Does Trade Liberalization with China Influence U.S. Elections?

This paper examines the impact of trade liberalization on U.S. Congressional elections. We find that U.S. counties subject to greater competition from China via a change in U.S. trade policy exhibit relative increases in turnout, the share of votes cast for Democrats and the probability that the county is represented by a Democrat. We find that these changes are consistent with Democrats in office being more likely than Republicans to support legislation limiting import competition or favoring economic assistance.

show that this relationship is associated with a change in U.S. trade policy the U.S. granting of permanent normal trade relations (PNTR) to China which eliminated the threat of substantial tari increases on Chinese imports. This heightened exposure to Chinese import competition may aect voters' preferences through several channels, including employment, wages, prots and goods prices. This paper examines the impact of increased exposure to competition from China on elections for the U.S. House of Representatives as well as the legislative activity of those elected to Congress. In the rst part of our analysis, we show that U.S. counties with greater exposure to the change in U.S. trade policy exhibit larger increases in turnout as well as the share of votes cast for Democrats and the probability that a Democrat represents the county. The second part of our analysis documents a rationale for this change in voting behavior by showing that Congressional Democrats are, in fact, more likely to support policies that place restrictions on imports and that provide economic assistance that might mitigate the impact of import competition.
Our measure of exposure to increased competition from China arises from the U.S.
granting of PNTR to China in October 2000. Prior to this change in U.S. trade policy, U.S. imports from China faced the risk, each year, that taris on a subset of products would rise from the low NTR tari rates oered to WTO members to the substantially higher non-NTR rates set in the Smoot-Hawley Tari Act of 1930. These potential tari increases created a disincentive for U.S. rms to take advantage of production in China and for Chinese rms to expand into the U.S. market. By eliminating the possibility of these future tari increases, PNTR removed these disincentives.
We examine voting in elections for the U.S. House of Representatives because House members serve two-year terms and are expected to maintain close personal contact with constituents. As a result, House members may be more responsive to the demands of voters than elected ocials with longer terms such as Senators or Presidents. 1 We examine voting at the county rather than Congressional district level in order to track changes within constant geographic areas over time. That approach is not possible at the district level because the borders of Congressional districts change substantially during the period we examine (1992 to 2010) as a result of redistricting after the 2000 1 Karol (2012) nds that Senators and Presidents are more likely to support policies (like free trade) that are in the long-run interests of the country as a whole, even if they run counter to the shortrun passions of voters. Conconi et al. (2014) show that Senators are more likely to support trade liberalization than Representatives, but that the result does not hold for Senators facing elections within the next two years.
Census. County borders, by contrast, are stable over this period. One potential additional benet of focusing on counties is that they are smaller than Congressional districts in terms of both area and population, allowing us to capture greater variation in both exposure to Chinese import competition and residents' demographic characteristics.
Our dierence-in-dierences empirical strategy examines whether counties more exposed to the change in U.S. policy (rst dierence) experience dierential changes in voting for Democrats after the policy is implemented (second dierence). Across specications that are either unweighted or weighted by counties' initial population, coecient estimates suggest that moving a county from the 25th to the 75th percentile in terms of exposure to the change in U.S. trade policy is associated with a 1 to 2 percentage point increase in the share of votes cast for Democrats, representing a 3 to 4 percent increase relative to the across-county average share of votes for Democrats in the 2000 Congressional election, the closest Congressional election to the change in U.S. trade policy. Coecient estimates from similar specications indicate that the probability of a switch in representation for a county from a Republican to a Democrat Representative increases by 2 to 3 percentage points.
We allow for the potential inuence of spillovers from nearby areas by controlling for changes in exposure to China experienced by neighboring counties that are part of the same labor market. Results from these specications are qualitatively similar to the baseline specications but somewhat larger in magnitude: moving a county from the 25th to the 75th percentile in terms of both own exposure to the policy change and neighboring counties' exposure is associated with a 4.4 percent increase in the share of votes won by the Democrat relative to the average share of votes won by Democrats in the year 2000 election, versus 3.7 percent in the baseline specication.
We also document other related evidence supportive of a role for PNTR in U.S. election outcomes. First, we nd that the increase in the share of votes cast for Democrats associated with PNTR is also present for Presidential and Gubernatorial elections, indicating eects for electoral contests besides the U.S. House of Representatives. Second, we nd that counties more exposed to PNTR's trade liberalization exhibit larger increases in voter turnout after the policy change, relating to the political science literature on the eect of economic conditions on voter turnout (e.g. Schlozman and Verba 1979).
The second part of our analysis examines Representatives' Congressional votes on legislation during the 1990s and 2000s using a regression discontinuity identication strategy that compares the voting of Democrats and Republicans who win oce by small margins. The analysis indicates that Democrats during this period are more likely to take positions that restrict trade and that oer economic assistance that may benet those adversely aected by trade, providing a rationale for the change in voting documented in the rst part of the paper. We nd that the tendency for Democrats to support such legislation is stronger after implementation of PNTR.
Together, the results in the rst and second parts of the paper suggest that voters who perceive themselves as being disadvantaged by trade are more likely to vote for politicians that might restrict imports. An interesting topic for future research is the extent to which PNTR contributes to the strong performance of candidates proposing to restrict trade or alter trade agreements among both Republicans and Democrats during the 2016 Presidential primaries.
This paper relates to literatures on voting in both political science and economics, and also complements the large literature examining the impact of international trade on worker outcomes. 2 A closely related paper in the voting literature is Feigenbaum and Hall (2015), which examines the eect of Congressional-district-level economic shocks from Chinese imports using the approach in Autor, Dorn and Hanson (2013) on the roll-call behavior of legislators and electoral outcomes. They nd that legislators from districts experiencing larger increases in Chinese import competition become more protectionist in their voting on trade-related bills, and that incumbents are able to insulate themselves from electoral competition via this voting behavior. Another closely related paper is Jensen, Quinn and Weymouth (2016), which nds that votes for presidential candidates' incumbent parties rise with expanding U.S. exports and fall with rising U.S. imports.
Using data from German labor markets, Dippel, Gold and Heblich (2015) nd that higher imports from Eastern Europe and China are associated with an increase in the share of votes for far right parties. We proceed as follows. Section 2 provides an overview of the growth of U.S.-China trade. Section 3 describes our data sources. Sections 4 and 5 present our empirical results. Section 6 concludes.
2 A substantial body of research documents a negative relationship between import competition and U.S. manufacturing employment, e.g., Freeman and Katz (1991), Revenga (1992)   show that commuting zones with industrial structures more similar to U.S. imports from China experienced greater declines in manufacturing employment. Beyond manufacturing employment, Pierce and Schott (2015) show that counties more exposed to PNTR experience both relatively higher levels of unemployment and lower levels of We match the voting data to county-level demographic data from the 1990 Decennial Census that have been found to be important correlates of voting behavior in the political science and economics literatures on voting.
7 These data are summarized in Table 1.

