Openness to international markets has long been a contentious domestic issue. Traditionally, a major source of opposition was the threat that import competition will hurt local producers (Irwin Reference Irwin2005; O'Rourke and Williamson Reference O'Rourke and Williamson1999). In recent years, however, sharp decreases in communication and transportation costs have increasingly enabled firms to take advantage of cost disparities between countries by “offshoring” manufacturing operations and business functions to locations overseas. This offshoring trend has substantially broadened the range of local jobs that are exposed to competition from abroad (Blinder Reference Blinder2006; Jensen and Kletzer Reference Jensen, Kletzer, Abraham, Harper and Spletzer2008) and elevated the threat to domestic workers posed by globalization into a salient electoral issue. Notably, political campaigns are not only raising the specter of local job losses, but also specifically highlighting foreign competition as a root cause (Public Citizen 2006).

In the U.S. presidential elections of 2004, for example, the Democrats made offshore outsourcing a staple issue of their campaign, charging that the president's policies were rewarding corporations for “shipping U.S. jobs overseas.”Footnote ¹ In the midterm elections held 2 years later, foreign competition was again a ubiquitous electoral issue used in 115 congressional campaigns,Footnote ² a trend that further intensified during the 2008 elections, when the number of paid campaign ads concerned with trade and offshoring increased almost sixfold.Footnote ³ This trend suggests that politicians sense that voters are anxious about globalization's impact on their employment prospects and also perceive this anxiety as an effective electoral issue, giving rise to two related questions: (1) does globalization's impact on the labor market have a demonstrable effect on people's voting preferences?; and (2) are voters sensitive to job losses per se, or is there a unique electoral response when job losses are caused specifically by foreign competition?

The notion that voters’ preferences are sensitive to the impact of economic openness underlies a range of arguments in the literature. For example, some scholars posit that trade liberalization leads to an increase in social spending as governments seek to prevent a backlash by voters in the face of growing employment risks from international competition (e.g., Burgoon Reference Burgoon2001; Cameron Reference Cameron1978; Garrett, Reference Garrett1998; Rodrik Reference Rodrik1998; Ruggie Reference Ruggie1982). Other studies explain governments’ choice of trade policy as a function of the likely support the policy would obtain by the electorate if it were put to vote (e.g., Dutt and Mitra Reference Dutt and Mitra2002; Hillman Reference Hillman1989; Mayer Reference Mayer1984). Again, the logic is that governments seek to avoid retribution from voters adversely affected by trade openness. Notably, both strands of research link citizens’ preferences to policy outcomes (on welfare expansion or on trade) by assuming that the consequences of international economic integration affect how citizens vote. Yet, to date, systematic evidence to back up this key assumption has been scant.

Several recent studies have made initial steps in examining the link between economic integration and voting by using survey data to reveal associations between self-perceived job insecurity and support for parties and candidates skeptical of globalization (e.g., Mughan, Bean, and McAllister Reference Mughan, Bean and McAllister2003; Mughan and Lacy Reference Mughan and Lacy2002). However, their reliance on observational survey data and the absence of objective measures of the labor market impact have made it difficult to establish a causal link between economic integration and voting outcomes. As a recent review of this literature concludes, there is a notable paucity of empirical evidence that globalization's consequences actually affect voting behavior (Kayser Reference Kayser2007).Footnote ⁴

To explore the electoral consequences of globalization's labor market impact and address some of the key methodological issues hampering past research, I assembled a novel dataset based on plant-level data from the U.S. Department of Labor (DOL). This dataset includes every application made over an 8-year period (1996–2004) to the DOL's Trade Adjustment and Assistance (TAA) division to request compensation to workers whose employment was harmed by trade-related competition. I use these data to generate geographically detailed measures of the impact of various forms of trade openness on layoffs in each U.S. county. Matching these objective measures with electoral data, I exploit the variation over time and across geographic units to estimate the localized effect of trade-related job losses on vote choice. In addition, by incorporating data on the TAA's actual certification decisions, I also explore the link between government compensation schemes and the sensitivity of voters to the labor market consequences of globalization.

A central finding of this article is that trade-related job losses, predominantly those resulting from offshoring, have a significant negative effect on support for the incumbent that is above and beyond the “generic” electoral effect associated with local reduction in employment. This effect is found across multiple election cycles, under both Republican and Democratic presidents. Between 2000 and 2004, the electoral cost to the incumbent of a marginal job lost due to foreign competition was, on average, more than twice as large as the effect of a job loss resulting from other causes (e.g., domestic competition). I demonstrate that this effect holds across a wide range of specifications and cannot be explained by measurement issues or by the method used to account for employment changes in the county. I also test my identification strategy with a placebo specification and offer further evidence that the finding is not spurious.

