Journal of International Economics 83 (2011) 126–136

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Journal of International Economics

j ourna l homepage: www.e lsev ie r.com/ locate / j i e

Lobbying costs and trade policy☆

Patricia Tovar ⁎Department of Economics, Mail Stop 021, Brandeis University, P.O. Box 9110, Waltham, MA 02454, USA

☆ I thank Robert Staiger and two anonymous referees fremaining errors are mine.⁎ Tel.: +1 781 736 5205; fax: +1 781 736 2269.

E-mail address: tovar@brandeis.edu.

0022-1996/$ – see front matter © 2010 Elsevier B.V. Adoi:10.1016/j.jinteco.2010.11.003

a b s t r a c t

a r t i c l e i n f o

Article history:Received 10 September 2009Received in revised form 3 November 2010Accepted 7 November 2010Available online 13 November 2010

JEL classification:F10F13

Keywords:Trade policyProtectionLobbiesLobbying expenditures

We study how endogenous lobbying costs influence trade policies. Although in practice lobbyingexpenditures far exceed campaign contributions, the literature on the political economy of trade policy hasfocused on the latter. In this paper we develop a model in which informational lobbying costs play a role indetermining the structure of protection. In the model, special interest groups can choose to send a signal tothe policymaker regarding some information they possess, and the policymaker observes the signal beforesetting the trade policies. We find that lobbying expenditures directly affect the equilibrium policies. In orderto test the predictions of the model we collected data on lobbying expenditures from the Center forResponsible Politics as well as data on trade and industry characteristic variables for the United States fromother sources. We perform a structural estimation of the equilibrium trade policies and find support for ourmodel. The empirical evidence indicates that lobbying expenditures play an important role in explaining thevariation of protection across sectors. Moreover, the model leads to considerably lower and more reasonableestimates of the weight that the government places on social welfare relative to political contributions.

or very helpful comments. Any

1 See, for example(2000).

2 See, for instance,empirical evidence omotivation for campa

3 Grossman and Hgeneral setup in whpolicy variable andparticular and in the

4 Also, during 199the average of PAC1997–1998 was $23

ll rights reserved.

© 2010 Elsevier B.V. All rights reserved.

, Goldberg and Maggi (1999) and Gawande and Bandyopadhyay

Wright (1985); Ansolabehere et al. (2002) and Langbein (1986) forn this and for references to studies that argue that buying access is aign contributions; and Grossman and Helpman (2001).elpman (2001) do model endogenous lobbying costs but in a

1. Introduction

Many government policies are used to redistribute income towardspecial interest groups (SIGs). Moreover, there is a significant andgrowing literature about the role that interest groups play indetermining economic policies. For example, how do lobbying costsaffect trade policies? Attention in the literature on the politicaleconomy of trade policy regarding this important question has beendirected toward campaign (or political) contributions provided bySIGs; however, it has been recognized that in practice lobbyingexpenditures far exceed campaign contributions.

The literature on SIGs identifies three types of costs related to SIGactivities, or “lobbying costs”. Grossman and Helpman (2001) refer tothose as exogenous costs, endogenous costs and access costs. The first aredefined as costs that the interest group does not control and do not varywith the content of its message. Endogenous costs are those that theinterest group can choose in order to send a signal to the policymakerregarding some information it possesses or the legitimacy of its claims.Access costs are costs imposed by the policymaker as a condition forgranting ameetingwith the SIG. Political economymodels of trade policy,which focus on the interaction between SIGs and the policymaker, haveincorporatedexogenous costs. Thesegenerally take the formoffixedcostsof forming an organization, as in Mitra (1999), who endogenizes lobbyformation in the framework of theGrossman andHelpman (1994)model

of trade protection. In addition, in the Grossman and Helpman (1994)model, SIGs provide contributions to the policymaker in exchange forprotection, and when testing this model, authors have used campaigncontributions to determine political organization.1 However, many haveargued that campaign contributions buy access only, which may then befollowedbyorganized lobbying efforts.2 One, if not themost important, ofthe types of lobbying costs has not receivedmuch attention, in particularby the trade policy literature: those associated with the informationallobbying activities directly devoted to influence policy.3

In comparing PAC contributions to lobbying, Milyo (2002)mentions“(...) the fact that firms typically devote far more resources to lobbying.Since the prevailing wisdom in political science has been that campaigncontributions are not a good proxy for lobbying activity, it then followsthat the real route for influence may well be through the lobbying, notPAC contributions.” (p. 158). In addition, Ansolabehere et al. (2002)findthat, for firms with both PACs and a Washington lobby, the ratio oflobbying expenditures to PAC contributions is about 10 to 1.4 Similarly,

ich the policymaker's objective depends on the level of somethe state of the world. Our model focuses on trade policies inpresence of campaign contributions as well, unlike theirs.7 and 1998, lobbying expenditures totaled $2.624 billion, whilecontributions in the two-year election cycles of 1995–1996 and1 million.

127P. Tovar / Journal of International Economics 83 (2011) 126–136

Grossman and Helpman (2001) state that “The total amount spent onlobbying exceeds the corresponding figure for federal campaigncontributions, making lobbying the most expensive as well as themost prevalent practice.” (p. 7). Bennedsen and Feldman (2002)mention that in most cases the dissemination of information in someform represents a far larger share of the interest groups' resources thanpolitical contributions. For instance, the top 100 contributing interestgroups gave a total of $144 million to federal candidates during the 1998election cycle, while a similar group of SIGs engaged in lobbying spentover $1 billion on lobbying activities during that period.5 Likewise, DeFiguereido et al. (2006) point out that “Perhaps surprisingly, lobbying,not campaign contributions, absorbs the bulk of ‘influence dollars’ spentby special interest groups.” (p. 1). Moreover, according to the Center forResponsible Politics, the amount of money spent on lobbying hasincreased from $1.45 billion in 1998 to $2.80 billion in 2007.6

In this paper we develop a model in which endogenousinformational lobbying activity – distinct from campaign or politicalcontributions – plays an important role in the determination of tradepolicies. In the first stage of the model, politically organized sectorsoffer the government a contribution schedule that matches tradepolicies to a campaign contribution level. However, at that stage thestate of the world is not fully known, and thus the contribution level isalso a function of the state of the world. In a second stage, the value ofthe unobserved variable is revealed to the lobbies, and they canchoose to send a signal to the policymaker regarding that variable. Thegovernment observes the signal and chooses the trade policies.

We start by deriving the lobbying expenditure function in anequilibrium with full revelation. We then proceed to derive theequilibrium trade policies. We find that lobbying expendituresdirectly affect the determination of trade policies. In particular, weshow theoretically that the elasticity of lobbying costs with respect tothe trade policy should be included as an additional variable that canhelp explain the variation of protection across industries. In theGrossman and Helpman (1994) model, the contribution is a transferof money from the lobby to the government, and thus it cancels out inthe joint-surplus-maximization condition and does not appeardirectly in the equilibrium protection expression. With lobbyingcosts of the type that wemodel here, in contrast, the costs are incurredby the lobby but do not accrue to the politician in the form of apayment, and they appear in the protection equation.

The second objective of this paper is to assess the empiricalimportance of endogenous lobbying expenditures in the determina-tion of protection, using product-level data for the United States in1999.7 We begin by estimating the derivative of lobbying costs withrespect to protection for each sector. In order to do this we collecteddata on lobbying expenditures from the Center for ResponsiblePolitics and matched it at the 3-digit ISIC level.8 When this variable isused in the estimation of the protection equation we correct for thefact that it is estimated. We then combine this data with data oninternational trade variables and industry characteristics fromdifferent sources to estimate the structural equation for theequilibrium trade policies, and we find that lobbying costs play animportant role in the determination of trade policies empirically. Theresults indicate that lobbying expenditures – or more precisely, theirderivative with respect to protection – directly affect the determina-

5 See Bennedsen and Feldman (2002), p. 920. Also, Gais and Walker (1991) pointout that in their survey, 80% of the groups said that lobbying is an important activity,while only 23% said that electioneering is.

6 http://www.opensecrets.org/lobby/index.php (last accessed 05/17/08).7 de Figuereido and Cameron (2006) are the first to test the predictions of a model

of endogenous cost (informational) lobbying, due to Potters and Van Winden (1992)and Grossman and Helpman (2001). They find empirical support for the predictions ofthe model; however, their model is not a trade policy model.

