Free Trade and the Formation of Environmental
Policy: Evidence from US Legislative Votes*
Jevan Cherniwchan

Nouri Najjar

October 20, 2023

Abstract
We test the hypothesis that governments alter environmental policy in response totrade by studying NAFTA’s effects on the formation of environmental policy in the
US House of Representatives between 1990 and 2000. We find that reductions in US
tariffs decreased political support for environmental legislation. This decrease appears to be due to: (i) a reduction in support by incumbent Republican legislators
in response to trade-induced changes in the policy preferences of their constituents,and (ii) changes in partisan representation in affected districts due to decreased electoral support for pro-NAFTA Democrats following the agreement.
JEL Codes: F18, F64, F68, Q56, Q58
Keywords: NAFTA, trade liberalization, voting, environmental policy* Cherniwchan:

McMaster University; 1280 Main Street West, Hamilton ON, Canada, L8S 4M4;
cherniwj@mcmaster.ca. Najjar: Western University; 1255 Western Rd, London ON, Canada, N6G 0N1;
nnajjar@ivey.ca. We would like to thank Sarah Anderson, Brian Copeland, Christian Dippel, Adam
Fremeth, Jason Garred, Jury Gualandris, Brad Hackinen, Bård Harstad, Guy Holburn, Giovanni Maggi,
Carol McAusland, Juan Moreno-Cruz, Romel Mostafa, Brandon Schaufele, Robert Staiger, Scott Taylor,
and Zhihao Yu for helpful feedback. We also thank participants at the International Trade and Environmental Policy workshop, the Nordic International Trade Seminars, the annual meetings of the Canadian
Economics Association, the Canadian Resource and Environmental Economics Association, the Eastern
Economics Association, the Occasional Workshop in Environmental and Resource Economics, and the virtual workshop on Trade, Spatial Economics, and the Environment, and seminar participants at Carleton
University, HEC Montreal, McMaster University, Queen’s University, the University of Alberta, the University of Arkansas, and the University of Guelph for helpful comments and suggestions. We would also
like to thank Arik Levinson for sharing data from the Pollution Abatement Cost and Expenditures survey.
Funding from the Canada Research Chairs program and the Spencer Family Professorship is gratefully
acknowledged (Cherniwchan). All remaining errors are our own.

11

Introduction

The hypothesis that governments alter environmental policy in response to trade underlies much of the debate over the environmental consequences of globalization. It is at thecore of much of the theoretical literature examining the environmental effects of trade,and manifests in popular concern that governments will seek to counter the effects oftrade liberalization by weakening or eliminating environmental regulations to ease theregulatory burden facing domestic firms. Yet despite the prominence of this hypothesis in both the academic literature and policy debates, there is currently little empiricalevidence of whether individual governments alter environmental policy in response totrade.1 This makes it difficult to assess whether such changes are empirically relevant.
In this paper, we make progress on this issue by examining how a key determinant offederal environmental policy in the United States (US) – legislative voting by members ofthe House of Representatives during roll call votes (RCVs) on environmental legislation –was affected by trade liberalization between the US and Mexico after the enactment of theNorth American Free Trade Agreement (NAFTA) on January 1, 1994. NAFTA is an ideal
context for our study for at least two reasons. First, it was an episode of bilateral tradeliberalization, making it possible to examine the effects of reductions in both domestic(US) and foreign (Mexican) tariffs on the voting behavior of affected US legislators.2
Importantly, these tariff reductions were accompanied by significant increases in tradevolumes (Romalis, 2007; Caliendo and Parro, 2015), suggesting that the agreement could
have had a material impact on legislator decisions. Second, previous research suggeststhat NAFTA’s effects varied across the continental US (Hakobyan and McLaren, 2016;
Cherniwchan, 2017). This geographic variation allows us to study voting by legislators
who represent the districts most affected by the agreement.
We begin our analysis by examining the effects of both US and Mexican tariff reductions on the environmental RCVs cast by representatives of affected congressional
districts. To do so, we use a generalized difference-in-difference (DID) research designthat compares the voting choices of legislators who represent districts that were highly
exposed to each tariff cut to those representing districts that were not (first difference),
before and after NAFTA (second difference). We follow the approach taken elsewherein the literature examining the regional effects of trade policy (e.g. Topalova (2010),
Hakobyan and McLaren (2016), or Pierce and Schott (2020)), and calculate district-level
1 For recent overviews of existing work examining the relationship between international trade and theenvironment, see Cherniwchan et al. (2017), Copeland et al. (2022), or Cherniwchan and Taylor (2022).
2 While NAFTA also involved Canada, trade between the US and Canada was previously liberalized
as a result of the Canada-US Free Trade Agreement (CUSFTA).

2changes in US and Mexican tariffs using initial labor market shares as weights. We employ a data set that contains information on the votes of legislators in the US House ofRepresentatives on environmental bills from the League of Conservation Voters (LCV),
district tariff cuts, and other district characteristics over the period 1990-2000.3
Our results provide robust evidence that US tariff reductions reduced support for environmental legislation amongst representatives of affected districts.4 The estimate fromour preferred specification indicates that a one percentage point (pp) reduction in a district’s average US tariff reduced the likelihood its representative casts a pro-environment
vote by over 15 pp. This implies that the US tariff cuts reduced the likelihood thatan affected representative casts a pro-environment vote by close to 4 pp on average.
In contrast, the estimate from our preferred specification suggests that reductions in
Mexican tariffs had little effect on the likelihood an affected representative casts a proenvironmental vote.5
One potential explanation for these findings is that representatives of districts affected by US tariff cuts altered their voting behavior in response to concerns by theirconstituents or local industry that new or revised environmental policy would cause industrial flight to Mexico, whereas representatives of districts affected by Mexican tariff
cuts did not.6 This type of offshoring in response to environmental policy differences
was a salient policy issue for many US voters both before and after NAFTA was signed;
for example, over two-thirds of respondents to a 1999 opinion survey expressed concernthat companies would relocate to countries with weak environmental standards to avoid
the costs associated with stringent regulation (Kull, 2000). Furthermore, previous re3 We end our study in 2000 to avoid contamination created by the effects of trade liberalization follow-

ing China’s ascension into the WTO (e.g. Autor et al. (2013), Pierce and Schott (2016)).
4 We perform a number of robustness exercises, including estimating an event-study version of ourmain empirical specification, accounting for reductions in tariffs on intermediate inputs, controlling forthe effects of changes in Most-Favored Nation tariffs, the effects of CUSFTA, and the effects of trade with
China, as well as accounting for the alignment between a representative and the party in power in theHouse, Senate, and Presidency, differential voting behavior on RCVs in election years, differential trends
across Census Divisions, and pre-existing industrial decline. We also show our results are robust to accounting for redistricting, restricting our sample to exclude bills that may include non-environmental
components, restricting our sample to exclude bills that are subject to multiple RCVs, and treating abstentions as negative votes as in the LCV. We also show that our main estimates are not biased by ouruse of a two-way fixed effects estimator, provide evidence that NAFTA did not systematically alter of theset of bills introduced in the House of Representatives and show that NAFTA did not have systematicallydifferent impacts on RCVs on final bills, amendments or motions. For the sake of brevity, these results arereported in the online appendix.
5 Specifically we find that reductions in Mexican tariffs decreased the likelihood of a pro-environmental
vote by 1.5 pp, but this effect is not statistically significant at conventional levels.
6 Indeed, concerns of industrial flight in response to reductions in US tariffs partially underpinned
Ross Perot’s claim during the 1992 presidential campaign that NAFTA would lead to a “giant sucking
sound going South.”3

search has shown that trade liberalization can create incentives for industry to lobby thegovernment for weaker environmental policy (Fredriksson, 1997, 1999); legislators may
be more responsive to such lobbying efforts given the possibility of industrial flight. As
such, the effect of US tariff reductions could potentially be rationalized as a productof legislator concern over post-liberalization industrial flight, either in response to theviews of their constituents, or the lobbying activities of dirty industries who would be
impacted by legislation.7
Our main findings could potentially also be rationalized as a product of the agreement’s effects on both economic and political outcomes. Increased import competition
from Mexico following NAFTA significantly lowered wages (Hakobyan and McLaren,2016) and employment (Choi et al., 2022) in vulnerable areas, whereas increased export opportunities for US firms had limited effect on local employment (Choi et al.,2022). Standard theories of trade and the environment (e.g. Copeland and Taylor (1994,
1995)) suggest that this type of localized negative income shock will lead to decreased
demand for environmental policy in these regions, meaning our results could be explained as a product of representatives of affected districts altering their voting behavior
in response to NAFTA-induced changes in the environmental policy preferences of theirconstituents.8 However, increased import competition following NAFTA also caused significant reductions in support for the Democratic party in vulnerable regions (Choi et al.,2022). Previous research indicates that Democratic representatives are more likely tosupport environmental legislation than Republicans (Nelson, 2002; Kim and Urpelainen,2017), meaning our baseline estimates need not reflect changes in voting tied to viewson environmental policy. Instead they could simply be due to NAFTA-induced changes
in partisan representation resulting from decreased support for the Democratic party.
Our examination of these mechanisms suggests that our main results are consistent
with trade-induced changes in both the demand for environmental policy and in partisan representation caused by reductions in US tariffs. We find no evidence to suggestthat our estimates reflect legislators responding to concerns of industrial flight by polluting industries. Instead, we find that our baseline estimate of the effects of US tariff
reductions can be rationalized as a product of: (i) incumbent Republican legislators who
represent affected districts decreasing their support for environmental policy in response
7 It is worth noting cross-country differences in environmental regulation affected the pattern of US-

Mexico trade even prior to NAFTA (Levinson and Taylor, 2008), meaning new environmental legislationin the US could have materially impacted where goods were produced.
8 The underlying intuition is straightforward: if environmental quality is a normal good, then thechanges in incomes and pollution levels brought about by trade will alter the demand for environmental
policy in the affected population.

4

to trade-induced changes in the policy preferences of their party’s primary constituency,and (ii) constituents in affected districts electing Republican representatives to replace
pro-NAFTA Democrats. Each mechanism explains close to half of the effect of reductions
in US import tariffs. Furthermore, we also find that reductions in Mexican tariffs did notaffect constituent support for environmental policy or partisan representation. This suggests that our baseline finding that reductions in Mexican tariffs did little to change how
affected representatives vote on environmental RCVs may simply reflect the fact that
Mexican tariff changes did not create meaningful regional disparities in economic andpolitical conditions (Choi et al., 2022).
As the final step in our analysis, we examine the possibility that our baseline estimates of the effects of US tariff reductions may not be capturing changes in views thatare specific to the environment, but rather reflect a broader NAFTA-induced shift towards “conservatism” on a range of policy issues. There is reason to believe this may
be the case, as previous research has documented that import competition can lead togeneral rightward shifts in political preferences (e.g. Autor et al. (2020)). However, wefind little evidence that our results are simply the result of a rightward shift in response
to NAFTA. We find that reductions in US tariffs had little effect on constituent viewson other policy issues. We also find that NAFTA had little effect on the voting behavior
of incumbent legislators on RCVs on reproductive rights, a well known partisan issue.
This runs counter to what would be expected if NAFTA induced their constituents toadopt more conservative policy views. Instead, we find NAFTA only impacted RCVs on
reproductive rights through changes in partisan representation. This further suggeststhat our main results do not reflect a systematic conservative shift in response to trade.
Taken together, our findings contribute to a large literature examining how international trade affects the environment. As noted at the outset, trade-induced changes inenvironmental policy are thought to be a core determinant of the environmental effectsof trade but quasi-experimental evidence highlighting the empirical relevance of thischannel remains scarce. Hence, our paper contributes to the literature by providing such
evidence in the context of the formation of federal environmental policy in the US.9 Our
results also provide empirical support for a mechanism that has featured prominently inthe theoretical literature, namely that governments respond to trade-induced changes in
9 By focusing on the US, our work is most closely related to Ederington and Minier (2003) and McAus-

land and Millimet (2013) who both study how changes in trade flows affect indirect measures of thestringency of US environmental policy. Ederington and Minier measure policy stringency using data on
industry pollution abatement costs, while McAusland and Millimet employ data on legislator LCV scoresfrom the LCV congressional scorecard. In contrast to these studies, we examine the effects of changes intrade policy created by a specific episode of trade liberalization on environmental RCVs.

5

the demand for environmental policy by their constituents.10 However, our results also
highlight the potential importance of a mechanism that has been previously overlookedin this literature – partisan politics – suggesting that trade’s effect on environmental
policy, and thus, the environment, may hinge on the relevant political context.
Our research also contributes to a large literature examining the political economy
of environmental policy.11 Researchers have examined numerous factors that affect how
legislators enact environmental policy, including changes in constituent demographics(Kahn, 2002), ideology and party affiliation (Nelson, 2002; Beland and Boucher, 2015),
lobbying and public persuasion (Yu, 2005; Pacca et al., 2021), electoral incentives (Listand Sturm, 2006; Bouton et al., 2021) and weather (Herrnstadt and Muehlegger, 2014).
We add to this line of research by providing the first evidence that international tradeinfluences legislative votes on environmental policy. Our work also contributes to a related body of research studying the impacts of economic shocks on voter support forenvironmental policy (Kahn and Kotchen, 2011; Meyer, 2016, 2022). Our work builds
on these studies by providing evidence that such changes in voter support can help rationalize changes in legislative support for environmental policy following an economic
shock.
Finally, our work contributes to the literature studying the interaction between international trade and political outcomes. Much of this work has focused on how tradeaffects voters (e.g. Autor et al. (2020); Jensen et al. (2017); Che et al. (2022); Dippel et al.
(2022); Choi et al. (2022)) or legislative votes on trade policy (e.g. Conconi et al. (2012,2014); Feigenbaum and Hall (2015)). Our results contribute to this literature by providing the first evidence that trade also impacts the formation of domestic policies suchas environmental policy both by altering political representation, and by changing how
incumbent politicians vote on legislation.
The rest of this paper proceeds as follows. Section 2 provides some further background on NAFTA, and discusses our research design. Section 3 presents our data. Our
main results are summarized in Section 4. Section 5 examines potential mechanisms
driving our main results, while Section 6 examines whether our results are capturing
a broader NAFTA-induced shift towards conservatism on a range of issues. Finally,
Section 7 concludes.
10 This mechanism has its origins in the pioneering work of Grossman and Krueger (1991), and has

been formalized in theoretical models in which governments respond directly to the demands of a representative agent (e.g. Copeland and Taylor (1994, 1995); McAusland and Millimet (2013)) or groups withdifferent preferences (e.g. Antweiler et al. (2001); McAusland (2003); Copeland and Taylor (2003)).
11 For an overview of this literature, see Oates and Portney (2003).

6

2

Research Design

Our goal in this paper is to assess whether bilateral trade liberalization between the
United States and Mexico following NAFTA altered federal environmental policy in
the US. We face two primary empirical challenges in doing so: (i) measuring federal
environmental policy, and (ii) identifying the causal effects of trade liberalization.
The challenge we face in measuring environmental policy arises, in part, because policy creation is a complex process that embeds economic, scientific, and political dimensions (Dixit, 1996). As such, capturing the entire policy process is effectively intractable.
Instead, we adopt an approach that is common in both economics and political science,and focus on a particular dimension of policy: roll call votes (RCVs) cast by legislatorsin the US House of Representatives (Lee et al., 2004; Feigenbaum and Hall, 2015; Bouton
et al., 2021). For any House bill to become law, it must achieve majority support in an
RCV by Congress, making these votes an important component of the federal policy
making process.12 In addition, RCVs provide insight into how legislators view an issue(Ansolabehere and Jones, 2010), which may manifest in other dimensions of the policy
process. As a result, we focus our analysis on environmental RCVs.13
Though environmental policy can be set at municipal and state levels, studying federal legislation is attractive because many important improvements in environmental
quality in the US have been the result of federal laws. For example, the Clean Air Act(CAA) and subsequent amendments caused large improvements in air quality in the US(Currie and Walker, 2019), the Clean Water Act reduced water pollution in US rivers(Keiser and Shapiro, 2019), and the Superfund law has led to over $4 billion in disbursements to cleanup over 1,500 chemical sites (Environmental Protection Agency, 2018).
To identify the causal effects of bilateral trade liberalization between the US and Mexico due to NAFTA, we exploit plausibly exogenous variation in trade protection acrosscongressional districts created by the elimination of US and Mexican tariffs following
the agreement’s implementation. There are three features of NAFTA that make thesetariff changes an attractive source of variation for our study. First, the agreement wascomprehensive, meaning that it eliminated all bilateral tariffs between the US and Mexico according to a set schedule that was negotiated in advance (Kowalczyk and Davis,
1998). As a result, the magnitude of each tariff reduction was determined by the pattern of protection that was in place prior to the agreement, and the timing of tariff
reductions was determined ex-ante. Second, political uncertainty surrounding NAFTAs
12 Bill amendments must also pass an RCV. Thus, we consider both amendment and bill passage RCVs.
13 We describe the process we use to identify relevant House RCVs for our purposes in Section 3.

7

passage through Congress means the agreement acted as a de-facto shock to trade policy in 1994.14 Third, previous research suggests that although NAFTA was a federal
policy that led to common reduction in tariff rates across the US, there were large geographical differences in the effects of these tariff reductions across different regions due
to pre-existing differences in industrial structure (e.g. Hakobyan and McLaren (2016),
Cherniwchan (2017)).
We exploit the temporal variation in US and Mexican tariff rates and geographic
variation in exposure to their effects via a generalized difference in differences research
design. We exploit the temporal variation in both US and Mexican tariff rates by comparing RCVs cast by the representative of each district before NAFTA (pre-1994) to thosecast after, allowing us to account for any time invariant differences in factors affecting
RCVs across districts. We exploit the geographic variation in exposure to the effects of
the NAFTA tariff reductions by comparing RCVs cast by legislators in highly-exposed
districts for which liberalized industries constitute a large fraction of economic activity
to RCVs cast by legislators in less-exposed districts for which liberalized industries areof less importance. This allows us to account for any national-level shocks that may
affect RCVs in all districts, such as political factors like changes in the presidency or theparty in control of the Senate, or aggregate changes in the US economy. Furthermore,because the relative reductions in US and Mexican tariffs varied across industries due
to pre-existing differences in tariff protection in the two countries, we are able to jointly
estimate the effects of both import and export liberalization across districts. That is, ourresearch design embeds two generalized difference-in-differences; one exploiting geographic exposure to NAFTA’s liberalization of US import tariffs and the other exploiting
geographic exposure to NAFTA’s liberalization of Mexican import tariffs.
We implement our research design by estimating the following regression:


yvrt = β 0 + βUSA ∆τrUSA x Postt+ β Mex ∆τrMex x Postt+ λr + ψt + evrt ,(1)

where yvrt is an indicator for any pro-environment RCV v cast by representative for
district r in year t, ∆τrUSA and ∆τrMex , respectively, are the average changes in US and
Mexican tariffs faced by district r’s following NAFTA, Postt is an indicator for any year
after 1993, λr is a district fixed effect, ψt is a year fixed effect, and evrt is an error term
14 Although negotiations began in 1991 and the initial agreement was signed a year later, there wassubstantial uncertainty over whether it would be ratified after the 1992 election. This uncertainty was
resolved shortly before NAFTA came into force on January 1st , 1994 after the agreement passed both theHouse and Senate in November 1993. For further discussion, see Cherniwchan (2017).