I find that the overall national electoral effect of trade-related job losses in the 2004 elections was about a 0.2 percentage point drop in support for the incumbent, equivalent to the electoral effect of an increase of half a percentage point in counties’ unemployment rates between the elections. Notably, my analysis suggests that this effect was probably offset by the electoral gains associated with trade's contribution to the national economy. Yet, I also find significant geographic variation in the electoral impact of job losses stemming from trade, whereby the president's support was almost unaffected in some areas but dropped by upward of 4 percentage points in the hardest hit counties. In Wisconsin, a state with 10 electoral votes, the electoral impact associated with job losses due to foreign competition was in fact larger than the swing needed to overturn the election's outcome. These findings suggest that the localized electoral impact of trade-related job losses, although modest at the national aggregate, could still have a significant influence on a government's trade agenda by potentially risking the president's chances in specific closely fought states or by threatening the electoral chances of some of the administration's allies in Congress, thus depriving the president's trade policy of crucial support in the legislature.

A final notable result is that during the first Bush Administration, the anti-incumbent effect of trade-related job losses was smaller in those counties where more of the harmed workers were made eligible to receive trade adjustment assistance from the government. This result ties into the ongoing debate over the policies needed to sustain public support for globalization (e.g., Kletzer Reference Kletzer2001; Marcal Reference Marcal2001; Scheve and Slaughter Reference Scheve and Slaughter2007) and suggests that a government-funded compensatory scheme can do more than help workers readjust in the labor market. It can also serve as a political tool for politicians that want to advance trade liberalization but fear its electoral repercussions.

This article contributes to the literature on the political economy of trade (e.g., Hillman Reference Hillman1989; Hiscox Reference Hiscox2002; Rogowski Reference Rogowski1987) by estimating the electoral impact of a key political aspect of trade liberalization, namely, its effect on domestic job losses. It also adds to the literature on economic voting that holds that vote choice reflects citizens’ retrospective assessment of the economic conditions (e.g., Kinder and Kiewiet Reference Kinder and Kiewiet1979; Lewis-Beck and Stegmaier Reference Lewis-Beck and Stegmaier2000). Indeed, economic voting models typically include employment as one of the factors that influence vote choice. The finding that layoffs due to foreign competition have a uniquely large electoral impact, particularly when caused by offshoring, demonstrates that vote choice is not responsive to all job losses in an equal fashion. Rather, the electoral effect varies as a function of the cause of the job loss, indicating that the retrospective assessments of voters are perhaps more discriminating than assumed in most models of economic voting.

The remainder of the article is organized as follows. The next section provides a theoretical overview and background. I then explain the empirical strategy, describe the data, and review the main measurement issues. The results of the analysis ensue. I begin by examining the impact of trade-related job losses on voting. Next, I explore the political implications of the finding by focusing on the differential effects of offshoring and on the electoral impact of government compensation for trade-affected workers. The final section investigates the mechanism underlying the unique electoral response to trade-related job losses.

THEORETICAL OVERVIEW AND BACKGROUND

A large body of research examines how the distributive consequences of globalization, particularly its impacts on the labor market, affect various political outcomes. For example, some scholars attribute the growth in social spending to a shift in the public's preferences on welfare policy wrought by economic openness (e.g., Burgoon Reference Burgoon2001; Cameron Reference Cameron1978; Rodrik Reference Rodrik1998). Others assign an important role to the preferences of the constituents in shaping the policy positions that elected officials take on trade (e.g., Dutt and Mitra Reference Dutt and Mitra2002; Mayer Reference Mayer1984; Milner and Kubota Reference Milner and Kubota2005). These studies rely on the assumption that citizens will electorally punish candidates that ignore these preferences induced by economic openness. Yet, as noted, very little empirical evidence has been put forward to date to establish this key assumption.

For trade openness to have such an effect on voting behavior, two conditions must be met: (1) voters need to be able to make a connection between trade openness and its impact on their well-being, and (2) the impact needs to be sufficiently meaningful to influence their voting preferences. So far, the empirical literature has predominantly offered evidence on the first condition. By examining individual-level survey data, a number of studies find that people's preferences on trade policy correlate with the labor market consequences of trade (e.g., Mayda and Rodrik Reference Mayda and Rodrik2005; Scheve and Slaughter Reference Scheve and Slaughter2001). Baker (Reference Baker2005) offers cross-national evidence that people's attitudes on trade policy reflect the effect of trade not only on employment, but also on consumption options. Taken together, these empirical regularities suggest that people do make a connection between openness to trade and its impact on their material well-being.