8 The Lobbying Disclosure Act of 1995 made data on lobbying expendituresavailable.

tion of trade policies, and should be included as an additional variablethat helps explain the structure of protection across sectors.

An important puzzle in the political economy of trade policyliterature concerns the high estimates of the weight that thegovernment places on social welfare relative to political contributions.Those estimates are considered to be at odds with the view that tradepolicy is determined largely by political influences (Gawande andKrishna, 2003).We show that incorporating endogenous lobbyingcosts into the modeling of trade protection implies significantly lowerempirical values of that parameter, although the estimates that weobtain may still be considered relatively high. The explanation for thisresult is that the inclusion of informational lobbying costs reduces themarginal benefit from protection to the industry, and thus themarginal benefit to the government in the form of higher contribu-tions. Therefore, not accounting for these costs leads to anoverestimation of the response of political contributions to protectionand hence of the weight that the government attaches to socialwelfare relative to contributions.9 By estimating the expression for theequilibrium policy predicted by our model, we obtain values of theweight on social welfare as low as 20; significantly smaller and morereasonable than previous estimates for the U.S. (Gawande andBandyopadhyay estimate the value of a to be over 3000 for example).

We finish this section by providing a few examples of informa-tional lobbying related to trade policy. General ways in which SIGstransmit information through lobbying are by meeting with legisla-tors in their offices or having informal contacts with them; hiringlawyers and policy experts; submitting briefs; conveying researchresults and technical information; engaging in media advertising andmailings; participating in demonstrations and protests (e.g. duringmeetings of the WTO); etc. For example, U.S. dairy farmers have beenactive in favor of import quotas. The American Sugar Alliance is agroup representing major U.S. sugar growers and it is active inlobbying. They produce briefs on the outlook of the industry wherethey describe specific economic factors affecting sugar farmers, sendletters to the press, meet with government officials in Washington D.C.and at symposiums, etc. In a press release on their website it ismentioned that they have lobbied the U.S. Department of Agricul-ture against an increase in the tariff rate quota (TRQ) by providinginformation about prices and supply: “Large candy companies haveengaged in a months-long lobbying campaign to pressure the USDAto increase the TRQ in hopes of boosting their profits. Sugarproducers have countered by pointing to stable sugar prices andsurplus raw sugar supplies as evidence that the market has enoughsugar and no TRQ increase is necessary.” (“USDA: No TRQ IncreaseRight Now”, August 2009).10 Furthermore, on another press releasethey mention that sugar producers delivered a study commissionedby the American Sugar Alliance on foreign sugar subsidies to U.S.government officials: “Sugar producers hope this handbook offoreign sugar subsidies – which was delivered today to key officialsat the U.S. Trade Representative's office, the U.S. Department ofAgriculture, and Congress – will give American negotiators theammunition they need to go after market-distorting practices atupcoming WTO discussions.” (“Foreign Sugar Subsidies Exposed”,September 2008).

9 Imai et al. (2009) mention that the fact that in the Grossman and Helpman (1994)model contributions do not explicitly enter the equilibrium protection equation mighthelp explain the low estimates of the weight on contributions relative to socialwelfare. In our model, in contrast, lobbying expenditures affect the equilibriumpolicies directly.10 See www.sugaralliance.org. A similar case is made on a letter to the Secretary ofAgriculture in July, 2010, in which they also provided an update on the domestic sugarmarket. Another similar example is mentioned on a previous press release: “Low andfalling sugar prices point to a U.S. market that's already well supplied, and noadditional imports are needed, America's sugar producers told Agriculture SecretaryTom Vilsack in a May 18 letter.” (“Study Shows Sweet Deal on U.S. Sugar; NoAdditional Imports Needed”, June 2009).

11 We are assuming that lobbying entails dissipation of resources, as in the case ofrent-seeking activities. However, we could assume instead that a fraction 0≤λ≤1 ofthe lobbying expenditures are earned by some members of the society and that wouldnot affect our results. The only difference would be that the parameter “a” that appearsin the second term inside the brackets in Eq. (11) would be multiplied by 1−λ; but aswill be clear later, this would not affect the coefficient or parameter estimates that wereport either.12 Our focus on equilibrium with full revelation follows Grossman and Helpman(2001) and also allows us to gain tractability to solve for the equilibrium policies.

128 P. Tovar / Journal of International Economics 83 (2011) 126–136

An additional example is the American Iron and Steel Institute(AISI), which defines its mission as: “To influence public policy,educate and shape public opinion in support of a strong, sustainableU.S. and North American steel industry (…)” (www.steel.org). In anoral testimony to the U.S. Trade Representative available on theirwebsite, they talked about China's subsidies and other tradedistorting measures and mention that “AISI urges the U.S. govern-ment to take a more aggressive approach to this issue”, and theyprovide information on output: “China's actions are particularlystriking when viewed in light of the recent global economic crisis. Inthe first half of 2009, the U.S. steel industry reduced crude steelproduction by over 50% compared to the first half of 2008. Similarly,worldwide crude steel production (excluding China) decreased by35%. In contrast, Chinese crude steel production actually increased torecord levels.” They add: “the U.S. government should aggressivelyenforce U.S. CVD law against subsidized imports from China.”Moreover, regarding the China-specific safeguard provision, theysay: “AISI commends the Administration for providing relief in theSection 421 case on tires”.

Finally, in the U.S. and other countries, antidumping and safeguardinvestigations are conducted using information provided by thepetitioning industry.

The rest of the paper is organized as follows. In the next section weintroduce the model, derive the lobbying expenditure function andthe equilibrium trade policies. In Section 3 we provide empiricalevidence on the importance of lobbying costs in trade policydetermination as well as various sensitivity analyses. Section 4concludes.

2. The model

The economic environment that we use is analogous to that ofGrossman and Helpman (1994). We consider a small competitiveeconomy for which world prices are given. Individuals have identicalpreferences but their factor endowments may be different. Theymaximize their utility, which is given by

u = x0 + ∑n

i=1ui xið Þ ð1Þ

where x0 is consumption of the numeraire good; xirepresentsconsumption of good i, i=1, 2, …, n. The sub-utility functions ui(⋅)are differentiable, increasing and strictly concave. If his income is E,an individual will consume xi=di(pi)=[u 'i(pi)]−1 of good i, andx0=E−∑ ipidi(pi) of the numeraire good. The indirect utilityfunction is given by v(p, E)=E+ s(p), where p is the vector ofdomestic prices and s(p)=∑ iui(di(pi))−∑ ipidi(pi) is the consumersurplus derived from the non-numeraire goods.

Good 0 is produced using only labor with a marginal product ofone. It is assumed that the supply of labor is large enough to ensurethat some of this good is always produced. Then, the wage is equal to 1in equilibrium. Each of the non-numeraire goods is produced withlabor (li) and a sector-specific factor (ki), under constant returns toscale. The specific factors are available in fixed supply. The rentsderived from the specific factors are a function of the domestic priceonly, given that the wage is fixed. These returns are denoted byΠi(pi).By Hotelling's lemma, output is given by yi=Π′i(pi).

The government can set trade taxes and subsidies. The net percapita revenue fromthesepolicies is givenby r(p)=∑ i(pi−pi*)[di(pi)−(1/N)yi(pi)], where pi* denotes the world price of good i and N is the totalpopulation. We assume that the government redistributes revenueuniformly to all individuals and thus r(p) equals the net transfer to eachindividual.

We also assume that each individual owns at most one specificfactor. The owners of each specific factor may decide to organizethemselves for political activity. Let J be the set of sectors that have

organized into lobby groups. Each organized group will offer thegovernment a contribution schedule Ci(p), which maps each policythat the government might choose into a campaign contribution level,and now we depart from Grossman and Helpman's (1994) setup byassuming that each organized group can also devote some resourcesto lobby in order to send a signal to the policymaker regarding thestate of the world (we say more about this in the next section). Thejoint gross welfare of the members of lobby i (gross of contributionsand lobbying expenditures) is given by:

Ωi = li + Πi pið Þ + θiN r pð Þ + s pð Þ½ � ð2Þ

where li is their labor supply (and labor income) and θi is the fractionof the population that owns some of the specific factor used inindustry i. We assume that ownership in any given sector is highlyconcentrated, so that θi→0 and each industry lobbies only for its ownproduct. This allows us to focus on the interaction between each lobbyand the government and abstract from lobby competition.