8

that captures idiosyncratic variation in RCVs across districts and time.15 For inference,
we use cluster-robust standard errors two-way clustered by state and bill, to address
potential heteroskedasticity across districts within states and across representatives on aparticular issue, and to address potential autocorrelation within districts over time.
Our coefficients of interest, βUSA and β Mex , capture the effects of a 1 pp reduction in
US and Mexican tariffs, respectively, on the likelihood an affected House legislator casts
a pro-environment RCV. For these coefficients to credibly identify the causal effects of
the NAFTA tariff cuts on environmental RCVs, it must be the case that there are no otherfactors that are correlated with NAFTA driving differences in voting on environmental
RCVs across districts over time.
Given that the timing and magnitude of NAFTA tariff cuts were determined in prior
to the agreement, there are two main potential channels through which this assumption
could be violated. First, it is possible that the willingness of legislators affected by the
NAFTA tariff cuts to cast a pro-environment RCVs may reflect the underlying trends inexisting environmental regulations in their districts. There is reason to believe that such
regulatory trends may be of material importance in our setting as previous research
has found that major federal environmental regulations in the US –the CAA and its
subsequent amendments– have significantly impacted domestic labor markets (Currie
and Walker, 2019). Second, it is possible that the the RCVs of affected legislators reflect
pre-existing differences in trends in local socioeconomic or political conditions acrossdistricts tied to trade. Indeed, in Online Appendix A we investigate this possibility
directly and find that a district’s exposure to NAFTA is uncorrelated with pre-existing
political conditions, but is correlated with several socioeconomic variables.
To help ensure that our estimates are not capturing the effects of existing environmental regulations or pre-existing trends in district socioeconomics, in our main analysis
we estimate several specifications where we control for these factors directly. Specifically,
we estimate specifications in which we directly control for district exposure to CAA regulations and control for differential trends across districts though the inclusion of a setof initial demographic and economic characteristics interacted with year fixed effects.16
In addition to these two exercises, we also engage in a number of additional robustness
15 While we formally define ∆τ USA and ∆τ Mex in Section 3, it is worth noting here that we measurerr

trade liberalization in the US and Mexico as the interaction of the average tariff changes faced by each
district interacted with a post-NAFTA indicator ([∆τrUSA x Postt ] and [∆τrMex x Postt ], respectively) rather
than using contemporaneous changes in each district’s average tariff level. We do so to reflect the fact thatthe tariff reductions implemented as a result of NAFTA were known in advance.
16 Though exposure to NAFTA is uncorrelated with the district’s pre-existing political conditions, in
Online Appendix B we report the results from several robustness checks in which we control for preexisting differences in political conditions.

9tests to further ensure that our estimates of βUSA and β Mex can credibly be interpreted
as causal, including controlling for other potential confounding factors and estimating
an event study version of Equation (1) to examine whether are estimates are capturing
pre-existing differences in trends across districts. These exercises are described in moredetail in Section 4.1.

3

Data and Measurement

Implementing our research design requires information on environmental RCVs, tariff
rates, and district characteristics. We obtain these data from a variety of sources.
We obtain information on environmental RCVs from the League of Conservation Voters’ (LCV) National Environmental Scorecard database. Each year since 1971, the LCV
has employed a panel of experts to assess RCVs in the US House of Representatives.
These experts determine which bills and amendments are relevant for the environment,
classify each of the relevant RCVs into various categories, determine whether supporting the bill/amendment is “pro-environment” or “anti-environment,” and record thevote of each congressperson.17 We use these assessments to construct a database of all
RCVs cast on environmental bills from 1990 to 2000 in the House.18 Each observationin the database reflects an RCV cast on a particular bill by a particular Congressperson.
We use this information to construct an indicator of whether the RCV on bill v by the
representative of district r in year t is “pro-environment.”19
We construct measures of the tariff changes experienced by each Congressional district using data on tariff rates from Romalis (2007), and employment data from Eckert
et al. (2020). We calculate the change in both US and Mexican tariffs by industry between
1993 and 1999 to measure the extent of trade liberalization during our period of study,
and then aggregate these industry level changes to the Congressional district level using
17 The LCV codes both negative votes and abstentions as not supporting a bill. We exclude such absten-tions from our main analysis, but as we discuss in Section 4.1, we examine the robustness of our results toadopting the LCV definition and coding abstentions as not supporting a bill.
18 We exclude RCVs cast by the sole independent representative not affiliated with the Democratic or
Republican parties over our sample period from our analysis.
19 Several previous studies have used the LCV scorecard database to study the formation of environmental policy, either by examining LCV scores over time or by examining specific RCVs (e.g., Nelson(2002), Herrnstadt and Muehlegger (2014), or Bouton et al. (2021)).

10

the 1990 industry employment shares as weights.20,21 More concretely, the change in US
import tariffs experienced by district r, ∆τrUSA , is constructed as:∆τrUSA =

∑



i


i
lir,90 hUSA
USA,Tari f f i,99
− Tari f f i,93
lr,90

(2)

where lir,90 is employment in industry i in district r in 1990, lr,90 is total employment in
USA is the tariff assessed on Mexican imports to the US from
district r in 1990, and Tari f f i,jindustry i in year j.22 The Mexican tariff change for district r, ∆τrMex , is constructed as:∆τrMex =

∑
i




i
lir,90 h
Mex
Mex,
Tari f f i,99
− Tari f f i,93
lr,90

(3)

Mex is the tariff assessed on US exports to Mexico from industry i in year j,
where Tari f f i,j
and all other variables are as in Equation (2).
We obtain data on initial district characteristics from Adler (2021) and the adjusted
county business patterns (CBP) database by Eckert et al. (2020). From Adler, we compute
1990-level data on: the share of the district’s population aged 65 and older, the sharethat identify as black, the share born outside the US, the share living in rural areas, themedian income in the district, and the share of the workforce employed in farming, andin “blue-collar” occupations. From the CBP data, we compute the share of employment
in manufacturing in 1990. We also use the CBP data to construct a measure of district
exposure to regulation under the CAA. Specifically, we measure a district’s exposure to
the CAA as the share of district employment in counties that are in non-attainment withat least one of the CAA’s National Ambient Air Quality Standards in 1990.
Summary statistics for our main dependent variable and US and Mexican tariffchanges are shown in Table 1. The indicator for a pro-environment RCV is shown in
the first row, while the second and third rows shows the reduction in district USA import tariffs and district Mexican tariffs due to NAFTA, respectively. The mean, standard
20 As the data from Romalis (2007) is reported at the HS-8 level, we convert the commodity-level tariff

data to the four-digit Standard Industrial Classification-level using the concordance developed in Pierce
and Schott (2012). We weight the commodity level data using trade data from Schott (2008) and the UN
Comtrade database so the resulting industry tariff measures are import-weighted.
21 We aggregate the county-level employment data from Eckert et al. (2020) to the Congressional districtlevel using the Geocorr crosswalks created by the Missouri Census Data Center. We employ two crosswalks
to address redistricting in the 103rd congress: one for 1990-1992 that uses the 102nd Congressional district
boundaries and one for 1993-2000 that uses the 103rd Congressional district boundaries. In our analysis,
we examine the robustness of our results to ensure they are not capturing the effects of redistricting.
22 It is worth noting that prior to NAFTA, Mexico received preferential tariff treatment under the GenUSA , reflects these preferences.
eralized System of Preferences (GSP); our measure of applied tariffs, Tari f f i,93
Mexican imports were no longer subject to the GSP after NAFTA entered into force.

11

Table 1: Summary Statistics
(1)
Mean

(2)
SD

(3)
Min

(4)
Max

1{Pro-Environment Vote}∆τrUSA∆τrMex

0.51
0.25
1.12

0.50
0.31
0.90

0.00
0.00
-8.63

1.00
2.00
3.14

Number of Bills
Number of Votes Cast109
50,322

Variable

Notes: Table shows summary statistics for the NAFTA tariff cuts and legislator roll call vote outcomes between 1990 and 2000.
The first row reports summary statistics for our main dependent variable: an indicator of whether the roll call vote cast is proenvironment. Rows two and three report summary statistics for the reduction in US import tariffs and Mexican tariffs created by
NAFTA across congressional districts. The calculation of these tariff changes are defined in the main text. Row four reports the total
number of environment-related bills voted on between 1990 and 2000. Row five reports the total number of roll call votes cast on
environment-related bills between 1990 and 2000.

deviation, minimum, and maximum of each variable are shown in Columns (1) through(4), respectively. Table 1 also reports the number of environmental bills voted on in theHouse between 1990 and 2000, as well as the total number of RCVs cast on those bills.
As Table 1 shows, there are 50,322 RCVs on 109 bills in our sample,23 across which
51% of all RCVs are pro-environment. This suggests that even a small change in RCVs
could have material effects on the formation of environmental policy by potentially altering the outcomes of some bills. Moreover, there is substantial variation in NAFTA tariff
reductions across districts. The average district experienced a 0.25 pp reduction in US
import tariffs, with a range from zero to 2 pp. Districts are, on average, more exposedto the change in Mexican tariffs, with the average district experiencing a 1.12 pp tariff
reduction. There is also considerable variation in the change in Mexican tariffs acrossdistricts, which ranges from a 8.63 pp increase24 to a 3.14 pp decrease.
We further illustrate the variation in tariff reductions following NAFTA in Figure 1,
which displays two maps highlighting the magnitudes of the average US and Mexican
tariff cuts across districts across the continental US, using district definitions from the
101st Congress.25 Panel (a) shows the reduction in average US import tariffs by district,
23 Note that some bills are subject to multiple RCVs.

For these bills, we include each RCV in our
analysis, but consider them as one bill for the sake of clustering, when including bill fixed effects, and in
our counterfactual analysis. Table 1 reports the collapsed bill count.
24 Twenty-four districts experienced an increase in average Mexican tariffs over our study period. These
increases are driven by increased protection for a small number of agricultural commodities. Our research
design includes controls for differential trends by district characteristics, including characteristics capturing agricultural activity, in part, to address potential issues this may raise. We also perform a robustness
test in which we drop these districts from our main sample; doing so does not affect our conclusions.
25 Although they are included in our analysis, Hawaii and Alaska are omitted from this figure forconvenience.

12

Figure 1: Exposure to NAFTA Across House Districts(a) Average Change in US Import Tariffs(b) Average Change in Mexican Tariffs

Notes: Figure shows maps of each Congressional district’s exposure to NAFTA for the continental US only. Panel (a) shows the
reduction in the average US import tariff by district, grouping districts by tariff change quintile. Lighter blue districts experienced
smaller changes in US import tariffs, while darker blue districts experienced larger changes. Panel (b) shows the reduction in the
average Mexican tariff by district, grouping districts by quintiles of the change in Mexican tariffs. Lighter red districts experienced
smaller changes in Mexican tariffs, while darker red districts experienced larger changes. These maps were constructed using the
101st Congress district boundaries.

∆τrUSA , grouping districts by quintiles. Districts shown in light blue were in the bottom
quintile of the distribution of US import tariff reductions, while districts in dark blue
were in the top quintile. Panel (b) shows the reduction in average Mexican tariffs by
district, ∆τrMex , again grouping districts by quintiles. Districts shown in light red werein the bottom quintile of the distribution of Mexican tariff changes, while districts indark red were in the top quintile.
Figure 1 highlights two main facts. First, the NAFTA tariff reductions are distributed
widely across the continental US. This suggests our research design will not simply
capture differential trends in political conditions across broad regions, such as Eastern
vs. Western states or coastal vs. inland districts. Second, there is variation in therelative exposures of districts to the US and Mexican tariff reductions, which we exploit
to estimate the effects of both import and export liberalization.
To highlight how environmental RCVs changed during our period of study, Figure 2
shows trends in the number of environmental bills that were put forth for an RCV in
the House and their outcomes over time. The number of bills put up for an RCV ranges
from five to sixteen per year, with an annual average of just under ten and a slightincrease over time. Most notable is the stark reduction in the share of bills that passed
a simple majority after NAFTA’s introduction. Between 1990 and 1993, between 45%
and 80% of environmental bills passed a simple majority. Following the implementationof NAFTA, however, this share fell immediately to below 50%, and declined each year
until 1997, hovering near 25% for the rest of our sample. In the analysis that follows, we
attempt to determine how much of this change is in fact due to NAFTA by exploiting
the geographic variation in exposure to NAFTA across Congressional districts.
13

0

0

5

Number of Bills
10

15

.25
.5
.75
Share of Bills Passed

1

20

Figure 2: House Environmental Bills Over Time

1990

1992

1994

1996

1998

2000

Year
Bill Count

Share Passed

Notes: Figure shows the number of environmental bills voted on and the share that passed a simple majority in the House ofRepresentatives from 1990 to 2000. Bill count is shown in blue bars (left axis) and share passed is shown in the red line (right axis).

4

NAFTA and Environmental Roll Call Votes in the Houseof Representatives

Given our difference-in-difference research design, we begin our analysis with a simple
exercise in which we divide districts into two groups based on the magnitude of theiraverage tariff changes (above and below median reductions), and plot the share of proenvironment roll call votes in each year by the districts that comprise these two groups
over our period of study. Our purpose for doing so is to provide a simple test of ourresearch design; if NAFTA did, in fact, affect voting on environmental bills in the US
House of Representatives, then we should observe distinct changes in voting patterns
across these two groups after the agreement went into effect on January 1, 1994.
The results of this exercise are displayed in Figure 3. Panel (a) shows how the share of
pro-environmental votes changed over time for districts that experienced relatively highand low changes in US import tariffs, while panel (b) shows the corresponding changes
for Mexican tariffs. In both panels, the voting pattern of districts that experienced belowand above-median tariff changes are depicted with blue and red lines, respectively.
The results of this exercise lend confidence to our research design, and provide suggestive evidence that changes in US tariffs due to NAFTA affected federal environmental
policy in the United States. As panel (a) of Figure 3 shows, while there were small level
differences in the likelihood of a pro-environment vote across districts that experienced
large and small changes in US tariffs, the trends in voting across the two groups followed
a similar pattern prior to 1994. After NAFTA’s enactment, the trends appear to diverge
due to reductions in the pro-environmental votes of districts that are highly exposed to
the US tariff reductions. In contrast, panel (b) of Figure 3 suggests Mexican tariff changes
14Figure 3: House Pro-Environment Voting Over Time(a) House Votes & US Import Tariff Changes(b) House Votes & Mexican Tariff Changes.65.6

Pr(Pro−Environment Vote)

Pr(Pro−Environment Vote)

.65

.55

.5

.45

.4

.6

.55

.5

.45
1990

1992

1994

1996

1998

2000

1990

1992

1994

Year
Below Median Exposure

1996

1998

2000

Year
Above Median Exposure

Below Median Exposure

Above Median Exposure

Notes: Figure shows the annual share of pro-environment roll call votes on environmental bills in the House of Representatives from1990 to 2000. Panel (a) and Panel (b) show the plots by the size of each district’s change in US import tariffs and Mexican tariffs,
respectively. In Panel (a), the blue line (circles) shows voting patterns for districts that receive a below-median change in importtariffs and the red line (triangles) shows voting patterns for districts that receive an above-median change in import tariffs. In Panel(b), the blue line (circles) shows voting patterns for districts that receive a below-median change in Mexican tariffs and the redline (triangles) shows voting patterns for districts that receive an above-median change in Mexican tariffs. In both panels, whiskers
display 95% confidence intervals.

did little to affect the formation of environmental policy in the United States, as there areno meaningful differences in the likelihood of a pro-environmental vote across districts
that experienced large and small changes in Mexican tariffs before or after NAFTA.
While Figure 3 is suggestive of NAFTA’s effects on pro-environmental voting, it does
not fully exploit the variation in tariff changes created by trade liberalization. As such, as
the next step in our analysis we present estimates of the average effects of the reductions
in US import tariffs and Mexican tariffs using our main empirical specification.
These estimates are displayed in Table 2, which reports the coefficient estimates fromsix empirical specifications based on Equation (1). Columns (1) through (3) report estimates from our simplest specifications, which only includes district and year fixed
effects. Among these specifications, columns (1) and (2) show the effects of the US and
Mexican tariff reductions in isolation, respectively, while column (3) includes both tariffchanges. The specification reported in column (4) includes initial district NAAQS nonattainment status interacted with year fixed effects to account for the effects of the CAA.
Column (5) includes initial district-characteristics interacted with year fixed effects toaccount for the possibility of differential trends across districts due to systematic differences in demographics and industrial composition. Finally, our baseline specification,
reported in column (6), simultaneously includes initial district CAA non-attainment status and characteristics interacted with year fixed effects. In all four columns, standard
errors two-way clustered by state and bill are reported in parentheses.
The estimates presented in Table 2 indicate that reductions in US import tariffs after15

Table 2: The Effects of NAFTA on House Roll Call Votes(1)∆τrUSA x Postt

(3)

(4)

(5)

(6)

-0.010(0.011)-0.125a(0.039)-0.007(0.010)-0.125a(0.040)-0.007(0.011)-0.155a(0.046)-0.012(0.009)-0.154a(0.046)-0.013(0.009)

X
0.38
50322

X
X
0.38
50322

-0.126a(0.039)∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

(2)

X
0.36
50322

0.36
50322

0.36
50322

0.36
50322

Notes: Table shows results of the reductions in US import tariffs and Mexican tariffs on roll call votes on environmental bills in
the House of Representatives between 1990 and 2000. The dependent variable in all regressions is an indicator for whether the rollcall vote cast by a representative on a particular bill is pro-environment. All regressions include congressional district and year
fixed effects. Column (1) shows the results of a simple difference-in-difference regression of the reduction in US import tariffs only.
Column (3) shows the results of a simple difference-in-difference regression of the reduction in Mexican tariffs only. Column (3)shows the results of a simple difference-in-difference regression jointly estimating the effects of both tariff changes. Column (4) adds
controls for the effects of the Clean Air Act with initial district non-attainment status by year fixed effects. Column (5) adds districtbaseline characteristic by year fixed effects. Column (6) is our baseline specification, which includes all additional controls and fixed
effects. Standard errors two-way clustered by state and bill are shown in parentheses. Significance at the 1%, 5%, and 10% levels aredenoted by a , b , and c , respectively.

NAFTA decreased support for environmental policy. For example, our baseline estimate,reported in column (6), indicates that a 1 pp decrease in US import tariffs reduced
the likelihood of a pro-environment vote in affected congressional districts by 15.4 pp.
Given that the average district in our data faced an import tariff reduction of 0.25 pp,
this estimate implies that NAFTA’s import liberalization decreased the likelihood thatan affected representative cast a pro-environment vote by 3.9 pp, on average. Whilesmall, this effect is economically meaningful given that the average likelihood of a proenvironmental vote in our sample is 51%, suggesting that on the margin the effects ofimport liberalization may have altered the outcomes of some bills. In contrast, the change
in Mexican tariffs appears to have caused a relatively small and statistically insignificant
change in support for environmental policy. Our baseline estimate indicates that a 1 pp
decrease in Mexican tariffs decreased the likelihood of a pro-environment vote in affectedcongressional districts by 1.3 pp. As the average district faced a Mexican tariff reductionof 1.12 pp, this estimate means that the tariff reduction decreased the likelihood of apro-environmental vote by 1.5 pp, although this effect is not statistically significant atconventional levels.

16

4.1

Robustness

We probe the robustness of our baseline results along several dimensions. For brevity,
we briefly describe these tests here, and relegate a full discussion to the online appendix.
We begin by examining whether the estimates of the effects of reductions in US
import tariffs reported in Table 2 are purely capturing the effects of increased importcompetition from Mexico, or are also capturing the effects in reductions in the cost ofimporting intermediate inputs from Mexico. There is is reason to believe this may be thecase as there was significant trade in intermediate goods between the US and Mexico
prior to NAFTA. To examine this possibility, we re-estimate the specifications presented
in Table 2 but replace reductions in district level US import tariffs with the change ineach district’s Effective Rate of Protection (ERP) (Corden, 1966).26 As the ERP captures
the net effect of lowering tariffs on both output and intermediate inputs, this exercise
allows us to examine the extent to which the results presented in Table 2 are driven
by changes in tariffs on intermediate inputs. The results from this exercise, reported in
Online Appendix B, suggest that this is not the case, meaning our estimates primarilyreflect the effects of increased import competition.
Next, we examine other potential explanations for our baseline results. First, we
examine whether our estimates are capturing the effects of other episodes of trade liberalization, particularly the ongoing effects of the Canada-US Free Trade Agreement(CUSFTA), changes in Most Favored Nation tariffs, and increased trade with China. We
then examine whether our results are capturing the effects of other factors that may affect voting on environmental RVCs, including the alignment between a representative
and the party in power in the House, Senate, and Presidency, idiosyncratic aspects ofspecific bills, differential voting incentives in election years, differential trends acrossCensus Divisions, pre-existing industrial decline, and pre-existing differences in political conditions across districts. The results from these tests, reported in Online Appendix
B, indicate that our baseline estimates are not capturing the effects of other factors.
We then examine whether our baseline estimates are capturing differential trends
in outcomes across districts. Although the data plotted in Figure 3 provides suggestive
evidence to the contrary, we further examine this possibility by estimating an event-study
version of our baseline specification. These results, presented in Online Appendix B,
corroborate the evidence presented in Figure 3; they suggest that our baseline estimates
are not simply capturing pre-existing differences in trends across districts.
we replace ∆USA
with ∆ERPr = ∑i [lir,90 /lr,90 ][ ERPi,99 − ERPi,93 ], where ERPi,t =rUSAUSA ] / [1 −[ Tari f f i,t − ∑ j αij Tari f f i,t∑ j αij ] and αij is industry j’s input share in the production of output
26 Specifically,

from industry i.

