Political Money Contributions of US IPOs

Dimitrios Gounopoulos1, Konstantinos Kallias

December 2013

Abstract

We produce the first study to explore the effect of political donations on IPO

performance. Employing a large and comprehensive sample of US IPO deals, we provide

evidence that monetary contributions to politics pay off on the floatation day by means of

significantly less underpricing. With much of the literature attributing to the merits stemming

from ‘political connections’ a contingent character, our research shows how a lister can reap

immediate and measurable benefits by signaling access to Congress. Given the contribution

alternatives, political donations may fulfill their role as a signaling mechanism upon a carefully

crafted strategy, only. This necessitates spending on both lobbying and PAC campaigns and

further caution for PAC recipients’ affiliation. In devising the optimal spending pattern, we find

that the effect on IPO return is maximized by targeting candidates identifying with the

Republican Party, representing the firm’s State and exhibiting the greatest geographic

dispersion in case of non-local candidacies. Notably, we register no incremental effect for

Congress Chamber affiliation.

Keywords: Initial public offering; IPO underpricing; Political connections

JEL classification: G10, G14, G39.

Dimitrios Gounopoulos is from School of Business, Management and Economics, University of Sussex; Kostadinos

Kallias School of Business, Management and Economics, University of Sussex;

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Introduction

In the last week of October 2013, with barely 15 days remaining to the planned IPO,

Twitter Inc was intensifying effort to finalize a price range for its offering. Interestingly, the

firm chose this busy week to file its first lobbying report. The issues lobbied for comprise a

long agenda, mainly, pertaining to consumer matters, foreign relations, technology and

copyright. This lobbying investment came complementary to Twitter’s newly formed federal

political action committee (‘Twitter#PAC’) in a timely and coordinated effort to reach

Washington just before the company’s equity reaches the New York Stock Exchange.

Twitter, hardly pioneered the practice of political money spending in light of an imminent

IPO. The rival social media network, Facebook, also established its own political action

committee in the year preceding its IPO and, within a similar time frame, Google began

contributing to lobbying.

While the list of prospective issuers with a record of political money contributions

(PMC) goes on, the corporate finance literature has yet to draw the line to IPO performance.

Considering the numerous studies advocating the information flow, or signaling, in favor of

the least informed party in an IPO sale (e.g. Beatty, (1989); Megginson and Weiss, (1991);

Carter et al., (1998); Certo et al., (2003); Chemmanur and Paeglis, (2005) and Francis et al,

(2010)), it is surprising that PMC activity has not been explored as a means of the firm to

communicate access to the highest echelon of Government. The present study explores the

impact of such cash flows on a company’s IPO endeavor by raising questions of broader

public interest. Is the level of a firm’s PMC spending a suitable proxy for ‘political

connectedness’? If yes, do PMC mitigate uncertainty low enough for investors to require

significantly lower premia for their capital? Further, how do the two main PMC types,

namely lobbying and PACs, compare in terms of their signaling value and overall effect on

the IPO process? Finally, which groups of recipients should PMC firms be targeting at in

terms of political party (i.e. Democrats or Republicans), House (i.e. Representatives or

Senators) and US State affiliations? After all, is there such a thing as an ‘ideal’ PMC

strategy?

In an important departure from prior studies that focus on the potential benefits

accruing to public firms maintaining connections with prominent political figures (see, e.g.,

Cooper et al., 2010; Ramanna and Roychowdhury, 2010; Yu and Yu, 2010 and Chaney et al.,

2011), we investigate new issuers’ possibility to mitigate some of the uncertainty burden in

the going public process by means of political donations. We conjecture that contributions to

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lobbying and PAC campaigns, within a reasonably short period before the floatation day,

constitute a time-and-cost effective way to signal firm’s ‘political connectedness’, even as a

work in progress. Being both traceable and publicly available, a record of PMC activity can

be plausibly associated with access to the upmost decision-making bodies. As a consequence,

IPO investors confide in the firm’s ability to maneuver with less friction in the institutional

environment and require smaller premia for purchasing its equity. This means that the listing

firm can hit the ground running as a public company, having left as little money on the table

as possible during its IPO day.

To test our conjecture, we assemble a large and comprehensive sample of US IPO

deals spanning the period 1 January, 1998 to 30 June, 2013. We manually investigate each

firm in the archives of the US Federal Election Commission (FEC) for evidence of PMC

activity within a period of 5 years prior to the listing date2. This way, we come up with our

special sample of interest, PMC firms. Comparing PMC firms’ mean underpricing of 19%

with the rest of the firms’ mean underpricing of 29%, we obtain strong preliminary evidence

for our hypothesized effect of political donation on IPO returns. Most importantly, assessing

the fundamentals of PMC firms, we find these issuers to be associated with superior quality

as proxied by market share, profitability, leverage, and years of operational experience. It

becomes, thus, apparent that PMC firms rather than seeking a life jacket in politics, they are

involved in order to manage, promptly, for the legal and institutional environment risks lying

ahead.

Our empirical findings show that this strategy becomes discernible by market

investors and pays off on the IPO day. Regressing underpricing on the level of PMC activity,

we confirm the inverse relation; lobbying money, PAC contributions and any combination of

these two PMC routes result in leaving significantly less money on the table during the first

day of trade. The evidence from our special PMC firms’ sample is even more compelling.

Having registered the direction of the relation, we conduct further testings in order to identify

the spending manner producing the most constraining effect upon underpricing. Interestingly,

we find that lobbying expenditure alone, without the support of PAC money, will, simply, not

do the job. Firms that realize the least underpricing in the going public process have

employed a mix of lobbying and PAC spending. On these grounds, we conclude that PMC

activity in order to fulfill its role as a signaling mechanism needs to be both sizable and

2 We expect the effect of PMC on IPO performance to be more pronounced with increased time proximity to the IPO day. Approximately, 81% of PMC firms have exhibited their spending within the 12-month period preceding the IPO. In our robustness checks section we also test the validity of our results in this special sub-sample.

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targeted. Lobbying contributions cater for the size factor by being uncapped. PAC

contributions entail the more personalized dimension by entering directly into candidates’

campaign coffers.

In addition, we take advantage of the traceable nature of PAC contributions (as

opposed to lobbying opaqueness) and study the differential effect on IPO return by the

various groups of PAC money recipients. First, we split across party lines and, in consistency

with the popular view surrounding the Republican Party as the ‘pro-business party’, we find

that IPO firms contributing more to Republican campaigns realize the least underpricing.

Second, we draw a distinction between the two Congress Chambers and test for an

incremental Senate effect. The findings, in this case, run contrary to common wisdom which

attaches special prestige to US Senators. PAC contributing firms need not consider a

candidate’s particular electoral race; sponsoring campaigns for the House of Senate does not

signal any different, in the IPO process, than sponsoring campaigns for the House of

Representatives. Third, we show that an effective PAC strategy prioritizes candidates

representing the State of IPO firm’s headquarters, even more so for firms with an extended

operational base in the home State or heavily relying on government contracts. Outside the

local State’s borders, firms attain the lowest IPO return with contributions to candidates

exhibiting the largest geographical dispersion in terms of the US States they represent.

To further corroborate our findings on the information revelation role of political

donations, we visit the book-building period. Following both the magnitude and the direction

of filing price revisions, we explore how a PMC record weighs in the derivation of the

offering price. According to the information production theory (as in Benveniste and Spindt,

1989 and Hanley, 1993) a greater deal of positive information disclosed by informed

investors triggers more upward revisions. Intuitively, it follows that a publicly available

record of PMC activity levels the informational playing field and mitigates the need for

extracting costly private information. We, therefore, conjecture that apart from first-day

market return, PMC spending also constrains the extent of upward filing price revisions.

Indeed, running a battery of regression tests, we confirm the negative association of PMC

level to underwriter’s revisions. Political donations, thus, are not only associated with

market-based returns but also constitute an input in the IPO valuation process per se.

To test the validity of our results we employ a series of robustness checks. First, we

validate our proposed effect of PMC on underpricing by rerunning all tests excluding the

firms with PMC activity dating older than 12 months from the IPO time. Second, we

substitute dollar value with number of actual recipients for all of our PAC contribution

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variables. Registering a similar constraining effect on IPO returns, we confirm that political

donations are a suitable proxy for ‘political connectedness’, i.e. the market weighs more

proximity to people, with the precise dollar magnitude of contributions being of lesser

importance. Third, we test and confirm our no endogeneity assumption.

This study makes important contributions to IPO and corporate finance literature

while addressing concerns of broader public interest such as the symbiotic relation between

the corporate world and politics. First, we illustrate that a firm’s political donations,

commonly associated with uncertain and indirect benefits, generate an immediate and

measurable gain in the special context of an IPO. No matter the precise dollar magnitude,

such contributions have a profound effect on mitigating issuer-specific uncertainty; for

market investors are shown to factor in a firm’s Washington strategy and consent to provide

their capital at a lower return. Second, we contrast lobbying and PAC spending, as the two

main PMC types, and disentangle their effect on IPO performance. Highlighting special

strengths and weaknesses for each strategy, we make a case about their complementary

nature towards an effective signaling mechanism. Third, differentiating among PAC money

recipients by Congress Chamber, political party and US State affiliation, we devise an

optimal target group for the most constraining effect upon underpricing. The implications for

prospective listers are unambiguous; a dollar spent on PMC activity, in the pre-IPO period,

saves many more on the actual listing day. Sure enough, uncertainty-driven underpricing can

be fought with alternative tools; most commonly, marketing campaigns. In that case,

however, the advantage of PMC practicing would be twofold as: (1) it entails a dramatically

lower investment; and (2) any likely benefits are expected to accrue over long past the IPO.

Our study relates to the works of Beatty (1989), Megginson and Weiss (1991), Carter

et al., (1998), Certo (2003), Faccio (2006), An and Chan (2008), Francis et al. (2009), Cooper

et al. (2010), Ramanna and Roychowdhury (2010), and Yu and Yu (2010). A focal point in

the IPO literature has been issuers’ effort to overcome what Certo (2003) calls “the market

newness liability”, i.e. the perceived uncertainty surrounding their future prospects. The

relevant studies confirm that firms, exhibiting notable resourcefulness, employ a plethora of

means in order to signal quality. In a non-exhaustive list of such works, issuers claim prestige

for themselves by: (1) hiring reputable auditors (Beatty, 1989), (2) inviting VCs with a

proven record of successful IPOs (Megginson and Weiss, 1991), (3) employing top-notch

underwriters (Carter et al., 1998), (4) infusing the management team with prestigious

executives (Certo, 2003), and (5) seeking a credit rating (An and Chan, 2008). Expanding

further this literature, we produce the fist study to relate political donations to IPO

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performance and we propose PMC activity as an alternative signaling mechanism. Another

strand of literature stemming from the interplay of politics with business (Faccio, 2006;

Cooper et al., 2010; Ramanna and Roychowdhury, 2010 and Yu and Yu, 2010), draws

evidence from firms with several years of experience as public corporations that have,

similarly, built their connections over a large time span. Our study, instead, advocates firm’s

possibility to promulgate such connections in the pre-IPO period, so that it cashes in the

benefits as early as its first day of trade.

The rest of the paper has the following structure. Section I discusses the relevant

literature. Section II develops our hypotheses. Section III provides insight of the alternative

PMC types and describes our sample. Section IV examines the effect of PMC activity on the

going public process. We test the robustness of our results in Section V. Finally, Section VI

concludes the paper.

