3.1. Changes in debt issuances For both sample and control firms, we present the mean change in debt market transactions from two years before to two years after the event year and test for whether the change is significant. In addition, we present the mean difference between sample and control firms in changes in corporate transactions, i.e., ((SamplepostSampleprior) (ControlpostControlprior)). We use both parametric (paired t-statistic) and nonparametric (Wilcoxon signed-rank statistic) inference procedures under three levels (99%, 95% and 90%) of confidence to determine the statistical magnitude of these differences. Both sample and control firms had fewer debt issues in the two years following the event year than in the two years before. Sample firms had 58 debt issues in the two years before but had only 52 debt issues in the two years after their move to the NYSE. Debt issues by control firms dropped from 24 to 16 during the same period. Though the drop in debt issues for both sample and control firms is not significant, the interesting question for this study is the difference between sample and control firms. Consistent with our hypothesis,

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we find that the drop in the number of debt issues for sample firms is less than that for control firms though only the median difference is statistically significant.7 The gross proceeds from debt issues, however, increased from $3,756 million to $6,894 million for sample firms, while it dropped from $2,363 million to $1,450 million for control firms during the same period. Though the number of debt issues drops in the period after moving, the average debt issue is larger for firms that move. The average debt issue almost doubles in the period after moving, whereas it declines by 8% for control firms. This increase in the proceeds from debt issues, relative to the control firms, is significant in both means and medians. These univariate results are mirrored in an OLS model that includes a sample dummy that takes the value one for firms that move exchanges and zero otherwise.8 Change in the number of debt issues do not differ between sample and control firms though sample firms have significantly higher proceeds from debt issues (see Table 6). However, these results do not control for the effect of other factors that might impact changes in debt issues. In particular, as the transaction costs of issuing debt are large, firms do not access the debt markets every year but usually raise debt to cover the anticipated future financial shortfall. Consequently, if a firm had issued debt in the two years prior to moving it will be less likely to have a debt issue in the two years after the move. To control for prior debt issues, model 2 includes the number and proceeds from prior debt issues. As expected, firms that raise debt in the prior period have a lower likelihood of issuing debt after the move. Once we control for prior debt issues we find that sample firms are significantly more likely to issue debt after moving to NYSE. This is because, consistent with our hypothesis, sample firms access the debt markets more frequently. In particular, there are only nine firms that issue debt in both the prior and the later period, and six of them are sample firms. Next, we control for firm characteristics that might impact the likelihood of issuing debt. Firms often raise capital or acquire other firms to exploit their growth opportunities. We use market-to-book value of equity in the year prior to the event year to capture growth opportunities for a firm.9 We include the value of cash and equivalents to control for financial slack, as firms with large cash deposits are unlikely to raise capital. The age of a firm could also have a bearing on a firm’s need to initiate corporate transactions. Firms are more likely to access the capital market when they are young. Older firms with stable operations are more likely to be generating cash flows or have retained earning to finance their investment and growth. Capital structure, especially leverage, could determine the choice of issuing debt or equity or undertake acquisitions using stock or cash. We define leverage as the ratio of long-term debt to total assets in the years prior to moving. Like

7

The drop in the number of debt issues could be due to capital market conditions, interest rate expectations and other factors. Studying sample firms with respect to similar control firms over the same time period controls for these factors that impact the propensity of all firms to issue debt. 8 Though the dependent variable – change in the level and size of corporate transactions – could take the value zero, we believe OLS to be the most appropriate model for estimation. A tobit model is not appropriate as the data are not truncated at zero. Similarly, probit and logit models cannot be fitted as the dependent variable is not qualitative. The Poisson regression model for count data is also not appropriate on account of negative values. 9 The results are qualitatively similar if we use cash and sales growth over the two years prior to the event year as well as its Tobin’s Q in the year prior to proxy for growth opportunities instead of the market-to-book value of equity.