The government's objective function is a weighted sum ofcontributions and social welfare:

G = ∑i∈J

Ci pð Þ + aW pð Þ; a≥0 ð3Þ

where social welfare (obtained by adding indirect utilities over allindividuals) is given by:

W pð Þ = l + ∑n

i=1Πi pið Þ + N r pð Þ + s pð Þ½ �−∑

i∈JL μið Þ ð4Þ

The last term denotes endogenous lobbying expenditures, whichwill be defined in the next section.11

2.1. Lobbying costs

We allow the interest groups to choose the size of their lobbyingexpenditures. Our modeling of lobbying expenditures is based on theapproach of Grossman and Helpman (2001, Ch. 5.2), applied to thespecific case of trade policies and extended to also include campaigncontributions along the lines of Grossman and Helpman (1994) andpreviously described. We focus on an equilibrium with full revelationand many possible states of nature.12 Let output of good i beyi = μi f li; ki

� �, where μi is a continuous random variable uniformly

distributed, say, between zero and one (e.g. a Hicks-neutral productivityshock). Thus, the policymaker initially believes that all values betweenzero and one are equally likely, but will update his beliefs based on thesignal that the interest group sends by incurring lobbying expenditures.The policymaker expects that the interest group will spend an amountL(μi) if the state of nature is μi, and that each state will lead to a differentexpenditure level. Therefore, he believes that he can discern the state ofnature by observing the amount that the interest group spends onlobbying. Thewelfare of lobby i, net of lobbying expenditures (but grossof contributions), can thus be written as:

Wi = li + pi μið Þμi f li; ki� �

−wli−L μið Þ ð5Þ

and its welfare net of contributions is thenWi−Ci(μi). The reasonwhyC depends on μ is that we assume that the lobby offers C to the

15 There may be alternative ways of modeling the role of access costs/campaigncontributions for trade policy determination. We take one (standard) approach hereand leave other possibilities for future research. Our main focus, however, is onintroducing endogenous informational lobbying expenditures. We also note that if wedid not include contributions in our model and had the government maximize apolitical support function instead, the equilibrium protection (Eq. (11)) would be

129P. Tovar / Journal of International Economics 83 (2011) 126–136

government before learning the value of the state of nature. Thus, C isoffered contingent on the value of μ but will be paid after the state ofnature is revealed to the lobby and signaled to the government. Weexplain this further in the next section.

Next, we need to find a lobbying expenditure function such thatthe interest group's strategy validates the beliefs of the policymaker.We have that L(0)=0, since in that case output is zero and there is noreason to lobby. We also need that, in any state, the marginal cost ofsignaling a slightly higher value of μi be equal to the marginal benefitthat the interest groupwould get from having the policymaker believethat μi is a little higher. The marginal cost of signaling a higher value ofμi is given by L′(μi). The marginal benefit is given by:

∂Ωi

∂ti∂ti∂μi

− dCi

dμi= p4i yi

∂ti∂μi

− dCi

dμi= p4i μi f li; ki

� � ∂ti∂μi

− dCi

dμi

where ti is the ad valorem trade tax or subsidy. Therefore, we need:

L′ μið Þ = p4i μi f li; ki� � ∂ti

∂μi− dCi

dμi

Integrating both sides of the previous equation we get13:

L μið Þ = tip4i μi f li; ki� �

−∫μ maxμ min

tip4i f li; ki� �

dμ−Ci ð6Þ

We can verify that if the policymaker believes that the interestgroup will spend L(μi) when the state of nature is μi, the interest groupwill in fact want to follow that behavior. Given a state μi, the lobbycould signal that the state is x by spending L(x) on lobbying, whereL xð Þ = tip4i xf li; ki

� �−∫tip4i f li; ki

� �dx−Ci xð Þ. The policymaker would

then set a tariff ti(x) instead of ti(μi). The welfare for the interest groupgross of contributions would then be Wi xð Þ = li + pi xð Þμi f li; ki

� �−

wli−L xð Þ, and its net welfare would be Vi(x)=Wi(x)−Ci(x). But thevalue of x that maximizes Vi is determined by:

p4i∂ti∂x μi f li; ki

� �−L′ xð Þ− dCi

dx= 0

and since L′ xð Þ = p4i∂ti∂x xf li; ki

� �− dCi

dx , we have that Vi is maximizedwhen x=μi for all μi. That means that the interest group has noincentive to deviate and signal a different state of nature.

From Eq. (6) we have that the lobbying function depends onoutput. This is because the marginal benefit from protection increaseswith output, and thus when output is higher (e.g. due to higher μ) thesector will devote more resources to lobbying and obtain moreprotection (we show this in the next section). It also depends on t,since in order to receive higher protection the sector needs to spendmore on lobbying. Finally, it depends on C because if the industryobtains higher protection it will have to pay higher contributions, andthat reduces the marginal benefit from lobbying.14

13 After this equation we omit the limits of integration to simplify notation.14 The potential for transmission of information via lobbying depends on certainsimilarity in the interests of the policymaker and the lobby. When one considersinformation regarding output, we have that if for example output increases, ceterisparibus both the lobby and the government have a preference for higher protection.This may not be the case if one focuses on information on demand conditions. Supposethat there is a shock that increases demand. Since that increases imports, the socialcost of protection increases (for given values of the other variables), and this createsan incentive for the government to lower protection; however, the lobby does notwant a lower tariff in such a situation (for a given output and world price). This createsa problem for the transmission of information. For example, the condition that themarginal cost of signaling a higher value of the state of nature be equal to the marginalbenefit for the lobby would not hold since the lobby does not benefit from lowerprotection. The shock we focus on both affects the industry's profits directly andimproves the prospects for information transmission, and thus may be more relevantin terms of its applicability also.

2.2. Trade policies

In the first stage, each interest group offers the government acontribution schedule. We assume that at that time the state of naturehas not been determined, and thus contribution schedules areselected as functions of the state of nature. In other words, for eachpossible value of the state of nature there is a schedulematching tradepolicies to contribution levels. However, we note that the relevantcontribution level here is the one associated with the lobby's desiredtrade policy. The lobby can offer the government what it would get ifthe lobby's offer was absent. Under our assumption of ownershipconcentration, contribution levels associated with other possiblepolicies do not affect other lobbies' offers; e.g. the lobby can offer zerofor other alternatives and only offer a positive contribution for thepolicy level it wants. Thus, the lobby offers a schedule to thegovernment stating that if the state of nature takes a value of, say,μ0, it will give a contribution of C0⁎ in exchange for t0⁎, which is thelobby's desired policy when μ=μ0; and analogously for the otherpossible values of μ. We consider that this is a reasonable assumption,since, as stated by Grossman and Helpman (2001), “Groups oftensecure such access long before they know what issues will appear onthe policy agenda. Accordingly, it makes sense to think of the accesscosts as being incurred before a group learns the state of the world.”(p. 144).15 In the second stage, the state of nature is determined andobserved by the lobbies. Each interest group can choose to spendsome amount on lobbying in order to signal the state of nature to thepolicymaker. The government observes the lobbying expendituresand then sets the policies and collects the contributions.

Therefore, as mentioned before, the contribution is offeredcontingent on the value of the state of nature but is paid once thelatter is revealed to the lobby and signaled to the government. Oncethe lobby has revealed the state of nature, the next stage proceeds in away similar to Grossman and Helpman (1994) with concentratedfactor ownership in the sense that the government knows the value ofμ and thus knows that the lobby is effectively offering a certaincontribution C⁎ in exchange for the policy it desires, t⁎. It will thenchoose the policy and collect the contribution.

For each lobby i, the equilibrium policy must maximize the jointwelfare of that lobby and the government16:

p0i ≡arg max Wi pið Þ−C0i pið Þ

n o+ C0

i pið Þ + aW pð Þn o

= Wi pið Þ + aW pð Þ

similar with the exception that the lobbying function would not be affected by C. Weinclude contributions for two reasons. First, we want to show that introducinginformational lobbying costs into the Grossman and Helpman (1994) model allows usto obtain lower values of the weight that the government attaches to social welfarerelative to political contributions, since the high values previously obtained areconsidered a puzzle in the literature. Second, we also want to allow for the existence ofaccess costs/contributions since those have been identified as a type of lobbying costsby the literature on SIGs (see Grossman and Helpman, 2001 for a discussion of whypoliticians may require these payments). Analogously, and in contrast to the Grossmanand Helpman (1994) model, if the government maximized a weighted sum ofconsumer surplus, producer surplus redefined to be net of lobbying expenditures, andtariff revenue, with a larger weight given to the producer surplus of organized sectors,we would not obtain an identical expression for the equilibrium policies. Thedifference is that in such case the lobbying function would not be affected by C, and adifferent lobbying function would thus translate into a different protection equation.16 This is similar to condition c) from Proposition 1 in Grossman and Helpman(1994).