Counties' Exposure to PNTR
We make use of the structure of the U.S. tari schedule to dene a measure of each industry's and in turn, each county's exposure to PNTR. The tari schedule has two basic sets of taris: NTR taris, which average 4 percent across industries and are applied to goods imported from other members of the World Trade Organization (WTO); and non-NTR taris, which were set by the Smoot-Hawley Tari Act of 1930 and are typically substantially higher than the corresponding NTR rates, averaging 37 percent across industries. While imports from non-market economies, such as China, generally are subject to the higher non-NTR rates, U.S. tari law allows the President to grant such countries access to NTR rates on an annually renewable basis, subject to approval by Congress. 2016 We refer to this dierence as the NTR gap, and compute it for each four-digit SIC industry j using ad valorem equivalent tari rates provided by Feenstra et al (2002) for 1999, the year before passage of PNTR. As illustrated in Figure 4, NTR gaps vary widely across industries, with a mean and standard deviation of 33 and 15 percentage points, respectively. As noted in Pierce and Schott (2016), 79 percent of the variation in the NTR gap across industries is due to non-NTR rates, set 70 years prior to passage 8 Intuition for these incentives can be derived, in part, from the literature on investment under uncertainty (e.g., Pindyck 1993 and Bloom, Bond and Van Reenen 2007), which demonstrates that rms are more likely to undertake irreversible investments as the ambiguity surrounding their expected prot decreases. Handley (2014) introduces these insights to rms' decisions to export. of PNTR. This feature of non-NTR rates eectively rules out reverse causality that would arise if non-NTR rates were set to protect industries with declining employment or surging imports. Furthermore, to the extent that NTR rates were raised to protect industries with declining employment prior to PNTR, these higher NTR rates would result in lower NTR gaps, biasing our results away from nding an eect of PNTR. 11 We compute U.S. counties' exposure to PNTR as the employment-share weighted average NTR gap across the sectors in which they are active, where L jcb is the base-year b employment of SIC industry j in county c and L cb is the overall employment in county c in base year b. trade policy. Given that services comprise a large share of employment, the distribution of county-level N T R Gap c is shifted leftwards relative to the distribution of manufacturing and other industries for which the N T R Gap j is dened: the mean and standard deviation of the county-level NTR gap are 7.3 and 6.5 percentage points, as displayed visually in Figure 5. The dierence between the 25th and 75th percentiles is We also compute counties' exposure to PNTR via the average NTR gap of surrounding counties in the same commuting zone, a geographic area roughly analogous to a local labor market.
13 The correlation of own-and commuting-zone NTR gaps across counties, 0.58, is displayed visually in Figure  12 NTR gaps can only be calculated for products subject to import taris, such as manufacturing, agriculture and mining products. NTR gaps for services, which are not subject to import taris are, by denition, zero. we measure the extent to which industry quotas were binding under the MFA as the import-weighted average ll rate of the textile and clothing products that were under quota in that industry, where ll rates are dened as the actual imports divided by allowable imports under the the quota. Industries with higher average ll rates faced more binding quotas and are therefore more exposed to the end of the MFA. Products The dependent variable is the percent of votes received by the Democrat in county c in year t. The rst term on the right-hand side is the DID term of interest, an interaction of a post-PNTR (i.e., t > 2000) indicator with the (time-invariant) county-level NTR gap, as dened in the preceding section.
X c represents a vector of initial period county demographic attributes taken from the 1990 Census that are found to be important in the economics and political science literatures on voting. These attributes are median household income, share of population achieving higher education, the share of non-white population, the share of veterans and the share of voters over 65. Including interactions of these attributes with the P ost P N T R t indicator allows the relationship between these demographic characteristics and voting outcomes to dier before and after passage of PNTR. X ct represents a matrix of time-varying policy attributes including the average U.S. import tari rate associated with each county's mix of industries as well as the county's exposure to the phasing out of the MFA. δ c and δ t represent county and year xed eects.
One advantage of this DID identication strategy is its ability to net out characteristics of counties that are time-invariant, while also controlling for aggregate shocks that aect all counties identically in a particular year, such as whether the election occurs during a presidential versus non-presidential election year.
14 We consider both unweighted regressions (Tables 2 to 4), which are representative of the relationship for the average county, and regressions for which observations are weighted by counties' initial population (Table 5), making them representative of the average individual.