I. Related Literature

A. Theoretical Framework

The price discovery for new equity offerings is an inherently uncertain process. The

relevant literature invariably quantifies uncertainty magnitude by means of the listing day

market performance. Since the seminal works of Stoll and Curley (1970), Logue (1973) and

Ibbotson (1975) have revealed a definite pattern of abnormal positive returns, a plethora of

theories attempt to explain the conundrum of IPO first-day return, or underpricing.

Information asymmetries between the various parties involved in the IPO process serve as a

focal point for most explanations offered. Thus, Rock (1986) and Beatty and Ritter (1986)

suggest that in light of a de facto informational disadvantage, risk averse investors are

inclined to push for a discount price. At the same time, effective book building requires

unbiased feedback from engaged investors and, if available, private information; this critical

input to IPO pricing comes at a cost, to account for which, underwriters need to mark the

offer price downwards (see Benveniste and Spindt, (1989); Benveniste and Wilhelm, (1990),

and Spatt and Srivastava, (1991)).

Another strand of literature, also stemming from the asymmetric information

framework, assigns value to underpricing and conjectures that issuers may proactively allow

for it. Far from the market friction view, Welch (1992), Habib and Ljungqvist (2001) and

Demers and Lewellen (2003) consider a low offer price, under conditions, as a cost-effective

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marketing tool which will attract investors and, ultimately, recoup any money left on the table

during the IPO day. Chemmanur (1993) adds increased analyst coverage to the merits of a

high initial return while a number of studies assessing the legal implications for IPO issuers,

highlight the lawsuit deterrence effect of a strong first-day close (Hughes and Thakor (1992),

Drake and Vetsuypens (1993), Lowry and Shu, (2002)).

Lastly, Loughran and Ritter (2002), making a notable turn from signaling to prospect

theory, describe underpricing as a rather harmless vice suggesting that the initial investors,

already being in a prosperous state by the amassment of IPO proceeds, rarely reckon the

marginal prosperity they forego leaving money on the table. Yet, it is Jay Ritter, in his

website, to estimate the global cost of IPO underpricing at $135.12 billion, over the period

1998-2012, and, thus, it is the mere magnitude of this amount to foster skepticism against any

behavioral explanations assigning a lesser importance to efficient pricing.

B. Political Connections as a Value Adding Strategy

The value adding component of corporate political connections is explored in

literature via two main routes; that is either tracing company insiders’ interpersonal

relationships or applying a ‘follow-the-money’ approach focusing on cash flows directed

form corporate pockets to politics.

Within an international or cross-country context, poor data availability or deliberately

opaque interrelations between corporate world and local governments typically leave no

option but to directly investigate the individual profiles of corporate officials; in which cases,

companies derive their connections through directors either actively engaging in politics or

being closely related to others who do. Faccio (2006) applies this methodology in a

comparative study of 47 countries and finds that connected firms are able to sustain larger

market shares while this benefit may not necessarily be reflected on the company’s bottom

line (also Boubakri et al. (2008)). The study also observes that connected firms afford to

operate with significantly more leveraged capital structures as they enjoy preferential access

to debt financing (e.g. by lenient debt covenants), even though, there is no evidence of

incurring a smaller interest expense than their peers. Chaney et al. (2011) assessing the

reporting quality of more than 4,500 firms in 19 countries reach the conclusion that

politically connected firms are not penalized for consistently delivering subpar output.

Apparently, in light of political reach, accounting data shrinks in value relevance.

Tracing political connections in the US at the director’s level similar to the above

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studies would likely produce less enlightening results. In the Faccio (2006) database out of a

total of 6,007 US firms examined, merely 13 firms qualify to be classified as politically

connected. US-centering literature circumvents this research limitation by expanding the

concept of political connectedness in order to encompass corporate expenditure for political

purposes (overwhelmingly coming in the form of lobbying or PAC contributions). Within

this methodological framework, Chen et al. (2010) and Cooper et al. (2010) set out from

different starting points, lobbying spending and PAC contributions, respectively, to meet into

the same conclusion; political money spending firms enjoy, robustly, superior financial and

accounting returns. Besides performance, political money expenditure has been documented

to facilitate more questionable ends. Indicatively, Correia (2012) finds that political money

contributions lower the probability of an SEC enforcement action and even if the firm is

subjected to one the financial penalty is expected to be considerably moderate. Yu and Yu

(2010) take this argument one step further and stress the immunity to fraud that lobbying may

provide “firms that lobby on average have a significantly lower hazard rate of being detected

for fraud, evade fraud detection 117 days longer, and are 38% less likely to be detected by

regulators”.

C. Political Connections in the Going-Public Process

Recent evidence from China shows that political connections can play a decisive role

towards a successful IPO. For example, Fan et al. (2007), focusing on the (partial)

privatizations of firms with CEOs incumbent or past government officials, record

significantly less underpricing during the floatation day. Corroborating this research, Francis

et al. (2009) discuss on the threefold benefit that a strong association with the government

entails by supporting premium valuations, imposing discipline on first-day returns and

reducing issuance costs all the way. Yet, the distinct character of the Chinese economy

cripples the robustness of these findings in a cross-country framework. Resorting to the

international privatization literature, the studies of Jenkinson and Mayer (1988) and Perroti

and Guney (1993) find that state-owned enterprises (SOEs) induce greater underpricing than

the average private company issuer; a conjecture that is challenged in Dewenter and

Malatesta (1997). Even so, any links to be drawn from SOEs to the typical corporate issuer

remain, at best, dubious, as the ex ante uncertainty that investors face is fundamentally

different when the state is a counterparty.

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Within a US context, Colak et al. (2013) explore the upset factor that gubernatorial

elections impose upon equity issuance activity. In a state (than federal) level, they find the

12-month period preceding gubernatorial elections to attract weak IPO activity by local

issuers. The brave few, systematically, undergo a downward mean revision of their offering

price as the political uncertainty casts its shadow on the book-building process. The

reservation sentiment extends equally to the floatation day and moderate investors’ demand

allow for moderate returns, only. The present study, takes this research one step further by

exploring a framework in which prospective issuers are not simply carried away by political

uncertainty but plan well before the IPO time and proactively establish links to politics via

monetary contributions. Within this context, we conjecture that elections need not be an

external shock but a window of opportunity for prospective issuers to invest in political

reach; and, even though, the actual benefits of these contributions can be vague, in nature,

and accrue over many fiscal periods post-issuance, their transparent and easily-traceable

character can signal to market investors the company’s ability to maneuver smoothly within

the institutional environment.

II. Hypotheses Development

Since the seminal work of Spence (1973) made a case about the incremental value of

signals in mitigating labor market frictions, the corporate finance literature resorts extensively

to signaling theory in order to explain firm’s behavior in light of informational asymmetries.

On these grounds, high quality firms have been claimed to communicate above par financial

standing by means of a leveraged capital structure (Ross, (1977)), or dividend issuance

(Bhattacharrya, (Bhattacharya 1979)). In either case, the signal is both readily identifiable

and costly to imitate, fulfilling, also, Certo’s (2003) two basic requirements pertaining to an

efficient signal. The going public process generates inherent informational disparities and,

thus, a unique testing environment for signaling practices. Carter et al., (1998) contend that

IPO firms hire prestigious underwriters with the implicit purpose of gaining in prestige

themselves. For the same purpose, issuers favor reputable auditors (Beatty, (1989)) or try to

affiliate with established venture capital firms (Megginson & Weiss, (1991)).

The long list of signaling mechanisms employed by IPO firms goes on in the

literature, yet, the firm’s own political activity is, surprisingly, excluded from it. Addressing

this gap, our study holds that a firm’s political footprint, evidenced by political money

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contributions in the pre-IPO period, should, similarly, alleviate ex ante uncertainty by giving

up proximity, if not influence, to legislative and other key decision-making bodies.

Consistent with Ritter and Welch ((2002)) stating that “all theories of underpricing based on

asymmetric information share the prediction that underpricing is positively related to the

degree of asymmetric information”, we contend that a traceable and publicly available record

of PMC activity should also limit first day returns.

H.1. Underpricing is negatively related to the aggregate dollar level of contributions made to politics

by IPO firms.

Considering the alternative routes available to reach political coffers, we expect PAC

spending to exert direct influence on IPO performance due its personalized nature (also

registered in Durden et al., 1991; Stratmann 1991, 1995, 1998 and Kroszner and Stratmann,

1998). On the other hand lobbying, by being uncapped, comes in multiples of a typical PAC

contribution (see also Descriptive Statistics). As such, it entails the most substantial cash

flows made by corporations to the Congress Chambers. We conjecture that PMC, in order to

constitute an effective signaling mechanism, necessitate contributions that are both sizable

and strategically targeted. Therefore, a blend of lobbying and PAC money is required for both

leveraging the strengths of each contribution type and signaling ‘political connectedness’ in

the most unambiguous manner.

H.2. The least underpriced IPOs are more likely to have engaged in both lobbying and PAC

contributions in the pre-IPO period.

If lobbying and PAC contributions are complementary PMC types, the firm has to

devise an efficient portfolio of PAC recipient candidates. Considering the cash-constrained

environment in which a typical pre-IPO firm operates, the candidates’ targeting in terms of

House, political party, and US State affiliation merits further study.

The Senate is commonly surrounded with greater prestige than the House of

Representatives. Two plausible reasons can be Senate’s filibuster prerogative (the right to

delay or postpone a proposal by extending debate indefinitely) as well as its right “to advice

and consent” to major presidential appointments (U.S. Const. Art. II, sec. 2). Yet, the

majority of studies simply point to the size differential between the 100 Senatorial seats and

the 435 (voting) seats available in the House of Representatives in order to make a case about

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the Senate’s prevalence (e.g. Grier et al., 1990 and Grier and Munger, 1993). Given the

above, we expect additional prestige accruing to firms contributing more generously to

Senate candidates. In turn, the merits of being associated with the more privileged Congress

Chamber should be apparent on the IPO day.

H.3.a. Underpricing decreases with larger PAC contributions to Senate rather than House

candidates.

Disentangling the effect of PAC contributions across political party lines is a more

complex task. The relevant studies highlight firms’ strategy to target incumbents, irrespective

of party affiliation, converging to the conclusion that firms spend for ensuring access rather

than influencing the elections outcome or other ideological reasons (Stigler, 1971; Grossman

and Helpman, 1994 and Milyo et al., 2000). Thus, Lowery and Brasher (2004: 133) explain

that “most of the economic sectors do not put all of their eggs in one partisan basket. They

give to both parties; or, more specifically they give to incumbents, which means that they

give to both parties”. Given the corporate donors’ indifference, literature has turned its

attention to the partisan orientation weighing, potentially, more favorably in the US markets.

For instance, some early evidence from Niederhoffer et al. (1970) and Riley and Luksetich

(1980) associates a bullish market with the aftermath of Republican victories. At the firm

level, however, the evidence is mixed. Goldman et al. (2009) tracing corporate political

contributions from the 2000 election cycle refute altogether an association of the elections

outcome with firm’s post-election market returns. On the contrary, Shon (2010), using

evidence from the turbulent period of the 2000 Florida recount, evidences significant relation

between campaign donations and stock performance. With a much broader time window,

Cooper et al. (2010) conclude that PAC contributions have a strong positive relation with

both market and accounting measures of performance, documenting an incremental

contribution effect for Democrats. Overall, considering the puzzling empirical findings, we

hypothesize that a recipient candidate’s partisan camp is associated with special signaling

value in the IPO process. However, contrary to the popular view, Republicans may not be,

necessarily, perceived by the market investors as the definite ’pro-business’ party.