17 Alternatively, this expression can also be obtained by solving for a from Eq. (11).18 Gawande and Krishna (2003) refer to the previous estimates of the weight that thegovernment attaches to political contributions relative to social welfare as puzzlinglylow (i.e. a would be puzzlingly high) and “(...) enough to cast doubt on the value ofviewing trade policy determination through this political economy lens.” (p. 20).19 They are that the import demand function is not too convex and the supplyfunction is not too concave or too convex. In addition, if m′ipi+ tim″i(pi)2b0 anothersufficient condition is that a is small enough. None of those conditions are necessary.20 See Karacaovali (Forthcoming) for a review of the previous literature on that topicalso. He uses an extension of the Grossman and Helpman model but does not considerinformational lobbying.

130 P. Tovar / Journal of International Economics 83 (2011) 126–136

The first-order condition is:

∂Wi

∂pi+ a

∂W∂pi

= 0 for all i∈ J ð7Þ

From Eq. (6) we can write the lobbying expenditure function as:

Li = p4i ℓ ti; yi;Ci = p4i� � ð8Þ

where ℓ ti; yi;Ci = p4i� �

= tiμi f li; ki� �

−∫ti f li; ki� �

dμ−Ci = p4i . UsingEqs. (7), (8) and the definitions of Wi and W, we can obtain theequilibrium policies as follows. Recall that Eq. (5) is: Wi = li + piyi−wli−Li. Therefore, we have:

∂Wi

∂pi= yi−

∂Li∂pi

= yi−∂Li∂ti

1p4i

; since pi = ð1 + tiÞp4i

Or:

∂Wi

∂pi= yi−L′t

1p4i

ð9Þ

From Eq. (4) we obtain:

∂W∂pi

= yi−L′t1p4i

+ pi−p4i� �

m′i + mi−di = yi−L′t

1p4i

+ pi−p4i� �

m′i−yi

Or:

∂W∂pi

= −L′t1p4i

+ pi−p4i� �

m′i ð10Þ

Using Eqs. (9) and (10), we can rewrite the first-order condition (7)as:

yi−1 + að Þp4i

L′t + a pi−p4i� �

m′i = 0

which in turn can be rewritten as:

pi−p4ip4i

= − 1am′i p4i =mi

yimi

− 1 + að Þp4i mi

L′t

" #

Or, since Li=pi*li and the equilibrium policy corresponds to anorganized sector:

ti1 + ti

=1aei

yimi

−1 + ami

ℓ′t ti; yi;Ci = p4i� �� �

Ii ð11Þ

where ti = p i−p4i� �

= p4i is the equilibrium ad valorem trade tax or sub-sidy for i∈J; Ii=1 if i∈ J and zero otherwise; and ei =−m′i pi

� �pi =mi pi

� �is the elasticity of import demand (defined to be positive) or exportsupply (defined to be negative). All other equilibrium variables aredenoted with a tilde.

This expression differs from the one in the Grossman and Helpman(1994) model in that we have a second term in the brackets reflectingthe lobbying costs that the SIG incurs in order to obtain its desired policylevel. Thus, from Eq. (11), protection (for an organized industry)increases with output and falls with imports because a higher outputmeans a higher benefit from protection for the lobby, and the welfarecost from protection is lower the lower is the volume of imports. Itdecreases with the elasticity of import demand, since a higher elasticityis associated with a larger deadweight loss from protection. Finally,protection decreases with the derivative of the lobbying cost withrespect to the tariff because a higher value of this derivative means alarger cost to the lobby from obtaining a certain increase in protection.Furthermore, we have that a lower value of a (the weight that the

government places on socialwelfare)may be needed for given values ofthe output–import ratio divided by the elasticity as compared to theGrossman and Helpman (1994) model. Mathematically, joint efficiencyimplies equal marginal rates of substitution for the government andlobby, as follows: Gt/GC=Vt/VC, or a[ti(pi*)2m′

i −L′t ]/1=(yipi*−L′t)/(−1), which in turn implies a=(yipi*−L′t)/[ti(pi*)2(−m′

i)+L′t ].17 IntheGrossmanandHelpmanmodel, in contrast,weobtain a=yipi*/ti(pi*)2

(−m′i). Thus, not accounting for the informational lobbying costs (the

term L′t) leads to a higher value of a. The intuition is the following. Thesecond term on the right-hand side of Eq. (11) is the marginal lobbyingcost of protection, which is essentially the marginal cost of signalinginformation. Due to this additional lobbying cost, themarginal benefit tothe industry from an increase in protection is lower, which implies thatthe marginal benefit to the government in the form of extracontributions is now smaller. Not including these informationallobbying costs leads to overestimate the increase in contributions dueto an increase in protection, and this larger response of C in turn wouldimply the government attaches a lower weight to contributions (givent) or a higher weight to social welfare relative to our model. This mayhelp solve an important puzzle in the political economy literature oftrade policy, which is the high values of a that have been estimated inempirical tests of the Grossman and Helpman (1994) model.18

For the government to be able to infer the state of nature from theamount spent on lobbying it should also be true that lobbyingincreases with productivity (μ). We can verify this by showing thathigher productivity leads to higher protection. In the Appendix weshow that and provide sufficient conditions for that relationship tohold.19 The reasonwhywhen productivity is higher a sector will lobbyfor higher protection is that the sector has more to gain fromprotection. Similar to the size effect in the Grossman and Helpman(1994) model, we have that the marginal benefit of protection alsoincreases with productivity (as it does with size). There is evidence insupport of this prediction. Karacaovali (in press) is the first paper toestimate the relationship between trade liberalization and produc-tivity in a way that properly accounts for the potential endogeneity.20

He finds that between 1983 and 1998, tariffs in Colombia were higherin more productive sectors, the intuition being similar to theexplanation provided previously.

So far we assumed that the interest groups can choose exactly howmuch to spend on lobbying, for any value of μi. In the Appendix weconsider the possibility that there is a minimum cost that the lobbieshave to incur in order to send a signal to the policymaker. Aninteresting result that arises if there are fixed lobbying costs is that it ispossible to have that (organized) sectors that do not spend money onlobbying receive protection.

3. Empirical evidence

3.1. Econometric specification

Eq. (11) defines the equilibrium trade policies. Based on this wespecify the following equation to be estimated:

ti1 + ti

= β0 + β1yi

mieiIi + β2

ℓ′timiei

Ii + εi ðE1Þ

131P. Tovar / Journal of International Economics 83 (2011) 126–136

where β1=1/aN0, β2=−(1+a)/ab0 and εi is the regression errorterm. The latter is included to capture potential measurement error inthe variables and other factors we may not be accounting for in themodel that could influence the determination of trade policy. We willtest the predictions regarding the signs of the coefficients as well asobtain an estimate for the parameter a—the weight that thegovernment places on social welfare relative to contributions.

From Eq. (E1) it is clear that we cannot directly observe thederivative of the lobbying cost with respect to the policy. Therefore,we will proceed in two stages. First, this derivative will be estimatedfor each sector in a way that will be detailed later on, and after that weestimate Eq. (E1). We will also correct that variable for the fact that itis estimated, as explained in Section 3.3.

3.2. Data

Weuse data for the U.S. at the 6-digit HS level in 1999. Protection ismeasured as the ad valorem equivalent of non-tariff barriers (NTBs).The reason for using NTBs rather than tariffs is that tariffs weredetermined by multilateral (GATT/WTO) negotiations, while themodel assumes that the country is able to set its trade policiesunilaterally.21 NTB data for the U.S. is available for 1999, and thus wefocus on that year. The ad valorem equivalents of NTBs are estimatedby Kee et al. (2009) at the HS-6 level. Data on import demandelasticities at the HS-6 level are from Kee et al. (2008). We decided toleave the elasticity on the right-hand side, in contrast to Goldberg andMaggi (1999) who take it to the left-hand side, for two reasons: i) itallows us to have variation at the HS-6 level in the right-hand sidevariables, and ii) the elasticities that we use are estimated with muchgreater precision, with about 90% of them being significant at the 1%level.22 Gawande and Bandyopadhyay (2000) and Mitra et al. (2002),among others, also adopt the approach of leaving the elasticity on theright-hand side.