Representatives
The rst three columns of Table 2   Estimates for the remaining covariates included in the regression suggest that voters with a college degree and at least some graduate education are more likely to support Democrats after 2000, while those over 65 are less likely to do so.
The nal column of Table 2  In this section we examine whether voters in one county might be inuenced by economic conditions in neighboring counties that are part of the same labor market. The specication we consider is similar to that considered in the previous section but it is augmented with an additional dierence-in-dierences term, an interaction of the post-PNTR indicator variable with the average NTR gap across other counties in the same commuting zone (z).
As illustrated in Table 3

Weighting Counties by Population
The coecient estimates reported in the previous three sections are based on unweighted regressions, and therefore are representative of the relationship between PNTR and voting behavior for the average county. In this section we consider the eect of weighting by initial (1990) population, which provides estimates representative of the average individual.
As indicated in Table 2 Table 3 (3.7 and 27, respectively), while the estimated eect for turnout is higher (1.8 in Table 3).

Party Aliation and Legislator Voting Behavior
The previous section establishes that voters in counties facing larger increases in competition from China are more likely to vote for Democratic candidates. One explanation for this result is that workers displaced by Chinese imports sought to elect ocials that would either protect U.S. workers from international trade or soften the eect of this competition by promoting economic assistance programs. This section investigates whether Congressional Democrats in the U.S. House of Representatives during the 1990s and 2000s were more likely to vote for legislation along these lines. We use a regression discontinuity approach to examine whether Republicans' and Democrats' votes dier on trade-related and economic assistance-related bills. We begin by discussing the classication of bills as being either for or against free trade or economic assistance and then describe our identication strategy before presenting the results. 19 A ranking of r (0, 100) indicates that the sponsor is more liberal in their voting than r percent of House members. Bills whose primary sponsor's ranking exceeds 50 are coded as anti-free-trade. The remaining bills are coded as pro-free-trade. One drawback of this approach is its reliance on a ranking system based exclusively on a principle component analysis of members' votes on economic issues.

Classication of Trade and Economic Assistance Bills
A major benet of the approach, in addition to its simplicity, is the independence of the rankings. We note that the results discussed below are also robust to the authors' qualitative classication of bills as either pro-or anti-free trade.

Economic Assistance Bills
We consider bills to be related to economic assistance if they fall into the following categories of the Rohde database: jobs (code 810 of the database), welfare benets/social services (code 811), job training (code 816), nutrition programs (code 831), family assistance (code 832), homeless (code 835), unemployment assistance (code 962), and minimum wage (code 966). As above, we use the National Journal rankings to classify bills as pro-versus anti-economic assistance according to whether the bills' sponsors' economic liberalness rankings are above or below 50.
18 The complete list of codes can be found at http://sites.duke.edu/pipc/data/.

Identication Strategy
We examine the relationship between House members' votes on trade and economic assistance bills and their party aliation using the following specication, We are therefore unable to include district xed eects in equation 4.
In this specication, identication of β requires that Representatives' party aliation be uncorrelated with the error term. As there may be several reasons why this assumption is violated, we follow Lee (2008) in identifying the causal eect of party aliation on voting behavior using a regression discontinuity (RD) approach.