17Next, we show that our results are robust to several alternative samples, including restrictions to account for the effects of redistricting, and districts that experience increases
in average Mexican tariff rates, expanding our sample to include abstentions and following the LCV’s approach of coding both negative votes and abstentions as not supportinga bill, as well as omitting bills that include non-environmental provisions, are subject
to multiple RCVs, or are related to fossil fuels. The results of these sample restrictions,shown in Online Appendix B, all support our main findings.
We also investigate whether NAFTA’s effects on the likelihood of a pro-environmental
vote depend on the type of legislation being considered given that voting incentives may
be different for final bills, bill amendments or motions. The results from this exercise,
which are also presented in Online Appendix B, suggest that this is not the case; wefind that NAFTA had a similar effect on the likelihood an affected legislator cast a proenvironmental vote across each of these vote types.
We then turn to examine whether NAFTA also altered the set of bills that are subject to an RCV in the House. While we do not believe this is a major concern in our
setting because we focus on RCVs used by the LCV to construct their Environmental
Scorecard and the LCV is explicit in considering “the most important issues of the year”
ensuring our sample only includes meaningful environmental bills, if tariff changes systematically alter the bills that are proposed, then our estimates may be biased due to aselection effect. We examine this possibility in two ways. First, we use data on the fullset of bill proposals in the House between 1990 and 2000 to examine whether NAFTA
affected the likelihood with which a congressperson introduced a new environmental
bill. Second, we examine NAFTA’s effect on the complexity of environmental bills byfollowing an approach used in political science (e.g. Davidson et al. (1988)) and measuring complexity as the number of committee referrals received by each bill. As we showin Online Appendix C, the results from these exercises suggest bill selection is not ofmaterial importance for our analysis. We find that NAFTA had statistically insignificant
and economically small effects on both bill proposals and on the likelihood that a newenvironmental bill was referred to multiple committees.
Lastly, we investigate whether our estimates are biased due to our reliance on a twoway fixed effect estimator to implement our research design. To ensure this is not a cause
for concern, we implement our research design using the DIDl estimator proposed byde Chaisemartin and D’Haultfouille (2022), which is robust to the presence of treatmentheterogeneity and dynamic treatment effects when treatment is both non-staggered andnon-binary. As we show in Online Appendix D, this alternative implementation leaves
our baseline result – that reductions in US import tariffs caused a reduction in the like18

lihood of a pro-environmental vote – unchanged. The DIDl estimation results show that
US tariff reductions caused a significant reduction in pro-environment RCVs in all years
following NAFTA, with the magnitude of this effect growing throughout the decade.
The placebo estimates produced by the DIDl estimator also provide further evidence
that treated and control districts are not trending differently prior to NAFTA.

5

Mechanisms

Thus far, we have shown that reductions in US import tariffs as a result of NAFTA
significantly reduced support for new environmental legislation in the US House ofRepresentatives. We now turn to examine three potential explanations for our results:(i) legislators responding to concerns that dirty industry would relocate to Mexico following NAFTA, (ii) legislators responding to trade-induced changes in the demand forenvironmental policy by their constituents, and (iii) trade-induced changes in support
for the Democratic party.

5.1

NAFTA and Concerns Over Industrial Flight

We begin by asking if our baseline results can be rationalized as a result of concerns that“dirty” industries – those for which complying with environmental regulation comprises
a significant share of production costs – would relocate production to Mexico to take advantage of weaker environmental regulation. There are at least two reasons to believe
this mechanism could explain our results. First, the threat of outsourcing in response todifferences in environmental policy was a salient issue for much of the US public aroundthe time of NAFTRA. For example, 67% of respondents on a 1999 US opinion survey indicated that they believed companies that wanted to avoid the costs associated with highenvironmental standards would relocate to countries where standards were weak (Kull,
2000). Second, previous research suggests that trade liberalization can create incentives
for dirty industries to lobby the government for weaker environmental policy (Fredriksson, 1997, 1999). Legislators could be more responsive to this type of lobbying given thepotential threat that these industries could re-locate to Mexico. Hence, one explanationfor our results is that they are capturing the effects of legislators from affected districts
altering their voting behavior in an effort to prevent industrial flight.
We test this hypothesis by examining if the effects of the NAFTA tariff reductions varyacross districts on the basis of their initial specialization in relatively dirty industries forwhich the cost of abating pollution and complying with environmental regulation is19relatively high.27 If legislators are motivated by concerns that passing environmental
legislation would cause the relocation of dirty industry abroad, then the magnitude ofthe estimated effect of US tariff reductions should be larger in districts for which theseindustries comprise a relatively high share of economic activity. To test this formally, we
estimate four regressions based on Equation (1) in which we allow the effects of the tariff
cuts to vary across districts on the basis of whether the initial average cost of complying
with environmental regulation for industries in the district is relatively high or low.
The results of this exercise are reported in the two panels of Table 3. Each panel ofthe table presents results using a different measure of the average cost of compliancewith environmental regulation. In Panel (a) we measure the costs of complying withenvironmental regulation in each industry as the ratio of pollution abatement operating
costs (PAC) to the total cost of materials, following the approach taken by Ederington
et al. (2005). In Panel (b) we follow Levinson and Taylor (2008) and measure the costs ofcomplying with environmental regulation as the share of PAC in industry value added.
In both cases, we measure a district’s average cost of compliance with environmental
regulation as the employment weighted share of 1990 industry compliance costs using
1990 industry employment shares as weights.28 In the first column of each panel, weclassify districts as having relatively high or low compliance costs (High and Low PAC,
respectively) if the average costs of complying with environmental regulation are above
or below that of the average district. Similarly, in the second column of each panel,
we classify districts as having High or Low PAC if the average costs of complying withenvironmental regulation are above or below that of the median district.
As the results reported in Table 3 show, the estimated effects of the reduction in US
import tariffs following NAFTA in High PAC districts appear to be similar in magnitude
to those in Low PAC districts, regardless of measurement. For example, the estimatesreported in column (1) of the table indicate that a 1 pp decrease in US import tariffs
reduced the likelihood of a pro-environment vote in affected High PAC districts by 16.6
pp and by 15.2 pp in Low PAC districts. Moreover, these estimates are not statisticallydifferent from each other, and the same is true for the estimates reported in the remainingcolumns of the table. This pattern stands in stark contrast to that which would arise if
legislators were motivated by the potential relocation of dirty industries; if it were themotivating concern, the estimated effects of the US import tariff reductions should be
27 We do not study outsourcing and lobbying directly, as data on lobbying activities is not available

prior to 1998. Rather, we examine whether these channels could be of empirical relevance in our setting.
28 We obtain industry PAC data from the 1990 Pollution Abatement Cost and Expenditure survey conducted by the US Census Bureau, and data on total materials costs and value added by industry from the
NBER-CES Manufacturing Industry Database Bartelsman and Gray (1996).

20

Table 3: The Effects of NAFTA on Roll Call Votes in High and Low Pollution Abatement
Cost Districts
Panel (a): PAC/Materials Costs(1)(2)∆τrUSA x Postt
x High PAC
x Low PAC
∆τrMex x Postt
x High PAC
x Low PAC
R2
Obs.

Panel (b): PAC/Value Added(3)(4)-0.166b(0.082)-0.152a(0.053)-0.110(0.070)-0.173a(0.055)-0.125(0.077)-0.164a(0.049)-0.136b(0.064)-0.160a(0.053)-0.013(0.023)-0.012(0.010)-0.024(0.019)-0.013(0.010)-0.020(0.017)-0.013(0.009)-0.014(0.015)-0.014(0.010)

0.38
50322

0.38
50322

0.38
50322

0.38
50322

Notes: Table reports estimates of the effects of the NAFTA tariff reductions on roll call votes in the House of Representatives allowing
the effects to vary across districts on the basis of their average costs of complying with environmental regulation. The dependent
variable in all regressions is an indicator of whether the roll call vote cast by a representative on a particular bill is pro-environment.
In Panels (a) and (b), the cost of complying with environmental regulation are measured as the ratio of PAC to the total cost of
materials, and the ratio of PAC to value added, respectively. In the first column of each panel, districts are classified as having
relatively high or low compliance costs (High and Low PAC, respectively) if the average costs of complying with environmental
regulation are above or below that of the average district. In the second column of each panel, districts are classified as having Highor Low PAC if the average costs of complying with environmental regulation are above or below that of the median district. All
regressions include district and year fixed effects, as well as controls for the effects of the Clean Air Act and differential trends inbaseline characteristics. Standard errors two-way clustered by state and bill are shown in parentheses. Significance at the 1%, 5%,
and 10% levels are denoted by a , b , and c , respectively.

largest in High PAC districts. As such, the estimates reported in Table 3 suggest ourbaseline results are not due to legislators responding to concerns over industrial flight.

5.2

NAFTA and the Demand for Environmental Policy

Given that our baseline estimates do not appear to be a product of a concerns over industrial flight, we next turn to examine if they can be rationalized as a result of legislators
altering their voting behavior in response to trade-induced changes in the policy preferences of their constituents. There is strong reason to believe that this mechanism may beunderlying our findings, as trade has long been thought to alter the level of environmental policy demanded by affected individuals. This hypothesis stems from the pioneering
work of Grossman and Krueger (1991), who argued that if environmental quality is anormal good, then the changes in incomes and pollution levels brought about by trade
will alter the public’s demand for environmental policy. Thus, the responses of incumbent legislators documented in Table 2 could simply reflect changes in the demand for21

environmental policy induced by trade liberalization.
We explore this possibility in two ways. First, we take a direct approach and use
survey data to examine NAFTA’s effects on the stated policy views of voters. Specifically, we investigate NAFTA’s effects on voters’ stated views on environmental policy.
To do so, we use data from the American National Election Studies (ANES) survey from1990 to 2000. These data are well suited for our purposes because contain information the ideology, policy views, demographic characteristics and congressional districtof between 1,300 and 2,500 respondents in each federal election year. Furthermore, they
have been used previously in the context of NAFTA to study the political affiliations ofprotectionist voters (e.g. Choi et al. (2022)).
We use the ANES data to construct a measure of each voter’s support for environmental policy. Specifically, we create an indicator of whether the respondent thought thefederal government should increase spending to improve and protect the environment.
While the ANES includes other questions related to environmental issues, we focus onenvironmental spending because this question was asked consistently throughout ourperiod of study, making it possible to examine how responses changed as a result oftrade liberalization following NAFTA.
Although the ANES data provides a direct measure of voter policy views, given that
individuals could misrepresent their preferences in surveys, we also adopt an indirect
approach for inferring changes in the demand for environmental policy. This approachis informed by models of trade and the environment that formalize the intuition outlined by Grossman and Krueger (1991) and allow for endogenous environmental policychanges in response to trade (e.g. Copeland and Taylor (1994, 1995)). These models
suggest that the demand for environmental policy is determined by real incomes andenvironmental quality. Given this, we examine NAFTA’s effects on average income levels
and environmental conditions to see if they change in a manner that would suggest thatthe demand for environmental policy changed, at least in theory. We examine NAFTA’s
effects on income levels and environmental conditions using annual county-level datafrom 1990 to 2000.29 We obtain these data from two main sources. We measure average
income levels using data on income per capita from the Bureau of Economic Analysis. We measure local environmental conditions using data on the average annual daily
29 We perform this analysis at the county, rather than district, level as regional economic data is not

publicly available for congressional districts. An alternative approach would be to use the Geocorr crosswalk to convert county economic data to the district level. However, as we use this same crosswalk toconstruct our district-level tariff cut measures, doing so would introduce non-classical measurement error.
As such, we opt to perform this analysis at a finer level of geographic aggregation. For consistency, we
also perform our analysis of air quality at the county level.

22

concentration of total suspended particulates (TSPs) collected from the Environmental
Protection Agency.30
We estimate the effects of NAFTA’s tariff cuts on stated support for environmental
policy in affected districts, and on county per-capita incomes and ambient TSP concentrations using specifications analogous to Equation (1). Two key differences bearmention. First, in our direct approach that relies on ANES surveys, we supplement our
specifications with respondent demographic-by-year and demographic-by-region fixed
effects to account for the possibility of differential trends across different groups of voters. Specifically, we allow for the possibility of such trends by gender, age group, race,
education level, family income level, and number of children.31 We also weight these
regressions using the ANES sample weights. Second, as our measures of pollution andincome are reported at the county level, in our indirect approach we estimate the following regression:hihizct =α0 + αUSA ∆τcUSA x Postt + α Mex ∆τcMex x Postt + ϕc + ψt + ect ,(4)where zct is either the level of income per capita or natural log of the annual average daily
TSP concentrations in county c in year t, ∆τcUSA and ∆τcMex are the county analogues
to Equation (2) and Equation (3), respectively, and ϕc and ψt are county and year fixed
effects.32 As such, αUSA and α Mex measure changes in the outcome of interest in response
to a one pp reduction in average USA import tariffs and Mexican tariffs, respectively.
The results of the direct and indirect analyses are reported in the three panels ofTable 4. Panel (a) reports estimates of the effects of the NAFTA tariff cuts on voters’
stated support for environmental policy, while panels (b) and (c) report the corresponding estimates for income per capita and ambient pollution concentrations, respectively.
In each panel, the first column reports a specification analogous to our “simple” specification reported in Table 2; panel (a) includes district and year fixed effects, as well as
voter and interviewer characteristic by year fixed effects, while panels (b) and (c) include
county and year fixed effects. The second column in each panel is our baseline specification, which also accounts for differential trends due to environmental regulations andregional characteristics. In all cases, standard errors clustered by state are reported in
30 We focus on particulate matter as it poses considerable health consequences and has been previously

studied in the context of NAFTA (Cherniwchan, 2017). Furthermore, we use TSPs as our measure ofparticulate matter because it was consistently monitored over our sample period. However, it is worth
noting that we restrict our analysis of TSPs to county-years that contain a valid air quality monitor reading.
31 We also include similar controls for interviewer characteristics in these regressions to allow for the
possibility of differential trends across voters owing to differences in the characteristics of interviewers.
32 We employ the log transformation for TSPs to address the underlying skewness in its distribution.

23

parentheses.
The estimates reported in panel (a) indicate that reductions in US tariffs significantly
reduced support for environmental policy among voters. Our preferred specification,
reported in column (2), indicates that a 1 pp US tariff reduction reduced the likelihoodof a respondent agreeing that the federal government should increase spending on environmental protection by 14 pp. In contrast, reductions in Mexican tariffs have a muchsmaller effect on stated support; a 1 pp Mexican tariff reduction only reduced the likelihood of a respondent agreeing that the federal government should increase spending
on environmental protection by 2.4 pp, although this effect is imprecisely estimated.
Moreover, this pattern is capable of rationalizing the estimates presented in Table 2; itsuggests that NAFTA-induced changes in constituent policy demands are driving legislator responses on environmental RCVs.33
Together, the estimates reported in panels (b) and (c) yield similar conclusions. Theseestimates indicate that, on average, reductions in US import tariffs decreased per capita
incomes and TSP concentrations in affected counties. For example, our estimate in column (4) indicates that a 1 pp reduction in US import tariffs decreased per capita incomesin affected counties by $113, while the estimate in column (6) indicates that a 1 pp reduction in US import tariffs reduced TSP concentrations in these counties by 4%. As
the average county received a 0.54 pp tariff reduction, this suggests that the US importtariff reductions caused per capita incomes in affected counties to fall by just over $61
per year, and TSP concentrations in these counties to decrease by just under 2.2%. Wheninterpreted through the lens of models in which the demand for environmental policy
is determined by income levels and environmental quality, these estimates suggest that
constituent demand for environmental policy should fall, as the willingness to pay for
improvements in environmental quality will decrease if either incomes or ambient pollution levels decrease. Our estimates also suggest that reductions in Mexican tariffs shouldhave little effect on the demand for environmental quality, as they had little effect on percapita income levels, but caused a very small increase in ambient TSP concentrations.34

5.3

NAFTA and Support for the Democratic Party

The estimates presented above suggest trade-induced changes in constituent preferences
for environmental policy may explain why affected legislators altered their votes on envi33 In Online Appendix E, we present estimates from an event-study specification of the effects of tariff
reductions on voter views on the environment and find no evidence of pre-trends.
34 We report the corresponding event-study estimates in Online Appendix E. These estimates indicate
pre-trends in per capita incomes or TSP concentrations are not a concern in our setting.

24

Table 4: The Effects of NAFTA on the Demand for Environmental Policy∆τrUSA x Postt∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

Panel (a): Support forEnv. Prot’n(1)(2)

Panel (b): Income
Per Capita(3)(4)-0.062b(0.025)-0.012(0.018)-0.140b(0.059)-0.024(0.017)-153.803a(39.877)
9.672c(5.390)-112.738a(41.356)
2.652(5.289)

0.20
7766

X
X
0.20
7766

0.95
33374

X
X
0.96
33374

Panel (c):ln(TSP)(5)(6)-0.030a(0.010)0.010a(0.003)-0.040a(0.012)0.008b(0.003)

0.88
1975

X
X
0.89
1975

Notes: Table shows results of the NAFTA tariff reductions on stated views on environmental policy (Panel (a)), local economic
conditions (Panel (b)), and local environmental conditions (Panel (c)). The dependent variable in Panel (a) is an indicator for whether
a survey respondent believes the federal government should increase spending on environmental protection. Data is taken from theAmerican National Election Studies (ANES) survey. The dependent variable in Panel (b) is the county’s average income per capita.
Data is taken from the Bureau of Economic Analysis’s Regional Economic Accounts. The dependent variable in Panel (c) is thenatural log of the county’s median daily ambient total suspended particulate concentration. Data is taken from the Environmental
Protection Agency’s Air Quality System. All regressions in Panel (a) include congressional district fixed effects, year fixed effects,
and voter and interviewer characteristic by year fixed effects, and are weighted by the ANES sample weights. All regressions inPanels (b) and (c) include county and year fixed effects. In each Panel, the first column shows the result of a difference-in-difference
regression without regional economic, regulatory, and demographic by year fixed effects, the second column adds in these regional
controls based on baseline conditions in districts (Panel (a)) or counties (Panels (b) and (c). Standard errors clustered by state arereported in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

ronmental RCVs following NAFTA. However, a plausible alternative hypothesis is thatour baseline estimates are instead a product of trade-induced changes in the partisan
representation of affected districts due to decreased support for the Democratic Party.
There is reason to believe that this could be the case. Previous research by Choi et al.
(2022) indicates that NAFTA decreased support for Democrats due to their position as
the pro-trade party around the time of the agreement.35 Moreover, the environment is apartisan issue; Republican legislators are less likely to support environmental legislation
than their Democratic counterparts (e.g. Nelson (2002), Kim and Urpelainen (2017)). As
a result, our baseline estimates need not reflect trade-induced changes in views on environmental policy; they could instead be an incidental byproduct of a backlash against
the Democratic Party in response to NAFTA.
We examine the veracity of this alternative hypothesis by studying the effects of the
NAFTA tariff cuts on electoral outcomes. If our baseline estimates can be rationalized asa product of trade-induced decrease in support for Democrats, then we should observe
35 Additional research by Che et al. (2022) also highlights that the Democratic party was pro-tradeduring our period of study. Using a regression discontinuity approach to study legislative voting on protrade bills by congressional representatives elected in close elections, Che et al. document that Democrats
are 4.5 pp more likely to support pro-trade bills over the 1992-2000 period.