Data on output and imports are from the World Bank's Trade,Production and Protection database (Nicita and Olarreaga, 2007) andare measured at the 3-digit ISIC level.23 Furthermore, it can easily beverified using Eq. (8) that the third term in Eq. (E1) is equivalent to L′tdivided by the value of imports at world prices and the elasticity,which is how we measure it. We collected data on lobbyingexpenditures from the Center for Responsible Politics (available atwww.opensecrets.org), which uses its own coding system to classifycontributions by industry and interest group.24 A significant amountof work was devoted to collect these data and match it at the 3-digitISIC level.25

According to the data we collected, the industry with highestlobbying expenditures during 1998–2006 (the period for which thedata was available) was transport equipment, with over $1.3 billion,followed by petroleum refineries, other manufactured products,tobacco, and industrial chemicals (see Fig. 1).

21 For this reason empirical tests of the Grossman and Helpman (1994) model alsofocused on NTBs (e.g. Goldberg and Maggi, 1999; Gawande and Bandyopadhyay,2000). However, an improvement in our study is that we use ad valorem equivalents ofNTBs rather than their coverage ratios, which as is well known have the potentialproblem that they may understate or overstate protection.22 Moreover, any remaining measurement error is addressed via the use ofinstrumental variables.23 Since output is measured at domestic prices and imports are measured at worldprices, in order to construct the output–import ratio we divide output by (1+ t) beforedividing it by imports.24 Their data is compiled using the semi-annual lobbying disclosure reports filed withthe Secretary of the Senate's Office of Public Records.25 In several cases this involved looking for online information about individual firms'activities in order to match them to an ISIC-3 sector. Matching the data at the ISIC-3level was a reasonable choice given the level of aggregation at which the lobbying datais reported by the Center for Responsible Politics, and that it also allows us to avoidclassification errors that would be likely at a more disaggregated level.

The organization indicator is initially determined following anapproach similar to Goldberg and Maggi (1999), but with theimportant difference that we focus on lobbying expenditures insteadof campaign contributions. We classified a sector as organized if itslobbying expenditures in 1998 exceed $2 million, which are also thesectors with expenditures higher than $2 million in 1999. This alsoincludes all sectors with PAC contributions above $500,000. Thiscutoff level was chosen for two reasons: i) we think this is a naturalbreak given that there is an important difference in the level ofexpenditures between sectors below and sectors above it26; and ii) itallows us to have a meaningful number of both organized andunorganized sectors. With this classification we obtain that 57% of theISIC-3 sectors are organized. We use this classification as a startingpoint but we also experiment with alternative thresholds asrobustness checks. We also perform another sensitivity analysis anddetermine which industries are organized using data on organizationslisted in the World Guide to Trade Associations, as described inSection 3.3.2.

3.3. Methodology and results

3.3.1. Baseline estimation and robustnessSince the dependent variable is censored below zero and above

one, we begin by using a Tobit estimation procedure with doublecensoring. As we mentioned before, in order to estimate Eq. (E1) wefirst need to obtain estimates of the derivative of the lobbying costwith respect to trade protection for each sector. We do this by alsoexploiting time series variation in data on lobbying expenditures andprotection. In particular, for each ISIC-2 sector, we regress lobbyingexpenditures (at the ISIC-3 level) on protection during the period1998–2004.27 Since data on NTBs and their ad valorem equivalents isonly available for 1999, the protectionmeasurewe use here is the sumof the ad valorem tariff, for which data is available from 1998 to 2004,and the NTB ad valorem equivalent. Both are taken at the ISIC-3 levelfrom the World Bank Trade, Production and Protection database. Basedon Eq. (8), we also include PAC contributions as a regressor.28 Sincethere is reason to believe that protection is endogenous to lobbyingexpenditures, we use instrumental variables, as discussed next.

Variables suggested by the literature that may be used asinstruments for protection include exports (see Trefler, 1993; Leeand Swagel, 1997); therefore, protection was instrumented for usingthe lag of the change in exports and the value of exports.29 We alsoinclude as an instrument the European Union's tariff levels. These arecorrelated with U.S. protection levels and would be a valid instrumentas long as lobbying expenditures in the U.S. do not determineEuropean tariffs. We think this is a reasonable assumption given thatthe latter are more likely to be influenced by the lobbyingexpenditures of European firms.30 Despite the fact that due to thedata limitations the average number of observations we have for eachISIC-2 industry is about 30, the majority of the derivative estimatesthat we obtain are positive (about 70%), as expected, and about half

26 For example, in 1998 the lobbying expenditures of the two sectors right below thisthreshold were $1.8 million and $1.6 million; while those of the two sectorsimmediately above were $2.7 million and $2.9 million.27 This allows us to have a sufficient number of observations at the ISIC-3 level withineach ISIC-2 sector.28 The data on PAC contributions was also obtained from the Center for ResponsiblePolitics. Eq. (8) also suggests that we may want to include output in the regression, butdata on output is only available until 2001, which would not leave us with enoughobservations. However, since we use instrumental variables we expect that this shouldnot affect our results in an important way, and we confirm this for a couple of sectorsthat had the most observations. Year dummies are also included.29 Other potential instruments such as industry concentration or factor shares are notcompletely available for the time period we are using.30 We also explored the possibility of using tariffs from other developed countries,including countries that trade less with the U.S., but either tariff data was not availablefor that period or their tariffs were not positively correlated with U.S. tariffs.

0

200000000

400000000

600000000

800000000

1000000000

1200000000

1400000000

384

353

390

314

351

313

342

372

331

371

341

311

369

352

382

381

383

385

355

322

321

362

324

356

332

323

361

354

Fig. 1. Lobbying expenditures (US$) by ISIC-3 industry 1998–2006.Source: Author's calculations using data from the Center for Responsible Politics.

132 P. Tovar / Journal of International Economics 83 (2011) 126–136

had significance higher than the 5% level (these results are not shownto save space, but details are available on request). Later on we alsocorrect in the second stage for the fact that this variable is estimated,but as will be shown this does not affect our results.

Table 1 shows summary statistics. The results from the Tobitestimation of the protection Eq. (E1) are presented in the first columnof Table 2. The coefficients are significant at least at the 5% level andhave the expected signs, providing support for themodel. Using β1 wecan obtain an estimate of the weight that the government places onsocial welfare, which we find to be about 1000. This value of a is lowerthan the over 3000 value obtained by Gawande and Bandyopadhyay(2000) for the U.S. in 1983, but it is still very high (lower estimates areobtained and shown below when we use an instrumental-variableTobit). We do not retrieve the value of a from the second coefficient,

Table 1Summary statistics.

Variable Mean Standarddeviation

Minimum Maximum

Dependent variablet/(1+ t) 0.043 0.117 0 0.758

Explanatory variablesI×y/(m×e) 5.615 65.806 0 3763.693I×ℓ′t /(m×e)a 5.247 58.966 −11.035 2624.300Unorg 0.493 0.500 0 1

a Indicates that the variable was scaled by 1000. Number of observations is 3657.

Table 2Tobit estimates of the determinants of protection.

Explanatory variables (1) (2) (3) (4)

I×y/(m×e) 0.0009*** 0.0008*** 0.0008*** 0.0008***(0.0003) (0.0003) (0.0003) (0.0003)

I×ℓ′t /(m×e) −0.0005** −0.0005** −0.0005** −0.0005**(0.0002) (0.0002) (0.0002) (0.0002)

Unorg −0.0100(0.0153)

Unorg×y/(m×e) −0.0030** −0.0029**(0.0013) (0.0013)

Unorg×ℓ′t /(m×e) −0.0005(0.0018)

Constant −0.2676*** −0.2623*** −0.2601*** −0.2601***(0.0125) (0.0148) (0.0127) (0.0127)

Observations 3657 3657 3657 3657Pseudo R-squared 0.005 0.005 0.007 0.007

Notes: Standard errors in parentheses. * significant at 10%; ** significant at 5%; ***significant at 1%.

β2, because the size of this coefficient is sensitive to units ofmeasure.31

We can also compare the performance of our model versus theGrossman andHelpmanmodel (under the assumption of concentrationof ownership of the specific factors). The Log-likelihood in our modelwas −1410.8, which is higher by a non-negligible amount than the−1413.4 value obtained under the Grossman and Helpman model.More importantly, the likelihood ratio test rejects the Grossman andHelpmanmodel in favor of ourmodel at the 5% level. This indicates thatincluding endogenous lobbying costs in the model is important toexplain the variation of protection across sectors.