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Panel A: number of debt issues Model 1

Model 2

Panel B: proceeds from debt issues Model 3

Constant 0.034 (0.6) 0.036 (1.52) 0.162 (1.44) Sample dummy 0.008 (0.11) 0.083** (2.48) 0.081** (2.34) 0.003*** (5.8) 0.003*** (4.8) Proceeds from prior issues Num of prior issues 0.399*** (15.2) 0.401*** (13.4) Cash  100 0.023 (1.43) Age 0.000 (0.01) Leverage 0.068 (0.65) Log of total assets 0.046** (2.0) Market-to-book 0.006* (1.85) Number of analysts % by institutions # of institutions R Square 0.000 0.825 0.831 Observations 474 474 455

Model 4

Model 5

Model 1

Model 2

Model 3

Model 4

Model 5

0.062 (1.22) 0.239* (1.67) 3.857 (0.81) 1.760 (0.51) 34.0** (2.07) 4.982 (0.66) 45.7** (2.16) 0.086** (2.25) 0.085** (2.18) 17.1*** (2.55) 13.88*** (2.83) 13.4*** (2.64) 15.22*** (2.71) 14.9*** (2.6) 0.003*** (4.93) 0.003*** (4.47) 1.35*** (18.1) 1.36*** (14.9) 1.37*** (15.7) 1.36*** (13.7) 0.40*** (13.8)

0.003 (0.47) 0.040 (0.37) 0.000 (0.17) 0.837 401

0.400*** (12.5) 0.008 (0.34) 0.001 (0.36) 0.209 (1.64) 0.081** (2.5) 0.007* (1.78) 0.003 (0.52) 0.055 (0.46) 0.001 (0.88) 0.845 389

77.76*** (20.4)

0.014 474

0.478 474

77.7*** (17.8) 2.29 (0.96) 0.547 (1.52) 18.739 (1.24) 8.53** (2.54) 0.081 (0.15)

0.491 455

78.3*** (18.4)

0.173 (0.22) 13.384 (0.84) 0.030 (0.27) 0.490 401

77.8*** (16.5) 1.27 (0.37) 0.802* (1.86) 38.1** (2.02) 12.27*** (2.6) 0.008 (0.014) 0.521 (0.64) 3.82 (0.22) 0.058 (0.36) 0.508 389

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Table 6 Cross-sectional regressions of changes in debt market transactions. This table presents results of cross-sectional regressions of the change in debt market transactions in the two years after the move to the NYSE over the two years before the move. The dependent variable for Panel A is the change in the number of debt issues and for Panel B is the proceeds from debt issues. Sample dummy takes the value one, if the firm is a sample firm, and zero, if it is a control firm. Age is the number of years since the firm first appeared on CRSP at the time of moving. Leverage is the ratio of long-term debt to total assets. Proceeds from (number of) prior issues represent the proceeds raised from (number of) debt issues in the two years prior to moving. Cash is the cash balance in the year prior to moving and market-to-book is the ratio of market-to-book value of equity. Number of analysts, number of institutional owners and the percentage owned by institutions is measured one year prior to the move. Absolute value of t-statistics are in parenthesis. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively.