However, evidence on the second condition (i.e., on the electoral consequences of openness) is a lot more tentative. In fact, some studies argue that if governments are perceived by voters to be constrained by the international market, economic integration may decrease the prevalence of economic voting (Hellwig Reference Hellwig2001; Hellwig and Samuels Reference Hellwig and Samuels2007). Yet, other findings in the literature point to several reasons why jobs lost due to economic openness might bring about a uniquely strong electoral response.Footnote ⁵

An Emerging Threat. Offshoring, particularly in the services sector, is a relatively new phenomenon that is predicted to accelerate dramatically over the next two decades. As Blinder (Reference Blinder2006) notes, “We have so far barely seen the tip of the offshoring iceberg, the eventual dimensions of which may be staggering” (114). According to his estimates, “offshoring encompasses between 22% and 29% of all the jobs in the 2004 U.S. workforce, with the upper half of that range perhaps more likely than the lower half” (Blinder Reference Blinder2009, 77). This implies that up to 38 million U.S. jobs could potentially be offshored in the coming years. Jensen and Kletzer (Reference Jensen, Kletzer, Abraham, Harper and Spletzer2008) estimate the figure to range between 15 million and 20 million jobs, still a sizable portion of the U.S. labor force. In addition, offshoring could adversely affect workers whose jobs are not outsourced by suppressing wages of certain low-skilled sectors in large economies (Grossman and Rossi-Hansberg Reference Grossman and Rossi-Hansberg2008). Voters may thus be more electorally sensitive to job losses that result from offshoring because it is perceived as an emerging threat to a broad segment of the population.Footnote ⁶

Intensity of Media Coverage. The very visible nature of offshoring (i.e., of a local plant relocating its operations abroad) might be drawing greater media attention to instances of job losses due to this specific cause. Because the media has substantial influence over the issues that voters use to assess politicians (e.g., Iyengar and Kinder Reference Iyengar and Kinder1987; Miller and Krosnick Reference Miller and Krosnick2000), more frequent reporting on job losses when caused by offshoring may bring about a stronger shift in citizens’ vote choice in localities hurt by this form of foreign competition.

Severity of Consequences. Empirical analyses show that displaced workers in import-competing manufacturing are on average older and less educated, tend to suffer lower reemployment rates, and experience more sizable earning losses postplacement than the average displaced worker in the non–manufacturing sector (Kletzer Reference Kletzer2001, Reference Kletzer2004).Footnote ⁷ Voters in communities hurt by trade might therefore be more electorally responsive because the consequences of trade-related job displacements on the workers and their families are more damaging in objective terms.

Clarity of Responsibility. Voters tend to punish elected officials for adverse outcomes in conditions when assignment of responsibility is clearer (e.g., Powell Reference Powell2000; Powell and Witten Reference Powell and Whitten1993).Footnote ⁸ If job losses due to trade are perceived by the electorate as a direct outcome of government policy (e.g., due to the signing of a trade agreement), then people's vote choice might be more affected than when the cause of the job loss is less clear.

Economic Nationalism and Ethnocentricism. A number of studies find a close empirical relationship between opposition to trade openness and nationalist and ethnocentric sentiments (e.g., Mansfield and Mutz Reference Mansfield and Mutz2009; Margalit Reference Margalit2006; O'Rourke and Sinnott Reference O'Rourke and Sinnott2001). If a perception that foreigners are taking away “our jobs” is stirring such sentiments, then trade-related job losses may instigate a strong electoral backlash. Lou Dobbs’ “Exporting America,” a television series dedicated to exposing local businesses that are “sending American jobs overseas,” is a prominent example of this sentiment.

These different factors suggest that the adverse labor market effects of economic openness, particularly those resulting from offshoring, may generate a strong electoral response. Indeed, several studies offer survey-based evidence that the consequences of economic openness are associated with shifts in voting preferences. Mughan and Lacy (Reference Mughan and Lacy2002) use survey data of U.S. voters from the 1996 presidential elections to show that Americans that reported higher levels of job insecurity were more likely to vote for the third-party candidate Ross Perot. They attribute this vote choice to Perot's opposition to the North American Free Trade Agreement (NAFTA) and his appeal to the “widespread sense of job insecurity rooted in the perception that free trade . . . was depleting the stock of good jobs for Americans” (515). Mughan, Bean, and McAllister (Reference Mughan, Bean and McAllister2003) study voting in the 1998 Australian general elections and find that a sense of personal job insecurity increased support for restrictionist immigration policies, which in turn led to a higher probability of voting for the populist One Nation Party. In a similar vein, Walter (Reference Walter2010) uses survey data from Switzerland to show that employment in a sector exposed to competition from overseas (a proxy for globalization-induced job insecurity) was associated with greater support for welfare expansion, which in turn increased the probability of voting for the Social Democratic Party.