As mentioned earlier, a few sectors were estimated to have anegative value for the lobbying derivative. So far we have kept thosevalues as they were estimated, which we expect would bias theresults against finding support for our model. We also examined thesensitivity of the results to dropping the three sectors with negativevalues from the sample. When we do this we find that bothcoefficients are now significant at the 1% level (andwith the predictedsign); i.e. we find stronger support for the model, as expected.32

Similarly, now the likelihood ratio test rejects the Grossman andHelpman model in favor of our model at the 1% level.

In column 2 of Table 2 we add a dummy variable equal to one forunorganized sectors, and the previous results are robust to adding thisdummy. Its coefficient is negative and not significant. In column 3 weinteract this dummy with the output–import ratio divided by theelasticity (y/me). We do this because we do not model the effects oflobby competition, and in the general form of the Grossman andHelpman (1994) model, competition among lobbies leads to anegative effect of y/me on protection for unorganized sectors. Wefind a similar effect here but our previous results still hold. As anadditional robustness test, in column 4 we also interact theunorganized dummy with our second regressor. We expect againthat the predicted effects of themodel's variables on protection do nothold for unorganized industries and this is indeed what we find (thefirst regressor has the opposite sign for unorganized sectors and thesecond is not significant).

3.3.2. Additional sensitivity analysisPotential concerns associated with the results in the previous

section are possible attenuation bias due to measurement error in thevariables and endogeneity. In this section we address these concerns

31 For example, while the first regressor includes the output–import ratio, the secondincludes the level of imports and thus the magnitude of its coefficient depends on theunits of measure used.32 The results are available on request.

Table 3IV Tobit estimates of the determinants of protection and errors-in-variables correction.

Explanatory variables Errors-in-variables correction

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

I×y/(m×e) 0.0198*** 0.0077*** 0.0136*** 0.0100*** 0.0161*** 0.0103***(0.0071) (0.0023) (0.0040) (0.0038) (0.0043) (0.0038)

I×ℓ′t /(m×e)a −0.0236*** −0.0078** −0.0097*** −0.0039** −0.0206*** −0.0073**(0.0090) (0.0034) (0.0029) (0.0018) (0.0056) (0.0034)

Constant −0.2731*** −0.0372 −0.2649*** 0.1270 −0.2697*** 0.1236(0.0269) (0.0861) (0.0195) (0.1407) (0.0200) (0.1394)

Sector fixed effects No Yes No Yes No YesObservations 3657 3657 3657 3657 3657 3657Wald test of exogeneity (p-value) 0.33 0.12 0.24 0.23 0.22 0.23

Notes: Standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. All specifications use an IV Tobit. We instrument for the import demand elasticityusing the average of the elasticities for the European Union, Canada and Mexico. The instruments for the other variables are described in the text.

a Indicates that in columns (3)–(6) the variable was scaled by 1000 and we also corrected for the errors-in-variables problem.

133P. Tovar / Journal of International Economics 83 (2011) 126–136

via the use of instrumental variables. Furthermore, we correct for thefact that we have estimated the derivative of the lobbying cost withrespect to protection.

The right-hand side variables in Eq. (E1) are potentially endogenousand enter the equation nonlinearly. In addition, the organizationindicator, the elasticity and the lobbying cost derivative may bemeasuredwith error. Therefore,we use a two-step IV Tobit procedure.33

Some of the instruments we use are motivated by previous tests ofpolitical economy models by other authors. The variables used toinstrument for the political organization variable include the inverseof the number of establishments (a measure of concentration), ameasure of scale (value added per firm) and the number ofemployees. The instruments for the output to import ratio includethe ratio of labor to value added and scale. The import demandelasticity is instrumented using the average of the elasticities for threeother countries as well as its square. Finally, the lobbying costderivative is expected to depend on how much a sector needs toincrease its lobbying expenditure in order to obtain an increase inprotection, which in turn may be affected by the bargaining power ofthe lobby relative to the government. Some studies of the determi-nants of a firm's bargaining power relative to its workers have relatedit to variables such as capital intensity (Brock and Dobbelaere, 2006;Doiron, 1992), industry concentration (Veugelers, 1989; Dumontet al., 2006) and asset liquidity (Brock and Dobbelaere 2006), amongothers. Some of these should also be correlated with firms' bargainingpower relative to the government. Thus, we instrument for thelobbying cost derivative using the labor share of value added, theinverse of the number of establishments, and we also include aHerfindahl index of export value.34

The results corresponding to our baseline specification appear incolumn 1 of Table 3. Both of the coefficients of interest are significantat the 1% level and have the predicted signs. The estimate that weobtain for the parameter a, the weight the government attaches tosocial welfare, is now about 50 (based on the first coefficient fromcolumn 1), which is much lower than the value we obtained when wedid not use instrumental variables in the Tobit estimation. We also

33 As is well known, full maximum likelihood estimation of instrumental-variableTobit is extremely difficult when there is more than one endogenous regressor. Wethus follow the usual approach of employing a two-step estimation procedure thatuses Newey's minimum chi-squared estimator.34 The idea behind the inclusion of the last variable is that if the source of exports ismore concentrated, exporters will have a smaller incentive to free ride when it comesto retaliation or negotiation of trade policy bindings in the WTO, which would make itmore difficult or costly for domestic lobbies to obtain higher protection. As for theother variables, a higher labor share generally implies a lower capital share in valueadded, indicating more flexibility for the industry in shifting resources to alternativeuses and thus increasing its bargaining power. A more concentrated industry may havemore bargaining power due to larger market power and higher profits (although theevidence on the sign of this effect on bargaining power of the firm relative to the unionis mixed—Dumont et al., 2006).

note that in all the instrumental-variable results that we report theWald test of exogeneity (shown at the bottom of the tables) is passed.

In column 2 we test for the robustness of our results to controllingfor unobserved heterogeneity by adding industry fixed effects(defined at the HS-1 level).35 The results are robust to this. Inaddition, the results are robust to clustering the standard errors at theISIC-3 level.36

Since we estimated one of our variables prior to performing theTobit estimation of the protection equation, we also use an errors-in-variables correction procedure based on Gawande (1997) and Fuller(1987).37 The results corresponding to our baseline specification aftercorrecting for this potential problem are shown in column 3 of Table 3.Our previous results still hold; both coefficients have the expectedsign and are significant at the 1% level. Furthermore, the probability ofthe F-statistic in the first stage was 0.000 for all instruments.

In column 4 we add sector fixed effects to the specification ofcolumn 3. The results are again robust to controlling for unobservedheterogeneity. So far we defined our sector fixed effects at the HS-1level. This has the advantage that it does not lead us to lose additionalobservations in the estimation. We examined the sensitivity of ourresults to the way of defining the fixed effects by re-estimating thespecification of column 3 but including ISIC-2 fixed effects. The results(not shown but available on request) are robust to this.

We also examined the robustness of the results to introducingnon-linearities in the initial stage in which we estimate the lobbyingcost derivative. We tried including the squares of the regressors –

protection and PAC contributions – as well as their cross product, andfound that only the square of contributions was significant in some ofthe by-sector regressions. Therefore, in column 5 of Table 3 we showthe results of the IV Tobit estimation in which the derivative of thelobbying cost was estimated including also the square of contribu-tions, and corrected for the errors-in-variables problem. Column 6shows results from a similar specification but including sector fixedeffects. The results are robust to allowing for non-linearities in theinitial stage as explained.

Table 4 reports the results from several additional robustness tests.All specifications use an IV approach and correct for the errors-in-variables problem as previously described. In the first two columnsweadd to our baseline specification a dummy for unorganized industries,

35 Later on we test the robustness of the results to using other types of fixed effects(defined at the ISIC level).36 In order be able to do this we used an IV-GMM estimation procedure. Althoughthis procedure does not account for the data censoring, the coefficients weresignificant at the 1 and 5% levels, and the results are also robust to heteroskedasticity.We also note that although some variables do not vary at the HS-6 level due to theindustry-level nature of their data, the regressors we use all vary at the HS-6 level dueto interactions with the other variables.37 See Gawande (1997) or Gawande and Bandyopadhyay (2000) for a description ofthe procedure.