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most related studies, we control for firm size, as measured by the logarithm of total assets and market capitalization, as well. Firm characteristics, overall, do not substantially explain changes in debt issues and do not appear to differentially impact sample and control firms. In other words, the coefficient of the sample dummy continues to be significant (see Model 3) when we control for firm characteristics. Firm size, as proxied by total assets, positively impact debt activity. As we capture public debt issues, this is consistent with smaller firms that face higher information asymmetry, finding it optimal to use bank and private debt. As expected we find that firms with higher leverage have fewer debt issues, though the effect is not always significant. Several studies have documented the role of visibility in facilitating corporate transactions such as equity issues (see Merton, 1987; Barry and Brown, 1986; Bhardwaj and Brooks, 1992). Visibility is also likely to impact debt issuance, and to control for this, we include three variables that capture the pre-listing visibility enjoyed by the firm: analyst coverage, the percentage of the firm held by institutional investors and the total number of institutional investors in the firm in the year prior to the event year. Inclusion of these variables will capture any change in debt issues that are related to high initial visibility of the firm. We expect the sample dummy to reflect any benefits from the increase in visibility following the move to the NYSE. As seen in Model 4 of Table 6, these proxies for initial visibility do not significantly explain changes in debt issues. We continue to find significant debt activity by sample firms even in the full model that includes all the variables. In summary, we find that prior debt activity is important for understanding the changes in debt issues in the future. Controlling for the differences in prior activity between sample and control firms, we find that firms that move exchanges have significantly higher debt activity – both the number of debt issues and the proceeds from debt issue – in the years after moving relative to control firms in accordance with Hypothesis 1. 3.2. Changes in equity issues Patterns in equity issuance are similar to those in debt issues. Like debt issues, the number of equity issues and proceeds from equity issues drops in the two years following the event relative to the two years before for both sample and control firms. However, unlike debt issues changes in equity issues do not significantly differ between sample and control firms. There is little univariate evidence that sample firms issue more equity in the years after moving relative to control firms. As in the previous section, we control for prior equity issues as firms are unlikely to issue equity every year. As seen in Table 7, Model 2 firms are less likely to issue equity if they have issued equity in the prior two years. Of the 77 firms in our data that issued equity after moving, 31 had also issued equity in the two years prior. Of these 31 firms, 21 are sample firms. Consequently, once we control for equity issues prior to moving, the sample dummy is quite significant, i.e., sample firms are more likely to issue equity after moving. Though sample firms are also likely to have higher proceeds from equity issues after moving, this difference is not significant at the conventional levels. Next we control for firm characteristics that might impact the likelihood of equity issuance. Consistent with the prior analysis we include market-to-book value of equity in the year prior to the event year to capture growth opportunities, cash and equivalents to

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Panel A: number of equity issues

Constant Sample dummy Prior proceeds Num of prior issues Cash  100 Age Leverage Log of total assets Market-to-book Number of analysts % by institutions # of institutions R Square Observations

Panel B: proceeds from equity issues

Model 1

Model 2

Model 3

Model 4

Model 5

Model 1

Model 2

Model 3

Model 4

Model 5

0.25*** (5.14) 0.021 (0.31)

0.087*** (3.1) 0.116*** (3.1) 0.000 (0.6) 0.94*** (22.8)

0.126 (0.99) 0.102*** (2.68) 0.000 (0.78) 0.96*** (21.4) 0.001 (0.49) 0.006** (2.15) 0.168 (1.53) 0.003 (0.11) 0.006 (1.69)

0.055 (1.0) 0.11*** (2.74) 0.000 (0.16) 0.96*** (22.0)

0.092 (0.59) 0.104** (2.52) 0.000 (0.75) 0.97 (20.6)*** 0.012 (0.58) 0.005 (1.58) 0.139 (1.05) 0.041 (1.18) 0.008 (2.0) 0.006 (0.97) 0.22* (1.74) 0.002** (2.08) 0.731 389

8.29* (1.71) 3.38 (0.49)

9.11** (2.27) 8.72 (1.64) 0.95*** (12.83) 1.132 (0.19)

17.615 (0.96) 7.09 (1.29) 1.01*** (12.6) 0.903 (0.14) 1.82 (0.78) 0.96** (2.23) 8.459 (0.53) 6.835* (1.82) 0.105 (0.18)

4.207 (0.50) 7.949 (1.29) 0.97*** (11.8) 1.082 (0.16)

50.7*** (2.12) (1.17) 1.05*** (11.9) 1.75 (0.24) 2.22 (0.66) 1.05** (2.0) 6.29 (0.31) 12.1** (2.29) 0.287 (0.47) 0.105 (0.11) 50.9*** (2.65) 0.33* (1.91) 0.437 389