These studies make headway by offering evidence that links economic openness, job insecurity, and shifts in voting preferences. Although certainly plausible, the evidence put forward is either indirect or based on survey data that have significant limitations. In particular, most studies (with the exception of Walter) rely solely on respondents’ self-assessments of job insecurity and are therefore vulnerable to the possibility that survey respondents are rationalizing their vote choice ex post: After voting for a party that made a certain issue salient, respondents may seek to “justify” their vote choice by reporting that issue (in this case, job insecurity) as a major concern. A second and more serious limitation is that in using only cross-sectional survey data without temporal or spatial variation, these observational studies are constrained from identifying a causal effect.

In this article, I offer new evidence that helps address the deficiencies described previously and sheds new light on the link between globalization's labor market impact and vote choice. I study the effect of trade-related job losses on voting in U.S. presidential elections between 1996 and 2004. During the latter election, a relatively new form of international trade, commonly referred to as offshoring or offshore outsourcing, became a central campaign theme.Footnote ⁹ It rose to national prominence following a statement in the 2004 Economic Report of the President, which asserted that “When a good or a service is produced more cheaply abroad, it makes more sense to import it than to make or provide it domestically” (229). Seizing on this statement, Senator Kerry criticized the president as being intent on “export[ing] more of our jobs overseas” and introduced new legislation that proposed to eliminate the deferral of corporate tax on some overseas earnings of U.S. multinationals. Soon after, the president responded by warning of “politicians in Washington” whose response is to “build a wall around this country and to isolate America from the rest of the world.”Footnote ¹⁰ Figure 1 presents the monthly frequency of media reports that discuss either offshoring or international trade and its impact on jobs in five major news outlets. The graph illustrates the sharp spikes in the media's interest in offshoring during the year preceding the 2004 elections.Footnote ¹¹

FIGURE 1.

Media Reports on Offshoring or on Trade and Jobs in Major News Outlets (January 1996–March 2005)

Note: This figure reports the monthly number of media reports that discuss offshoring and its variants or trade and jobs in five media outlets: New York Times, USA Today, Washington Post, Houston Chronicle, Los Angeles Times.

Throughout the year preceding the elections, the threat posed by international competition to the U.S. workforce was a highly contentious topic. However, despite the Democrats’ success in elevating the issue in the public debate, President Bush won the 2004 elections by a fairly comfortable margin of 2.4%. In the months immediately following the elections, offshoring and trade policy faded from the media spotlight. Whether the threat of foreign competition had an effect on vote choice remains open for debate. In the following sections, I explore this issue in some detail.

EMPIRICAL STRATEGY

Studying the electoral impact of trade openness poses a substantial empirical challenge. First and foremost, the difficulty lies in measuring the effect of trade openness on the voters. Simply assuming that all individuals with a certain skill set or that all those employed in a given industry were harmed by trade liberalization is grossly inaccurate.Footnote ¹² As a way to address this measurement issue, I collected data from the DOL's TAA division, which is in charge of certifying workers hurt by trade-related competition to receive government compensation. This data cover every DOL review of job dislocations claimed to be a result of trade openness. With this detailed data, I generate measures for each U.S. county of the proportion of its workforce whose employment was hurt by trade-related competition. I then estimate the electoral effect of those job dislocations on the change in the president's vote share in each county between the two elections.

I begin the analysis by examining the shift between the 2000 and 2004 elections because data on the exact causes of the trade-related layoffs (e.g., imports, offshoring) was not collected during the previous election cycle (1996–2000). However, I also later incorporate data from the previous elections using a more aggregated measure of trade-related job losses.

By using the first difference in the president's vote share across the two elections as the dependent variable, the model is essentially controlling for any unobserved time-invariant, county-level characteristics that are correlated with support for the president. I estimate a linear model, where the main regression is

(1)

where i denotes the county, and X_i is a vector of covariates of county-level social, economic, and demographic characteristics. Trade Comp is the percent of workers hurt by trade-related competition as a share of the total county workforce. To test whether there is an electoral consequence to the fact that job dislocations are caused specifically by international competition, the model also controls for the level of unemployment in the county, as well as the change in unemployment rate in the year preceding the elections and in the 4-year period between the elections.Footnote ¹³ To ensure that the results are representative of the average voter, and because the precision of the county vote share decreases the smaller the number of votes, I weight the observations by the number of votes cast in the county in the 2000 elections.Footnote ¹⁴