Table 4IV Tobit estimates of the determinants of protection: robustness.

Explanatory variables (1) (2) (3) (4) (5) (6)

I×y/(m×e) 0.0098⁎⁎ 0.0183⁎⁎⁎ 0.0133⁎⁎⁎ 0.0111⁎⁎⁎ 0.0489⁎⁎⁎ 0.0224⁎⁎⁎

(0.0047) (0.0055) (0.0040) (0.0042) (0.0172) (0.0084)I×ℓ′t /(m×e)a −0.0088⁎⁎⁎ −0.0110⁎⁎⁎ −0.0110⁎⁎⁎ −0.0040⁎⁎ −0.0530⁎⁎⁎ −0.0050⁎⁎

(0.0029) (0.0021) (0.0030) (0.0019) (0.0107) (0.0021)Unorg −0.0561 0.1051

(0.0652) (0.0890)Unorg×y/(m×e) −0.0073⁎ −0.0047 0.0186 0.0092

(0.0042) (0.0042) (0.0289) (0.0103)Unorg×ℓ′t /(m×e) −0.0035⁎⁎ −0.0020⁎⁎

(0.0014) (0.0008)Constant −0.2137⁎⁎⁎ 0.2942 −0.2379⁎⁎⁎ 0.0931 −0.1775 −0.2154

(0.0532) (0.1995) (0.0259) (0.1615) (0.1517) (0.3132)Sector fixed effects No Yes No Yes No YesObservations 3657 3657 3657 3657 3657 3657Wald test of exogeneity (p-value) 0.73 0.35 0.71 0.54 0.11 0.41

Notes: Standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%.a Indicates that the variable was scaled by 1000. In all specifications we corrected for the errors-in-variables problem.

Table 5IV Tobit estimates of the determinants of protection: robustness to organization classification.

Explanatory variables Lobbying expenditures cutoff Number of groups inWGTANmean

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

I×y/(m×e) 0.0136*** 0.0113*** 0.0148*** 0.0247*** 0.0055***(0.0040) (0.0037) (0.0047) (0.0059) (0.0017)

I×ℓ′t /(m×e)a −0.0097*** −0.0077*** −0.0090*** −0.0157*** −0.0028**(0.0029) (0.0027) (0.0030) (0.0036) (0.0014)

Constant −0.2649*** −0.2577*** −0.2635*** −0.2790*** −0.2371***(0.0195) (0.0185) (0.0202) (0.0223) (0.0192)

Observations 3657 3657 3657 3657 3657Wald test of exogeneity (p-value) 0.236 0.260 0.275 0.223 0.104

Notes: Standard errors in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%.a Indicates that the variable was scaled by 1000. All specifications are corrected for the errors-in-variables problem.

134 P. Tovar / Journal of International Economics 83 (2011) 126–136

without and with sector fixed effects, respectively. The results areagain robust to the inclusion of this variable.38 In columns 3 and 4 weinteract this dummy with the output–import ratio divided by theelasticity (without and with fixed effects). As we found in the non-IVregressions the coefficient of this variable is negative, although oncefixed effects are included it becomes not significant. More impor-tantly, our key variables are still significant with the predicted signs.The last two columns of Table 4 also add the unorganized-industrydummy interacted with the second regressor of our baselinespecification. Although in this case we find this variable's coefficientto be negative, it is smaller in magnitude than the one for organizedindustries. This is consistent with the model, which predicts that weshould find stronger effects for the industries more likely to beorganized. Furthermore, based on the results from column 5 we findthe value of a to be 20, muchmore reasonable than previous estimatesobtained for the U.S. Moreover, this lower estimate of a is obtaineddespite our assumption of concentration of ownership of the specificfactors, and thus it may actually be an overestimate.39

38 We note that in these two specifications we can still use the two-step Tobitprocedure to test for the exogeneity of the regressors even though one of theregressors is not continuous (the dummy for unorganized sectors). As shown at thebottom of the table, we cannot reject the null hypothesis of exogeneity, which alsoindicates that the analogous results and coefficients from column 2 of Table 2 are valid.39 We thank an anonymous referee for pointing this out.

We had initially classified an industry as organized if its lobbyingexpenditures were higher than $2 million. As additional sensitivitytests to the way of defining the organization variable, we classify anindustry as organized if its lobbying expenditures in 1999 exceeded$3 million, $4 million, $5 million and $6 million, respectively. Theresults from re-estimating our baseline regression using thesethresholds appear in Table 5 (the results with the $5 million thresholdare identical to those with $4 million and thus are not reported). Asshown, they are robust to these alternative classifications as well.

We also perform another sensitivity analysis and determinewhether a given sector is politically organized by using data onorganizations listed in theWorld Guide to Trade Associations in 1999.We classify an industry as organized if the number of groups it listedin the World Guide to Trade Associations exceeded the mean numberof groups listed by U.S. industries. The results are robust to this and arereported in column 5 of Table 5.

4. Conclusion

We study the role that endogenous informational lobbying costsplay in the determination of trade policies. Although the focus of thepolitical economy literature on trade policy has been on campaign (orpolitical) contributions, in practice lobbying expenditures far exceedcampaign contributions. In addition, several authors have argued thatPAC contributions buy access only, which may then be followed bylobbying activities. In this paper we develop a model in which special

135P. Tovar / Journal of International Economics 83 (2011) 126–136

interest groups can send a signal regarding the state of the world tothe policymaker, which is not directly observed by the latter. Wederive the equilibrium lobbying expenditure function and then showthat lobbying costs affect the equilibrium policies directly. Theyshould thus be taken into account when seeking to explain thestructure of protection across sectors.

We then perform a structural estimation of the equilibriumpolicies obtained under our model using data for the United States,and show that lobbying expenditures play an important role inshaping the level of trade protection across sectors. In order to do thiswe collected data on lobbying expenditures from the Center forResponsible Politics and matched the data at the 3-digit ISIC level. Wecombined this with data on international trade variables and industrycharacteristics from different sources. In addition, we find signifi-cantly lower and more reasonable values for the parameter thatcaptures the weight that the government attaches to social welfarerelative to political contributions than previous studies for the UnitedStates.

We think of this paper as a first step in incorporating informationallobbying in the determination of trade policies and hope that it mayhelp draw more attention to the effects of lobbying expenditures oninternational trade as well as other types of policies.

Appendix A

Proof. d ti/d μiN0

Using Eq. (11) and applying the implicit function theorem weobtain:

dtidμi

= −f li; ki� �

= aeimi

y′ip4i − 1 + að Þl″t �= aeimi− yi− 1 + að Þl′t �ap4i e′imi + eim′iÞ= aeimið Þ2−1= 1 + tið Þ2:���ðA1Þ

The numerator is positive and the last term in the denominator isnegative. The term in brackets in the second term in the denominatoris positive (that must be true as long as the tariff is positive). We alsohave (e′imi+eim′i )=−m″i pi−m′i after simplifying, which is positiveas long as the import demand function is not too convex. Therefore, ifthe first term in the denominator is negative the denominator will benegative.

Using the expression for l(ti,yi,Ci/pi*) given in the text we obtain:

l″t = 2y′ip4i + tiy″i p4i� �2− ∂2

∂t2i∫ti fi ⋅ð Þdμ−∂2 Ci = p4i

� �∂t2i

: ðA2Þ

Since each lobby has to contribute a times the deadweight loss, wehave that Ci = a W p4ð Þ−W pð Þ½ �, and therefore we can find:

∂2 Ci = p4i� �∂t2i

= −a m′ip4i + tim

″i p4i� �2−l″t

h i: ðA3Þ

Using Eqs. (A2) and (A3) we obtain:

y′ip4i − 1 + að Þl″t = − y′ip4i + tiy″i p4i� �2− ∂2

∂t2i∫ti fi ⋅ð Þdμ + a m′

ip4i + tim″i p4i� �2h i !

:

ðA4Þ

The first term inside the parenthesis on the right-hand side ofEq. (A4) is positive. The signs of the second and third terms depend onthe second derivative of outputwith respect to the price. As long as thesupply curve is not too concave or too convex, if either of those terms isnegative it will be relatively small in absolute value. Moreover, the last

term in the parenthesis in Eq. (A4) could be positive or negativedependingon the sign ofm″. If it is positive itwould helpmake Eq. (A4)negative. If it is negative, a sufficient condition for Eq. (A4) to benegativewould then be that a is small enough. Note that neither of theprevious conditions is necessary. They are sufficient conditions thatwould ensure that Eq. (A4) is positive, which in turn would guaran-tee that, but again is not necessary for Eq. (A1) to be positive and hencedti/dμiN0.