0.000 474

0.697 474

0.705 455

0.008 (1.39) 0.165 (1.44) 0.002** (2.29) 0.721 401

0.001 474

0.408 474

0.420 455

0.542 (0.63) 46.6*** (2.67) 0.178 (1.56) 0.421 401

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Table 7 Cross-sectional regressions of changes in equity market transactions. This table presents results of cross-sectional regressions of the change in equity market transactions in the two years after the move to the NYSE over the two years before the move. The dependent variable for Panel A is the change in the number of equity issues and for Panel B is the proceeds from equity issues. Sample dummy takes the value one, if the firm is a sample firm, and zero, if it is a control firm. Age is the number of years since the firm first appeared on CRSP at the time of moving. Leverage is the ratio of long-term debt to total assets. Proceeds from (number of) prior issues represent the proceeds raised from (number of) equity issues in the two years prior to moving. Cash is the cash balance in the year prior to moving and market-to-book is the ratio of market-to-book value of equity. Number of analysts, number of institutional owners and the percentage owned by institutions is measured one year prior to the move. Absolute value of t-statistics are in parenthesis. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively.

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control for financial slack, firm age, leverage and firm size. Inclusion of firm characteristics does not impact our basic results. In accordance with Hypothesis 1 we continue to find significant evidence of higher number of equity issues. However, we find that sample and control firms do not differ in the total proceeds raised from these equity issues. This is inconsistent with Hypothesis 1. Overall, equity issues provide mixed evidence with respect to Hypothesis 1. 3.3. Changes in asset transactions We find interesting patterns in the level of asset sales and purchases initiated by sample and control firms around their event year. While sample firms had a 51% increase (from 332 deals to 502 deals) in the number of asset transactions from two years before to two years after they move to the NYSE, control firms showed only a 26% increase (from 283 deals to 358 deals) over the same time period (see Table 5). As mentioned before, most of these deals involve asset purchases for both sample and control firms. The number of asset purchases increased by 47% (from 288 deals to 423 deals) for sample firms, but only by 18% (from 257 deals to 303 deals) for control firms, over the four-year period straddling the firm’s event year. The increase in asset transactions following the move to the NYSE for a sample firm, be it an average firm or a median firm, is significantly greater than the increase for its corresponding control firm. The coefficient of sample dummy is positive and significant in an OLS regression (see Table 8). As a majority of asset transactions involve a purchase rather than a sale, we examine the results for transactions that involve purchases and find that results are stronger. Firms that move to the NYSE are significantly more likely to increase asset transactions especially acquisitions, in comparison to control firms as discussed in Hypothesis 2. High growth rates in firms and firm size appear to weakly enhance and diminish asset transactions, respectively, though their coefficients remain statistically insignificant. Firms with higher pre-listing analyst coverage are likely to increase their asset transactions over time while institutional ownership has a smaller and mixed effect on the incidence of such transactions. In short, we find significant evidence that sample firms have more equity issues, debt issues and asset transactions in the years after moving to NYSE relative to control firms. However, a firm that chooses not to issue debt or equity in the years after moving to NYSE may choose to engage in increased asset transaction and vice versa. We therefore examine all transactions together to examine if firms that move to NYSE have greater number of corporate transactions—irrespective of its nature. As seen in Table 9, we find strong evidence that sample firms that move to NYSE significantly increase the total number of corporate transactions. The results are robust to controlling for firm characteristics, ownership structure and prior analyst coverage. In summary, we find significant differences between sample and control firms in the changes in corporate transactions surrounding the event year. Though sample firms access the debt, equity and asset markets more in the years after moving the most compelling evidence is in looking at the whole picture, i.e., all corporate transactions. Sample firms engage in greater corporate transactions, of all kinds, in the two years after moving than the control group. Our evidence on corporate transactions presents a contrast between firms that move to the NYSE and firms that chose to remain in Nasdaq, suggesting that

124

Panel A: number of asset transactions

Constant Sample dummy Cash Age Leverage Log of total assets Market-to-book Number of analysts % by institutions # of institutions R Square Observations