H.3.b. Underpricing is associated with larger PAC contributions to Republican rather than Democrat

candidates

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Faccio and Parsley (2009), in a provocative manner of pinpointing the interdependent

relations between firms and local politicians, register the decrease in value for firms

headquartered in a politician’s home town upon the announcement of her unexpected death.

Within a US context, Roberts (1990) had already witnessed a similar effect for Washington-

located firms subsequently to Senator’s Henry" Scoop" Jackson death in September of 1983.

Cooper et al. (2010) confirm the positive impact of PAC money on firm’s performance with a

larger number of candidates representing the donor’s state. The literature, thus, accords with

the intuitive appealing hypothesis for a symbiotic relation between the local pillars of power.

Government contracts, labor union politics and state-level authorities, for instance,

necessitate interventions from same state politicians, not less than the latter ones require

corporate contributions in order to come into office in the first place. We therefore,

conjecture that candidates representing the state of the IPO firm should rank high in the PAC

recipients list, especially for firms maintaining an extended operational base in the

headquarters’ state.

H.3.c. Underpricing decreases with larger PAC contributions to candidates from the state of firm’s

headquarters.

Underpricing is the dominant surrogate for investor demand in IPO literature but need

not be the only proxy. Price revisions in the book-building process (i.e. the percentage

difference of the offering price from the midpoint of the initial filing range) capture

underwriter’s effort to gauge relevant feedback from informed investors. Information

revelation, however, comes at a cost. As per Cornelli and Goldreich (2001, 2003) and

Aggarwal et al. (2002), underwriters compensate positive news about a firm’s prospects by

means of the allocation of under-priced shares. Alternatively, investors lack any incentive to

disclose their private information. Thus, the information production theory (as introduced by

Benveniste and Spindt, 1989 and confirmed by Hanley, 1993) predicts that the extent of price

revisions increases in proportion with informational asymmetries. On these grounds, we pose

that a publicly available record of PMC activity, levels the informational playing field and

mitigates the need for extracting costly private information. Ceteris paribus, PMC activity

should inversely relate to filing price revisions.

H.4.Filimg price revisions are negatively associated with the aggregate dollar level of contributions

made to politics by IPO firms.

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III. Data and Sample

A. Sample Selection Criteria

To assemble our sample we retrieve information from the Securities Data Company

(SDC) covering the entire population of IPOs that have been floated on US exchanges for the

period 1 January, 1998 to 30 June, 2013. Consistent with prior literature (e.g. Loughran and

Ritter, 2002) , we eliminate those IPOs priced less than $5 per share, limited partnerships,

reverse LBOs, ADRs, and foreign issuers whose shares may be already trading in local

markets. In addition, even though we allow for financial firms, we exercise caution not to

include closed-end funds, REITs, royalty trusts and special purpose investment vehicles. To

this end, we do not consider firms with SIC codes between 6723 and 6999 as well as

companies which even though bypass Thomson Reuters filters for closed-end funds, they still

operate as such. At last, we restrict corporate spin-offs; these firms have typically been parts

of large, mature businesses and, thus, entail considerably less uncertainty than the average

issuer. The remaining sample is merged with the databases of Compustat and the Center for

Research in Security Prices (CRSP) from which we obtain IPO firms’ accounting

fundamentals and aftermarket performance, respectively. With these interventions, we end up

with a final sample of 1,578 unique IPO deals.

We investigate political money spent by IPO firms within a time frame of up to five

years before the IPO date by means of lobbying expenditure and / or PAC contributions. This

methodology generates our special sample of interest of 273 IPO companies with PMC.

Lobbying expenditure data comes from the files of Center for Responsive Politics

(CRP). CRP derives information directly from the semi-annual lobbying disclosure reports

filed with the Secretary of the Senate’s office of Public Records (SORP) and initiates

coverage of corporate lobbying in the year of 1998 (inclusively). Matching the IPO deals

with the CRP database, we are able to identify 244 IPO firms that have reportedly engaged in

lobbying.

We utilize as a source for PAC contributions data the Federal Election Commission

(FEC) electronic archive. To make the most out of the enhanced transparency that PAC

money offers compared to lobbying expenditure we manually search for each IPO firm

within the “Candidate Master” and “Contributions to Candidates from Committees” files so

that we capture, besides the PAC timing, the detailed profiles of the cash flow recipients

(party affiliation, house membership, state of origin etc). Our search yields 89 IPO firms that

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have contributed to PACs.

Notably, the discernible pattern for both lobbying and PAC spender firms is towards

multiple election cycle contributions. More often than not, once firms have contributed any

form of political money, they tend to repeat their contributions in the election cycles to

follow, with significant consistency as to the contribution type and magnitude. Thus, out of

the 244 lobbying IPO firms, 184 firms have engaged in multiple lobbying activity while

almost the totality of PAC IPO firms (81out of 89) have supported candidacies in prior

period(s).

B. The Two Alternate Routes to PMC: Lobbying & PAC

Lobbying and PAC contributions comprise the two main avenues available for US

corporations to reach to the Congress chambers. The decision to engage in either of the above

activities is made by a firm’s top-echelon executives.

Lobbying is the prevalent means in terms of both frequency and dollar magnitude of

contributions by which US companies interfere in the making of politics (de Figueiredo and

Richter, 2014). A dollar spent in lobbying aims to advocate firm’s perspective about the

institutional framework it operates. As such, lobby expenditure, rather than being directed at

specific politicians, pertains to the essence of the policy making process per se. The fact that

lobbying money does not enter candidates’ campaign coffers, makes lobbying a blurred

proxy for ‘political connections’ traceable down to the individual level. For instance, the

disclosure document acknowledging a lobbying contribution briefly mentions that the firm

lobbied the “U.S. House of Representatives” or the “U.S. Senate.” Yet, the contribution

amount (publicly disclosed under the Lobbying Disclosure Act of 1995) evidences the level

of firm’s political involvement.

PACs (political action committees) with the explicit purpose of supporting or fighting

against a candidate’s political campaign are commonly set up by firms within election cycle

periods. The firm is eligible to provide for the PAC’s operating expenses but may not engage

in additional financial support. For this purpose, the firm invites solicits key stakeholders

(management, employees, and stockholders) to contribute. Most U.S. studies look at PAC

contributions as a proxy for political connections (see Milyo et al., 2000 for an overview of

these studies).

15

C. Descriptive statistics & sample identification

Table 1 provides a preliminary description of our full sample (N=1,578) of companies

as well as the subsample (N=273) of politically connected firms. The period 1 January, 1998

to 30 June, 2013 spans 8 elections cycles which we set as time frames for the IPO deals. With

this grouping, we show that the number of PMC firms need not fluctuate in proportion with

overall IPO activity. For example, 2004-2005 was the election cycle with the most PMC

firms (60) but the total IPOs (271) were almost half of the IPOs in the1998-1999 cycle (465).

The latter cycle, coinciding with the bubble period of late 90s’, gave rise to the majority of

IPOs (29.47% of our full sample), but, notably, the number of PMC firms (30), from that

period, equals the number registered in the most recent election cycle of 2012 - 30 June,

2013. There is, thus, evidence that the numbers of issuers contributing money to politicians

close to the IPO time is on the rise.

Breaking down further by the Standard Industrial Classification (SIC) code we find

most PMC firms (34.8%) to fall within the manufacturing division followed by the service

division (26.74%) and finance, insurance and real estate division (15.02%). These findings

appear plausible in light of the heavy regulatory frameworks accompanying a lot of industries

within the above divisions (see Appendix A). On the contrary, divisions experiencing

minimal regulations are more frugal towards PMC activity (e.g. wholesale and retail trade

division accounting for a mere 5.49% of total PMC firms). Intuitively, then, firms most

directly affected by legislation are inclined to make payments towards the legislators more

frequently.

This trend also reflects on the third panel of Table 1. PMC firms compared to full

sample are less likely to be associated with Internet or technology, venture capital financing,

and the NASDAQ exchange. Yet, 29.30% of PMC firms come from regulated industries

while the respective percentage for the full sample drops to 21.36%. Lastly, Table 1 assesses

the market value of the two samples in terms of both market capitalization and Tobin’s Q

(taken as market capitalization over the replacement cost of assets). Measured in market

capitalization, PCM firms worth 3 times more ($ 2,441 million) compared to the full sample

mean ($ 835 million). Yet, PCM firms are not overvalued as proven by a lower Tobin’s Q of

2.33 compared to the full sample Tobin’s Q of 2.87.

Table 2 provides basic descriptive statistics and mean comparisons between IPOs

with PMC sample (N=273) and IPOs without PMC sample (N=1305) for key variables used

in this study. Panel A offers preliminary evidence in support of our main hypothesis that

16

PMC firms experience less underpricing. In numerical terms, IPOs with PMC are

underpriced, on average, by 19% compared to 29% for IPOs without PMC, and the difference

is significant at the 1% level.

Panel B reports the descriptives for the PMC variables used in this study. The mean

PMC expenditure (measured by aggregating any spending for lobbying and PAC) reached $

300 thousand while the median $ 90 thousand. The implied skewness can also be attributed to

the fact that lobbying contributions are uncapped. The mean lobbying contribution for the

IPOs with PMC sample has been about $ 270 thousand with a median of $ 60 thousand and a

maximum as high as $ 9.57 million that can be traced to General Motors Co and the 2010-

2011 election cycle. The mean PAC contribution for the IPOs with PMC sample at $ 30

thousand seems to be dwarfed by lobbying spending, yet it is important to remember that this

amount ends up directly at candidates’ coffers. In addition, PAC contributions need not be

small. Notably, UPS, in the election cycle 1998-1999, spared on PACs $ 1.53 million. PAC

contributions, as is the case with lobbying contributions, typically tend to be repeated by

PMC firms over multiple election cycles. Interestingly, the correlation of the two different

types of PMC is a modest 0.47 which reveals that lobbying and PAC money do not,

necessarily, come out of the same pockets.

Tracing PACs down to the recipient level, we obtain further insight as to the targets of

these contributions. First, the mean PAC contribution towards the Congress is $ 20 thousand

or double the size of PAC contribution towards the Senate. The same means apply for PAC

contribution towards the Republican ($ 20 thousand) and the Democratic party ($ 10

thousand). In total, PMC firms support PACs for about 12 candidates representing 4 different

US States. As for the spending manner, ‘lobby only’ firms dominate those active in ‘both

lobby and PAC’ and even more so PMC firms exhibiting ‘PAC only’ contributions.

Panel C sheds lights on the individual characteristics of issuers. On a comparative

basis, PMC firms are considerably larger organizations as evidenced by gross proceeds ($

354 million), total assets ($ 4,483 million) and revenues ($ 1,514) which all score multiple

figures compared to the mean values of the IPOs without PMC sample ($ 61 million, $ 301

million, and $ 156 million, respectively). They also deliver superior profitability (proxied by

both return on assets and earnings per share), rely less on leverage, and are less likely to have

resorted to venture capital financing. PMC firms less often come from the Internet or the

broader technology sector and more often from regulated industries. More characteristically,

PMC firms have been longer in business with a mean age close to 25, or ten years more than

the average firm from the IPOs without PMC sample. Interestingly, the credit crunch period

17

of 2007-2009 witnessed more PMC firms than the bubble ‘dot.com’ period of 1998-1999 in

spite of record IPO activity in the latter period.