A few comments regarding the interpretation of the estimates and the limitations of my empirical approach are in order. First, by including controls for the county's employment level in 2004, as well as controlling for changes in employment in the years between elections, the value γ in Equation (1) should be interpreted as an estimate of the localized effect of the job dislocation resulting specifically from foreign competition, not as an estimate of the total electoral impact of the job dislocation itself. Second, this analysis estimates the localized electoral effect of trade-related losses using the within-county variation. This specification allows us to estimate the effect of additional trade-related job losses across counties, but it does not capture nationwide shifts in support for the incumbent due to trade's impact on jobs. In the model, such a national time trend is captured in the constant term [α in Equation (1)]; however, one cannot distinguish the specific nationwide effect of trade openness from other national trends that shifted the electorate's preferences. Given that the nationwide impact of trade-related job losses on support for the incumbent is probably not positive, this analysis most likely provides a conservative estimate of the electoral effect of these job losses on the nationwide vote.

Third and finally, the analysis should not be seen as estimating the total impact of trade openness on voting. It could be, for example, that a county that experienced many trade-related job losses gained other jobs from trade-related investments, perhaps leading to a net gain of jobs. Moreover, trade openness has an impact on the overall state of the economy (e.g., by spurring growth), which in turn also affects voters’ preferences. The findings of this analysis should therefore be interpreted as capturing the electoral impact of one aspect of trade, albeit a politically salient one, namely, the loss of local jobs.

DATA AND MEASUREMENT

The analysis covers all 3,111 U.S. counties on which complete voting data are available. The counties of Alaska are excluded because its electoral wards do not match the county boundaries. The voting data comes from the Congressional Quarterly's Voting and Elections Collection. Data on trade-related job losses are based on applications submitted to the TAA program in the DOL. Because the measure of trade-related job losses is central to all subsequent analyses, this section describes the TAA data in some detail.

Trade Adjustment and Assistance Data

The TAA program was established as part of the Trade Expansion Act in 1962, with the objective of providing reemployment services and benefits to workers whose employment was hurt by America's trading relations. By providing legislatures with a means to compensate constituents hurt by the signing of new free trade agreements, the TAA was seen as a useful political tool for helping pass legislation geared toward trade liberalization. To be eligible for TAA benefits, a worker must receive certification by the DOL confirming that certain requirements are met: (1) the worker's employer produces an article; and (2) the workers applying have been totally or partially laid off as a result of (a) import competition that led to decline in sales or production, (b) a shift in production to another country with which the United States has a trade agreement, or (c) due to loss of business as an upstream supplier or downstream producer for another company that is TAA certified.Footnote ¹⁵

Each application, which requires at least three petitioners, refers to a group of workers at a specific location that produces a specific product for a specific company. Applications made to the TAA division are then reviewed by investigative teams at the DOL and, if found to have merit, are granted a TAA certification that provides the workers with eligibility to a range of benefits.Footnote ¹⁶ If the petition is certified, then the certification covers all workers in the group regardless of whether their names appeared as claimants on the petition.

TAA petitions include information about the name of the employer, the estimated number of affected workers, the application and determination date, and the address of the workplace.Footnote ¹⁷ In total, the dataset I use for the 8-year period between 1996 and 2004 includes 22,287 applications representing 2,110,310 employees.Footnote ¹⁸ Table 1 provides the key summary statistics.Footnote ¹⁹

TABLE 1.

Descriptive Statistics: TAA Applications 1996–2004, by Administration Period

Notes: NAFTA, North American Free Trade Agreement; TAA, Trade Adjustment and Assistance. Data prior to 2002 includes both TAA and NAFTA-TAA programs combined.

As noted, the key dependent variable of interest in the analysis is the relative change in Bush's vote share between the 2000 and 2004 elections. I therefore calculate all trade-related job dislocations that occurred in the 4 years between the two elections based on the determination dates provided by the TAA. Within this period, I classify the applications along two dimensions. The first dimension distinguishes between applications that the DOL certified for TAA benefits and those that were denied. The second dimension is the cause that brought about the job dislocation: (1) offshoring of production, (2) import competition, and (3) indirect foreign competition.Footnote ²⁰ I then calculate the percentage of workers affected by each cause as a share of the total workforce in the county.

The DOL produces a report explaining each decision to deny workers TAA certification. A reading of those reports, as well as conversations with personnel at the TAA division, suggest that many of the cases denied TAA certification are nonetheless instances in which workers were hurt by foreign competition, even if not in a way that met the DOL's eligibility criteria for receiving government compensation. The TAA's reports reveal two common reasons for denial. The first is when the applicant is not able to prove that the job dislocation was caused primarily by foreign competition. That is, workers whose employer was hurt by both foreign competition and other reasons are often denied TAA certification. The second reason is when the employer is judged not to produce an “article,” a definition that can exclude some providers of services.Footnote ²¹ In both cases, the workers included in the applications had good reason to view themselves as hurt by trade openness, despite being ineligible for TAA certification. For this reason, in the subsequent analysis, I measure trade-related job dislocations using all applications submitted to the TAA, whether certified or denied. I then repeat the analysis using separate measures for certified and denied cases.