Panel B: number of asset transactions when firm was an acquirer

Model 1

Model 2

Model 3

Model 4

Model 1

Model 2

Model 3

Model 4

0.316** (1.97) 0.401* (1.77)

1.176 (1.59) 0.46* (1.94) 0.002** (2.41) 0.002 (0.14) 0.864 (1.25) 0.173 (1.13) 0.028 (1.17)

0.259 (0.75) 0.44* (1.7)

1.402 (1.48) 0.49* (1.84) 0.002 (1.47) 0.022 (1.13) 0.579 (0.68) 0.38* (1.78) 0.027 (1.06) 0.075** (1.97) 0.592 (0.73) 0.004 (0.49) 0.048 389

0.194 (1.3) 0.376* (1.77)

1.31* (1.89) 0.424* (1.93) 0.002** (2.49) 0.004 (0.26) 0.984 (1.53) 0.220 (1.55) 0.018 (0.82)

0.165 (0.51) 0.427* (1.79)

1.51* (1.72) 0.484** (1.97) 0.002* (1.78) 0.026 (1.41) 0.999 (1.25) 0.37* (1.84) 0.018 (0.76) 0.052 (1.46) 0.234 (0.31) 0.003 (0.49) 0.051 389

0.007 474

0.029 455

0.082** (2.27) 0.242 (0.33) 0.002 (0.52) 0.027 401

0.007 474

0.033 455

0.056 (1.66) 0.198 (0.29) 0.000 (0.08) 0.020 401

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Table 8 Cross-sectional regressions of changes in asset market transactions. This table presents results of cross-sectional regressions of the change in asset market transactions in the two years after the move to the NYSE over the two years before the move. The dependent variable for Panel A is the change in the number of asset transactions and for Panel B the change in the number of asset transactions when the firm was an acquirer. Age is the number of years since the firm first appeared on CRSP at the time of moving. Leverage is the ratio of long-term debt to total assets. Cash is the cash balance in the year prior to moving and market-to-book is the ratio of market-to-book value of equity. Number of analysts, number of institutional owners and the percentage owned by institutions is measured one year prior to the move. Absolute value of t-statistics are in parenthesis. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively.

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Table 9 Cross-sectional regressions of changes in all corporate transactions. This table presents results of cross-sectional regressions of the change in all corporate transactions in the two years after the move to the NYSE over the two years before the move. Corporate transactions include number of debt issues, equity issues and asset market transactions. Sample dummy takes the value one for firms that move to NYSE and num of prior transactions is the number of corporate transactions in the two years prior to moving. Age is the number of years since the firm first appeared on CRSP at the time of moving. Leverage is the ratio of long-term debt to total assets. Cash is the cash balance in the year prior to moving and market-to-book is the ratio of market-to-book value of equity. Number of analysts, number of institutional owners and the percentage owned by institutions is measured one year prior to the move. Absolute value of t-statistics are in parenthesis. The asterisk superscripts, *,**,***, represent statistical significance at the 10%, 5%, and 1% level respectively. Number of all corporate transactions

Constant Sample dummy Num. of prior transactions Cash Age Leverage Log of total assets Market-to-book Number of analysts % by institutions # of institutions R Square Observations

Model 1

Model 2

Model 3

0.038 (0.20) 0.39 (1.46)

0.793*** (4.47) 0.1358 (0.17) 0.2119 (0.60) 0.098 (0.10) 0.615*** (2.63) 0.676*** (2.78) 0.726*** (2.76) 0.72*** (2.64) 0.46*** (11) 0.48*** (11) 0.49*** (11) 0.48*** (10.29) 0.0016 0.0093 0.7158 0.2070 0.0017

0.0045 474

0.2297 474

0.2427 455

Model 4

(1.54) (0.53) (1.01) (1.25) (0.07) 0.048 (1.29) 1.196 (1.61) 0.0041 (0.81) 0.2651 401