Tables 3 and 4 take advantage of the enhanced transparency and traceability that PAC

contributions offer providing greater detail on the subsample of PAC contributing firms

(N=89). Sampling as such, the mean PAC contribution per election cycle becomes $ 88,108

with a median of $ 21,000. In terms of candidates, there are, on average, 38 PAC recipients

per election cycle with a median of 12. Republicans attract a mean contribution of $ 54,385

(median $ 15,000) which is to be split among 23 candidates (median 8). Democratic

campaigns come second in PAC spenders’ preferences with a mean of $ 33,380 (median $

6,500) for 15 candidates, on average (median 4). The mean contribution to candidates for

Congress (regardless of party affiliation) is $ 63,538 (median 13,550) for 29 candidates, on

average (median 9). Respectively, the mean contribution to candidates for Senate is $ 24,570

(median 8,000) for 9 candidates, on average (median 4). Once these contributions, however,

are adjusted for the different number of seats available in Congress and Senate, (435 and 100,

respectively), it becomes apparent that Senate attracts both larger and more frequent

contributions.

Table 4 identifies the full activity of PMC firms both chronologically (per election

cycle) and geographically (per state). Over the eight election cycles under study, PMC firms

have channeled $ 73.5 million towards lobbying and $ 7.84 million to PAC, approximating a

1 to 10 dollar spending relation. The number of contributor firms varies each election cycle as

does the level of contributions. In fact, what confirms itself in each election cycle is the

universal nature of PAC contributions across the US territory. It is noteworthy that no US

state was deprived PAC money within the period of our study, even though some of the least

populous states experienced election cycles of zero PAC contributions (e.g. Vermont or

Wyoming). Unsurprisingly, the states targeted more heavily by PAC contributors are those

occupying the largest number of seats in the Congress (as each state is granted exactly two

seats in Senate). Therefore, California, New York, and Texas top the list of recipient states

with the amassment of $ 690.3 thousand, $ 478.3 thousand and $ 440.8 thousand,

respectively, over 1 January, 1998 to 30 June, 2013.

18

IV. Empirical Results A. The effect of PMC on IPO underpricing

Table 5 reports our empirical results explaining underpricing for the full sample of

firms (N=1,578). The dependent variable is the IPO-day return estimated as the percent

difference between the listing day closing price and the offer price. Among the regressors, we

include key variables that have been found in the relevant literature to account for much of

the variability in IPO returns. Specifically, we use:

Pre-IPO assets. A broad asset base offers firms increased visibility as larger

companies, inevitably, leave a bigger footprint within the investor community. Therefore, the

latter one can relate with more clarity to the firm and issuer-specific uncertainty diminishes.

Proceeds raised by the IPO is our alternative proxy for size.

Pre-IPO leverage. We estimate leverage as the ratio of pre-IPO total liabilities to pre-

IPO total assets. A high value of pre-IPO leverage is expected to impose discipline on

management consistent with the mechanisms described in Jensen (1986). Ceteris paribus, we

expect firms relying heavily on debt financing to leave less money on the table.

Pre-IPO ROA (return on assets) is defined as the pre-IPO net income over pre-IPO

assets. We choose ROA as a proxy for profitability. Firms consistently reporting a sizeable

accounting return should be associated with less uncertainty and, thus, lower first-day returns.

At the same time, the profitability, in the pre-IPO period, comes second to presenting a

convincing vision for sustainable profitability in the post-IPO period. At the extreme,

Trueman et al. (2000) find that, in the case of internet stocks, non-financial measures of

performance such as number of unique visitors and pageviews dominate net income in value

relevance. Consequently, we have mixed expectations about the sign of the ROA coefficient.

Venture-capital affiliation. Hsu, (2004) demonstrates how “VCs ‘extra-financial’

value may be more distinctive than their functionally equivalent financial capital”. Reputable

venture capital financiers, with a proven record of successful IPOs, lend credibility to their

investment portfolio firms. Also, Megginson and Weiss (1991), note that they are typically

there to stay as opposed to cashing out at the IPO time. This long-term horizon makes venture

capitalists extra cautious against any excesses on the amount of money to be left on the table

during the floatation day.

Underwriter rank pertains to the perceived quality of the agent underwriting the issue.

Carter and Manaster (1990) evidence significant underpricing by firms engaging prestigious

19

underwriters and attribute it to the positive signals that this strategy disseminates. Arguably,

an established underwriter would not risk impairing his reputational capital by facilitating an

offering of dubious quality.

Overhang, defined as the ratio of shares retained by pre-IPO shareholders to the total

equity given up in IPO (refer also to Bradley and Jordan, 2002), reflects the natural dilution

caused by the offering. The cost doe to dilution is incurred proportionately by all

shareholders who retain equity post-offering. Therefore, with a large number of new shares

(low overhang ratio), the costs increase making incentives to underprice less compelling.

Firm age is set equal to the years elapsing from firm’s incorporation day to the IPO

day. Prior literature frequently (Carter et al., 1998; Ritter, 1984, 1991; Schultz, 1993) uses

age as a surrogate for IPO firm’s risk. The conjecture is that firms with operations dating

back a larger number of years have proven their resilience against market swings and, thus,

constitute safer investments. Acknowledging the lesser degree of uncertainty surrounding the

long lived corporate organizations, we expect to record smaller underpricing in such cases.

Market return is estimated as the average return realized on the value-weighted CRSP

index over the last 20 days preceding the offering. It is a measure of overall market sentiment

prevailing at the time of the IPO, and as per prior research ((Hanley, 1993; Logue, 1973;

Loughran and Ritter, 2002; Lowry and Schwert, 2004), it is expected to positively relate to

underpricing.

Market condition controls capture the impact of the hot period of 1999-2000

(thoroughly described in Ljungqvist and Wilhelmand, 2003) and the 2007-2009 turbulence in

financial markets caused by the credit-crunch crisis.

Industry controls enter our model by means of indicator variables for technology and

Internet IPOs to account for the excessive underpricing that these firms typically experience

(e.g. Aggarwal 2002). We also use an indicator variable for Regulated to capture the potential

effect of operating in a regulated industry on the IPO return (refer to appendix A for industry

identification by regulatory environment). Lastly, we control for the exchange by means of a

NASDAQ dummy, as this has historically been the preferred marketplace for the majority of

IPOs.

Columns 1, 2, and 3 of Table 5 list the coefficients of regressing IPO returns

(underpricing) on the variables of political money (i.e., any combination of lobbying and

PAC contributions), lobby money, and PAC money as well as the covariates from the

literature discussed above. All of the variables of interest exhibit significance at the 5% level

and confirm the predicted (negative) sign. The political money coefficient, in column 1,

20

shows that a 10% increase in spending reduces underpricing by about 0.29%. In particular,

intensifying lobbying and PAC contributions by 10% results in a lower initial return by

0.28% (Column 2) and 0.55% (Column 3), respectively. The above results, even though small

in percentage terms, obtain substantial economic significance once viewed in conjunction

with the median political money expenditure which does not surpass $ 70,000 thousand.

The results obtained for the control variables accord with the relevant literature. Size,

proxied by proceeds, is significant at all conventional levels of significance and, inversely,

relates to underpricing. Similarly, the coefficient on age (significant and negative)

corroborates previous research showing long-lived companies to be associated with more

chances of survivorship and, thus, less uncertainty. Further, consistent with Bradley and

Jordan (2002), we register the constraining effect of ownership given, on underpricing, due to

high dilution costs. On the contrary, underpricing, significantly, increases with Internet and

technology stocks as per Ljungqvist and Wilhelm (2003). This explanation may, righteously,

extend to the coefficient (also positive and significant) on NASDAQ for being the preferred

listing place for technology issuers. Intuitively, the coefficient on the ‘DotcomPeriod’ is

positive and highly significant evidencing the excessive funds that has been left on the table

in the bullish period of 1998-1999. The fact that the overall market sentiment reflects on

initial returns is also captured by the coefficient on market return (positive and significant at

all levels). The positive and significant coefficients on venture capital and underwriter rank

contradict the findings from Carter and Manaster (1990) and Megginson and Weiss (1991)

but, are strongly aligned with the evidence from Beatty and Welch (1996), Loughran and

Ritter (2004), and Lowry and Murphy (2007). Lastly, we register no significant effect on

underpricing for firm’s leverage, return on assets and level of regulations confirming our

conjecture about the mixed signals that all of the above may disseminate to market investors.

In Table 6, we focus on the PMC sample (N=273) in order to gauge further the effect

of PMC related variables on underpricing. Including the same control variables as previously,

we now scale political money (Column 1), lobbying (Column 2), and PAC (Column 3)

variables by the amount of proceeds raised from the IPO in order to account for differences in

size. The coefficients on our variables of interest have now become significant at all

conventional levels of significance while maintaining their negative sign. Therefore, the

preliminary findings from the full sample have pointed to the right direction; the evidence

from the PMC firms’ sample fully supports the impact that a dollar invested in politics can

have on underpricing. In column 4, we run one additional regression in order to test the effect

of the geographic dispersion of PAC contributions measured by the number of US states that

21

their recipient candidates represent. This coefficient, too, turns out significant (p=5%), and

with the right sign (negative) alluding that PMC firms should plan strategically their spending

in order to reap the maximum benefits; a fact of paramount importance in light of the cash-

constrained environment in which the typical IPO firm operates.

B. The differential effect of lobbying and PAC contributions on IPO return

Having proved the mitigating impact of PMC on underpricing, we now turn our

attention to the various alternatives open to firms to exhibit PMC activity and seek to

determine if there is such thing as an optimal PMC strategy. Specifically, we ask whether

lobbying, PAC contributions or, any particular combination of the two, is rewarded by less

money left on the table or it is, rather, the mere involvement in PMC (no matter the chosen

route) that suffices to signal less uncertainty to investors. For this purpose, in Table 7, we run

three probit regressions with the dependent variable being the firm’s preferred spending

pattern. Column 1 is headed by the indicator variable ‘Bothlobbypac’ pertaining to firms

active in both lobbying and PAC contributions. Column 2 considers the same firms as in

column 1 but in the special sample of PMC firms (N=273) instead of the full IPO sample.

Finally, column 3 uses the categorical variable ‘Justlobby’ for those firms with a registered

lobbying, but no PAC, record.

The results disentangle the differential impact of lobbying and PAC spending on IPO

return. Interestingly, it comes out that only PMC firms employing both contribution types

reap the benefit of less underpricing. This is evidenced by a negative (and significant at

p=5%) coefficient on underpricing for the full as well as the PMC samples. Yet, Column 3

reports a positive coefficient on underpricing (also significant at p=5%) implying that

lobbying contributions, only, do not favor the issuer on the IPO date. It becomes evident,

then, that in the context of an imminent IPO, lobbying and PAC spending do not substitute

but complement each other. We speculate that the personal nature of PAC contributions

reinforces and guarantees more effective lobbying, in the sense, that it creates more ‘eager

ears’ for the issues the company lobbies for. Alternatively, lobbying, without the support of

PAC money, is perceived by market investors as a substantially riskier investment.