25

that reductions in US tariffs lead to a decline in the likelihood that a Democratic legislator is elected, whereas reductions in Mexican tariffs have little-to-no effect on electoral
outcomes. As such, we study NAFTA’s effects on electoral outcomes along two margins:
the party of the elected representative, and the “flipping” of districts from one party toanother.
To do so, we adopt a variant of our research design and estimate the effects of the
NAFTA tariff cuts on electoral outcomes from the 102nd to 106th congresses using dataon electoral results from the MIT Election Data Lab. Specifically, we estimate:

vrl =δ0 + δUSA ∆τrUSA x Postl+ δMex ∆τrMex x Postl+ λr + ηl + erl ,(5)where vrl is a measure that reflects the outcome of the election in House district r andcongressional election l, ηl is an election fixed effect, δUSA and δMex are our estimatesof the effects of a 1 pp reduction in US import and Mexican tariffs, respectively, on
the likelihood of a particular electoral result, and all other variables are as defined in
Equation (1). vrl is either an indicator for whether the representative elected is in the
Democratic party, an indicator for whether the district changed parties as a result of theelection, an indicator of whether the district changed from Republican to Democrat, oran indicator of whether the district changed from Democrat to Republican.
Our coefficient estimates from Equation (5) are reported in Table 5. For each dependent variable, we report results from two specifications: the first is analogous to our“simple” specification from Table 2 and only includes district and election fixed effects,
while the second corresponds to our baseline specification and includes district characteristic and CAA non-attainment status by year fixed effects. In the table, columns (1)and (2) display the effects of the NAFTA tariff cuts on the likelihood of a Democrat being elected, where the dependent variable is an indicator reflecting whether the elected
representative is a member of the Democratic party. Columns (3) through (8) report theeffects of the NAFTA tariff cuts on the likelihood of a Congressional district changing
partisan representation, examining three different dependent variables. The dependent
variable in columns (3) and (4) is an indicator for whether the district changed parties
from the last to current election. The dependent variable in columns (5) and (6) is anindicator for whether the district changed from a Republican representative to a Democratic representative. The dependent variable in columns (7) and (8) is an indicator forwhether the district changed from a Democratic representative to a Republican representative. In all cases, standard errors clustered by state are reported in parentheses.
The estimates presented in Table 5 suggest that the reductions in US import tariffs
26

27
0.73
2148

-0.250a(0.063)0.001(0.016)
X
X
0.75
2148

-0.256a(0.084)-0.003(0.015)

(2)

0.27
2148

0.135a(0.039)0.020(0.014)
X
X
0.30
2148

0.141a(0.051)0.014(0.014)Pr(Change
Party)
(3)
(4)

0.21
2148

-0.002(0.023)0.002(0.008)

X
X
0.22
2148

0.016
(0.032)0.000(0.008)Pr(Change
Rep. to Dem.)
(5)
(6)

0.20
2148

0.097a(0.027)0.013(0.011)

X
X
0.21
2148

0.114a(0.035)0.015(0.012)Pr(Change
Dem. to Rep.)(7)(8)

Notes: Table shows results of the NAFTA tariff reductions on results of elections in the House of Representatives for the 102nd to the 106th congress. The dependent variable inColumns (1) and (2) is an indicator for whether the representative elected is a member of the Democratic party. The dependent variable in Columns (3) and (4) is an indicator forwhether the district changed party in the last election. The dependent variable in Columns (5) and (6) is an indicator for whether the district changed from the Republican to Democratic
party in the last election. The dependent variable in Columns (7) and (8) is an indicator for whether the district changed from the Democratic to Republican party in the last election.
All regressions include district and year fixed effects, and regressions in Columns (2), (4), (6), and (8) also include district baseline characteristic and CAA non-attainment by year fixed
effects. Standard errors clustered by state are shown in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

CAA Trends
Charac. Trends
R2Obs.

∆τrMex x Postt∆τrUSA x Postt(1)

Pr(Democrat)

Table 5: The Effects of NAFTA on Electoral Outcomesfollowing NAFTA led to considerable changes in political representation. The estimate
in the first row of column (2) indicates that a 1 pp reduction in US tariffs decreased
the probability of a district electing a Democrat by 26 pp. In contrast, the reduction in
Mexican tariffs had almost no effect on representation, with a 1 pp reduction in Mexican tariffs leading to a 0.3 pp decrease in the probability of a Democrat being elected,
although this effect is not significant at conventional levels.
In addition, the estimates presented in columns (3) to (8) of Table 5 indicate that
this change in political support led to changes in political representation. For example,
the result in column (4) shows that the reduction in US tariffs increased the likelihoodof a district flipping between parties, while reductions in Mexican tariffs had no effect.
Columns (6) and (8) indicate that this flipping primarily benefited the Republican party.
The estimate in column (8), for example, shows that a 1 pp reduction in US import tariffs increased the likelihood a district switched from Democrat to Republican by 11.4 pp,
while the estimate in column (6) indicates that the US tariff change had no significant effect on the likelihood a Republican district switched to a Democrat. Moreover, NAFTA’s
effect on Democrat-to-Republican switching was economically meaningful. Multiplying
the coefficient estimate in column (8) by the average district US tariff reduction suggests that NAFTA increased these district switches by 2.9 pp. Over our entire sample,
the odds of a Democrat-to-Republican switch is 5.9 pp, indicating that the effects of
the NAFTA tariff reductions following NAFTA explain just under 50% of the observed
district switches between 1990 and 2000. This suggests that changes in partisan representation could have had a material impact on the outcomes of environmental RCVs.36

5.4

The Demand for Environmental Policy vs. Partisan Representation

The estimates reported in Sections 5.2 and 5.3 suggest that our main finding – that
reductions in US import tariffs caused a reduction in support for new environmental
legislation in the US House of Representatives – could be rationalized via two starkly
different mechanisms: (i) incumbent politicians responding to trade-induced changes inthe demand for environmental policy, and (ii) trade-induced changes in partisan representation. As they have very different implications for how international trade affects
the formation of environmental policy, as well as other domestic policies, we now turnto assess the extent to which our main estimates can be attributed to these mechanisms.
To do so, we estimate a series of regressions based on Equation (1) in which we allow
the effects of the tariff cuts to vary by either the political party of the district’s represen36 The corresponding event-study estimates are presented in Online Appendix E.

28

tative or an indicator of the representative’s political ideology as an alternative measureof partisanship.37 In each case, we estimate three regressions. The first is analogous toour baseline specification reported in Table 2, and uses our full sample of data. Since ourunit of observation for this specification is a district-year pair, these estimates potentially
capture both the responses of incumbents as well as changes in political representation.
As such, we supplement the second regression with representative fixed effects to isolate
NAFTA’s effects on incumbent voting behavior. As an alternative to this approach, ourthird regression again estimates a specification analogous to our baseline specification,
but restricts the sample to the set of districts that are represented by a single, “continuing,” incumbent legislator throughout our period of study. Although endogenous,
this restriction allows us to purge our estimates of any partisan switching. If NAFTA
primarily affects RCVs by changing affected incumbent legislators’ support for the environment, then our estimates should be closely aligned across all three regressions.
The results from this exercise reported in Table 6. Panel (a) displays the effects of
NAFTA, interacting both the change in US and Mexican tariffs with an indicator thatreflects the party (i.e. Republican or Democrat) of the district’s representative. Panel (b)also reports the effects of NAFTA, instead interacting both tariff changes with indicators capturing the ideology (i.e. Conservative or Liberal) of the district’s representative.
In each panel, the estimates of the effect of changes in US tariffs on pro-environmental
voting by legislators from districts that are represented by Republicans (panel (a)) or
Conservatives (panel (b)) are reported in the first row. The second row reports theseestimates for districts represented by Democrat (panel (a)) or Liberal (panel (b)) legislators. The results in the third and fourth rows display analogous estimates for the effectsof the Mexican tariff changes. Each panel reports results from the three specifications
described above, starting with the regression for the full sample of districts, then adding
representative fixed-effects, and finally estimating the initial regression with the set of
districts the have continuing representatives only. In all cases, standard errors two-way
clustered by state and bill are reported in parentheses.
The estimates reported in column (1) of panel (a) show that our baseline estimatesof the effects of changes in both US import tariffs and Mexican tariffs mask considerable heterogeneity on the basis of a district’s political representation. As the estimatesreported in column (1) show, in districts represented by a Republican legislator, a 1 pp re37 We adopt a common measure of legislator ideology used in political economy and political science(Poole and Rosenthal, 1997): a legislator’s DW-Nominate score. This score is calculated using each legislator’s vote on all House bills throughout their career. The score is a rating on a Liberal-to-Conservative
scale, with a range of -1 (the most Liberal) to +1 (the most Conservative). We use the DW-Nominate score
to label representatives as either Liberal (a negative score) or Conservative (a positive score).

29

Table 6: The Effects of NAFTA on Roll Call Votes by Party and Ideology
Panel (a): Party
(1)
(2)
(3)
∆τrUSA x Postt
x Rep./Cons.
x Dem./Lib.
∆τrMex x Postt
x Rep./Cons.
x Dem./Lib.
Leg. FEs
Contin. Leg.
R2
Obs.

Panel (b): Ideology
(4)
(5)
(6)

-0.232a(0.047)-0.001(0.059)-0.114b(0.045)-0.020(0.043)-0.146a(0.046)-0.064(0.047)-0.239a(0.054)0.010(0.058)-0.144b(0.056)-0.012(0.042)-0.150a(0.052)-0.063(0.047)-0.066a(0.014)0.098a(0.020)-0.014(0.013)0.015(0.025)-0.058c(0.031)-0.002(0.029)-0.066a(0.015)0.095a(0.019)-0.012(0.014)0.011(0.023)-0.058c(0.031)
0.002(0.029)

X
0.40
50322

X
X
0.46
16174

0.45
50321

0.40
50322

0.45
50321

X
0.46
16174

Notes: Table shows results of the NAFTA tariff reductions on roll call votes in the House of Representatives allowing the effect oftreatment to vary by either the party of the current representative or their ideology score. The dependent variable in all regressions
is an indicator of whether the roll call vote cast by a representative on a particular bill is pro-environment. Panel (a) allows theeffect of NAFTA to vary by the representative’s party. Panel (b) allows the effect of NAFTA to vary by the representative’s ideology,
as measured by their DW-Nominate score (a positive score indicates conservative ideology and a negative score indicates a liberal
ideology). All regressions include district and year fixed effects, and baseline district characteristic and CAA non-attainment status
by year fixed effects. The first column in each panel shows the results of our baseline analysis for our full sample. The second
column adds legislator fixed effects, and is estimated on the set of legislators that cast more than one roll call vote in our sample.
The third column eschews legislator fixed effects, but restricts the sample to legislators that hold their district for the entirety of oursample. The first row reports the effect of a reduction in US import tariffs for districts currently with a Republican or conservative
representative. The second row reports the effect of a reduction in US import tariffs for districts currently with a Democratic or liberal
representative. The third row reports the effect of a reduction in Mexican import tariffs for districts currently with a Republican orconservative representative. The fourth row shows the effect of a reduction in Mexican import tariffs for districts currently with a
Democratic or liberal representative. Standard errors two-way clustered by state and bill are shown in parentheses. Significance atthe 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

duction in US tariffs reduced the likelihood of a pro-environment RCV by approximately
23 pp. Conversely, US tariff reductions had almost no effect in districts represented bya Democrat. Moreover, a 1 pp reduction in Mexican tariffs caused the representativesof Republican districts to reduce their support for environmental legislation by 6.6 pp,
but caused the representatives of Democratic districts to increase the likelihood of voting
pro-environment by 9.8 pp.38
The estimates reported in the first row of columns (2) and (3) suggest that the effectsof US tariff reductions in Republican districts reported in column (1) are a product of
38 These differences across parties and ideologies are statistically significant. For example, a Wald testcomparing the baseline import liberalization estimates (Column (1)) for Republicans to that for Democrats
returns an F-statistic of 22.9 and a p-value of 0.00. A Wald test comparing the baseline export liberalization
estimate for Republicans to that for Democrats returns an F-statistic of 38.31 and a p-value of 0.00.

30

changes in both political representation and voting by incumbent politicians. As column(2) shows, including legislator fixed effects causes our estimate of the effect of a change
in US tariffs in affected Republican districts to attenuate; a 1 pp reduction in US importtariffs reduced the likelihood of a pro-environmental RCV by 11.4 pp among Republican
representatives.39 As column (3) shows, adopting our alternative approach to assessing
within-legislator responses to NAFTA yields similar conclusions. This estimate indicatesthat a 1 pp reduction in US import tariffs reduced the likelihood of a pro-environmental
RCV by an affected incumbent Republican by 14.6 pp. Together these estimates suggestthat the effects of changes in political representation and changes in incumbent voting
are both substantial; our estimates from columns (1) and (2) indicate that changes in incumbent voting explain 49% of the reduction in pro-environmental voting in Republican
held districts.
In contrast, the estimates reported in the last two rows of columns (2) and (3) suggestthat the effects of Mexican tariff reductions are entirely due to changes in political representation. The estimates of the effects of the Mexican tariff reductions reported in bothcolumns are small and statistically insignificant, indicating that changes in incumbent
voting behavior explains little of the observed effect. However, as the results in Table 5
indicate that voters responded to the reduction in US import tariffs as a result of NAFTA,
but not to the reduction in Mexican tariffs, this suggests that the estimates in column (1)of Table 6 are driven by electoral churn unrelated to NAFTA.40
Panel (b) paints a similar picture to panel (a). For example, the estimated effects
of reductions in US import tariffs appear to be concentrated in districts represented
by ideological conservatives (Column (4)), with over half of the estimated effect being
driven by changes in the voting behavior of incumbent conservative legislators (Columns(5) and (6)). Similarly, Mexican tariff reductions appear to have significantly impacted
voting in both conservative and liberal districts (Column (4)), but these effects again
appear to be entirely due to changes in political representation (Columns (5) and (6)).
5.4.1

Further Evidence

Altogether, the estimates presented in Table 6 indicate that our baseline finding thatthe formation of federal environmental policy in the US was negatively affected by reductions in US import tariffs following NAFTA can be attributed to both changes in
39 Note that, by necessity, representatives that participate in only one RCV over our sample are omitted

from this regression. We lose one observation as a result.
40 Due to the stark differences in environmental support across parties, any district that changed from
Democrat to Republican would likely see a large reduction in pro-environment RCVs, and any district
that changed from Republican to Democrat would likely see a large increase, as we observe in column (1).

31the voting behavior of incumbent Republicans and changes in political representation inroughly equal proportions. In Online Appendix E.2, we report additional results thatprovide further empirical support for these mechanisms. For the sake of brevity, we
briefly discuss these results here.
To start, we examine whether the changes in the voting behavior of incumbent Republicans that we observe can still be rationalized as a product of trade-induced changes
in the policy preferences of their constituents. We do so in two steps. First, we estimate
a series of regressions analogous to our preferred specifications from Table 4, in which
we allow the effects of the US and Mexican tariff cuts on the demand for environmental
policy to vary on the basis of the political party of the district’s (or county’s) representative. Similar to Table 6, we estimate three specifications: the first reports estimatesfor our full sample of data, while the second and third are restricted to the set of “continuing” districts (or counties) that are held by a single party (or legislator) throughout
our period of study and the set of “non-continuing” districts (or counties) that change
parties (or legislators) at least once during our period of study, respectively. Given that
estimates for our full sample capture the average effects of US and Mexican tariff cuts
across Democratic and Republican held regions, the estimates from these sample restrictions allow us to examine whether these estimates are driven by districts that are held bea single party throughout our period of study, as would be expected if the voting behavior of incumbent Republicans is due to trade-induced changes in the policy preferencesof their constituents.
The results from this exercise match this expectation. Using both our direct and indirect measures of policy demand, we find that reductions in US tariffs caused a decreasein support for environmental policy in Republican represented districts and counties,
and this effect is larger in incumbent districts and counties that were represented by the
Republican party throughout our period of study.
These results also suggest that that reductions in US tariffs also appear to have
reduced the demand for environmental policy amongst constituents represented by
Democrats throughout our period of study, which is at odds with the results presented
in Table 6 which indicate incumbent Democratic legislators, unlike their Republicancounterparts, do not change their voting behavior on environmental bills in responseto reductions in US tariffs. To investigate this discrepancy further, we exploit the factthat the ANES also contains information as to whether each respondent is a memberof the Democratic or Republican parties, or identifies as an independent and examine
whether there is heterogeneity in the effects of the NAFTA tariff cuts on stated support
for environmental policy across voters with different political affiliations.
32

The key insight from this investigation is that reductions in the demand for environmental policy in response to US tariff reductions that we observe in districts thatare represented by a single party throughout our period of study are driven by the responses of constituents who self identify as either a Republican or an Independent. This
result provides a natural explanation for the observed difference in the change in votingof incumbent Republican and Democratic legislators in response to the US tariff cuts:
Democratic legislators appear not to change their votes because trade liberalization does
not impact the environmental policy demands of their main political constituency.
These two examinations also suggest that trade-induced changes in partisan representation are unlikely to be due to the effects of tariff reductions on constituent preferences for environmental policy, as both US and Mexican tariff cuts have little effect on
voter views in non-continuing districts. Hence, as a final step, we examine whether the
NAFTA induced change in partisan representation that we observe is consistent withaffected voters decreasing support of Democratic legislators in response to their adoption of pro-NAFTA positions prior to the agreement’s ratification. To do so, we again
estimate the effects of the NAFTA tariff cuts on electoral outcomes, but we now consider
the effects of the tariff cuts across two sub-samples differentiated according to whether
the district’s representative voted for or against the NAFTA Implementation Act (HR3450), the roll call vote to ratify the agreement.
Consistent with Choi et al. (2022), the results from this exercise indicate reductions in
US tariffs following NAFTA caused voters to reduce their support for Democratic representatives who had voted in favor of the agreement. We find that among the sample
of districts whose representative voted in favor of NAFTA, US tariff reductions significantly increased the likelihood of the district flipping from Democrats to Republicans.
In contrast, we find no such evidence for districts whose representative voted against
NAFTA, and find no evidence to suggest that US tariff reductions significantly affected
the likelihood of the district flipping from Republicans to Democrats. Together, theseresults suggest that much of NAFTA’s effect on the formation of environmental policyin the US House of Representatives can be rationalized as a byproduct of voters electing
Republicans to replace pro-NAFTA Democrats.

6

Is Environmental Policy Different?

Altogether, our results suggest that NAFTA significantly impacted legislative voting on
environmental bills in the US House of representatives by: (i) causing a reduction in
support for environmental policy by Republican legislators in response to trade-induced
33

changes in the demand for environmental policy by their constituents, and (ii) causing
voters in affected districts to elect Republicans to replace Democrats who had supported
the trade agreement. One question that remains is whether the first of these mechanisms
is unique to environmental policy. There is reason to believe that this might not be thecase, as previous research has documented that import competition can lead to a generalrightward shift in political preferences (e.g. Autor et al. (2020)). This means our findings
could be capturing a broader NAFTA-induced shift towards “conservatism” on a range
of issues, rather than a specific change on environmental policy.
We explore this possibility in two ways. First, we examine whether NAFTA similarly affected constituents’ policy preferences for five alternative policy issues: welfare,social security, crime, abortion, and immigration. To do so, we again rely on data fromthe ANES. We construct indicators analogous to our environmental policy indicator forviews towards welfare, social security, and crime reduction using the questions related
to whether the federal government should increase spending on each program. We construct an indicator of whether respondents support legal abortion based on whether the
respondent thought women should always be able to access abortion, by law. We construct a similar indicator of support for immigration based on whether the respondent
thought the US should increase employment-based immigration.41
We then use these indicators as dependent variables in five specifications analogous
to Equation (1) to examine if the NAFTA tariff cuts significantly impacted voter policy
views on non-environmental issues. As in our baseline specification for views on environmental policy, each regression includes district and year fixed effects, and initial
district characteristics and CAA non-attainment status interacted with year fixed effects
as well as controls to allow differential trends across different groups of voters as well asinterviewers with different characteristics. Each regression is weighted using the ANES
sample weights, and standard errors are clustered by state in all cases. Lastly, as weare interested in performing several joint hypothesis tests (i.e. testing the significanceof NAFTA’s tariff changes on multiple policy views), we adopt the stepwise multiple
testing procedure of Romano and Wolf (2005) to control for the familywise error rate
across all tests.
The results from this exercise are reported in Table 7. Column (1) again reports ourbaseline estimates of the effects of the NAFTA tariff cuts on stated support for environmental policy from column (2) of Table 4, whereas columns (2) through (4) report how
NAFTA affected voters’ views on federal spending on welfare, social security, and crime,
41 It is worth noting that the questions pertaining to federal spending were not asked in the 1998 ANES

questionnaire. The questions on crime, welfare, and immigration were not asked in 1990.