Businesses from about half the U.S. counties (50.2%) applied to the TAA in the 4 years preceding the 2004 elections. In those counties from which TAA applications were submitted, an average of 2% of the workforce was represented. In total, 76% of the applicants were certified to receive TAA compensation. The most common reason for certification was import competition (43%), followed by offshoring (42%). Notably, the location of trade-related job losses was not evenly spread geographically. As the map in Figure 2a shows, the areas that suffered the highest share of trade-related layoffs were the Northeast, the “Rust Belt,” the South, and the Midwest. In contrast, employment in the Great Plains region (e.g., Nebraska, North and South Dakota, Oklahoma) was almost unaffected by trade-related competition. Notably, Figure 2 also highlights the fact that the geographic pattern of trade-related layoffs differs from the pattern of the overall change in unemployment in that period (Figure 2b), the concentration in absolute levels of unemployment in 2004 (Figure 2c), and the pattern of “generic” (i.e., not only trade-related) layoffs in that same 4-year period.Footnote ²² These variables capture related, yet clearly different phenomena.

FIGURE 2.

Geographic Distribution of Job Dislocations and Unemployment (November 2000–November 2004)

Note: Each map represents a different measure of the employment situation by county (clockwise): (a) the share of county workforce applying for Trade Adjustment and Assistance (TAA) compensation for trade-related job dislocations between 2000 and 2004, (b) the unemployment change in the county (2004 level minus 2000 level), (c) the county's absolute unemployment rate in 2004, and (d) the share of county workforce laid off for any reason as part of a mass layoff (≥ 50 workers) between 2000 and 2004.

The prevalence of trade-related layoffs varied not only across geographic units, but also across industries. Overall, applications to the TAA were made by 340 different industries.Footnote ²³ Between 2001 and 2004, the industry with the highest number of affected workers was the “electronic components and accessories,” followed by “men's and boys' furnishing, work clothing, and allied garments” (with 115,218 workers and 65,119 workers, respectively). See Table A2 in the online Appendix (available at http://www.journals.cambridge.org/psr2011003) for more details on the distribution of TAA applications across industries.

One potential concern in using the TAA data for this analysis is selection bias. For selection bias to affect the results of the analysis, one must consider two distinct possibilities. The first is that the “nonapplicants” (i.e., those workers whose employment was hurt by trade-related competition but did not apply to the TAA) are dispersed geographically in a similar fashion to those that did apply. Put differently, no location factors account for, or correlate with, workers’ decision to apply for TAA certification. If that is the case, estimates of the electoral effect of trade-related layoffs will be overstated. However, this concern is at least partly alleviated by the fact that the analysis relies on the firm-level data collected as part of the DOL's investigation of an application, not on each affected worker petitioning individually. In other words, a single application from a plant that laid off workers is sufficient for the entire number of affected workers in the plant to be recorded in the TAA data, regardless of whether those workers then collected the TAA benefits.Footnote ²⁴

The second possibility is that some characteristics of the counties from which applications were submitted also account for the propensity of workers to apply for TAA compensation. Given this possibility, we must again consider two scenarios. The first is that these county characteristics are also correlated with decreasing support for the president. Although theoretically possible, for this to be the case, any determinant of the decision to apply for TAA compensation must be—as revealed by the results presented here—dispersed geographically in a manner that correlates with opposite partisan shifts between the 1996–2000 elections (Democrats losing votes) and the 2000–04 elections (Republicans losing votes). This possibility, in itself, seems quite improbable. The second option is that the same county characteristics that explain workers’ decisions to apply for TAA compensation are orthogonal to voting preferences. In this case, the results would be biased against finding that trade-related layoffs have a larger electoral effect; this would be because counties from which no TAA applications were made did in fact experience trade-related job losses that are not captured in the data. My estimates, in this case, would represent a lower bound of the true electoral effect of trade-related job losses. In conclusion then, selection bias is unlikely to be the explanation for the findings presented in the later analyses.