22
Specically, we make use of the principle that the probability of a Democrat winning a congressional election disproportionately increases at the point where they receive a larger share of votes than the Republican competitor.
Formally, dene the assignment variable M argin dh ≡ V oteShare Democratic dh − V oteShares Republican dh as the dierence in voting share between the Democratic and Republican candidates in the Congressional district d for election to Congress h. As illustrated in Figure 8, the probability of a Democratic candidate winning an election conditional on the margin of victory has a discontinuity at the cuto 0. That is, this probability is substantially near 1 for values of m just above zero compared with values of m just below zero. 23 Hahn Lee and Lemieux (2010) show thatβ RD is essentially an instrumental variable estimator. Specically, the rst stage of the instrumental variable estimation is while the second stage is  The second check directly examines pre-determined characteristics between Congressional districts in the neighborhood of the cuto point. If there were full manipulation at the cuto, districts on the margin would not be balanced and these 24 Using RD to investigate the incumbent advantage, Lee (2008) argues: It is plausible that the exact vote count in large elections, while inuenced by political actors in a non-random way, is also partially determined by chance beyond any actor's control. Even on the day of an election, there is inherent uncertainty about the precise and nal vote count. In light of this uncertainty, the local independence result predicts that the districts where a party's candidate just barely won an electionand hence barely became the incumbentare likely to be comparable in all other ways to districts where the party's candidate just barely lost the election.
pre-determined district characteristics would show discontinuities in their distribution at the cuto point. Figures A.2 to A.10, reported in the appendix reveal that none of the distributions of district attributes used in our analysis exhibit discontinuities at the cuto 0, indicating that our hypothesis of a valid RD setting cannot be rejected.

Results
We start with a visual presentation of the relationship between Democrats' margin of victory, M argin dh , and the districts' subsequent votes for trade and economic assistance bills, y dh , across the 103 rd (January 1993 through January 1995) to the 112 th  Table 8 compares results for the nal specications reported in Tables 6 and 7 for the pre-versus post-PNTR time periods. As indicated in the table, we nd that for both types of legislation, Democrats are less likely to support pro-free trade and more likely to support proeconomic assistance legislation in Congresses after 2000 versus before.
25 See Section B of the online appendix for further discussion.

Conclusion
This paper examines the eect of increased import competition from China on U.S. political outcomes. Our primary measure of exposure to competition from China comes from the U.S. granting of Permanent Normal Trade Relations to China, and we examine its eect in a dierences-in-dierences specication.
We nd that U.S. counties more exposed to increased competition from China experience increases in the share of votes cast for Democrats in Congressional elections, along with increases in the probability that a Democrat represents a county and the probability of a county switching from a Republican to a Democrat Representative.
The results are also economically signicant we nd that moving a county from the 25th to the 75th percentile of exposure to China increases the Democrat vote share in Congressional elections by 1.5 percentage points, or a 3.7 percent increase relative to the average share of votes won by Democrats in the 2000 Congressional election. Moreover, we nd that the eect of the increase in import competition on voting is slightly larger once we account for the exposure of other counties in the same labor market, and that increased import competition is associated with higher voter turnout and a higher share of votes cast for Democrats in Presidential and gubernatorial elections.
The second half of our analysis investigates potential links between these voting outcomes and the policy choices of legislators in Congress. We use a regression discontinuity approach to examine dierences between Democrats' and Republicans' voting on bills related to trade and economic assistance programs. We nd that Democrats are more likely to support policies that limit import competition and that provide economic assistance that may benet workers adversely aected by trade competition, providing an explanation for the voting behavior documented in the rst part of our

B Approaches for Estimating Regression Discontinuity Coecient
The nonparametric approach is a local linear estimation that uses observations within a window of width w on both sides of the cuto point and assumes that g(.) and f (.) are linear, with potentially dierent slopes on the two sides of the cuto point. We implement this approach using the procedure developed by Imbens and Kalyanaraman (2014) to calculate the optimal bandwidth w * , and estimate analytical standard errors using the procedure developed in Porter (2003). In robustness checks, we examine whether our estimates are sensitive to dierent bandwidths, e.g., halving and doubling w * , as in Lee and Lemieux (2010). As indicated in Table A.1, we obtain similar results in both cases for both sets of bills.
Parametric estimation, by contrast, uses all of the observations over the domain of the assignment variable and assumes high-order polynomial functions of g(.) and f (.).
In the main text, we implement this approach using third-order polynomial functions with potentially dierent coecients on the two sides of the cuto point. Following Lee and Card (2008), we calculate standard errors clustered at the assignment variable level. Here, we report results using second-and fourth-order polynomials to examine the sensitivity of our estimates to using third order polynomials. As indicated in Table   A