34

Table 7: The Effects of NAFTA on Voters’ Policy Views(1)∆τrUSA x Postt∆τrMex x Postt
R2
Obs.

(2)

(3)

(4)

(5)

(6)

Increase Federal Spending on:
Env.
WelfareSocialCrime
Prot’nSec.

Other Policies:
Legal
Increase
Abortion
Immig.

-0.140b†(0.059)-0.024(0.017)-0.025(0.055)0.015(0.022)-0.019(0.054)0.042c(0.022)-0.008(0.058)-0.029(0.019)0.003(0.061)0.032c(0.018)0.031(0.033)-0.004(0.013)

0.20
7766

0.22
6111

0.26
7791

0.19
6160

0.21
8761

0.19
6912

Notes: Table shows results of the NAFTA tariff reductions on views expressed on federal policy issues by voters between 1990 and
2000. Voter views are taken from the American National Election Studies survey. The dependent variables in columns (1) through(4) are indicators of whether the survey respondent believes the federal government should increase spending on: environmental
protection (column (1)), welfare (column (2)), social security (column (3)), or crime reduction (column (4)). The dependent variable incolumn (5) is an indicator for whether the respondent believes abortions should always be permitted by law. The dependent variablein column (6) is an indicator for whether the respondent believes the government should allow more immigration. All regressions
include congressional district and year fixed effects, baseline district Clean Air Act non-attainment status and characteristic byyear fixed effects, and voter and interviewer demographic by year fixed effects. All regressions are weighted by the ANES sample
weights. Standard errors clustered by state are shown in parentheses. Significance in a standard t-test at the 1%, 5%, and 10% levels
are denoted by a , b , and c , respectively. Significance in a Romano and Wolf (2005) multiple hypothesis test at the 10% level is denotedby † .

respectively. Columns (5) and (6) show how NAFTA affected voters’ views on abortionand immigration, respectively. The first row in the table reports the effect of reductions
in US tariffs, while the second row reports the effects of Mexican tariff reductions.
The estimates presented in Table 7 suggest that NAFTA did not cause a systematic
shift in constituent policy preferences. If such a shift occurred, then in response to US
tariff reductions we should observe changes in support for all forms of Federal spending, and changes in support for legal abortion and immigration. Instead, it appears thatthese tariff reductions did little to change constituents’ stated preferences for other policies, meaning that trade liberalization altered support for environmental policy amongst
affected voters without systematically impacting their views on other issues.42
Although the estimates presented in Table 7 provide strong evidence that our findings are not capturing a systematic conservative shift in affected constituent preferencesin response to trade liberalization, it is possible that respondents are misrepresenting
their views on the ANES. Hence, as our second exercise we examine if the NAFTA tariff
cuts had similar effects on RCVs for an alternative policy issue: abortion. Reproductive
42 Meyer (2022) documents a similar pattern for US voters in response to an alternative negative eco-nomic shock: the Great Recession. He finds that increases in the local unemployment rate reduces voter
support for policies to address climate change, but do not impact their support for other partisan issues(namely gun control, abortion rights, and support for same-sex marriage).

35

rights are a well known partisan issue (Bouton et al., 2021); if our results are simply
capturing a broader NAFTA-induced shift towards conservatism, then NAFTA shouldhave similar effects on votes on reproductive rights to those we observe on environmental policy. That is, we should observe that reductions in US tariffs decreased the
support for reproductive rights in affected districts by causing both changes in partisan
representation and decreasing support amongst incumbent legislators.
We examine NAFTA’s effects on support for reproductive rights using data from thecongressional scorecard constructed by the American Conservative Union’s Center forLegislative Accountability (CLA).43 We compile voting records on each RCV related toreproductive rights included in the CLA scorecard between 1990 and 2000, and thenuse this information to construct an indicator of whether the RCV on bill v cast by the
representative of district r at time t is pro-choice. We then estimate NAFTA’s effects on
the likelihood an affected legislator casts a pro-choice RCV using Equation (1).44
The results of this analysis are presented in the four columns of Table 8. Each column
corresponds to a different specification. Column (1) reports the average effects of the US
and Mexican tariff reductions for RCVs on each issue. For comparison, the analogous
estimate on environmental RCVs is reported in column (4) of Table 2. Columns (2)(4) allow the effect of both US and Mexican tariff reductions to vary by the party ofthe district’s representative, akin to the analysis of environmental RCVs presented inPanel (a) of Table 6. Column (2) reports estimates of the effect of each tariff allowing
the effect to vary across districts based on the contemporaneous party membership ofthe district’s representative. The specification in column (3) allows NAFTA’s effects tovary by party and includes a representative fixed effect. The specification in column (4)again allows NAFTA’s effects to vary by party, but restricts the sample to continuing
incumbent legislators who hold their district for the entirety of our sample.
The estimates presented in Table 8 provide further evidence that our findings are notcapturing a systematic conservative shift in constituent policy preferences in responseto reductions in US tariffs. While the estimate reported in the first row of column (1)suggests that, on average, a 1 pp reduction in US tariffs led to a 21.3 pp reduction in
the likelihood that the representative of an affected district casts a pro-choice vote, theestimates reported in the second and third rows of columns (2)-(4) indicate that this effect
43 Similar to the LCV, the CLA develops the its scorecard as a means of assessing the voting records ofeach member of the House of Representatives, and has been doing so since 1971. The CLA determines theconservative position of relevant bills and classifies them by issue. We use this information to determine
the set of bills that pertain to reproductive rights and each representative’s position on these bills.
44 Unlike with our analysis of NAFTAs effects on environmental RVCs, there are relatively few RCVs
on reproductive rights. Thus, we cluster standard errors by state, rather than state and bill.

36

Table 8: NAFTA and Roll Call Votes on Reproductive Rights(1)∆τrUSA x Postt

x Dem.

(4)-0.241a(0.062)-0.107b(0.042)-0.055(0.052)-0.136b(0.055)-0.086(0.093)-0.059(0.083)-0.051a(0.016)0.084a(0.019)0.017(0.016)-0.020(0.023)-0.013(0.028)-0.066c(0.036)-0.011(0.015)x Rep.
x Dem.
Leg. FEs
Contin. Leg.
R2
Obs.

(3)

-0.213a(0.056)x Rep.

∆τrMex x Postt

(2)

X
0.64
6920

0.65
6920

0.76
6916

X
0.75
2221

Notes: Table shows results of the NAFTA tariff reductions on roll call votes on bills relating to reproductive rights. The dependent
variable in all regressions is an indicator of whether the roll call vote cast by a representative on a particular bill corresponds to the“pro-choice” position. Column (1) shows the overall effect of both the US and Mexican tariff changes. In columns (2)-(4), the effectsof NAFTA are allowed to vary by the representative’s party. Column (2) reports results from our baseline specification. Column(3) adds legislator fixed effects, and is estimated on the set of legislators that cast more than one roll call vote on the panel’s issue.
Column (4) eschews legislator fixed effects, but restricts the sample to legislators that hold their district for the entirety of our sample.
All regressions include district and year fixed effects, and baseline district Clean Air Act non-attainment status and characteristic byyear fixed effects. Standard errors are clustered by state and are shown in parentheses. Significance at the 1%, 5%, and 10% levels
are denoted by a , b , and c , respectively.

is driven primarily by changes in political representation in Republican held districts.
As the estimate reported in the second row of column (2) shows, a 1 pp reduction in
US tariffs led to a 24.1 pp reduction in the likelihood the representative of an affected
Republican district casts a pro-choice vote. However, once we include legislator fixed
effects, as in column (3), or restrict the sample to the set of districts that were represented
by a single incumbent legislator, as in column (4), this estimate attenuates considerably
and is no longer statistically significant at conventional levels. This suggests that theestimate reported in column (2) is driven by changes in partisan representation rather
than changes in the voting behavior of incumbent legislators, which is consistent with
our finding from Table 7 that NAFTA did not meaningfully impact affected voters’ statedsupport for legalized abortion.45
45 It is worth noting that the results presented in the third row of Table 8 suggest that incumbent

Democrats may be reducing the likelihood they cast a pro-choice RCV in response to reductions in US
tariffs, although the evidence for this is mixed. However, as we show in Online Appendix E, this change37

7Conclusion

This paper examines whether trade liberalization between the US and Mexico following
the enactment of NAFTA affected the formation of federal environmental policy in the
US. We do so by examining the effects of bilateral tariff reductions between the US
and Mexico following NAFTA on the roll call votes cast by legislators in the US Houseof Representatives on environmental legislation over the period 1990-2000. We isolate
the causal effects of trade liberalization by leveraging: (i) temporal variation in US and
Mexican tariff rates created by the implementation of the agreement, and (ii) geographic
variation in the level of exposure to the tariff cuts across congressional districts createdby differences in initial industrial composition. We exploit these two sources of variation
in a generalized difference-in-difference research design.
We find robust evidence that trade liberalization following NAFTA significantly affected legislative votes on federal environmental policy in the United States. Our preferred estimates indicate that, on average, a 1 percentage point reduction in US importtariffs in an affected House district reduced the likelihood that the district’s representative votes in support of the environment by 14 percentage points. In contrast, we find noevidence to suggest that reductions in Mexican tariffs significantly altered the likelihoodof a pro-environment vote by representatives in affected districts.
These results appear to be caused by: (i) incumbent Republican legislators decreasing
their support for environmental policy in response to the demands of their main political constituency, and (ii) voters in affected congressional districts reducing support for
Democratic legislators who supported NAFTA, leading to the election of Republicans.
We find no evidence to suggest that legislator responses were motivated by concerns ofindustrial flight by dirty industries, despite such flight being a salient issue for muchof the US public at the time. We also find no evidence to suggest that our results arecapturing the effects of a broader trade-induced shift towards conservatism.
Altogether, our findings provide empirical support for a hypothesis that underlies
much of the debate over the environmental consequences of globalization, namely thatgovernments alter environmental policy in response to the effects of international trade.
However, there are at least two caveats worth mentioning. First, our study focuses on
an episode of North-South trade liberalization between countries with different environmental standards. While our results suggest that these differences did not meaningfully
alter the voting behavior of affected legislators, it is possible that this would not be true
appears to be due to these Democrats responding to changes in preferences of self-identified Independent
voters in their districts, as opposed to a general conservative shift in preferences across all groups.

38

of other episodes of trade liberalization. Second, our results also highlight the potential
importance of elections, electoral incentives, and partisan politics in mediating the relationship between trade and environmental policy. As such, it is possible that trade’s
effect on the formation of environmental policy may hinge on political context. We leavefurther investigation of these possibilities to future work.

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43

Online Appendix A

Additional Summary Statistics

This section provides additional summary statistics to complement those presented in
the main paper. First, Table A.1 shows correlations between the tariff changes resulting from NAFTA and various district characteristics, as these motivate the inclusion ofcharacteristic-trends in our analysis. District characteristics include various 1990 demographics, taken from Adler (2021), covering the share of the district’s population aged
65 and above, the share black, the share born outside the US, and the share living in arural area. We also include district median incomes and share of employment in farming, both from Adler, and the share of employment in manufacturing, taken from theadjusted county business patterns (CBP) database developed by Eckert et al. (2020). The
first column shows correlations for the US tariff change and the second column shows
correlations for the Mexican tariff change, with p-values in brackets.
Table A.1: Correlations Between District Tariff Changes and 1990 Characteristics

Pop. Share - Above 65
Pop. Share - BlackPop. Share - Foreign
Pop. Share - RuralMedian Income
Emp. Share - Farm
Emp. Share - Manuf.

(1)
US Tariff Change(2)
Mexican Tariff Change

0.036[0.453]0.138a[0.004]-0.064[0.186]0.119b[0.013]-0.408a[0.000]0.101b[0.037]0.555a[0.000]-0.089c[0.065]-0.104b[0.031]-0.011[0.813]-0.026[0.583]0.111b
[0.021]-0.142a[0.003]0.347a[0.000]Notes: Table shows pairwise correlations between the districts tariff change as a result of NAFTA and various district
characteristics. All district characteristics are measured for 1990. Column (1) shows correlations for the US import tariffchange, while Column (2) shows correlations for the Mexican tariff change. Rows one through four show correlations
between tariff changes and the share of the population aged 65 or older, black, born outside the US, and living in a ruralarea, respectively. Row five shows correlations between tariff changes and district median incomes. Rows six and sevenshow correlations between tariff changes and the share of the workforce employed in farming and manufacturing,
respectively. The p-value on each correlation is shown in brackets. Significance at the 1%, 5%, and 10% levels aredenoted by a , b , and c , respectively.

The statistics in column (1) of Table A.1 indicate that the size of a district’s US tariff reduction is positively correlated with the district’s rural population share, share of
the population that identifies as black, employment share in farming, and employment
share in manufacturing, but negatively correlated with the district’s income level. The
second column indicates that the size of a district’s Mexican tariff reduction is positively
correlated with the district’s employment share in manufacturing and income level, but
44

Table A.2: Correlations Between District Tariff Changes and 1992 Republican Vote Share

Republican Vote Share(1)
US Tariff Change(2)
Mexican Tariff Change-0.042[0.383]0.024[0.616]

Notes: Table shows the correlation between the district tariff change as a result of NAFTA and the vote share of the Republican
party in the election prior to NAFTA. Column (1) shows the correlation for the US tariff changes. Column (2) shows the correlation
for the Mexican tariff changes.

Table A.3: Correlations in Constituent Policy Views

Env. Spending
Welfare Spending
Soc. Sec. Spending
Crime Spending
Pro-Choice
Immig’n

(1)

(2)

(3)

(4)

(5)

(6)

Env.
Spending
1.000
0.167a0.109a0.126a0.091a0.049aWelfareSpending

Soc. Sec.
Spending

Crime
Spending

ProChoice

Immig’n

1.000
0.183a0.061a0.016
0.084a1.000
0.158a-0.027b
0.001

1.000
-0.039a-0.032b1.000
0.026c1.000

Notes: Table shows correlations between each of the respondent policy views assessed in Table 5. Voter policy views are taken fromthe American National Election Studies survey. Significance in a standard t-test at the 1%, 5%, and 10% levels are denoted by a , b ,and c , respectively.

negatively correlated with the share of the district’s population above the age of 65, theshare of the population that identifies as black, and the employment share in farming.
In addition, Table A.2 assess whether the magnitude of the NAFTA tariff changes
vary systematically depending on pre-NAFTA political conditions. We do so by computing the correlation between each of the district’s tariff changes (both Mexican andUS) and the share of votes received by the Republican party in 1993. In the table, thefirst column reports the correlation for the US tariff changes, while the second column
shows the correlation for the Mexican tariff changes, with p-values in brackets. As thetable shows, the correlation between each tariff and the Republican vote share in the
pre-NAFTA election are both small and statistically insignificant, suggesting changes intariffs were unrelated to political conditions.
Lastly, Table A.3 shows correlations between each of the six policy preference variables used in our analysis of policy preferences (Table 7). Of note is that views onenvironmental protection are positively correlated with all additional policy measures.
That is, respondents who believe the federal government should spend more on environmental protection are more likely to believe the government should spend more
on welfare, social security, and crime, and are more likely to be pro-choice and favor
increased immigration.

45

Online Appendix B

Robustness Tests

We probe the robustness of our main results along six main dimensions.
First we examine whether our estimates of the effects of reductions in US importtariffs solely capturing the effects of increased import competition from Mexico, or ifthey are also capturing the effects in reductions in the cost of importing intermediate
inputs from Mexico. As we noted in the main text, there is is reason to believe this may
be the case as there was significant trade in intermediate goods between the US and
Mexico prior to NAFTA. To examine this possibility, we re-estimate the specifications
presented in Table 2 but replace reductions in district level US import tariffs with thechange in each district’s Effective Rate of Protection (ERP) (Corden, 1966):
lir,90[ ERPi,99 − ERPi,93 ](B.1)∆ERPr = ∑
lr,90
i
USA −
USA ] / [1 −where ERPi,t = [ Tari f f i,t∑ j αij Tari f f i,t∑ j αij ] and αij is industry j’s input
share in the production of output from industry i. Because ∆ERPr captures the net
effect of lowering tariffs on both output and intermediate inputs, this exercise allows
us to determine if our main estimates are capturing the effects of changes in tariffs onintermediate inputs.
The results from this exercise are presented in Table B.4. As these estimates show,
accounting for the effects of reductions in tariffs in intermediate inputs has a modest
effect on the magnitude of our empirical estimates; the estimates reported in Table B.4
are smaller in absolute value than the corresponding estimates reported in Table 2 of themain text. However, the estimates reported in Table B.4 are not statistically distinguishable from those reported in Table 2 of the main text at conventional levels, suggestingthat our main estimates are primarily capturing the effects of changes in import competition created by reductions in tariffs on output.
In our second robustness exercise, we examine other potential explanations for our
results. The results of the first such exercise are reported in the nine columns of Table B.5. In columns (1) and (2) we examine whether our estimates are capturing theeffects of ongoing changes in tariffs as the result of other relevant trade agreements,
with column (1) addressing ongoing tariff changes due to the Canada-US Free Trade
Agreement (CUSFTA) and column (2) addressing multilateral trade negotiations as partof the General Agreement on Tariffs and Trade. In column (1), to flexibly control for theeffects of CUSFTA, we incorporate into our baseline regression an interaction between
the change in both the district’s Canadian and US tariffs resulting from CUSFTA that
occurred after NAFTA’s implementation (that is, between 1994 and 2000) with a postNAFTA indicator.46 In column (2), we include an interaction between the change in the
Most Favored Nation (MFN) tariffs that occurred after NAFTA’s implementation with apost-NAFTA indicator. In column (3) we account for each district’s exposure to tradewith China, to ensure our results are capturing the effects of the China shock (Autor
46 We follow the same procedure outlined in Section 3 of the main text, and create the district’s exposure

to CUSFTA as a weighted average of each industry’s tariff changed, using district employment shares as
weights.