22

C. Devising an efficient PMC plan & targeting strategically for less money left on the table

With the above analysis concluding that any PMC strategy aspiring to reduce

underpricing should involve PAC contributions, we, subsequently, explore whether there is a

differential effect based on candidates’ individual characteristics (i.e. House, party and State

affiliation). To this end, on Table 8 Column 1, we regress IPO underpricing on the same

control variables and; (1) on an indicator variable set to 1 for PMC firms spending a larger

amount towards candidates from the Republican Party (2) an indicator variable set to 1 for

PMC firms spending more dollars on Senate candidates and (3) an interaction variable for

money to candidates representing the state of the PMC firm. The negative and significant

(p=5%) coefficient on the ‘RepublicanIPO’ confirms the ‘pro-business’ orientation that

traditionally surrounds the Republican Party reputation. The coefficient on ‘SenateIPO’ also

comes out negative but statistically insignificant. The Senate, despite being associated with

more prestige, does not give an edge over Congress consistent with the findings of Cooper et

al. (2010) as well as the US Constitution commanding all revenue and appropriations bills to

be originated in the House. On these grounds, Cooper et al. (2010) speculate that “firms may

find that it is more expedient to support House members, where potential firm value–

increasing actions may be more suitably created”. The (negative) coefficient on the

interaction term of ‘samestate*political money’ is significant (p=5%) demonstrating the

commonsensical conjecture that politicians representing the state of the IPO firm constitute

critical relational capital, especially for firms with extended operational base in the home

state.

Columns 2 and 3 assess the additional dimension of multiple PMC activity. The

variables of interest are indicator variables (‘multiPC’ in column 2 and ‘multiPAC’ in column

3) that are set to 1 for any firm possessing previous experience from the PMC arena.

The test in this case pertains to the timing of PMC and assesses whether a past record of PMC

is incrementally significant as a signal of established, long(er) lasting ties with politics or if it

is only the latest cash flows that are of any value relevance to IPO investors. The resulting

regression coefficients support the former over the later conjecture (old, established

relationships do matter). Yet, there is a somewhat puzzling angle given that ‘multiPC’

demonstrates significance at all levels while ‘multiPAC’ at p=10%. This finding, however,

may again hint to the previously shown market preference towards the combination of

contributions (i.e. both lobbying and PAC) rather than any specific contribution in isolation.

23

D. The effect of PMC activity on the book-building process.

Lastly, we test our hypothesis about the negative impact of PMC on filing price

revisions. To this end, we employ the full IPO sample to regress revision on political money

(lobbying or PAC) scaled by IPO proceeds. We use the same set of controls as previously.

The resulting coefficient on the ‘PMBYP’ variable (Table 9, Column 1), negative and

significant, confirms our predicted relation. We reiterate the same procedure in Column 2 for

the PMC firms’ sample. The association between revisions and political money spent by

dollar raised in IPO proceeds now becomes significant at all conventional levels of

significance. In order to further illustrate the direction of the relation (and treat outliers) we

run two probit regression with the dependent variable being the direction of the revision (1

for an upward revision, 0 otherwise) while we leave unchanged the regressors. The results in

Columns 3 and 4 for the full and PMC firms’ samples, respectively, corroborate the findings

from the OLS regressions. Thus, in light of a traceable PMC activity investors have less

positive information to reveal about the firm. This reflects in book building as increased

probability of a downward price revision.

V. Additional Robustness Tests

This far in the study, we have been assessing the phenomenon of IPO underpricing

applying ‘a follow-the-money’ approach tracing monetary contributions to politics. To test

the validity of our results, we replicate our main regression (Table 9) substituting the

variables of interest in a way that they express number of physical PAC recipients, instead of

the dollar value of PAC contributions. Thus, total recipients (Column 1), Republican

recipients (Column 3), Democrat recipients (Column 4), House recipients (Column 5), and

Senate recipients (Column 6) are all groups of candidates, proximity to whom is conjectured

to mitigate IPO uncertainty. Running five regressions, one for each of the above variables, we

obtain strong evidence pertaining to the robustness of our results. Specifically, all of the

regression coefficients are significant at all conventional levels of significance and confirm

the predicted (negative) sign.

Motivated by the numerous IPO performance studies documenting an endogenous

relation of underpricing with a plethora of covariates such as venture capital backing (Lee

and Wahal, 2004), litigation risk (Lowry and Shu, 2002) disclosure quality (Leone et al.

24

2007) executive option granting (Lowry and Murphy, 2007 and Chahine and Goergen, 2011),

we run the omitted-variable version of Hausman’s (1978) procedure in order to test our

assumption about the exogeneity of the PMC variables. The results (not tabulated) do not

provide sufficient evidence in order to reject the null hypothesis. We attribute the absence of

a simultaneous relation between underpricing and political donations to the highly

discretionary nature and modest size, typically, entailing these cash flows.

It has been well-documented that firms exhibit extraversion and seek to expand their

sphere of influence as they prepare to solicit equity financing. The fact that 81% of our PMC

firms have engaged in donations 12 months or closer to the IPO period reflects management’s

effort to fine-tune these cash flows with the listing project. We use this narrower PMC

sample characterized by the upmost proximity to the IPO and rerun all of our previous

testings. Once again, our findings remain intact.

We have decided to consider for our analysis PMC activity within a time frame of 5

years or more recent to the IPO time. We believe that cash flows made in even earlier

periods can hardly be associated with an issuer’s IPO strategy. A useful illustration would

entail the longest-tenured (6 years) representatives, i.e. US Senators. Given the staggered-

terms structure, one-third of the Senate seats are up for election every two years. Therefore, a

donation dating longer than five years may pertain to Senate’s oldest third, only. But even

this minority of incumbent Senators would be, by that point, amidst their new electoral

campaign requiring fresh funding.

VI. Discussion and Concluding Remarks

In the first study to relate a firm’s political donations record to IPO performance, we

show that issuers with a prior established record of political donations experience

significantly lower underpricing in the first day of trade. Being both traceable and publicly

available, a record of PMC activity can be plausibly associated with access to the upmost

decision-making bodies. As a consequence, IPO investors confide in the firm’s ability to

maneuver with less friction in the institutional environment and require smaller premia for

purchasing its equity. This means that the listing firm can hit the ground running as a public

company, having left as little money on the table as possible during its IPO day.

In response to the questions raised in the introduction the study shows that a PMC

record constitutes a suitable proxy for firm’s ‘political connectedness’ on the premise that it

25

is both substantial and traceable to specific politicians. To this end, the study makes a case

about the twofold nature of the effective PMC strategy as it necessitates lobbying expenditure

for size and PAC contributions for identification. In devising the optimal spending pattern,

we find that the effect on IPO returns is maximized by targeting candidates identifying with

the Republican Party, representing the firm’s State and exhibiting the greatest geographic

dispersion in terms of States’ representation in the case of non-local candidates. Notably,

there is no incremental effect for Congress Chamber affiliation.

Most importantly, assessing the fundamentals of PMC firms, we find these issuers to

be associated with superior quality as proxied by market share, profitability, leverage, and

years of operational experience. It becomes, thus, apparent that PMC firms rather than

seeking a life jacket in politics, they are involved in order to manage, promptly, for the legal

and institutional environment risks lying ahead. Consequently, we anticipate with genuine

interest future studies drawing evidence from the long-term performance of these IPOs in

order to determine how diversifiable, risks of this nature, truly are.

26

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Appendix A: Variables Definition

Variable Definition

Panel A: IPO Pricing

Ln (1+underpricing) Revisions Revdummy

The natural logarithm (plus one) of the percentage difference of the closing price from offering price on the IPO date.

The percentage difference of the offering price from the midpoint of the initial filing range.

Dummy variable: one for an upwards revision, zero otherwise.

Panel B: Political Connections

Political Money

The natural logarithm of total political money contributions (either lobbying or PAC) in the election cycle most closely preceding the IPO date.

PMbyP Political money (either lobbying or PAC) divided by proceeds raised on IPO day. Lobbying Money The natural logarithm of lobbying money in the election cycle most closely preceding the IPO date. LbyP Lobbying money divided by proceeds raised on IPO day. MultiPC Dummy variable: one for multiple political money activity preceding the IPO date, zero otherwise. PAC Money The natural logarithm of PAC money in the election cycle most closely preceding the IPO date. PbyP PAC money divided by proceeds raised on IPO day. MultiPAC Dummy variable: one for multiple PAC activity preceding the IPO date, zero otherwise. House Money The natural logarithm of Congress money in the election cycle most closely preceding the IPO date. House Recipients Total number of PAC money recipients running for seats in the House of Congress. Senate Money The natural logarithm of Senate money in the election cycle most closely preceding the IPO date. Senate Recipients Total number of PAC money recipients running for seats in the House of Senate. Democrat Money The natural logarithm of PAC contributions to Democrat candidates in US$. Democrat Recipients Total number of PAC money recipients belonging to the Democratic party. Republican Money The natural logarithm of PAC contributions to Republican candidates in US$. Republican Recipients Total number of PAC money recipients belonging to the Republican party. Total State Recipients Total number of US States that the PAC recipients represent. Total Candidate Recipients Total number of PAC recipients. JustLobby Dummy variable: one for lobbying activity only (preceding the IPO date), zero otherwise. PAC Only Dummy variable: one for PAC activity only (preceding the IPO date), zero otherwise. Bothlobbypac Dummy variable: one for both lobbying and PAC activity (preceding the IPO date), zero otherwise. Local Candidates Total number of PAC money recipients representing the IPO company state (in Senate or Congress). Samestate*Total Political Money

Political money contributions to candidates representing the State of the IPO firm.

Panel C: IPO Characteristics

Age The natural logarithm plus 1of the years elapsed from firm’s incorporation to the IPO year.

Venture Capital Dummy variable: one for venture backed firms, zero otherwise.

‘Dot.com’ Period Dummy variable: one for IPO within the 1998-2000 period, zero otherwise.

Internet Firm Dummy variable: one for internet firm IPO, zero otherwise. Internet IPOs are classified those IPOs with business description section in the Thomson Financial SDC characterized by the words “Internet”, “Online”, “eBusiness”, “eCommerce”, and/or “Website”.

Tech. Firm

Dummy variable: one for IPO firms with SIC codes 3571, 3572, 3575, 3577, 3578 (computer hardware), 3661, 3663, 3669 (communications equipment), 3671, 3672, 3674, 3675, 3677, 3678, 3679 (electronics), 3812 (navigation equipment), 3823, 3825, 3826, 3827, 3829 (measuring and controlling devices), 3841, 3845 (medical instruments), 4812, 4813 (telephone equipment), 4899 (communications services), and 7371, 7372, 7373, 7374, 7375, 7378, and 7379 (software).

Regulated IPO firms with SIC codes of 4900–4939 (electric and gas), 1300 (oil and gas extraction), 4000– 4700 (transportation), 4800 (telecommunications), 4950–4959 (sanitary services) and all 6000s (financial companies).

Underwriter Ranking Dummy variable: one for most prestigious underwriters, zero otherwise. Prestige rankings are from Jay

30

Ritter's underwriter database.

Overhang Proportion of given ownership (OWN) during the going public process.

Industry classification Dummy variable: one for industrial classified companies, zero otherwise.

Credit Crunch Crises Dummy variable: one for IPO within the financial crisis of 2007–2008, zero otherwise.

NASDAQ Dummy variable: one for NASDAQ floated IPO, zero otherwise.

Market Return Market return is the compounded daily return realized by the CRSP value weighted index within the 20 trading days preceding the IPO day.