Fixed lobbying costs

In the text we assumed that the interest groups can choose exactlyhow much to spend on lobbying, for any value of μi. Here weassume that there is a minimum cost that the lobbies have to incur inorder to send a signal to the policymaker. First, we can ask whetherit is possible to have an equilibrium with full revelation in thiscase. We have that if μi is very close to zero, the lobby could get thepolicy ti(μi) instead of ti(0), but it would have to pay the fixed cost oflobbying, which we denote by Lf. Clearly, for values of μi sufficientlylow, the cost of lobbying would exceed the benefit. Therefore, anequilibrium with full revelation does not exist when there is a fixedlobbying cost.

Next, we define an equilibrium such that no lobbying occurs whenμi lies between zero and some positive value μ , and there is lobbyingwith full revelation for any value of μi above μ . We have that if there isno lobbying, the policy will be ti μ = 2

� �, while if the sector spends an

amount L(μi), the policymaker will learn the state of nature and willset the policy ti(μi). The lobbying function should satisfy the followingconditions: 1) There is no incentive to lobby when μib μ; 2) L(μi)≥Lffor all μi ≥ μ; and 3) Li=L(μi) for all μi≥μ .

For the first condition to hold, we should have that if μi = μ , theinterest group is indifferent between lobbying or not. We need:

li + pi μ = 2� �

μ f li μ = 2� �

; ki� �

−wli μ = 2� �

−Ci μ = 2� �

= li + pi μ� �

μf li μ� �

; ki� �

−wli μ� �

−Ci μ� �

−L μ� �

:

The previous equation implicitly defines μ (the left-hand side is thenet welfare for the interest group if it does not lobby and the right-hand side is its net welfare if it lobbies). For the last condition to hold,we need the marginal cost of signaling a higher value of μi to equal itsmarginal benefit. As shown in Section 2.1, this implies:

L′ μið Þ = p4i μi f li; ki� � ∂ti

∂μi−dCi

dμi:

We can now define a lobbying expenditure function that satisfiesall the previous conditions:

L μið Þ =0 if 0≤μib μ

Lf + tip4i μi f li; ki� �

−∫tip4i f li; ki� �

dμ−Ci if μ≤μi≤1:

8<:

Thus, when there is a fixed cost to lobbying, we have that theabsence of lobbying indicates that the state of nature belongs to arange of relatively low values. In that case the policymaker sets apolicy based on the average of those values. Positive lobbyingexpenditures, on the other hand, indicate higher values of the state,and in those cases the lobby is able to signal the exact value of μithrough the magnitude of its lobbying efforts.

We can now derive the trade policies that will arise in this setting.For values of μi that lead to zero lobbying expenditures, the government

136 P. Tovar / Journal of International Economics 83 (2011) 126–136

will set the policies knowing that μi∈ 0; μÞ�. This gives the following

equilibrium policies:

ti1 + ti

=1

aei μ = 2� � yi μ = 2

� �mi μ = 2� � Ii if μi∈ 0; μÞ:�

When μi∈ μ; 1�

, the government will be able to infer the exactvalue of μi, and the equation for the policies will be similar to thatderived in the previous section. Therefore, we can write the followingequation for the equilibrium trade policies, defined over all possiblevalues of the state of nature:

ti1 + ti

=

1aei μ = 2� � yi μ = 2� �

mi μ = 2� � Ii if 0≤μib μ

1aei μið Þ

yi μið Þmi μið Þ−

1 + ami μið Þℓ′t ti; yi;Ci = p4i

� �� �Ii if μ≤μi≤1

8>>><>>>:

We can see that, if there are fixed lobbying costs, it is possible tohave that (organized) sectors that do not spend money on lobbyingget trade subsidies.

References

Ansolabehere, Stephen, Snyder, James M., Tripathi, Micky, 2002. Are PAC contributionsand lobbying linked? New evidence from the 1995 Lobby Disclosure Act. Businessand Politics 4 (2), 131–155.

Bennedsen, Morten, Feldman, Sven E., 2002. Lobbying legislatures. Journal of PoliticalEconomy 110 (4), 919–945.

Brock, Ellen, Dobbelaere, Sabien, 2006. Has international trade affected workers'bargaining power? Review of World Economics 142 (2), 233–266.

Doiron, Denise, 1992. Bargaining power and wage-employment contracts in aunionized industry. International Economic Review 33 (3), 583–606.

Dumont, Michel, Rayp, Glenn, Willeme, Peter, 2006. Does internationalization affectunion bargaining power? An empirical study for five EU countries. OxfordEconomic Papers 58 (1), 77–102.

De Figuereido, JohnM., Cameron, CharlesM., 2006. Endogenous cost lobbying: theory andevidence, mimeo, Center for Law and Public Affairs, Princeton University.

Fuller, Wayne A., 1987. Measurement Error Models. Wiley, New York.Gais, Thomas L., Walker, Jack L., 1991. Pathways to Influence in American Politics. In:

Walker, J. (Ed.), Mobilizing Interest Groups in America. University of MichiganPress, Ann Arbor.

Gawande, Kishore, 1997. Generated regressors in linear and nonlinear models.Economic Letters 54, 119–126.

Gawande, Kishore, Bandyopadhyay, Usree, 2000. Is protection for sale? Evidence on theGrossman–Helpman theory of endogenous protection. Review of Economics andStatistics 82 (1), 139–152.

Gawande, Kishore, Krishna, Pravin, 2003. The political economy of trade policy:empirical approaches. In: Harrigan, J. (Ed.), Handbook of International Trade. BasilBlackwell, New York.

Goldberg, Pinelopi K., Maggi, Giovanni, 1999. Protection for sale: an empiricalinvestigation. American Economic Review 89 (5), 1135–1155.

Grossman, Gene M., Helpman, Elhanan, 1994. Protection for sale. American EconomicReview 84 (4), 833–850.

Grossman, Gene M., Helpman, Elhanan, 2001. Special Interest Politics. MIT Press,Cambridge.

Imai, Susumu, Hajime Katayama and Kala Krishna, 2009. Protection for sale or surgeprotection? European Economic Review 53 (6), 675–688.

Karacaovali, Baybars, in press. Productivity matters for trade policy: theory andevidence. International Economic Review.

Kee, Hiau Looi, Nicita, Alessandro, Olarreaga, Marcelo, 2008. Import demand elasticitiesand trade distortions. Review of Economics and Statistics 90 (4), 666–682.

Kee, Hiau Looi, Nicita, Alessandro, Olarreaga, Marcelo, 2009. Estimating traderestrictiveness indices. Economic Journal 119 (534), 172–199.

Langbein, Laura, 1986. Money and access: some empirical evidence. Journal of Politics48 (4), 1052–1062.

Lee, Jong-Wha, Swagel, Phillip, 1997. Trade barriers and trade flows across countriesand industries. The Review of Economics and Statistics 79 (3), 372–382.

Milyo, Jeffrey, 2002. Bribes and fruit baskets: what does the link between PACcontributions and lobbying mean? Business and Politics 4 (2), 157–159.

Mitra, Devashish, 1999. Endogenous lobby formation and endogenous protection: along-run model of trade policy determination. American Economic Review 89,1116–1134.

Mitra, Devashish, Dimitrios, Thomakos, Mehmet, Ulubasoglu, 2002. Protection for salein a developing country: democracy vs. dictatorship. The Review of Economics andStatistics 84 (3), 497–508.

Nicita, Alessandro, Olarreaga, Marcelo, 2007. Trade, production and protection: 1976–2004. World Bank Economic Review 21 (1), 165–171.

Potters, Jan, Van Winden, Frans, 1992. Lobbying and Asymmetric Information. PublicChoice 74 (3), 269–292.

Trefler, Daniel, 1993. Trade liberalization and the theory of endogenous protection: aneconometric study of U.S. import policy. Journal of Political Economy 101 (1),138–160.

Veugelers, Reinhilde, 1989. Wage premia, price-cost margins and bargaining power inBelgian manufacturing. European Economic Review 33, 169–180.

Wright, John R., 1985. PACs, Contributions, and Roll Calls: An OrganizationalPerspective. American Political Science Review 79 (2), 400–414.