46

Table B.4: The Effects of NAFTA on House Roll Call Votes(1)∆ERPr x Postt

(3)

(4)

(5)

(6)

-0.010(0.011)-0.087a(0.027)-0.008(0.010)-0.087a(0.027)-0.008(0.011)-0.103a(0.029)-0.013(0.008)-0.102a(0.029)-0.013(0.008)

X
0.38
50322

X
X
0.38
50322

-0.088a(0.026)∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

(2)

X
0.36
50322

0.36
50322

0.36
50322

0.36
50322

Notes: Table reports estimates of the effects of reductions the Effective Rate of Protection in the US and Mexican tariffs on roll callvotes on environmental bills in the House of Representatives between 1990 and 2000. The dependent variable in all regressions is
an indicator for whether the roll call vote cast by a representative on a particular bill is pro-environment. All regressions include
congressional district and year fixed effects. Column (1) shows the results of a simple difference-in-difference regression of the
reduction in US import tariffs only. Column (3) shows the results of a simple difference-in-difference regression of the reduction in
Mexican tariffs only. Column (3) shows the results of a simple difference-in-difference regression jointly estimating the effects of bothtariff changes. Column (4) adds controls for the effects of the Clean Air Act with initial district non-attainment status by year fixed
effects. Column (5) adds district baseline characteristic by year fixed effects. Column (6) corresponds to our baseline specification,and includes all additional controls and fixed effects. Standard errors two-way clustered by state and bill are shown in parentheses.
Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

et al., 2013). We do so by controlling for the natural logarithm of the district’s imports
from and exports to China in each year.47 In column (4) we supplement our baseline
specification with indicators that reflect whether a given representative is a member ofthe majority party in the House of Representatives and Senate, or whether the representative’s party affiliation aligns with the party of the President. We include these controls
to account for differential voting incentives that may arise depending on who controls
the Senate and Presidency. In column (5), we include bill fixed effects to ensure that
we are not capturing idiosyncratic aspects of specific bills. In column (6), we include
district by election-year fixed effects to account for the possibility of differential roll callvoting behavior in election years. In column (7), we include Census Division by year
fixed effects to ensure our results are not capturing differential trends across broadly
defined regions. In column (8), we control for each district’s share of workers employedin blue-collar jobs by including baseline blue-collar worker share by year fixed effects toensure our results are not capturing the effects of industries already on the decline priorto NAFTA (see, e.g. Hakobyan and McLaren (2016)). Column (9) controls for all of these
additional factors simultaneously.
As the estimates reported in Table B.5 show, our main findings are highly robust.
The estimates reported in the table are similar in magnitude to those from our baseline
specification, indicating that our baseline estimates are not capturing the effects of otherfactors.48
47 Similar to the approach taken by Autor et al., we construct measures of district imports and exports byallocating industry trade flows to the district level using the initial share of district industry employment
in national industry employment as weights.
48 Controlling for CUSFTA tariff changes appears to substantially increase the estimated effects of the US
tariff changes (Column (1)), while controlling for MFN tariff changes appears to substantially increase the

47

48
0.38
50322

X

-0.261a(0.086)-0.004(0.016)

0.38
50322

X

-0.124b(0.059)-0.054(0.040)

(2)

0.38
50322

X

-0.152a(0.046)-0.013(0.009)

(3)

0.39
50322

X

-0.124a(0.043)-0.015(0.009)

(4)

0.44
50322

X

-0.155a(0.048)-0.013(0.009)

(5)

0.38
50322

X

-0.152a(0.046)-0.013(0.009)

(6)

0.38
50322

X

-0.096c(0.053)-0.021b(0.010)

(7)

X
0.38
50322

-0.146a(0.046)-0.013(0.009)

(8)

X
X
X
X
X
X
X
X
0.46
50322

-0.184b(0.085)-0.090b(0.043)(9)Notes: Table shows results of the NAFTA tariff cuts on roll call votes in the House of Representatives. The dependent variable in all regressions is an indicator for whether the roll callvote cast by a representative on a particular bill is pro-environment. All regressions include district and year fixed effects, and district baseline characteristic and CAA non-attainment
status by year fixed effects. Column (1) includes interactions between the change in both the district’s Canadian and US tariffs resulting from the Canada-US Free Trade Agreement(CUSFTA) that occurred after NAFTA’s implementation (that is, between 1994 and 2000) with a post-NAFTA indicator. In column (2), we include an interaction between the change in
the World Trade Organization’s Most Favored Nation (MFN) tariffs that occurred after NAFTA’s implementation with a post-NAFTA indicator. Column (3) controls for the natural log
of each district’s exports to and imports from China. Column (4) adds variables capturing the representatives alignment with the party in power in the House, Senate, and Presidency.
Column (5) includes bill fixed effects. Column (6) adds district by election-year fixed effects. Column (7) includes census division by year fixed effects. Column (8) adds the district’sshare of workers in blue collar sectors to the set of baseline characteristic by year fixed effects. Column (9) adds to the baseline regression all additional controls and fixed effects from
Columns (1) to (8). Standard errors two-way clustered by state and bill are shown in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

CUSFTAMFN
China ShockAlignm. Vars.
Bill FEs
Dist.-Elec. FEs
Cen. Div-Year FEs
Blue Collar
R2Obs.

∆τrMex x Postt∆τrUSA x Postt(1)

Table B.5: The Effects of NAFTA on House Roll Call Votes - Robustness Tests

In our third robustness exercise, we examine the possibility that our results are capturing the effects of time-varying changes in political conditions. We omitted suchchanges from our baseline specifications as NAFTA exposure is uncorrelated with preNAFTA political conditions, as shown in Online Appendix A. For completeness sake,however, we report the results from controlling for such differential trends in Table B.6.
We adopt three approaches to account for the possibility of differential trends based on
initial political conditions. First, in column (1) we include an interaction between the
Democratic party’s initial vote share in the district and year fixed effects. Second, incolumn (2), we include an interaction between the party the holds the district’s seat in
the first year the district enters our sample (1990 for most districts, and 1993 for the
districts created following redistricting) and a year fixed effect. Third, in column (3), we
include both additional controls. As the estimates reported in Table B.6 show, accounting for a district’s party of representation or voting patterns prior to NAFTA causes nomeaningful change in our estimates of NAFTA’s effects on RCVs.
Table B.6: The Effects of NAFTA on House Roll
Call Votes - Additional Robustness Tests∆τrUSA x Postt∆τrMex x Postt
Init. Party
Democrat Share
R2
Obs.

(1)

(2)

(3)

-0.148a(0.044)-0.012(0.009)-0.149a(0.046)-0.012(0.009)-0.149a(0.044)-0.012(0.008)

X
0.38
50322

X
X
0.38
50322

X
0.38
50322

Notes: Table shows results of the reductions in US import tariffs and
Mexican tariffs on roll call votes on environmental bills in the House ofRepresentatives between 1990 and 2000, controlling for pre-NAFTA political conditions. Column (1) includes an interaction between the Democratic party’s vote share in the first year the district enters our sample
and a year fixed effect. Column (2) includes an interaction between theparty that holds the district’s seat in the first year the district enters oursample and a year fixed effect. Column (3) includes both controls. The
dependent variable is an indicator for whether the roll call vote cast by
a representative on a particular bill is pro-environment. The regression
includes district Clean Air Act and baseline characteristic by year fixed
effects, and district and year fixed effects. Standard errors two-way clustered by state and bill are shown in parentheses. Significance at the 1%,5%, and 10% levels are denoted by a , b , and c , respectively.

The fourth dimension along which we probe our main results is to ensure they do
not reflect differential trends in outcomes across districts. We do so by estimating theestimated effects of the Mexican tariff changes (Column (2)), both of which suggest our baseline regression
may be underestimating NAFTA’s effects on RCVs. However, these estimates are not statistically different
from our baseline estimates at conventional levels.

49

following event-study version of our baseline specification:M

yvrt = β 0 +

∑

βkUSA



τrUSA × 1(t = k )



k=−m
M

+

∑

βkMex



τrMex × 1(t = k )+ λr + ψt + evrt

(B.2)

k=−m

where the regression coefficients βkUSA and βkMex measure the effect of the changes in US
import tariffs and Mexican tariffs, respectively, in the m years before to the M years after
NAFTA, and all other variables are defined as before. If, as we have assumed, there areno other factors aside from NAFTA driving differential trends across districts, then weshould observe β̂kUSA = 0 and β̂kMex = 0 for m = {1990, 1991, 1992}.
The results of this analysis are displayed in the two panels of Figure B.1.49 Panel (a)depicts our estimates of βkUSA , while panel (b) depicts our estimates of βkMex . In bothcases the associated 95% confidence intervals constructed using standard errors that are
two-way clustered by state and bill are plotted around the estimates.
The coefficients plotted in the figure suggest that our baseline estimates are not simply capturing pre-existing differences in trends across districts, as β̂kUSA and β̂kMex are,for the most part, small and not statistically different from zero prior to 1994.50 Moreover, the coefficient estimates displayed in Panel (a) indicate that the effect of the US
import tariff reduction increased in magnitude between 1994 and 1998, suggesting that
NAFTA’s effect on environmental voting grew over time. This potentially reflects thefact that many of NAFTA’s tariff reductions were phased-in over our period of study.51
For our fifth robustness exercise, we examine whether our results are robust to several
alternative samples. First, we reproduce the analysis in Table 2 of the main text dropping
any environmental bills related to fossil fuels, as these bills may be treated differently
compared to legislation on other environmental issues. These results, shown in Table B.7,
indicate that the effects of NAFTA on non-fossil fuel related environmental bills are very
similar to our main estimates.
We also produce an event study using this sample of bills by estimating Equation (B.2). The results of the event study are shown in Figure B.2, with panel (a) showing
the estimates for the US tariff change and panel (b) showing the estimates for the Mexican tariff change. Omitting fossil fuel related bills lends further confidence to our results.
The US tariff reductions produce no significant change in RCVs prior to NAFTA, and
49 The corresponding point estimates and standard errors are available from the authors on request.
50 One notable exception is that β̂1992 is negative and statistically significant. This is caused by enviUSA
ronmental bills that regulate fossil fuels, of which there were an unusually large number in 1992. This
produces this effect for two reasons. First, fossil fuel-related bills in our dataset receive less support thanother environmental bills (42% vs. 50% pro-environment). Second, there is a negative correlation between
a district’s tariff change and their support for fossil fuel-related bills prior to NAFTA. In Figure B.2, weshow that dropping the 18 bills related to fossil fuels from our analysis eliminates any significant estimatesprior to NAFTA, but leaves our main results unchanged.
51 Over 50% of US tariffs on Mexican imports and 31% of Mexican tariffs on US imports were removed
immediately upon NAFTA’s implementation, while the majority of the remaining tariffs were removed
according to predetermined schedules within ten years (Kowalczyk and Davis, 1998).

50

Figure B.1: House Roll Call Vote Event Study(a) USA Import Tariff Reduction(b) Mexico Tariff Reduction

.1

.04

Pr(Pro−Environment Vote)

Pr(Pro−Environment Vote)

0

−.1

−.2

.02

0

−.02

−.3
−.04
−.4
1990

1991

1992

1993

1994

1995
Year

1996

1997

1998

1999

2000

1990

1991

1992

1993

1994

1995
Year

1996

1997

1998

1999

2000

Notes: Figure shows coefficient estimates from a difference-in-difference event study estimating the effects of the NAFTA tariff
reductions on roll call votes in the House of Representatives. Panel (a) shows estimates of the effects of US import tariff reductions
and panel (b) shows estimates of the effects of Mexican tariff reductions. The dependent variable is an indicator for whether theroll call vote cast by a representative on a particular bill is pro-environment. The regression includes district, year, and district-byelection year fixed effects, as well as initial CAA non-attainment status and district baseline characteristic by year fixed effects. The
year prior to NAFTA, 1993, is the omitted category. 95% confidence intervals from standard errors two-way clustered by state andbill are plotted around the coefficient estimates.

Table B.7: The Effects of NAFTA on Non-Fossil Fuel Roll Call Votes∆τrUSA x Postt∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

(1)

(2)

(3)

(4)

-0.159a(0.043)-0.007(0.011)-0.160a(0.043)-0.007(0.012)-0.185a(0.049)-0.012(0.009)-0.185a(0.049)-0.012(0.009)

X
0.43
42466

X
X
0.43
42466

X
0.41
42466

0.41
42466

Notes: Table shows results of the reductions in US import tariffs and Mexican tariffs on roll call votes onenvironmental bills in the House of Representatives between 1990 and 2000, omitting any bills that pertain
to fossil fuels. The dependent variable in all regressions is an indicator for whether the roll call vote cast by
a representative on a particular bill is pro-environment. All regressions include congressional district andyear fixed effects. Column (1) shows the results of a simple difference-in-difference regression. Column(2) controls for the effects of the Clean Air Act. Column (3) includes district baseline characteristics byyear fixed effects. Column (4) is the baseline analysis, which includes all additional controls and fixed
effects. Standard errors two-way clustered by state and bill are shown in parentheses. Significance at the
1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

cause a significant reduction in pro-environmental voting after NAFTA’s introduction.
We then examine five additional samples. The results of these regressions are shownin Table B.8. In column (1) we restrict our sample to the years 1993 onward to ensurethat our baseline estimates are not being driven by the district reapportionment that
occurred following the 1990 census. In column (2) we restrict our sample to exclude
bills where the issue classification includes “other” to ensure that our estimates are not51

Figure B.2: House Roll Call Vote Event Study(b) Mexico Tariff Reduction
.04

0

.02
Pr(Pro−Environment Vote)

Pr(Pro−Environment Vote)(a) USA Import Tariff Reduction
.1

−.1

−.2

−.3

0

−.02

−.04

−.4

−.06
1990

1991

1992

1993

1994

1995
Year

1996

1997

1998

1999

2000

1990

1991

1992

1993

1994

1995
Year

1996

1997

1998

1999

2000

Notes: Figure shows coefficient estimates from a difference-in-difference event study estimating the effects of the NAFTA tariff
reductions on roll call votes in the House of Representatives, omitting any bills that pertain to fossil fuels. Panel (a) shows estimatesof the effects of US import tariff reductions and Panel (b) shows estimates of the effects of Mexican tariff reductions. The dependent
variable is an indicator for whether the roll call vote cast by a representative on a particular bill is pro-environment. The regression
includes district and year fixed effects, and district baseline Clean Air Act non-attainment status and characteristic by year fixed
effects. The year prior to NAFTA, 1993, is the omitted category. 95% confidence intervals from standard errors two-way clustered bystate and bill are plotted around the coefficient estimates.

potentially capturing voting on other issues that have been included on environmental
bills. In column (3) we omit the twenty-four congressional districts that experienced anincrease in Mexican tariffs over our sample period, as the political conditions in these
districts may be systematically different from the rest of the country. In column (4) werestrict our sample to omit bills that are subject to multiple roll call votes, as the votes
for these bills may be subject to different incentives than other votes in our sample. In
column (5) we expand our sample to treat RCV abstentions as negative votes following
the classification scheme used by the LCV.
Table B.8: The Effects of NAFTA on House Roll Call Votes - Alternative Samples∆τrUSA x Postt∆τrMex x Postt
R2
Obs.

(1)

(2)

(3)

(4)

(5)

-0.216a(0.046)-0.008(0.011)-0.144a(0.044)-0.011(0.008)-0.168a(0.044)-0.025(0.033)-0.126a(0.046)-0.009(0.008)-0.139a(0.046)-0.014(0.009)

0.41
41694

0.35
39828

0.39
47702

0.35
41114

0.35
52312

Notes: Table shows results of the NAFTA tariff cuts on roll call votes in the House of Representatives for various samples. The
dependent variable in all regressions is an indicator for whether the roll call vote cast by a representative on a particular bill is
pro-environment. All regressions include district and year fixed effects, and district baseline characteristic and CAA non-attainment
status by year fixed effects. Column (1) restricts the sample to years after redistricting (1993-2000). Column (2) omits any bills
that may address non-environmental issues (in addition to environmental issues). Column (3) omits any districts that experienced
an increase in average export tariffs. Column (4) omits any bills that are subject to multiple roll call votes. Column (5) includes
abstentions and classifies them as “negative” votes. Standard errors two-way clustered by state and bill are shown in parentheses.
Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

52

As the estimates reported in Table B.8 show, all five restricted samples produce estimates that are not statistically distinguishable from those in our baseline specification,
which suggests that our preferred estimates are not capturing the effects of redistricting,particular characteristics of certain bills and districts, or the LCV’s treatment of abstentions.
Lastly, as our final robustness exercise, we examine whether the effect of NAFTA’s
tariff changes varies depending on the type of legislation being considered, given thatlegislator incentives may change throughout the voting process. Here, we separately
estimate NAFTA’s effects on three different types of RCVs: those on the final passage ofa bill, those on a proposed amendment to a bill, and those on a motion. These results,
shown in Table B.9, indicate that the effects of NAFTA on RCVs is remarkably consistentacross each of these three types of RCVs, suggesting our estimates are not masking
underlying heterogeneity in voting responses.
Table B.9: The Effects of NAFTA on RCVs, by Vote Type∆τrUSA x Postt∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

Final Bill
(1)

Amendment(2)

Motion(3)-0.168b(0.081)-0.001(0.012)-0.158a(0.047)-0.015(0.009)-0.159c(0.055)0.001(0.012)

X
X
0.45
12488

X
X
0.37
36166

X
X
0.63
1648

Notes: Table shows results of the reductions in US import tariffs and Mexican tariffs on roll call votes
on environmental bills in the House of Representatives between 1990 and 2000. Column (1) restricts the
sample to RCVs on bill passage. Column (2) restricts the sample to RCVs on proposed bill amendments.
Column (3) restricts the sample to RCVs on motions. The dependent variable in all regressions is anindicator for whether the roll call vote cast by a representative on a particular bill is pro-environment. All
regressions include congressional district and year fixed effects, controls for the effects of the Clean Air
Act, and district baseline characteristics by year fixed effects. Standard errors two-way clustered by stateand bill are shown in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c ,respectively.

Online Appendix C

The Introduction of New Environmental Bills

As discussed in the main text, a potential issue with our estimates is that they may
be biased due to a selection effect created by a NAFTA-induced change in the set ofbills that appear before Congress. That is, if NAFTA systematically changed the set ofenvironmental bills introduced in the House, then comparing roll call votes before andafter NAFTA would misrepresent NAFTA’s effect on RCVs. Though we have strong53reason to believe this concern is minor in our setting, as we discuss in Section 4.1 ofthe main paper, here we examine this issue directly by estimating NAFTA’s effects on
the likelihood that a congressperson introduced a new environmental bill, as well as thecomplexity of the environmental bills introduced (measured by number of committee
referrals). If bill selection is an important concern, then we should find a change in billproposals or complexity by legislators more exposed to NAFTA’s tariff reductions.
To perform this exercise, we collect data on all bill proposals in the House between
1990 and 2000 from the Congressional Bills Project data of Adler and Wilkerson (2021).
The Congressional Bills Project records information on all bill proposals to the House between 1947 and 2008. The dataset includes information on the bill’s sponsor, committee
referrals, and a categorization of it’s main topic.52 We use this information to construct
a district-level panel capturing the introduction of new bills by the district’s representative. We use this data to collect all bills that are related to the environment, and thenconstruct two measures for each district-year: an indicator of whether the district’s representative introduced at least one environment-related bill that year and an indicator ofwhether any of their environmental bills were referred to multiple committees.
Before discussing our analysis, we first describe our approach to measuring bill complexity. While a full examination of bill content is beyond the scope of this paper, we
examine a simple measure of bill complexity: the number of committees to which a billhas been referred. After a bill is introduced in the House, it must be referred to committee for further assessment, before potentially returning to the House floor for a rollcall vote. Bills may be referred to one or more committees for assessment. The ability
to refer bills to multiple committees is a relatively recent change to congressional rules;
it was introduced to the House in 1975 to both aid in assessing complex policy issues
and to encourage inter-committee cooperation on jurisdictional conflicts (Davidson et al.,1988). Thus, bills assigned to multiple committees should, on average, be more complex
than single-committee bills. We use this logic to examine whether NAFTA affected thecomplexity of new environmental bills.
With this data, we then estimate a generalized difference-in-difference regression
analogous to that used in our main analysis by estimating the following regression:




USA
Mex
brt = a0 + aUSA ∆τr
x Postt + a Mex ∆τr
x Postt + λr + ψt + ert ,(C.3)
where r and t index house districts and years, respectively, and brt is either the new billindicator or multiple referral indicator. In Equation (C.3), all other variables are as inEquation (1), and aUSA and a Mex are our estimates of the effects of a 1 pp reduction in
US and Mexican tariffs, respectively. Lastly, we cluster standard errors by state.
The results of this analysis are presented in the two panels of Table C.1. In Panel (a),the dependent variable is the indicator of whether the district’s representative introduced
at least one environmental bill in a particular year. The sample for this analysis includes
all district-years. In Panel (b), the dependent variable is an indicator for whether the
52 The dataset categorizes bills into 23 different topic areas, using the topic definitions from the Com-

parative Agendas Project. The topic list is available at: http://www.comparativeagendas.net/pages/
master-codebook.

54

district’s representative introduced an environmental bill that was referred to multiplecommittees that year. The sample for this analysis only includes district-years that introduced at least one environmental bill. Each panel shows results of four specifications,each of which includes a different set of controls, as indicated by the table.
Table C.1: NAFTA and the Introduction and Complexity of Environmental Bills(1)∆τrUSA x Postt∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

∆τrUSA x Postt∆τrMex x Postt
CAA Trends
Charac. Trends
R2
Obs.