Panel D: Firm Characteristics

Assets The natural logarithm the book value of assets in the last fiscal year prior to IPO. Revenues The natural logarithm the book value of revenues in the last fiscal year prior to IPO. Earnings Per Share (EPS) Dummy variable: one for positive EPS in the last fiscal year prior to IPO, zero otherwise. Returns on Assets (ROA) The return on assets in the last fiscal year prior to IPO. Leverage Total liabilities over total assets in the last fiscal year prior to IPO.

31

Table 1: Summary Statistics The Table presents statistics for a sample of US IPO deals announced within the period 1 January, 1998 to 30 June, 2013 drawn from the Securities Data Company (SDC) Database, side by side, with the subsample of IPO deals with a record of political money contributions (PMC). The IPOs are identified by: (1) the election cycle in which they occurred, (2) the Standard Industrial Classification (SIC) division in which they belong, (3) special industry environment, and (4) market value measures.

IPOs with PMC ( N = 273 )

Full sample ( N= 1578 )

Election Cycle No. % No %

98-99 30 10.99 465 29.47 00-01 24 8.79 160 10.14

02-03 15 5.49 94 5.96 04-05 60 21.98 271 17.17 06-07 52 19.05 247 15.65

08-09 20 7.33 56 3.55

10-11 42 15.38 151 9.57

12-13 30 10.99 134 8.49

SIC division No. % No %

Agriculture, Forestry and fishing 1 0.37 4 0.25 Mining and construction industries 13 4.76 49 3.11

Manufacturing 95 34.8 535 33.90 Transp., commun., and utilities 35 12.82 122 7.73 Wholesale and retail trade 15 5.49 122 7.73 Finance, insurance and real estate 41 15.02 185 11.72 Service industries 73 26.74 559 35.42 Public administration 0 0.00 2 0.13

Company specifics

Internet IPOs 26 9.52 198 12.55

Technology IPOs 76 27.84 599 37.96

VC Backed IPOs 97 35.53 745 47.21

Regulated Industry IPOs 80 29.30 337 21.36

NASDAQ IPOs 136 49.82 1095 69.39

Market Value Mean Median Mean Median

s.d s.d.

Market cap. (in mil $) 2441.55 708.08 834.51 322.91

9250.37 3980.58

Tobin's q 2.33 1.63 2.87 2.33

2.65 3.06

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Table 2: Sample Descriptives The Table presents statistics for a sample of US IPO deals announced within the period 1 January, 1998 to 30 June, 2013 drawn from the Securities Data Company (SDC) Database. The full sample splits further into (1) a subsample of IPO deals with a record of political money contributions (PMC) and (2) a subsample of the rest of IPO deals. The statistics provided describe the mean, median, minimum, maximum and standard deviation for the variables in each Panel. Panel A describes our main measure of IPO pricing, i.e. the first-day return, or underpricing. Panel B lists all the PMC-related variables employed by this study. Panel C describes the typical IPO characteristics suggested by the relevant literature and used in our analysis. Stock price data are from CRSP; accounting data are from Compustat. All variables are defined in Appendix A. Statistical tests for differences in means are also presented.

Full Sample (N= 1578) IPOs with PMC (N = 273) IPOs without PMC (N=1305) P-value of T -Diff Mean Median Min Max Mean Median Min Max Mean Median Min Max

s.d. s.d. s.d. Panel A – IPO pricing Underpricing 0.27 0.12 -0.71 6.84 0.19 0.09 -0.70 4.83 0.29 0.12 -0.37 6.84 0.01

0.58 0.43 0.60 Panel B – PMC characteristics PMC 0.05 0.00 0.00 9.86 0.30 0.09 0.00 9.86 0.00 0.00 0.00 0.00 0.00

0.39 0.89 0.00 Lobby money 0.05 0.00 0.00 9.57 0.27 0.06 0.00 9.57 0.00 0.00 0.00 0.00 0.00

0.36 0.83 0.00 Multiple lobbying 0.14 0.00 0.00 1.00 0.79 1.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

0.34 0.41 0.00 PAC money 0.01 0.00 0.00 1.53 0.03 0.00 0.00 1.53 0.00 0.00 0.00 0.00 0.00

0.05 0.12 0.00 Multiple PAC 0.06 0.00 0.00 1.00 0.34 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

0.24 0.48 0.00 House money 0.00 0.00 0.00 1.30 0.02 0.00 0.00 1.30 0.00 0.00 0.00 0.00 0.00

0.04 0.10 0.00 House recipients 1.65 0.00 0.00 348.00 9.51 0.00 0.00 348.00 0.00 0.00 0.00 0.00 0.00

15.29 35.78 0.00 Senate money 0.00 0.00 0.00 0.23 0.01 0.00 0.00 0.23 0.00 0.00 0.00 0.00 0.00

0.01 0.03 0.00 Senate recipients 0.52 0.00 0.00 60.00 3.03 0.00 0.00 60.00 0.00 0.00 0.00 0.00 0.00

3.74 8.58 0.00 Democrat money 0.00 0.00 0.00 0.41 0.01 0.00 0.00 0.41 0.00 0.00 0.00 0.00 0.00

0.02 0.04 0.00 Democrat recipients 0.86 0.00 0.00 185.00 4.95 0.00 0.00 185.00 0.00 0.00 0.00 0.00 0.00

7.84 18.33 0.00 Republican money 0.00 0.00 0.00 1.21 0.02 0.00 0.00 1.21 0.00 0.00 0.00 0.00 0.00

0.04 0.09 0.00 Republican recipients 1.31 0.00 0.00 249.00 7.54 0.00 0.00 249.00 0.00 0.00 0.00 0.00 0.00

11.11 25.86 0.00 Total candidate recipients 2.15 0.00 0.00 396.00 12.42 0.00 0.00 396.00 0.00 0.00 0.00 0.00 0.00

33

18.63 43.40 0.00 Total state recipients 0.76 0.00 0.00 49.00 4.39 0.00 0.00 49.00 0.00 0.00 0.00 0.00 0.00

4.42 9.87 0.00 Lobby only 0.12 0.00 0.00 1.00 0.67 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

0.32 0.47 0.00 PAC only 0.18 0.00 0.00 1.00 0.11 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

0.13 0.31 0.00 Both lobby and PAC 0.04 0.00 0.00 1.00 0.22 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

0.19 0.42 0.00 Panel C – IPO characteristics Gross proceeds 137.66 66.04 0.86 11,805 354.11 121.36 9.35 11,805.70 92.39 60.81 0.86 14,266.00 0.00

465.40 1,065.90 114.44 Venture Capital 0.47 0.00 0.00 1.00 0.36 0.00 0.00 1.00 0.50 0.00 0.00 1.00 0.00

0.50 0.48 0.50 Internet IPOs 0.13 0.00 0.00 1.00 0.10 0.00 0.00 1.00 0.13 0.00 0.00 1.00 0.10

0.33 0.29 0.34 Technology IPOs 0.38 0.00 0.00 1.00 0.28 0.00 0.00 1.00 0.40 0.00 0.00 1.00 0.00

0.49 0.45 0.49 Regulated industry 0.21 0.00 0.00 1.00 0.29 0.00 0.00 1.00 0.20 0.00 0.00 1.00 0.00

0.41 0.46 0.40 Underwriter Ranking 0.62 1.00 0.00 1.00 0.82 1.00 0.00 1.00 0.58 1.00 0.00 1.00 0.00

0.49 0.38 0.49 Share Overhang 3.53 2.88 0.00 80.75 3.70 2.97 0.00 50.34 3.49 2.87 0.00 80.75 0.35

3.41 3.67 3.35 NASDAQ 0.69 1.00 0.00 1.00 0.50 0.00 0.00 1.00 0.74 1.00 0.00 1.00 0.00

0.46 0.50 0.44 Assets 1,024 55.20 0.00 251,075 4,483 239.40 0.45 251,075 301 43.07 0.00 40,671 0.00

10,533 24,857 1,503 Revenues 391 46.21 0.00 78,277 1,514 175.45 0.00 78,277 156 38.62 0.00 6,036 0.00

2,504 5,837.59 394 Earnings per share 0.47 0.00 0.00 1.00 0.56 1.00 0.00 1.00 0.45 0.00 0.00 1.00 0.00

0.50 0.50 0.50 Returns on assets -0.36 -0.01 -40.8 1.14 -0.11 0.01 -4.28 0.86 -0.36 -0.01 -40.8 1.14 0.01

1.75 0.48 1.75 Leverage 1.50 0.94 0.00 81.50 1.17 0.91 0.00 6.78 1.56 0.95 0.00 81.50 0.05

3.11 0.96 3.39 Firm age 16.37 8.00 0.00 165.00 24.89 11.00 0.00 165.00 14.58 8.00 0.00 45.00 0.00

23.15 32.05 20.39 Dot.com period 0.37 0.00 0.00 1.00 0.15 0.00 0.00 1.00 0.42 0.00 0.00 1.00 0.00

0.48 0.36 0.49 Credit Crunch Crises 0.11 0.00 0.00 1.00 0.20 0.00 0.00 1.00 0.09 0.00 0.00 1.00 0.00

0.31 0.40 0.29

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Table 3: Firm Contribution Characteristics This table presents data from the Federal Election Commission (FEC) detailed files on PAC money contributions to House and Senate elections for the period from 1998 to June-30 2013. The sample includes $7.84 million in contributions made by 89 unique firms. The table reports firm contribution characteristics per firm, per election cycle.

Variable Mean Min 25thPer Median 75thPer Max Panel A: Dollar Amount of Firm Contributions per El ection Cycle closest to IPO

Total Contributions $88,108 1,000 9,500 21,000 68,050 1,527,649 Candidates

Democrats 33,380 0 1,500 6,500 22,780 411,983 Republicans 54,385 0 5,000 15,000 41,000 1,207,475

Races House 63,538 0 6,000 13,550 41,500 1,302,099 Senate 24,570 0 3,000 8,000 20,500 225,550

Panel B: Number of Firm Contributions per Election Cycle closest to IPO

No. of Candidates 38 0 5 12 37 396 No. of States 13 0 4 8 20 49

Candidates Democrats 15 0 1 4 11 185

Republicans 23 0 3 8 23 249 Races

House 29 0 3 9 22 348 Senate 9 0 1 4 10 60

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Table 4: Distribution of PAC Contributions by US State The table breaks down by election cycle the contributions made by US IPO firms, over the period 1 January, 1998 to 30 June 2013, to lobbying and PAC campaigns. For each election cycle, the top row gives the aggregate contribution value in million of US dollar and the bottom line the number of IPO firms that actually contributed. In the ‘PAC by US State’ panel we break down further by US State. The lobbying data comes from the files of the Center for Responsive Politics (CRP) and PAC contributions from the files of the Federal Election Commission (FEC).