Model 5

0.0007 0.0034 0.0508 0.0673 0.0036 0.0437 1.3382 0.0029 0.2630 389

(0.51) (0.16) (0.06) (0.30) (0.13) (1.10) (1.61) (0.37)

the decision to move is often nested among broader corporate objectives, a fact that has been largely ignored in the previous literature. 4. Conclusion Though several Nasdaq firms are eligible to list at the NYSE only few firms choose to do so. This is surprising given well-documented benefits that Nasdaq firms derive from a NYSE listing. Further firms that move to the NYSE wait for a few years after they become eligible. In this paper, we present evidence that suggests that involvement in capital raising and acquisition activities may determine whether and when Nasdaq firms decide to move to the NYSE. We study firms that moved from Nasdaq to the NYSE between 1986 and 1998 and a size and industry matched control group of Nasdaq firm that were eligible to list at the NYSE but chose not to move. We find that firms that move to the NYSE raised more capital through issue of debt and equity and were involved in more acquisitions than their control peers even while they were trading in Nasdaq. The increased propensity for corporate transactions after the move to the NYSE suggests that the decision to list and when to list is often taken in conjunction with these other corporate activities. By bringing to light the nesting of the listing decision among broader corporate objectives, a fact that has been

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largely ignored in the previous literature, our results provide a new perspective to why only some Nasdaq firms switch to the NYSE. Acknowledgement We thank an anonymous referee and the editor Avanidhar Subrahmanyam for helpful comments. All errors are ours. References Aggarwal R., Angel J., 1997. Optimal listing policy: why Microsoft and Intel do not list on the NYSE. Georgetown University Working Paper. Amihud, Y., Mendelson, H., 1986. Asset pricing and the bid-ask spread. Journal of Financial Economics 17, 223–249. Amihud, Y., Mendelson, H., 1988. Liquidity and asset prices: financial market implications. Financial Management 17, 5–15. Arbel, A., Strebel, P., 1982. The neglected and small firm effects. The Financial Review 17, 201–218. Baker, H., Johnson, A., 1990. Survey of management’s view on exchange listing. Quarterly Journal of Business and Economics 29, 3–20. Baker, H., Powell, G., Weaver, D., 1999a. Listing changes and visibility gains. Quarterly Journal of Business and Economics 38 (1), 46–63. Baker, H., Powell, G., Weaver, D., 1999b. Does NYSE listing affect firm visibility. Financial Management 28 (2), 46–54. Barry, C., Brown, S., 1986. Limited information as a source of risk. Journal of Portfolio Management 12, 66–72. Bhardwaj, R., Brooks, L., 1992. Stock price and degree of neglect as determinants of stock returns. Journal of Financial Research 15, 101–112. Christie, W., Huang, R., 1993. Market structures and liquidity: a transactions data study of exchange listings. Journal of Financial Intermediation 3, 300–326. Christie, W., Schultz, P., 1994. Why do Nasdaq market makers avoid odd-eighth quotes? Journal of Finance 49, 1813–1840. Cowan, A., Carter, R., Dark, F., Singh, A., 1992. Explaining the NYSE listing choices of Nasdaq firms. Financial Management 21, 73–86. Dharan, B., Ikenberry, D., 1995. The long run drift of post-listing stock returns. Journal of Finance 50, 1547–1574. Goyal, V., Lehn, K., Racic, S., 2004. Growth opportunities and corporate debt policy. Journal of Financial Economics 64, 35–59. Jacquier, E., Titman, S., Yalcin, A., 2001. Growth opportunities and assets in place. Boston University Working Paper. Kadlec, B., McConnell, J., 1994. The effect of market segmentation and market illiquidity on asset prices: evidence from exchange listing. Journal of Finance 49, 611–636. McConnell, J., Sanger, G., 1987. The puzzle in post-listing common stock returns. Journal of Finance 42, 119–140. Merton, R., 1987. Presidential address: a simple model of capital market equilibrium with incomplete information. Journal of Finance 42, 799–813. Reinganum, M., 1990. Market microstructure and asset pricing: an empirical investigation of NYSE and Nasdaq securities. Journal of Financial Economics 28, 127–148.