-0.035(0.048)-0.012(0.021)Panel (a): Pr(Environmental Bill)(2)(3)-0.032(0.048)-0.012(0.021)-0.085(0.066)-0.021(0.028)-0.084(0.066)-0.022(0.028)

X
0.27
4767

X
X
0.27
4767

X
0.24
4767
(5)
-0.135(0.138)0.056(0.035)0.25
4767

Panel (b): Pr(Multiple Referral)(6)(7)-0.119-0.014(0.139)(0.174)0.056
0.005(0.037)(0.030)
X

0.37
952

0.37
952

(4)

X
0.45
952

(8)
-0.020(0.207)0.009(0.029)
X
X
0.45
952

Notes: Table shows results of the NAFTA tariff cuts on the introduction of new bills pertaining to the environment, energy, or public
lands in the House of Representatives. The dependent variable in Panel (a) is an indicator of whether the district’s representative
introduced a new bill in a particular year. The dependent variable in Panel (b) is an indicator of whether an environmental bill
introduced by the district’s representative in a given year was referred to multiple committees, estimated on the sample of districtyears for which the district’s representative sponsored a new environmental bill. All regressions include congressional district andyear fixed effects. Column (1) shows the results of a simple difference-in-difference regression. Column (2) controls for the effectsof the Clean Air Act. Column (3) includes district baseline characteristic by year fixed effects. Column (4) is the baseline analysis,
which includes all additional controls and fixed effects. Standard errors clustered by state are shown in parentheses.

The results in Panel (a) of Table C.1 show reductions in both US import tariffs and
Mexican tariffs did not significantly impact the introduction of environmental bills. For
example, our baseline estimates (column (4)), indicate that a 1 pp reduction in US import tariffs reduced this likelihood by 8.4 pp. Not only is this estimate not statisticallydifferent from zero, but it is economically small as well. Given the average reduction
in US import tariffs across districts is 0.25 pp, this suggests that NAFTA reduced thelikelihood of introducing a new environmental bill by 2.1 pp.53
53 Note that representatives in 22% of district-years introduced a new environmental bill in our sample.

55

The results in Panel (b) indicate that neither the US nor Mexican tariff reductions hada measurable effect on committee referrals. For example, our baseline estimate (column(8)) shows that reductions in US import tariffs caused a small, but statistically insignificant, decrease in the likelihood that a district’s representative had an environmental
bill referred to multiple committees. On average, US import tariff reductions reduced
the likelihood of a multiple bill referral by less than 1 pp among district-years with atleast one environmental bill.54 As approximately 40% of district-years that introduce
an environmental bill have at least one referred to multiple committees in our sample,
the effects of both the US and Mexican tariff reductions on multiple referrals appear to
be relatively small. This suggests that NAFTA did little to alter the complexity of theenvironmental bills introduced in the House, as measured by committee referrals.
Figure C.1: Bill Selection Event Study(b) Number of Environmental Bills(a) Pr(Environmental Bill)
1.4

Pr(Environmental Bill)

Pr(Environmental Bill).5.2

US Tariff
Mexican Tariff

0

−.2

0
US Tariff
Mexican Tariff

−.5

−1

−1.5
−.4
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year

Notes: Figure shows coefficient estimates from an study estimating the effects of the NAFTA tariff cuts on the introduction of new
bills pertaining to the environment, energy, or public lands in the House of Representatives. The dependent variable in Panel (a) is
an indicator of whether the district’s representative introduced a new bill in a particular year. The dependent variable in Panel (b)is an indicator of whether an environmental bill introduced by the district’s representative in a given year was referred to multiplecommittees, estimated on the sample of district-years with at least one environmental bill. In each panel, coefficient estimates and
95% confidence intervals are shown for US tariffs (in blue) and Mexican tariffs (in red). All regressions include congressional district
and year fixed effects, and district characteristic and CAA non-attainment by year fixed effects. The year prior to NAFTA, 1993, isthe omitted category. 95% confidence intervals from standard errors clustered by state are plotted around the coefficient estimates.

To assess the robustness of the results presented in Table C.1, we estimate an event
study variant of Equation (C.3) for both dependent variables, adopting our baseline
specification (columns (4) and (8) in Table C.1). Coefficient estimates and associated 95%
confidence intervals from both event studies are shown in Figure C.1. In Panel (a), thedependent variable is the indicator of whether the district’s representative introduced atleast one environmental bill in a particular year. In Panel (b), the dependent variable isour multiple-committee referral indicator. Both event study estimates show no meaningful pattern for either the US or Mexican tariff reductions, further suggesting that bill
selection is not of material importance in our setting.
54 This statistic is computed by multiplying the point estimate in Column (4) of Table C.1 by the average

reduction in district import tariffs.

56Online Appendix D

An Alternative Estimator

As noted in the main text, one additional concern with our baseline estimates is that they
may be biased due to the presence of systematic differences in treatment effects acrossgroups or time. This potential concern arises because we have implemented our research
design using a two-way fixed effect estimator. However, as shown by de Chaisemartin
and D’Haultfouille (2022), if there are differences in treatment effects across groups ortime, then the treatment effect estimates returned from such estimators are a weighted
average of these underlying heterogeneous effects, where the weights may be negative.
Thus, one may be concerned that our finding of a negative effect of the US import tariffs
on RCVs is simply a spurious result due to the presence of negative weights in our twoway fixed effect regression. To address this concern, we implement our research designusing the DIDl estimator proposed by de Chaisemartin and D’Haultfouille (2022), which
is robust to the presence of treatment-heterogeneity and dynamic treatment effects.
Table D.1: The Effects of NAFTA on RCVs: An Alternative Estimator∆τrUSAx 1994x 1995x 1996x 1997x 1998x 1999x 2000
N

(1)

(2)

(3)

(4)

-0.036(0.015)-0.093(0.036)-0.084(0.030)-0.091(0.032)-0.119(0.033)-0.109(0.036)-0.128(0.033)-0.053(0.018)-0.123(0.039)-0.132(0.044)-0.161(0.058)-0.195(0.068)-0.200(0.074)-0.247(0.086)-0.101(0.035)-0.218(0.074)-0.274(0.104)-0.364(0.133)-0.439(0.163)-0.483(0.188)-0.578(0.217)-0.101(0.035)-0.218(0.074)-0.274(0.104)-0.364(0.133)-0.439(0.163)-0.483(0.188)-0.578(0.217)35,92935,92935,92935,929Notes: Table shows results of NAFTA’s US import tariff reduction on the likelihood of a pro-environment RCV,
using de Chaisemartin and D’Haultfouille (2020)’s DIDl estimator that is robust to treatment heterogeneity anddynamic treatment effects. Estimates for each year from 1994 to 2000 are shown. Results from three specifications
are shown. Each regression includes district and year fixed effects. Column (1) has no controls, Column (2) adds
initial Clean Air Act (CAA) non-attainment status by year fixed effects , Column (3) adds baseline characteristic byyear fixed effects, and Column (4) includes initial CAA non-attainment status and baseline characteristic by year
fixed effects. Standard errors are cluster-bootstrapped by state, using 300 repetitions. The table also shows thenumber of observations used in estimation (N).

The results of this exercise are reported in Table D.1, which displays estimates fromour main empirical specification (Equation (1)) as implemented by the DIDl estimator.
We report coefficient estimates from four specifications. As in Table 2 of the main paper,column (1) reports estimates which only includes district and year fixed effects. Column
57

(2) adds initial district CAA non-attainment status by year fixed effects. Column (3) includes initial district-characteristic by year fixed effects. Finally, column (4), corresponds
to our baseline specification which simultaneously includes initial district CAA nonattainment status and district-characteristic by year fixed effects. Given the nature of the
DIDl estimator, each specification reports estimates of the US import tariff’s effects on
the likelihood of casting a pro-environment RCV by year, controlling for Mexican importtariff changes. In all cases, bootstrapped standard errors, clustered by state, are reported
in parentheses.55
The estimates reported in Table D.1 are consistent with our main results. For ourbaseline specification (column (4)), a reduction in US import tariffs caused a statisticallysignificant reduction in pro-environment RCVs in each year from 1994 to 2000. As inthe event-study estimates reported in Figure B.1, the magnitude of the US import tariffchange effect also increases over time. In addition, the estimates from the alternative
specifications (columns (1)-(3)) all show a similar pattern, although the estimated magnitudes are smaller without the inclusion of initial district-characteristic by year fixed
effects.
For our baseline specification, (column (4) in Table D.1), we also use the DIDl estimator to perform an alternative event-study style placebo test for the presence of preexisting differences in trends across the treated and control groups. This exercise uses
DIDl estimation to estimate treatment effects two or more years prior to treatment, omitting the year immediately prior to treatment. The results of this exercise are shown in
Figure D.1, which shows the placebo estimates from 1990 to 1992 and the main treatment
effect estimates from 1994 to 2000. For each estimate, a 95% confidence interval is displayed, produced from standard errors bootstrap-clustered by state with 300 repetitions.
The placebo estimates in Figure D.1 indicate that are main results are not simply due
to pre-existing differential trends in RCVs, as they show no meaningful pattern prior to
NAFTA. The placebo estimates are all relatively small in magnitude and are statisticallyindistinguishable from zero in 1990 and 1992, and marginally significant in 1991.56 This
corroborates the results of the event study analysis presented in Figure B.1, which also
indicated that pre-existing differences by trade-exposure are not an issue in our setting.
As these placebo estimates are robust to the presence of dynamic treatment effects, they
provide further support for our research design.

Online Appendix E

Additional Results

This section presents additional empirical results referenced in the main text. Section E.1
presents additional event study results, while Section E.3 presents other results.
55 These standard errors are bootstrapped 300 times. We cluster by state rather than by state and bill as

the DIDl estimator does not allow for two-way clustering.
56 The estimate and standard error in 1992 is very small, which is why it appears omitted in the figure.

58

Figure D.1: DIDl Placebo Estimates

Pr(Pro−Environment Vote).50
US Tariff Estimate
95% C.I.
−.5

−1
1990

1992

1994

1996

1998

2000

Year
Notes: Figure shows results of NAFTA’s US import tariff reduction on the likelihood of a pro-environment RCV, using de Chaisemartin and D’Haultfouille (2022)’s DIDlestimator that is robust to treatment heterogeneity and dynamic treatment effects. Placebo treatment effect estimates from 1990 to 1992 and treatment effect estimates from 1994
to 2000 are shown with a 95% confidence interval. Standard errors are cluster-bootstrapped by state, using 300 repetitions.

E.1

Event Study Results

This subsection presents additional event study results to complement the analysis presented in the main paper. To save space, coefficient estimates and 95% confidence intervals are shown for each event study.57
First, to complement the analysis presented in Section 4.2 that examines NAFTA’s effects on the demand for environmental policy, we produce event studies for voters’ statedviews on environmental policy, and county economic and environmental conditions. The
event study on voters’ views on environmental policy is shown in Figure E.1. The dependent variable in this event study is an indicator for whether the respondent feels thefederal government should increase spending on environmental protection. The regression includes initial district CAA non-attainment status and baseline-characteristic byyear fixed effects, respondent and interviewer demographic-by-year and by-state fixed
effects, and district and year fixed effects, with standard errors clustered by state. The
omitted year in all regressions for both the US and Mexican tariffs is 1993, the year priorto NAFTA.58 Estimates for US tariff changes are shown in blue; estimates for Mexican
tariff changes are shown in red. As the figure shows, US and Mexican tariff changes
prior to NAFTA had no significant effect on environmental policy views of respondents.
Following NAFTA, US import tariff reductions reduced support for the environment,with the peak occurring in 2000. In contrast, Mexican tariff changes had no significant
effect on environmental policy views post-NAFTA.
Second, Figure E.2 shows the results of event studies examining the effects of NAFTA
on county income per capita (Panel (a)) and ambient total suspended particulate concentrations (Panel (b)) between 1990 and 2000. The dependent variable in Panel (a) is the
57 Result tables are available upon request.
58 The relevant ANES question was not asked in 1998. Hence, that year is omitted from the regression.

59

Figure E.1: Voter Environmental Policy View Event Study

Pr(Increase Fed. Spending on Env.).2

0
US Tariff
Mexican Tariff
−.2

−.4
1990

1992

1994
Election Year

1996

2000

Notes: Figure shows coefficient estimates from a difference-in-difference event study estimating the effects of the NAFTA tariff
reductions on views expressed on environmental policy stringency by voters between 1990 and 2000. Voter views are taken from theAmerican National Election Studies survey. The dependent variable is an indicator of whether the survey respondent believes thefederal government should increase spending on environmental protection. Coefficient estimates and 95% confidence intervals areshown for the US tariff reduction (in blue) and the Mexican tariff reduction (in red). The regression includes district and year fixed
effects, district baseline characteristic and CAA non-attainment by year fixed effects, and respondent and interviewer demographics
interacted with year and state fixed effects. Standard errors clustered by state are shown in parentheses. The year prior to NAFTA,
1993, is the omitted category. Standard errors are clustered by state. The year 1998 is omitted, as this question was not asked in thatsurvey.

county’s per capita income, while the dependent variable in Panel (b) is the natural logof the county’s average daily TSP concentration recorded over the year. Each regression
includes initial county CAA non-attainment status and baseline-characteristic by year
fixed effects, and county and year fixed effects, with standard errors clustered by state.
The omitted year for both the US and Mexican tariffs is 1993, the year prior to NAFTA.
Estimates for US tariff changes are shown in blue; estimates for Mexican tariff changes
are shown in red.
The results in Panel (a) of Figure E.2 show no significant effect of NAFTA on county
incomes prior to 1994, and a stark reduction tied to import tariffs beginning in 1994 andpersisting throughout the decade. The results in Panel (b) show no significant effect of
the import tariff reductions prior to NAFTA’s implementation, with a significant reduction in TSP following NAFTA, although the effect is not statistically significant in theyears between 1996 and 1998. Panel (b) also shows no meaningful pattern with respect
to the Mexican tariff reductions.
Third, we assess the robustness of our analysis of NAFTA’s effects on electoral outcomes, shown in Section 5.3, by estimating event study variants of the regressions included in Table 5 of the main text. Coefficient estimates and confidence intervals fromthese event studies are shown in Figure E.3. Results of four regressions are shown,each of which corresponds to the different dependent variables in Table 5 (as labeled in
the figure). All regressions include district baseline characteristic and initial CAA nonattainment by year fixed effects and district and year fixed effects, with standard errors
clustered by state. The omitted year in all regressions for both the US and Mexican tariffs is 1993, the year prior to NAFTA. Estimates for US tariff changes are shown in blue;
estimates for Mexican tariff changes are shown in red. The results of all four regressions
60Figure E.2: County Economic and Environmental Conditions Event Studies(b) Total Suspended Particulates

100

.2

0

.1

US Tariff
Mexican Tariff

−100

−200

ln(TSP)

Income Per Capita(a) Income Per Capita

US Tariff
Mexican Tariff

0

−.1

−300

−.2
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year

Notes: Figure shows coefficient estimates from a difference-in-difference event study estimating the effects of the NAFTA tariff
reductions on county economic conditions and environmental quality. The dependent variable in Panel (a) is the county’s average
income per capita, while the dependent variable in Panel (b) is the natural log of the county’s median daily ambient total suspended
particulate concentration. In each panel, coefficient estimates and 95% confidence intervals are shown for the import shock (in blue)
and the export shock (in red). Each regression includes county baseline characteristic and CAA non-attainment status by year fixed
effects, and county and year fixed effects. The year prior to NAFTA, 1993, is the omitted category. Standard errors are clustered bystate.

indicate that there is no evidence of differential trends in electoral outcomes between
treated and control districts prior to NAFTA, and a significant change in electoral outcomes following NAFTA’s introduction.

E.2

Further Evidence of NAFTA’s Effects on The Demand For Environmental Policy and Partisan Representation

This section presents additional results referenced in Section 5.4.1 of the main text.
E.2.1

NAFTA and the Demand for Environmental Policy: Redux

As we note in the main text, the estimates presented in Table 6 indicate that changes inthe voting behavior of incumbent Republicans explain close to half of NAFTA’s effects
on the formation of environmental policy in the US. The results presented in Table 4
suggest that such changes are due to these legislators responding to the demands oftheir constituents. However, those estimates capture the average effect of tariff changes
across all affected districts, meaning that they need not necessarily reflect changes in the
demands of constituents in Republican districts. Given this, here we examine whether
the changes in the voting behavior of incumbent Republicans we reported in Table 6 of
the main text can still be rationalized as a product of trade-induced changes in the policy
preferences of their constituents.
We do so by estimating a series of regressions analogous to our preferred specifications from Table 4 of the main text, in which we allow the effects of the US and Mexican
61Figure E.3: Electoral Outcome Event Studies(a) Pr(Republican)(b) Pr(Change Party).2.4

Pr(Democrat Elected)

US Tariff
Mexican Tariff

−.2

−.4

Pr(District Changes Party)

.3
0

.2
US Tariff
Mexican Tariff
.1

0

−.6

−.1
1990

1992

1994
Election Year

1996

1998

1990

(c) Pr(Change Rep. to Dem.)

1992

1994
Election Year

1996

1998

(d) Pr(Change Dem. to Rep.).2.1

US Tariff
Mexican Tariff

0

−.1

−.2

Pr(District Changes Dem. to Rep.)

Pr(District Changes Rep. to Dem.).3.2
US Tariff
Mexican Tariff

.1

0

−.1
1990

1992

1994
Election Year

1996

1998

1990

1992

1994
Election Year

1996

1998

Notes: Figure shows coefficient estimates from a difference-in-difference event study estimating the effects of the NAFTA tariff
reductions on electoral outcomes. The results of four regressions, corresponding to four different dependent variables, are shownin panels (a)-(d). The dependent variable in panel (a) is an indicator for whether the representative elected is a member of the
Democratic party. The dependent variable in panel (b) is an indicator for whether the district changed party in the last election. The
dependent variable in panel (c) is an indicator for whether the district changed from the Republican to Democratic party in the lastelection. The dependent variable in panel (d) is an indicator for whether the district changed from the Democratic to Republican
party in the last election. In each panel, coefficient estimates and 95% confidence intervals are shown for US tariffs (in blue) andMexican tariffs (in red). Each regression includes district baseline characteristic and CAA non-attainment by year fixed effects, anddistrict and year fixed effects. The year prior to NAFTA, 1993, is the omitted category. Standard errors are clustered by state.

tariff cuts to vary on the basis of the political party of the district’s (or county’s) representative. These results are presented in Table E.1. Panel (a) reports our estimatesof NAFTA’s effects on stated support for spending on environmental protection. Panels (b) and (c) report the corresponding estimates for income per capita, and ambient
pollution concentrations, respectively. In each panel, the first column reports estimates
for the full sample of data; as a result, these estimates capture the average effects of US
and Mexican tariff cuts across Democratic and Republican held districts (or counties, inpanels (b) and (c)). The specification reported in the second column restricts the sample to the set of “continuing” districts (or counties) that are held by a single party (orlegislator) throughout our period of study, while the third restricts the sample to theset of “non-continuing” districts (or counties) that change parties (or legislators) at least
62

once during our period of study.59 We include controls corresponding to the analogous
preferred specification in Table 4, and standard errors clustered by state are reported inparentheses.
Three key findings emerge from Table E.1. First, reductions in US tariffs caused a decrease in support for environmental policy in Republican represented districts and counties, and this effect is larger in incumbent districts and counties that were represented
by the Republican party throughout our period of study. For example, our estimatesindicate that a 1 pp reduction in US tariffs led to a 16.5 pp reduction in the likelihood a
respondent supported increased spending on environmental protection across all Republican districts, but a 41.7 pp reduction in Republican districts in our continuing sample.
Our estimates for income per capita and ambient pollution concentrations exhibit a similar pattern. This suggests that our finding that incumbent Republicans reduced theirsupport for environmental policy in response to reductions in US tariffs can indeed berationalized as a product of trade-induced changes in constituent preferences.
Second, reductions in US tariffs appear to have had, at most, a limited effect on the
demand for environmental policy in our non-continuing sample, regardless of the district’s party. For example, the estimates reported in column (3) indicate that a 1 pp
reduction in US tariffs led to a 8.5 pp reduction in the likelihood a respondent supported increased spending on environmental protection in Republican districts and a 4.5
pp reduction in Democratic districts, although these estimates are not statistically significant at conventional levels. Our corresponding estimates for income per capita andambient pollution concentrations are also small when compared with the estimates fromour sample of continuing counties. These findings suggest that changes in constituent
demands for environmental policy are unlikely to explain the observed shift away fromthe Democratic party in response to NAFTA, a point to which we return in Section E.2.2.
The third, and final, key finding that emerges from Table E.1 is that reductions in US
tariffs also appear to have reduced the demand for environmental policy amongst constituents represented by Democrats. For example, the estimate reported in the second
row of column (1) indicates that a 1 pp reduction in US tariffs led to a 13 pp reductionin the likelihood a respondent supported increased spending on environmental protection in Democratic districts, while the corresponding estimates in columns (2) and (3)suggest that a 1 pp reduction in US tariffs decreased per capita incomes and ambient pollution levels in affected Democratic counties by close to 88 dollars and 4.9%, respectively.
However, recall that the results presented in Table 6 indicate incumbent Democratic legislators, unlike their Republican counterparts, do not change their voting behavior on
environmental bills in response to reductions in US tariffs.
To investigate this discrepancy further, we exploit the fact that the ANES also contains
information as to whether each respondent is a member of the Democratic or Republicanparties, or identifies as an independent. This allows us to examine whether there isheterogeneity in the effects of the NAFTA tariff cuts on stated support for environmental
policy across voters with different political affiliations.
To do so, we estimate three regressions analogous to our preferred specification from59 As the ANES samples individuals from a subset of districts in each year, we define continuing districts

as those represented by a single party, rather than single representative, over our sample.