Election Cycle

98-99 00-01 02-03 04-05 06-07 08-09 10-11 12-13 TOTAL

Lobby Activity (in mil US $) 14.6 12.5 1.55 7.2 12.7 5.7 14.5 4.6 73.5 # of contributors 26 23 15 44 48 19 39 30 244

PAC Activity (in mil US $) 3.63 1.32 0.27 0.63 0.82 0.05 0.67 0.45 7.84 # of contributors 14 9 6 2 16 4 10 5 89

PAC by US State

Alabama (in 000's US $) 81.5 13.5 7.4 4.0 24.5 0.0 4.5 0.0 135.4 # of contributors 8 3 3 1 4 0 2 0 21

Alaska (in 000's US $) 28.6 5.0 7.5 14.5 3.0 0.0 2.0 2.5 63.1 # of contributors 5 3 3 5 1 0 2 1 19

Arizona (in 000's US $) 55.8 37.3 6.0 7.5 7.0 0.0 7.5 32.0 153.1 # of contributors 5 6 1 5 2 0 3 1 22

Arkansas (in 000's US $) 37.0 6.0 0.0 4.0 1.0 0.0 6.5 5.0 59.5 # of contributors 5 2 0 3 1 0 3 1 14

California (in 000's US $) 326.2 101.8 11.5 42.0 83.5 5.8 46.5 73.0 690.3 # of contributors 10 7 4 11 5 3 5 4 45

Colorado (in 000's US $) 55.3 8.0 7.0 12.3 2.0 17.0 5.0 5.5 112.1 # of IPO contributors 5 4 3 3 2 1 3 2 21

Connecticut (in 000's US $) 49.1 44.0 3.0 5.0 14.0 0.0 2.0 5.0 122.1 # of contributors 6 3 2 2 3 0 1 2 17

Delaware (in 000's US $) 7.1 19.0 0.0 2.0 12.0 0.0 3.6 5.0 48.6 # of contributors 3 3 0 1 2 0 3 1 12

Florida (in 000's US $) 120.5 57.0 7.0 59.0 42.5 2.0 16.0 22.3 326.3 # of contributors 7 4 3 7 5 2 5 3 33

Georgia (in 000's US $) 154.8 23.5 4.0 22.0 8.5 0.0 12.5 10.0 235.3 # of contributors 8 6 2 5 4 0 2 3 27

Hawaii (in 000's US $) 15.2 1.5 0.0 5.0 2.0 2.0 3.5 0.0 29.2 # of contributors 3 2 0 1 1 1 2 0 10

Idaho (in 000's US $) 38.0 1.5 1.0 7.0 11.5 0.0 7.0 1.0 67.0 # of contributors 6 2 1 3 2 0 3 1 17

Illinois (in 000's US $) 172.9 47.5 1.0 39.7 16.3 2.0 21.0 13.5 313.9 # of contributors 11 5 2 7 3 2 5 2 35

Indiana (in 000's US $) 128.0 16.5 4.5 9.0 23.0 0.0 19.5 1.5 202.0 # of contributors 9 5 1 6 2 0 4 1 27

Iowa (in 000's US $) 51.7 13.0 2.5 9.8 4.0 1.0 7.0 7.5 96.5 # of contributors 9 4 2 3 2 1 4 3 25

Kansas (in 000's US $) 46.6 7.5 1.0 2.5 15.5 0.0 9.0 2.0 84.1 # of contributors 6 3 1 2 4 0 2 1.0 18.0

Kentucky (in 000's US $) 84.4 22.0 6.5 16.7 10.0 4.8 11.0 12.0 167.4 # of contributors 9 4 2 5 4 1 4 2 29

Louisiana (in 000's US $) 79.5 15.0 3.0 17.5 7.0 0.0 11.0 2.0 135.0 # of contributors 6 5 2 8 3 0 3 1 27

Maine (in 000's US $) 6.8 9.5 3.0 0.0 1.0 0.0 0.0 2.0 22.3 # of contributors 3 4 2 0 1 0 0 2 10

Maryland (in 000's US $) 69.7 23.2 17.0 3.5 25.0 2.0 15.0 8.5 163.9 # of contributors 6 5 3 2 4 1 3 2 24

Massachusetts (in 000's US $) 39.2 42.5 0.0 1.0 3.5 0.0 23.0 12.0 121.2 # of contributors 6 3 0 1 2 0 3 2 15

Michigan (in 000's US $) 159.6 53.8 5.5 22.5 13.3 4.0 98.5 11.0 368.2 # of contributors 9 5 2 7 4 2.0 7 3 36

36

Minnesota (in 000's US $) 26.9 27.5 2.9 2.0 7.0 0.0 6.2 15.0 87.4 # of contributors 6 4 3 2 3 0 3 2 21

Mississippi (in 000's US $) 32.5 8.5 0.0 2.0 8.5 1.0 3.5 6.0 62.0 # of contributors 4 4 0 2 2 1 3 1 16

Missouri (in 000's US $) 115.6 53.4 4.5 40.4 19.0 0.0 20.5 9.5 262.9 # of contributors 8 4 2 8 5 0 3 1 30

Montana (in 000's US $) 5.5 12.0 1.0 6.0 5.0 0.0 4.5 10.5 44.5 # of contributors 4 5 1 4 2 0 3 3 19

Nebraska (in 000's US $) 29.5 38.0 4.0 2.5 13.5 0.0 7.0 2.5 97.0 # of contributors 6 5 1 3 2 0 3 1 20

Nevada (in 000's US $) 32.5 14.0 1.0 15.0 8.8 0.0 8.5 5.0 84.8 # of contributors 6 4 1 3 4 0 5 1 23

New Hampshire (in 000's US $) 26.5 0.0 1.0 6.0 4.0 0.0 2.0 4.5 44.0 # of contributors 6 0 1 3 3 0 2 1 15

New Jersey (in 000's US $) 95.7 59.5 3.1 10.0 27.0 2.0 2.0 10.1 209.4 # of contributors 7

2 3 6 1 2 3 27

New Mexico (in 000's US $) 44.5 11.5 5.5 1.8 19.0 0.0 10.5 6.0 98.8 # of contributors 6 4 3 2 4 0 2 2 21

New York (in 000's US $) 244.3 116.8 21.3 17.4 28.0 0.5 36.5 13.5 478.3 # of contributors 9 4 4 9 3 1 5 2 35

North Carolina (in 000's US $) 96.9 11.0 2.3 22.7 11.0 0.0 16.5 16.5 176.8 # of contributors 7. 3 2 6 2 0 4 3 24

North Dakota (in 000's US $) 25.2 32.5 2.0 9.5 2.1 0.0 6.4 0.0 77.7 # of contributors 7 4 1 3 1 0 3 0 19

Ohio (in 000's US $) 160.6 34.8 7.3 18.5 20.5 0.0 52.5 18.5 312.6 # of contributors 10. 5 3 6 5 0 5 3 34

Oklahoma (in 000's US $) 53.7 20.0 0.5 5.5 7.1 0.0 1.0 1.0 88.8 # of contributors 8 6 1 6 2 0 1 1 24

Oregon (in 000's US $) 27.5 5.5 1.3 0.0 0.0 0.0 8.0 7.5 49.8 ## of contributors 8 3 1 0 0 0 2 1 14

Pennsylvania (in 000's US $) 157.2 62.5 36.8 31.4 49.0 0.0 28.3 9.0 374.2 # of contributors 9 4 4 6. 6 0 5 3 34

Rhode Island (in 000's US $) 7.9 12.4 4.0 0.0 3.5 1.0 0.0 5.0 33.7 # of contributors 4 2 1 0 1 1 0 2 9

South Carolina (in 000's US $) 37.2 32.0 2.5 8.5 30.0 0.0 8.0 5.0 123.2 # of contributors 6 3 1 3 4 0 4 1 21

South Dakota (in 000's US $) 47.0 6.0 11.5 2.0 9.0 0.0 14.5 4.5 94.5 # of contributors 8 3 2 2 2 0 4 2 21

Tennessee (in 000's US $) 34.4 17.5 1.5 0.5 19.5 0.0 16.5 9.5 99.4 # of contributors 6 4 2 2 4 0 5 2 23

Texas (in 000's US $) 238.4 58.1 1.0 59.8 37.0 1.0 32.5 13.0 440.8 # of contributors 9 6 1 14 5 1 4 2 40

Utah (in 000's US $) 35.0 14.5 0.0 14.5 42.0 2.4 9.5 18.0 135.9 # of contributors 9 6 0 5 5 1 5 3 31

Vermont (in 000's US $) 0.0 17.0 0.0 0.0 0.0 0.0 0.0 0.0 17.0 # of contributors 0 4 0 0 0 0 0 0 4

Virginia (in 000's US $) 49.0 26.0 36.0 15.3 78.2 0.0 28.0 15.0 247.4 # of contributors 8 6 3 10 6 0 4 2 37

Washington (in 000's US $) 81.6 26.0 2.2 0.0 20.0 0.5 3.5 6.9 140.6 # of contributors 6 5 1 0 3 1 2 2 18

West Virginia (in 000's US $) 16.5 7.0 12.0 11.5 7.0 1.0 7.5 0.0 62.5 # of contributors 3 1 3 4 1 1 3 0 16

Wisconsin (in 000's US $) 89.4 12.0 0.5 1.0 1.0 0.0 6.3 1.5 111.7 # of contributors 7 2 1 1 1 0 2 1 14

Wyoming (in 000's US $) 10.0 12.0 0.0 21.0 3.0 0.0 1.5 2.5 50.0 # of contributors 3 3 0 4 3 0 1 1 14

37

Table 5: Political Money Contributions of IPO firms (Full Sample) The table reports results of the cross-sectional OLS regression analysis of IPO underpricing (dependent variable) on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size. Variables Political Money

All Type (1) Political Money

Lobby Money (2) Political Money PAC Money (3)

Constant -0.232*** -0.232*** -0.235***

(0.000) (0.000) (0.000)

lnproceeds 0.0446*** 0.0444*** 0.0442***

(0.000) (0.000) (0.000)

leverage 0.00177 0.00177 0.00178

(0.495) (0.493) (0.491)

ROA 0.00458 0.00458 0.00451 (0.288) (0.289) (0.298)

age -0.0145*** -0.0148*** -0.0135**

(0.00907) (0.00755) (0.0152)

venture capital 0.0487*** 0.0491*** 0.0475***

(0.00151) (0.00140) (0.00192)

‘dotcom’ period 0.167*** 0.167*** 0.171***

(0.000) (0.000) (0.000)

internet firm 0.0935*** 0.0935*** 0.0933***

(0.001) (0.001) (0.001)

tech. firm 0.0750*** 0.0753*** 0.0747***

(0.000) (0.000) (0.000)

regulated -0.0173 -0.0175 -0.0167

(0.222) (0.218) (0.239)

underwriter 0.0595*** 0.0591*** 0.0589*** (0.0002) (0.0002) (0.0002)

overhang 0.0128*** 0.0128*** 0.0127***

(0.00304) (0.003) (0.00275)

Nasdaq 0.0721*** 0.0727*** 0.0717***

(0.000) (0.000 (0.000)

market return 22.98*** 22.91*** 22.82***

(0.000) (0.000) (0.000)

political money -0.00289**

(0.0371)

lobbying money -0.00288**

(0.0427)

PAC money -0.00549***

(0.00639)

Obs. 1,578 1,578 1,578

Adj. R-squared 0.265 0.265 0.266

38

Table 6: Political Money Contributions (PMC Sample) The table reports results of the cross-sectional OLS regression analysis of IPO underpricing (dependent variable) on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013, with a record of PMC activity. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size.

