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Costly Jobs February 2011 FIGURE 1.Media Reports on Offshoring or on Trade and Jobs in Major News Outlets (January 1996-March 2005) 100 90 Offshoring .....Trade and Jobs 80 60 50 40 20 10 0 AA % 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. dislocations claimed to be a result of trade openness. toral consequence to the fact that job dislocations are With this detailed data.I generate measures for each caused specifically by international competition,the U.S.county of the proportion of its workforce whose model also controls for the level of unemployment in employment was hurt by trade-related competition.I the county,as well as the change in unemployment rate then estimate the electoral effect of those job dislo- in the year preceding the elections and in the 4-year pe- cations on the change in the president's vote share in riod between the elections.13 To ensure that the results each county between the two elections are representative of the average voter,and because I begin the analysis by examining the shift between the precision of the county vote share decreases the the 2000 and 2004 elections because data on the exact smaller the number of votes,I weight the observations causes of the trade-related layoffs (e.g.,imports,off- by the number of votes cast in the county in the 2000 shoring)was not collected during the previous election elections.14 cycle (1996-2000).However,I also later incorporate A few comments regarding the interpretation of the data from the previous elections using a more aggre- estimates and the limitations of my empirical approach gated measure of trade-related job losses. are in order.First,by including controls for the county's By using the first difference in the president's vote employment level in 2004,as well as controlling for share across the two elections as the dependent vari- changes in employment in the years between elections able,the model is essentially controlling for any unob- the value y in Equation(1)should be interpreted as an served time-invariant,county-level characteristics that estimate of the localized effect of the job dislocation are correlated with support for the president.I estimate resulting specifically from foreign competition,not as a linear model,where the main regression is an estimate of the total electoral impact of the job dislocation itself.Second.this analysis estimates the (ABush Vote)i.04-00=a+XiB+y(Trade Comp)i localized electoral effect of trade-related losses using the within-county variation.This specification allows +0(Unemp)i.04+02(AUnemp)i.04-03 us to estimate the effect of additional trade-related job +(△Unemp)i.04-0, losses across counties,but it does not capture nation- (1) wide shifts in support for the incumbent due to trade's where i denotes the county,and Xi is a vector of covari- ates of county-level social,economic,and demographic 13 In the Results section,I also test alterative measures of employ- ment shifts in the county based on Mass Layoff Statistics (MLS)data characteristics.Trade Comp is the percent of workers from the Bureau of Labor Statistics. hurt by trade-related competition as a share of the total 14 The results are similar if I weight by the votes cast in 2004 or by county workforce.To test whether there is an elec- the size of the population. 170Costly Jobs February 2011 FIGURE 1. Media Reports on Offshoring or on Trade and Jobs in Major News Outlets (January 1996–March 2005) 0 10 20 30 40 50 60 70 80 90 100 Jan-96 Jun-96 Nov-96 Apr-97 Sep-97 Feb-98 Jul-98 Dec-98 May-99 Oct-99 Mar-00 Aug-00 Jan-01 Jun-01 Nov-01 Apr-02 Sep-02 Feb-03 Jul-03 Dec-03 May-04 Oct-04 Mar-05 Freqeuncy of menons in news reports Offshoring Trade and Jobs 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. 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 (Bush Vote)i,04−00 = α + Xiβ + γ(Trade Comp)i + θ1(Unemp)i,04 + θ2(Unemp)i,04−03 + θ3(Unemp)i,04−00, (1) where i denotes the county, and Xi 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.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.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 13 In the Results section, I also test alternative measures of employment shifts in the county based on Mass Layoff Statistics (MLS) data from the Bureau of Labor Statistics. 14 The results are similar if I weight by the votes cast in 2004 or by the size of the population. 170