63

64
0.20
7766

-0.165b(0.064)-0.130b(0.062)-0.029(0.028)-0.021(0.018)

0.24
4359

X

-0.417a(0.141)-0.219(0.184)0.049(0.058)-0.024(0.070)
X
0.25
3407

-0.085(0.114)-0.045(0.105)0.026(0.061)0.010(0.055)

0.95
28649

-91.515b(39.357)-88.405b(39.053)
7.420(6.385)-3.964(4.412)

0.97
6226

X

-319.985a(90.058)-190.892a(47.614)16.946c(9.030)-10.149(30.574)
X
0.95
22423

-57.721(41.683)-41.681(39.035)
4.191(8.187)-3.858(5.120)Panel (b): Income
Per Capita
(4)
(5)
(6)

0.89
1291

-0.062b(0.023)-0.049b(0.020)0.009b(0.004)0.012c(0.007)

(7)

0.86
358

X

-0.131(0.154)0.046(0.054)0.031(0.028)-0.077(0.051)Panel (c):ln(TSP)
(8)

X
0.91
932

-0.054a(0.014)-0.030b(0.013)0.007(0.005)0.007(0.006)(9)Notes: Table shows results of the NAFTA tariff reductions on stated views on environmental policy (Panel (a)), local economic conditions (Panel (b)), and local environmental conditions (Panel(c)), allowing the effects to vary by each region’s political party. The dependent variable in Panel (a) is an indicator for whether a survey respondent believes the federal government should
increase spending on environmental protection. Data is taken from the American National Election Studies (ANES) survey. The dependent variable in Panel (b) is the county’s average income
per capita. Data is taken from the Bureau of Economic Analysis’s Regional Economic Accounts. The dependent variable in Panel (c) is the natural log of the county’s median daily ambient
total suspended particulate concentration. Data is taken from the Environmental Protection Agency’s Air Quality System. In each Panel, the first column shows the results allowing the effectof NAFTA’s tariff reductions to vary by the party held by the region’s representative. The second column in each panel restricts this analysis to regions represented by the same party (Panel(a)) or legislator (Panel (b) and (c)) throughout. The third column in each panel restricts this analysis to regions that change parties (Panel (a)) or legislators (Panel (b) and (c)). All regressions
in Panel (a) include congressional district fixed effects, year fixed effects, voter and interviewer characteristic by year fixed effects, initial district economic, regulatory, and demographic by year
fixed effects, an indicator of whether the district is held by democrats, and are weighted by the ANES sample weights. All regressions in Panels (b) and (c) include county and year fixed effects,
initial county economic, regulatory, and demographic by year fixed effects, and an indicator of whether the county is in a district held by democrats. Standard errors clustered by state arereported in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

Continuing
Non-Continuing
R2
Obs.

∆τrMex x Postt x Dem.

∆τrMex x Postt x Rep.

∆τrUSA x Postt x Dem.

∆τrUSA x Postt x Rep.

Panel (a): Support forEnv. Prot’n
(1)
(2)
(3)

Table E.1: The Effects of NAFTA on the Demand for Environmental Policy, by Partypanel (a) of Table 4, but we now allow the effects of the US and Mexican tariff reductions
to vary by both the political party of the district’s representative, as well as the respondent’s self-reported political affiliation. These results are reported in Table E.2. As inpanel (a) of Table E.1, we first examine the full sample (column (1)), and then our continuing and non-continuing samples (columns (2) and (3), respectively). All specifications
include controls corresponding to the preferred specification from panel (a) of Table 4,
and in all cases, standard errors clustered by state are reported in parentheses.
The estimates reported in Table E.2 indicate that the reductions in the demand forenvironmental policy in response to US tariff reductions documented in Table E.1 aredriven by the responses of constituents who self identify as either a Republican or an
Independent. For example, the estimates reported in the first three rows of column (1)suggest that a 1 pp reduction in US tariffs led to large reductions in the likelihood of
supporting spending on environmental protection amongst Independents and Republicans (reductions of 23.7 pp and 17.3 pp, respectively). In contrast, a 1 pp reduction in US
tariffs only led to a 4.6 pp reduction in the likelihood of support amongst Democrats inthese districts, although this effect is not statistically significant at conventional levels. A
similar pattern arises in districts represented by Democratic legislators; a 1 pp reduction
in US tariffs led to 6.1 pp, 22.8 pp, and 13.5 pp reductions in the likelihood of supporting spending on environmental protection amongst Democrats, Independents, andRepublicans, respectively (although only the estimate for Independents is statisticallysignificant). These results provide a natural explanation for the observed difference inthe change in voting of incumbent Republican and Democratic legislators in response to
the US tariff cuts: Democratic legislators appear not to change their votes because tradeliberalization does not impact the environmental policy demands of their main politicalconstituency.
A remaining concern is that our estimates of NAFTA’s effects on voting by incumbent legislators could also be capturing differential concerns over industrial flight acrossdistricts represented by Democrats and Republicans, due to factors such as differential lobbying in response to trade. To address this concern, we estimate the effects of
NAFTA’s tariff reductions on RCVs by incumbent politicians, allowing the effects oftreatment to vary by both the representative’s party and their district’s specialization in
polluting industries. To do so, we estimate regressions based on Equation (1), allowing the effect of treatment to vary by the representative’s political party and whether
the initial average cost of complying with environmental regulation for industries in the
district is relatively high or low. We also include legislator fixed-effects to restrict ouranalysis to changing views among incumbent politicians.
The results of this exercise are displayed in Table E.3. As in Table 3 of the main text,
each of the four columns corresponds to a different measure of the costs of regulatorycompliance. In Panel (a), our measure is the ratio of pollution abatement operating costs(PAC) to the total cost of materials. In Panel (b), our measure is the share of PAC inindustry value added. In each panel, the first column classifies districts as having relatively high or low compliance costs (High and Low PAC, respectively) if the averagecosts of complying with environmental regulation are above or below that of the average district; the second column makes this delineation based on the cost of regulatorycompliance for the median district.
65

Table E.2: Heterogeneity in NAFTA’s Effects on Voters’ Views on Environmental Policy∆τrUSA x Postt x Rep. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrUSA x Postt x Dem. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrMex x Postt x Rep. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrMex x Postt x Dem. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter
R2
Obs.

(1)

(2)

(3)

-0.046(0.068)-0.237a(0.084)-0.173c(0.091)-0.200(0.169)-0.637a(0.174)-0.241(0.163)0.035(0.130)-0.141(0.128)-0.125(0.161)-0.061(0.088)-0.228b(0.086)-0.136(0.092)0.014(0.232)-0.406b(0.170)-0.336b(0.159)-0.044(0.129)-0.010(0.118)-0.016(0.148)-0.032(0.033)-0.019(0.027)-0.029(0.031)-0.009(0.059)0.083(0.061)
0.007(0.052)0.027(0.065)0.025(0.063)0.042(0.071)-0.040c(0.023)0.020(0.024)-0.026(0.024)-0.094(0.083)0.029(0.063)-0.018(0.065)-0.009(0.055)0.043(0.066)0.002(0.062)

0.22
7766

0.25
4359

0.26
3407

Notes: Table reports estimates of the effects of NAFTA tariff reductions on views expressed on environmental policy stringency.
Panel (a) reports estimates using all districts, Panel (b) reports estimates using the sub-sample of districts that are always represented
by the same party over our period of study, and Panel (c) reports estimates using the sub-sample of districts whose party changes
over our period of study. The dependent variable in all regressions is an indicator of whether the survey respondent believes thefederal government should increase spending on environmental protection. All regressions include congressional district and year
fixed effects, baseline district Clean Air Act non-attainment status and characteristic trends, voter and interviewer demographic
trends, an indicator of whether the district is held by democrats, controls for the voter’s party affiliation, and are weighted using the
ANES sample weights. Standard errors clustered by state are reported in parentheses. Significance at the 1%, 5%, and 10% levels aredenoted by a , b , and c , respectively.

66

Table E.3: The Effects of NAFTA on Roll Call Votes by Party and Abatement Cost
Panel (a):PAC/Materials Costs(1)(2)∆τrUSA x Postt x Rep.
x High PAC
x Low PAC
∆τrUSA x Postt x Dem.
x High PAC
x Low PAC
∆τrMex x Postt x Rep.
x High PAC
x Low PAC
∆τrMex x Postt x Dem.
x High PAC
x Low PAC
R2
Obs.

Panel (b):PAC/Value Added(3)(4)-0.138c(0.070)-0.099b(0.046)-0.083(0.069)-0.121b(0.054)-0.121c(0.065)-0.117b(0.048)-0.065(0.044)-0.132b(0.058)-0.138c(0.069)0.007(0.047)-0.047(0.053)-0.012(0.049)-0.029(0.054)-0.016(0.048)-0.062(0.051)-0.010(0.046)-0.008(0.023)-0.010(0.009)-0.015(0.024)-0.015(0.010)-0.017(0.019)-0.013(0.013)-0.022(0.022)-0.012(0.011)

0.045(0.035)0.012(0.023)0.015(0.029)0.018(0.023)-0.001(0.023)0.023(0.026)0.016(0.025)0.016(0.024)

0.45
50321

0.45
50321

0.45
50321

0.45
50321

Notes: Table reports estimates of the effects of the NAFTA tariff reductions on roll call votes in the House of Representatives allowing
the effects to vary by party and across districts on the basis of their average costs of complying with environmental regulation. The
dependent variable in all regressions is an indicator of whether the roll call vote cast by a representative on a particular bill is proenvironment. In Panels (a) and (b), the cost of complying with environmental regulation are measured as the ratio of PAC to the total
cost of materials, and the ratio of PAC to value added, respectively. In the first column of each panel, districts are classified as having
relatively high or low compliance costs (High and Low PAC, respectively) if the average costs of complying with environmental
regulation are above or below that of the average district. In the second column of each panel, districts are classified as having Highor Low PAC if the average costs of complying with environmental regulation are above or below that of the median district. In eachcolumn, the first two rows show the effect of a reduction in US import tariffs for districts currently with a Republican or Democratic
representative, respectively.Tthe last two rows show the effect of a reduction in Mexican import tariffs for districts currently with a
Republican or Democratic representative, respectively. All regressions include district, representative, and year fixed effects, as wellas controls for the effects of the Clean Air Act and differential trends in baseline characteristics. Standard errors two-way clusteredby state and bill are shown in parentheses. Significance at the 1%, 5%, and 10% levels are denoted by a , b , and c , respectively.

These estimates indicate that the responses by incumbent politicians did not reflect
concerns over industrial flight. We find that, for both parties and across each of ourfour specifications, the estimated effects of the reduction in US import tariffs following NAFTA for Low and High PAC districts are not statistically distinguishable fromeach other. Similarly, we also find no significant differences across Low and High PAC
districts for the Mexican tariff changes.
67E.2.2NAFTA and Changes in Partisan Representation: Redux

The estimates reported in Table E.2 also provide further evidence that that trade-inducedchanges in partisan representation are unlikely to be due to the effects of tariff reductions
on constituent preferences for environmental policy, as both US and Mexican tariff cuts
have little effect on voter views in non-continuing districts. Hence, we next investigate
whether the change in partisan representation, that resulted in a change in voting on
environmental RCVs, is consistent with affected voters reducing support for Democratic
legislators for adopting pro-NAFTA positions prior to the agreement’s ratification.
There is reason to believe that this type of response could underlie the change inpartisan representation. As we noted in the main text, the work of Choi et al. (2022)
suggests that voters in regions most affected by NAFTA were more likely to switchfrom supporting Democrats to Republicans due to the former party’s support for theagreement. Given the stark difference in support for environmental issues across thetwo parties, this decrease in support for Democrats could manifest as a reduction inpro-environmental RCVs if it led to the election of more Republicans.
We investigate this possibility by again estimating the effects of the NAFTA tariff
cuts on electoral outcomes using Equation (5), and our data on electoral results from the
MIT Election Data Lab. However, we now consider the effects of the tariff cuts across
two sub-samples differentiated according to whether the district’s representative voted
for or against the NAFTA Implementation Act (HR 3450), the roll call vote to ratify theagreement. In the first, we restrict the sample to the set of districts whose representative
opposed NAFTA, while in the second, we restrict the sample to the set of districts whose
representative supported NAFTA. For each sample, we examine whether the NAFTA
tariff cuts affected the likelihood that the district flipped from Republican to Democrat,
and from Democrat to Republican.
The results from this exercise are reported in the two panels of Table E.4. Panel(a) reports estimates of the effects of the NAFTA tariff cuts on the likelihood a district
flipped from Republican to Democrat, while panel (b) reports estimates of these effects
for districts that flipped from Democrat to Republican. In all cases, standard errors
clustered by state are reported in parentheses.
Consistent with Che et al. (2022), the results presented in Table E.4 suggest that
NAFTA caused voters to reduce support Democratic representatives who voted in favor of NAFTA. For example, the results in column (4) show that among the sample
of districts whose representative voted in favor of NAFTA, a 1 pp reduction in importtariffs caused a 19 pp increase in the likelihood of the district flipping from Democrats
to Republicans. In contrast, the results in column (3) show no significant change inparty among the anti-NAFTA districts. Moreover, a Wald test comparing these two coefficients indicates that these differences are statistically significant (p-value = 0.07). In
addition, the table suggests no punishment occurred for Republicans, with the results inPanel (a) showing no significant effect of either tariff change on the likelihood of a district switching from the Republican to Democratic party in either sub-sample. Together,
these results suggest that much of NAFTA’s effect on the formation of environmental
policy in the US House of Representatives is an incidental byproduct of voters electing
Republicans to replace pro-NAFTA Democrats.
68

Table E.4: The Effects of NAFTA on Electoral Outcomes, by NAFTA Vote Status∆τrUSA x Postt∆τrMex x Postt
Pro-NAFTA Vote
R2
Obs.

Panel (a): Pr(Change
Rep. to Dem.)(1)(2)

Panel (b): Pr(Change
Dem. to Rep.)
(3)
(4)

0.071
(0.060)0.007(0.021)-0.028(0.045)0.003(0.008)0.028(0.050)-0.015(0.021)0.190a(0.068)0.019(0.016)

0.25
985

X
0.24
1159

0.24
985

X
0.23
1159

Notes: Table shows results of the NAFTA tariff reductions on election outcomes in the House of Representatives for the 102nd to the106th congress, splitting the sample by the representative’s vote status on the NAFTA Implementation Act (HR 3450). The dependent
variable in Panel (a) is an indicator for whether the district changed from the Republican to Democratic party in the last election.
The dependent variable in Panel (b) is an indicator for whether the district changed from the Democratic to Republican party inthe last election. The first column in each panel restricts the sample to districts whose representative opposed NAFTA, and thesecond column in each panel restricts the sample to districts whose representative voted in favor of NAFTA. All regressions include
district and year fixed effects and district baseline characteristic and CAA non-attainment trends. All regressions are restricted
whose representative voted on HR 3450. Standard errors clustered by state are shown in parentheses. Significance at the 1%, 5%,
and 10% levels are denoted by a , b , and c , respectively.

E.3

Additional Results

This section reports additional empirical results referenced in the main text.
As we discuss in Section 6 of the main text, our findings indicate that incumbent
Democrats may be less likely to cast a pro-choice RCV in response to US tariffs, and wenote that this appears to be due to these Democrats responding to changes in the preferences of self-identified Independent voters in their districts. The corresponding resultsthat suggest this are displayed in Table E.5, which reports estimates of the effects of the
NAFTA tariff reductions on expressed views on reproductive rights, using the public
opinion data from the ANES. In the table, Panel (a) reports estimates using all districts,
while Panel (b) reports estimates using the sub-sample of districts that are always represented by the same party over our period of study, and Panel (c) reports estimatesusing the sub-sample of districts whose party changes over our period of study. In allcases, the dependent variable is an indicator of whether the survey respondent believes
the federal government should allow abortion. All regressions include congressional
district and year fixed effects, baseline district Clean Air Act non-attainment status andcharacteristic by year fixed effects, and voter and interviewer demographic by year fixed
effects, and are weighted using the ANES sample weights. In the table, standard errors
clustered by state are reported in parentheses.
As the estimates reported in column (1) of Table E.5 show, the reduction in US tariffs
only had a statistically significant effect on the views of Independent voters that residein districts held by Democrats. While imprecisely estimated, the results reported incolumns (2) and (3) suggest that this effect is likely driven by independent voters in
districts that are held by Democrats throughout our period of study, suggesting that the69

responses of incumbent Democratic legislators that we observe in Table 11 of the main
text may be due to these legislators responding to the demands of an important electoral
constituency on this issue.

70

Table E.5: Heterogeneity in NAFTA’s Effects on Voters’ Views on Reproductive Rights∆τrUSA x Postt x Rep. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrUSA x Postt x Dem. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrMex x Postt x Rep. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter∆τrMex x Postt x Dem. Dist.
x Dem. Voterx Ind. Voterx Rep. Voter
R2
Obs.

(1)

(2)

(3)

-0.002(0.079)0.007(0.104)0.010(0.084)0.200(0.187)0.164(0.200)-0.083(0.170)-0.221(0.137)-0.169(0.136)-0.062(0.171)

0.053(0.082)-0.133(0.082)0.007(0.085)0.250c(0.146)-0.124(0.118)0.040(0.132)-0.186(0.154)-0.074(0.114)0.120(0.142)0.059c(0.032)0.045(0.031)0.030(0.023)0.068(0.068)0.052(0.072)0.035(0.064)-0.042(0.082)-0.056(0.076)-0.046(0.068)0.035(0.027)0.031(0.022)0.030(0.026)0.002(0.056)0.039(0.046)0.013(0.056)0.033(0.036)-0.009(0.054)0.006(0.054)

0.23
8761

0.27
4871

0.28
3890

Notes: Table reports estimates of the effects of NAFTA tariff reductions on views expressed on reproductive
rights. Panel (a) reports estimates using all districts, Panel (b) reports estimates using the sub-sample of districts
that are always represented by the same party over our period of study, and Panel (c) reports estimates using the
sub-sample of districts whose party changes over our period of study. The dependent variable in all regressions
is an indicator of whether the survey respondent believes the federal government should allow abortion. All
regressions include congressional district and year fixed effects, baseline district Clean Air Act non-attainment
status and characteristic trends, voter and interviewer demographic trends, an indicator of whether the districtis held by democrats, and controls for the voter’s party affiliation, and are weighted using the ANES sample
weights. Standard errors clustered by state are reported in parentheses. Significance at the 1%, 5%, and 10%
levels are denoted by a , b , and c , respectively.

71