Political Money (All Type) (1)

Lobby Money (2)

PAC Money (3)

Total Recipient States (4)

Constant -0.0511 -0.0524 -0.0502 -0.112

(0.533) (0.524) (0.541) (0.158) lnproceeds 0.005 0.003 0.003 0.015 (0.826) (0.819) (0.818) (0.279)

leverage -0.0197 -0.0197 -0.0199 -0.0200 (0.205) (0.205) (0.202) (0.192) ROA 0.130** 0.130** 0.132** 0.127** (0.0178) (0.0182) (0.0161) (0.0170) age -0.006 -0.006 -0.006 -0.0007

(0.473) (0.476) (0.491) (0.932) venture capital 0.0909** 0.0907** 0.0945** 0.0944**

(0.0208) (0.0213) (0.0154) (0.0143) ‘dotcom’ period 0.223*** 0.222*** 0.226*** 0.230*** (0.0002) (0.0002) (0.0002) (0.0002) internet firm 0.0391 0.0395 0.0376 0.0434 (0.561) (0.557) (0.576) (0.514) tech. firm 0.0527* 0.0527* 0.0501 0.0442

(0.0993) (0.0994) (0.112) (0.158) regulated -0.0190 -0.0191 -0.0199 -0.0197

(0.441) (0.438) (0.417) (0.423) financial crisis -0.0373 -0.0372 -0.0376 -0.0454*

(0.133) (0.134) (0.130) (0.0693) underwriter 0.0804* 0.0808* 0.0781* 0.0744* (0.0603) (0.0591) (0.0670) (0.0750) overhang 0.00635 0.00637 0.00617 0.00684 (0.245) (0.244) (0.254) (0.188) Nasdaq 0.111*** 0.111*** 0.111*** 0.111***

(0.0001) (0.0001) (0.0001) (0.0001) market return 22.95*** 22.95*** 23.16*** 23.00***

(0.0008) (0.0008) (0.0008) (0.0008) PMbyP -0.708***

(0.001) LbyP -0.749*** (0.0009)

PbyP -7.396*** (0.0008)

total States -0.00317** (0.0118)

Obs. 273 273 273 273

Adj. R-squared 0.351 0.351 0.352 0.357

39

Table 7: Probit regressions explaining the occurrence of political donations by type The table reports results of the probit regression analysis of alternate donation manners on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013 with a record of PMC activity. Column 1 pertains to the full sample and uses as dependent variable the probability that a firm has contributed via both lobbying and PAC. Column 2 pertains to the PMC sample and uses as dependent variable the probability that a firm has contributed via both lobbying and PAC. Column 3 pertains to the PMC sample and uses as dependent variable the probability that a firm has contributed to lobbying, only. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size

Bothlobbypac (1) Bothlobbypac (2) Justlobby (3)

Constant -3.645*** -1.854*** 1.014* (0.000) (0.0009) (0.0630) ln(1+underpricing) -0.615** -0.935** 1.053**

(0.0307) (0.0394) (0.0238) lnproceeds 0.372*** 0.202** -0.0657 (0.000) (0.0456) (0.492)

leverage -0.146** -0.202* 0.220* (0.0490) (0.0996) (0.0915)

ROA 0.128 0.212 -0.436*

(0.572) (0.348) (0.0831)

age 0.110* 0.121 -0.202** (0.0829) (0.158) (0.0130) venture capital -0.363* -0.418* 0.551**

(0.0680) (0.0991) (0.0172) ‘dotcom’ period -0.0519 0.516* -0.758**

(0.762) (0.0805) (0.0103)

internet firm 0.311 0.324 -0.181

(0.173) (0.328) (0.599) tech. firm -0.0624 -0.0451 0.174 (0.727) (0.843) (0.420)

regulated 0.132 0.134 -0.154 (0.388) (0.505) (0.427)

underwriter 0.162 0.00344 -0.245

(0.402) (0.991) (0.364)

overhang 0.0169 0.0121 0.00301 (0.164) (0.558) (0.888)

Nasdaq -0.0545 -0.0102 0.239

(0.724) (0.964) (0.256)

market return 12.47 -37.93 5.404

(0.728) (0.472) (0.914)

Obs. 1,578 273 273

Pseudo R^2 0.224 0.147 0.207

40

Table 8: Returns and PAC spending characteristics The table reports results of the cross-sectional OLS regression analysis of IPO underpricing on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013 with a record of PMC activity. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size.

lninitialreturnplus1 (1)

lninitialreturnplus1 (2)

lninitialreturnplus1 (3) VARIABLES

Constant -0.0894 -0.108 -0.0710 (0.271) (0.191) (0.382) lnproceeds 0.0120 0.0148 0.00752 (0.409) (0.329) (0.605) leverage -0.0199 -0.0189 -0.0199 (0.201) (0.222) (0.201) ROA 0.131** 0.129** 0.130** (0.0148) (0.0168) (0.0166) age -0.000658 -0.00450 -0.00168 (0.941) (0.624) (0.849) venture capital 0.0890** 0.0937** 0.0879** (0.0226) (0.0163) (0.0230) ‘dotcom’ period 0.224*** 0.220*** 0.223*** (0.0001) (0.0002) (0.0002) internet firm 0.0440 0.0404 0.0421 (0.515) (0.551) (0.531) tech. firm 0.0445 0.0488 0.0435 (0.161) (0.120) (0.175) financial crisis -0.0441* -0.0383 -0.0416* (0.0824) (0.119) (0.0973) underwriter 0.0826* 0.0763* 0.0848** (0.0550) (0.0726) (0.0477) overhang 0.00584 0.00650 0.00636 (0.285) (0.240) (0.222) Nasdaq 0.108*** 0.115*** 0.106*** (0.00165) (0.000) (0.0002) market return 22.95*** 23.35*** 23.45*** (0.000783) (0.000709) (0.000710) RepublicanIPO -0.0510** (0.0253) SenateIPO -0.0146 (0.631) samestate*total political money

-1.83e-08**

(0.0481) multiPC -2.82e-08***

(0.005) multiPAC -0.00442* (0.059) Obs. 273 273 273 Adj. R^2 0.354 0.353 0.349

41

Table 9: Returns and PAC Money Recipients Identity .The table reports results of the cross-sectional OLS regression analysis of IPO underpricing on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013 with a record of PMC activity. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size.

(1) (2) (3) (4) (5) (6) IRplus1 IRplus1 IRplus1 lRplus1 lRplus1 lRplus1 Constant -0.112 -0.112 -0.108 -0.115 -0.107 -0.130 (0.165) (0.158) (0.180) (0.156) (0.188) (0.100) lnproceeds 0.0145 0.0154 0.0140 0.0146 0.0134 0.0186 (0.311) (0.279) (0.328) (0.311) (0.356) (0.186) leverage -0.0195 -0.0200 -0.0195 -0.0194 -0.0194 -0.0199 (0.200) (0.192) (0.201) (0.203) (0.203) (0.191) ROA 0.128** 0.127** 0.127** 0.130** 0.129** 0.127** (0.0168) (0.0170) (0.0177) (0.0156) (0.0169) (0.0165) age -0.00219 -0.000750 -0.00255 -0.00171 -0.00244 -0.00112 (0.806) (0.932) (0.775) (0.848) (0.784) (0.899) venture capital 0.0993** 0.0944** 0.0980** 0.101** 0.0992** 0.0989** (0.0111) (0.0143) (0.0118) (0.0106) (0.0113) (0.0108) ‘dotcom’ period 0.241*** 0.230*** 0.240*** 0.242*** 0.240*** 0.243*** (0.0002) (0.0002) (0.0002) (0.0002) (0.0002) (0.0001) internet Firm 0.0363 0.0434 0.0375 0.0349 0.0361 0.0382 (0.589) (0.514) (0.576) (0.604) (0.591) (0.566) tech Firm 0.0445 0.0442 0.0445 0.0447 0.0445 0.0452 (0.155) (0.158) (0.155) (0.154) (0.157) (0.147) financial crisis -0.0405* -0.0454* -0.0408* -0.0397 -0.0398 -0.0433* (0.0997) (0.0693) (0.0985) (0.105) (0.106) (0.0797) underwriter 0.0730* 0.0744* 0.0745* 0.0720* 0.0738* 0.0724* (0.0796) (0.0750) (0.0746) (0.0831) (0.0773) (0.0812) overhang 0.00682 0.00684 0.00668 0.00701 0.00677 0.00698 (0.219) (0.188) (0.236) (0.197) (0.226) (0.191) Nasdaq 0.112*** 0.111*** 0.111*** 0.113*** 0.112*** 0.112*** (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) market return 23.58*** 23.00*** 23.63*** 23.41*** 23.69*** 22.79*** (0.00071) (0.00084) (0.000717) (0.0007) (0.0007) (0.0009) regulated -0.0187 -0.0197 -0.0197 -0.0171 -0.0189 -0.0178 (0.442) (0.423) (0.419) (0.483) (0.439) (0.465) total recipients -0.000767*** (0.00474) total states -0.00317** (0.0118) Republican Recip. -0.00125*** (0.00894) Democrat Recip -0.00185*** (0.00406) House Recip -0.000889*** (0.00655) Senate Recip -0.00446*** (0.00139) Obs. 273 273 273 273 273 273 Adj. R-squared 0.359 0.357 0.358 0.360 0.358 0.363

42

Table 10: Filing Price Revisions and Political Money The table reports results of the cross-sectional OLS and probit regression analysis of filing price revisions on political money contributions variables and other issuer- and deal-specific characteristics for a sample of U.S. IPOs announced over the period 1 January, 1998 to 30 June, 2013. Column 1 pertains to the full sample and uses as dependent variable the percentage difference of the offering price from the midpoint of the initial filing range. Column 2 pertains to the PMC sample and is otherwise identical test with Column 1. Column 3 pertains to the full sample and uses as dependent variable the probability of an upward price revision. Column 4 pertains to the PMC sample and is otherwise identical test with Column 3. Variables are defined in Appendix A. All regressions control for year fixed effects whose coefficients are suppressed. We use the symbols *, ** and *** to denote statistical significance at the 1%, 5%, and 10% levels, respectively. The t-statistics reported in parentheses are based on standard errors adjusted for heteroskedasticity. N refers to sample size

OLS Probit (1) (2) (3) (4) Constant -9.434*** -18.36*** -0.932*** -0.770*

(0.000) (0.005) (0.000) (0.0975)

leverage 0.233 -0.486 -0.00365 -0.0648

(0.230) (0.678) (0.897) (0.599)

ROA 0.913** 6.660* 0.142* 0.709**

(0.0272) (0.0699) (0.0972) (0.0464)

age 0.111 2.182 0.0182 0.0136

(0.784) (0.156) (0.673) (0.885)

venture capital 1.244 5.662** 0.195** 0.667***

(0.203) (0.0395) (0.0332) (0.00725)

‘dotcom’ period 5.182*** 9.566*** 0.399*** 1.138***

(0.000) (0.000) (0.000) (0.001)

internet firm 4.488*** 1.915 0.575*** 0.179

(0.0009) (0.675) (0.000) (0.597)

tech. firm 5.059*** 7.627*** 0.347*** 0.330

(0.000) (0.00285) (0.000) (0.146)

regulated 2.765*** 6.365** 0.177* 0.142

(0.00814) (0.0172) (0.0948) (0.538)

underwriter 3.668*** 4.362 0.483*** 0.615*

(0.000) (0.114) (0.000) (0.0568)

overhang 0.428** 0.419 0.0209 -0.0225

(0.0249) (0.416) (0.154) (0.640)

Nasdaq -0.766 2.416 -0.0966 0.0136

(0.417) (0.329) (0.308) (0.951)

market return 1,145*** -17.44 89.90*** 16.92

(0.000) (0.979) (0.000) (0.768)

PM by proceeds -14.52** -26.82** -215.2*** -318.9***

(0.0255) (0.0101) (0.0009) (0.0001)

Obs. 1,164 205 1164 204

Adjusted R2 0.136 0.139

Pseudo R2 0.1057 0.1763