ALTERNATIVE EXPLANATION: REVERSE CAUSALITY

The previous section indicates that the decrease in support for President Bush in 2004 associated with trade-related job losses was greater in counties with a higher share of workers denied TAA compensation than when the same share of workers were certified for TAA compensation. One interpretation of this finding is that during the Bush presidency, workers that lost their jobs were more prone to electorally punish the incumbent when they were denied the TAA benefits, but less inclined to do so when certified to receive the package of pecuniary and job retraining benefits. However, an alternative explanation of the finding might be that the DOL's certification decisions were granted on a political basis, rewarding counties that were seen as more likely to support the president's reelection bid and denying applicants in areas that were more likely to vote for the Democrats. Determining which of the explanations is correct is key for addressing the broader question of whether access to government assistance reduces the political backlash resulting from trade-induced job losses.

To arbitrate between the two explanations, I propose a falsification exercise aimed at showing that the process applied for allocating TAA certifications under the Bush Administration was not politically driven, or at least not in a way that can account for the observed voting patterns reported in the previous section. For the ideal falsification exercise, one would want to know the “true” merit of each application submitted to the DOL, and then examine whether a political logic can account for the DOL's certification decisions. Given that we do not know the true merit of each application, I exploit two features of the data that provide a useful test of this partisan-centered explanation. First, each application to the TAA is classified by the employer's three-digit SIC industry classification. Second, the dataset also covers the applications made to the TAA division during years in which the Democrats controlled the White House (1996–2000). With this data in hand, I am able to construct a new measure of the simulated certification rate for each county during the 2000–04 period, a measure based on the DOL's determination decisions made during the years of the second Clinton Administration.

The logic for constructing this falsification exercise is as follows: If the decisions made by the DOL during the years of the first Bush Administration were political rather than merit based (i.e., made in anticipation of the likelihood that a given locality would reward the Republicans with increased support), then we should observe that these certification decisions differ systematically from those made under the Clinton Administration. However, if we find that the actual certification rates made during the Bush Administration and the simulated Clinton-based rates in each county are very similar, then that would go against the argument that the DOL's certification process was dictated by a partisan logic.

The method for calculating the simulated rates of certification is a two-stage estimation. In the first stage, I estimate the probability that an application would be TAA certified based on the DOL's decisions during the Clinton Administration. To do so, I estimate a probit model that takes the form:

(3)

where the dependent variable is a binary measure denoting whether application j is certified. Industry SIC is a vector of indicator variables for each industry classification, taking the value “1” when the workers applying to the TAA belong to that industry and zero otherwise. Industry predictors are included in the model because certification decisions are likely to vary based on the industries’ exposure to foreign competition. Estimated Workers is the number of applicants represented in application j, a control included because the DOL may apply different certification standards for applications that represent a large number of workers. Finally, I control for the Year of the application because the DOL may have employed different certification standards over time. I then use the results of this estimation to generate the predicted probabilities of the applications made during the Bush years (2001–04) being certified. Multiplying these predicted probabilities by the number of workers represented in each application and aggregating the results by county, we can now examine whether political variables are able to predict the DOL's certification decisions during the first Bush Administration.

To do so, I divide all applications made to the TAA into three groups: applications made from states that were solidly Republican in the 2000 elections (>55% Republican), solidly Democratic (<45% Republican), or swing states (between 45% and 55% Republican vote share in 2000). If a political calculation was guiding the DOL's certification process, deviations between the actual and the simulated (Clinton-era) rate can be expected in areas that the Republicans favor, whereas lower values would be expected in areas that are politically expedient.Footnote ⁵⁰

The second stage of the estimation regresses the (actual) share of denied county workers on the two measures of the county's electoral characteristics (the Republican's 2000 vote share in the county; the closeness of the race at the state level in 2000), controlling for the simulated certification rates. The model I estimate thus takes the form:

(4)

where the dependent variable is the share of county workers TAA certified in county i in state s, X_i is the same vector of county-level demographics used in the benchmark specification, and Solid Democratic state and Swing State are binary variables that denote the closeness of the vote in the 2000 presidential elections in state s. In a second specification, I try an alternative measure of political considerations by using the county-level support for the Republican candidate in 2000.

Table 6 presents the results. The analysis shows that controlling for the simulated measure, the political characteristics of the county do not predict the DOL's certification decisions. Neither the Republican candidate's share of the county's 2000 vote nor the closeness of the state's voting in 2000 are significantly associated with the rate of denials to applicants from the county. These results provide quite strong evidence that the DOL's certification decisions are not based on a simple partisan logic.Footnote ⁵¹ In turn, this suggests that voters did indeed “punish” Bush electorally in areas where employment was hurt by foreign competition and that they were particularly inclined to do so in areas where the dislocated workers were denied the government trade adjustment compensation.Footnote ⁵²

TABLE 6.

Voting in 2000 as Predictor of TAA Certification Decisions under the Bush Administration (2001–04)

Notes: TAA, Trade Adjustment and Assistance. Standard errors are corrected for clustering at the state level. Models include the same demographic controls used in the benchmark specification.

† significant at 10%; *significant at 5%; **significant at 1%.

MEDIA COVERAGE AND VOTERS' SENSITIVITY TO OFFSHORING

An open question remains why trade-related job losses, predominantly those caused by offshoring, bring about a stronger electoral response. Based on past research, the Theoretical Overview section laid out a set of possible explanations for this finding. Untangling the exact explanation(s) underlying the results is beyond the scope of this article, yet this section seeks to provide an initial exploration of the empirical support for some of these explanations. I do so by comparing the media's coverage of layoff events that took place in the 2 years preceding the 2004 elections. Examining the intensity of the reporting and the information conveyed to readers about the various events of local job losses, this analysis can perhaps point to the factors that bring about the electoral response identified in this article.

The analysis centers on media reports of 500 layoff events randomly selected from five categories: a hundred cases from each of the four categories of TAA determinations (import competition, offshoring, indirect foreign competition, and denied applications) and an additional hundred “random” cases selected from BuildCentral, a general database of plant shutdowns. For each case, I count both local and national media reports that made an explicit mention of the specific layoff event. The search was conducted using the LexisNexis search engine and employed the exact same search string for every case, each time substituting only the name of the company and its location.

Table 7 presents the results of the analysis. The first column presents the percentage of layoff events in each category for which media reports were found, comparing whether job losses resulting from specific causes were reported more frequently in the news.Footnote ⁵³ The results indicate that this is not the case. All forms of layoffs were reported at almost the exact same rate, and as noted in parentheses, also at a similar level of intensity. This pattern helps discard the explanation that the sensitivity of voters to a specific cause of job loss is a consequence of greater media coverage of local instances of layoffs that are the result of that cause (e.g., offshoring).Footnote ⁵⁴ It is also notable from column (1) that only about one third of the layoff events were reported by the media, suggesting that media coverage of local plant closings does not play a major role in the politics of job loss.

TABLE 7.

Media Reports of Layoff Events, by Cause

Notes: TAA, Trade Adjustment and Assistance. Reports based on LexisNexis searches. N = 500, one hundred cases in each category. Trade-related layoff events were selected from TAA applications. Random cases based on plant shutdowns reported in the BuildCentral database.

Column (2) reports the share of lay-off events for which media reports provided a reason for the layoffs. These reported reasons differ quite substantially across cases, ranging from a report that attributes the shutdown of a local pasta producer to the fact that “consumers have given up pasta for low-carb regimens like the Atkins and South Beach diets” to a local producer of paper that “moved its operations to Mexico to increase profitability.” Indeed, the results indicate that readers were somewhat more likely to be offered a reason for the layoff in the media reports when the cause of the layoff was offshoring; however, the difference in frequency is not statistically significant across the various forms of job losses. Examining the reasons mentioned in those reports, column (3) indicates that hardly any of the reports explicitly described a government action (including a mention of a trade agreement) as the cause of the layoff. This seems to go against the “clarity of responsibility” explanation proposed earlier, namely, the notion that voters were more electorally responsive to trade-related job losses because those instances were more commonly attributed in the news in relation to government actions.

An explanation for voters’ unique sensitivity to job losses stemming from offshoring can perhaps be found in the final two columns of Table 7. Column (4) reports the share of cases for which foreign competition was mentioned as a cause of the layoffs, and column (5) reports the share of cases that mentioned a specific foreign country as either a contributing cause or as the destination of the domestic jobs that were lost. Here, a notable distinction arises: Media reports of offshoring-related events are much more likely to describe foreign competition and to name a foreign country as a contributing factor to the layoffs (predominantly, Mexico, China, and India). Compared to the random cases (which due to their selection process also include some job loss events caused by foreign competition), this difference in reporting patterns is sizable (54% vs. 31%, p = .03; 44% vs. 24%, p = .08). These findings are consistent with the notion that voter sensitivity to job losses caused by offshoring is greater because these are more clearly associated with overseas competition and perhaps even with a recognized “villain” in the form of an explicit name of a foreign country. This is also consistent with the explanation that economic nationalism or ethnocentric sentiments perhaps contribute to the unique electoral response to offshoring.

In sum, this exploratory analysis indicates that voters were not more likely to be exposed to media reports of local layoff events that resulted from a specific cause, nor did the reports attribute the job losses to government actions. Rather, the most distinct characteristic of the media's coverage was the prominence of the foreign threat as the source of the hardship and the mention of a specific foreign country when layoffs were caused by offshoring.